Topic Editors

Department of Robotics and Mechatronics, Faculty of Mechanical Engineering and Robotics, AGH University of Krakow, Al. Mickiewicza 30, 30-059 Krakow, Poland
Prof. Dr. Lei Qiu
Research Center of Structural Health Monitoring and Prognosis, State Key Lab of Mechanics and Control of Mechanical Structures, Nanjing University of Aeronautics and Astronautics, 29 YuDao Street, Nanjing, China
School of Civil Aviation, Northwestern Polytechnical University, Xi'an 710072, China
Department of Robotics and Mechatronics, AGH University of Krakow, 30-962 Krakow, Poland
Prof. Dr. Minh-Quy Le
Group of Mechanics of Materials & Structures, Department of Mechatronics, School of Mechanical Engineering, Hanoi University of Science & Technology, Hanoi, Vietnam

Structural Health Monitoring and Non-destructive Testing for Large-Scale Structures

Abstract submission deadline
closed (31 March 2023)
Manuscript submission deadline
closed (31 May 2023)
Viewed by
96050
Topic Structural Health Monitoring and Non-destructive Testing for Large-Scale Structures book cover image

A printed edition is available here.

Topic Information

Dear Colleagues,

Structural health monitoring (SHM) and non-destructive testing (NDT) have gained significant importance for civil, mechanical, aerospace, and offshore structures. Nowadays, we can find SHM and NDT applications being used on various structures with very different requirements. The SHM-NDT field involves a wide range of transdisciplinary areas, including smart materials, embedded sensors and actuators, damage diagnosis and prognosis, signal and image processing, wireless sensor networks, data interpretation, machine learning, data fusion, energy harvesting, etc. Since the 1970s, there has been a large and increasing volume of research on SHM and NDT; a great deal of effort has focused on developing cost-effective, automatic, and reliable damage detection technologies. However, few industrial and commercial applications can be found in the literature. The practical implementation of strategies for the detection of structural damage to real structures outside of laboratory conditions is always one of the most demanding tasks for engineers. One reason for the rare transfer of research into industrial practice is that most of the methods that have been developed have been tested on simple beam and plate structures in the laboratory, while many practical problems only manifest themselves in complex structures. Another reason is the influence of environmental and operational variations (EOVs) on damage-sensitive features. Thus, for the successful development of SHM and NDT for large structures, techniques should be enhanced to have the capability of dealing with the influence of EOVs. In addition, signal/data processing plays an important role in the implementation of SHM and NDT technologies. The processing and interpretation of the massive amount of data generated through the long-term monitoring of large and complex structures (e.g., bridges, buildings, ships, aircrafts, wind turbines, pipes, etc.) has become an emerging challenge that needs to be addressed by the community. This topical collection brings together the most established as well as newly emerging SHM and NDT techniques that can be used for the detection and evaluation of defects and damage development in large-scale or full-scale structures. We cordially invite you to submit your cutting-edge research for consideration. Suitable topics include:

  • SHM and NDT for aerospace, civil, mechanical, and offshore infrastructures
  • Global monitoring of large structures
  • Large-area monitoring for a part/region of a larger structure
  • Localised monitoring and damage detection
  • SHM and NDT for composite, steel, and concrete structures
  • SHM and NDT of bridges, buildings, ships, aircrafts, wind turbines, pipes, and industrial machines
  • Novel algorithms for SHM and NDT
  • Strategies for the removal of EOVs for SHM and NDT
  • Advanced signal processing for SHM and NDT
  • Artificial intelligence and machine learning for SHM and NDT
  • Time series analysis and statistical approaches for SHM and NDT
  • Damage detection, diagnosis, and prognosis

Dr. Phong B. Dao
Prof. Dr. Lei Qiu
Dr. Liang Yu
Prof. Dr. Tadeusz Uhl
Prof. Dr. Minh-Quy Le
Topic Editors

Keywords

  • structural health monitoring
  • non-destructive testing
  • condition monitoring
  • damage detection
  • remaining useful life prediction
  • smart materials and structures
  • embedded sensors and actuators
  • composite structures
  • steel structures
  • reinforced concrete structures
  • ultrasonic testing
  • laser vibrometry
  • infrared thermography
  • terahertz testing
  • thermal and hyperspectral imaging

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Aerospace
aerospace
2.6 3.0 2014 22.3 Days CHF 2400
Energies
energies
3.2 5.5 2008 16.1 Days CHF 2600
Materials
materials
3.4 5.2 2008 13.9 Days CHF 2600
Sensors
sensors
3.9 6.8 2001 17 Days CHF 2600
Applied Sciences
applsci
2.7 4.5 2011 16.9 Days CHF 2400

Preprints.org is a multidiscipline platform providing preprint service that is dedicated to sharing your research from the start and empowering your research journey.

MDPI Topics is cooperating with Preprints.org and has built a direct connection between MDPI journals and Preprints.org. Authors are encouraged to enjoy the benefits by posting a preprint at Preprints.org prior to publication:

  1. Immediately share your ideas ahead of publication and establish your research priority;
  2. Protect your idea from being stolen with this time-stamped preprint article;
  3. Enhance the exposure and impact of your research;
  4. Receive feedback from your peers in advance;
  5. Have it indexed in Web of Science (Preprint Citation Index), Google Scholar, Crossref, SHARE, PrePubMed, Scilit and Europe PMC.

Published Papers (44 papers)

Order results
Result details
Journals
Select all
Export citation of selected articles as:
15 pages, 4850 KiB  
Article
Triangular Position Multi-Bolt Layout Structure Optimization
by Xiaohan Lu, Min Zhu, Yilong Liu, Shengao Wang, Zijian Xu and Shengnan Li
Appl. Sci. 2023, 13(15), 8786; https://doi.org/10.3390/app13158786 - 29 Jul 2023
Cited by 1 | Viewed by 792
Abstract
Stress concentration often occurs around bolt holes in load-bearing joint structures of large complex equipment, ships, aerospace and other complex machinery fields, which is an important mechanical factor leading to the failure of joint structures. It is of great engineering significance to study [...] Read more.
Stress concentration often occurs around bolt holes in load-bearing joint structures of large complex equipment, ships, aerospace and other complex machinery fields, which is an important mechanical factor leading to the failure of joint structures. It is of great engineering significance to study the phenomenon of stress concentration on connected structures for the safety of large and complex equipment; meanwhile, the layout of bolts seriously affects the stress around holes. Many scholars have studied the layout optimization of multi-bolted structures through experiments and simulations, but few algorithms have been applied to the layout optimization of bolted structures. And most of the studied types of multi-bolt structures are symmetrical. Therefore, in this paper, the gray wolf algorithm is used to optimize the layout of nickel steel plate connectors with a bolt layout in triangular position, and the optimal objective function is found based on the hole circumferential stress of the nickel steel plate, maximum shear stress of the bolt and bending stress of the nickel steel plate. Comparing the optimal values obtained by the fruit fly optimization algorithm, particle swarm optimization algorithm, gray wolf optimization algorithm, multiverse optimization algorithm and wind driven optimization algorithm, the accuracy of selecting the gray wolf algorithm for optimization is verified. A multi-bolt connection structure model was established in ABAQUS, and the surface stress before and after optimization was compared to verify the correctness of the gray wolf algorithm applied to the structure layout optimization of the nickel steel flat bolt connection. The results show that under the force of 15 KN, compared with the original bolt structure layout, the optimized upper side nickel steel plate bore peripheral stress is reduced by 73.1 MPa, and the optimization rate is 24%; bolt stress is reduced by 47.7 MPa, and the optimization rate is 12.5%; when the load is less than 18 KN, the optimization effect of both the upper nickel steel plate and bolt group is more than 10%. When the load is greater than 18 KN, the optimization effect is reduced, and when the load is greater than 21 KN, the nickel steel plate has exceeded the yield limit. Due to the existence of fixed constraints, the optimization of the lower nickel steel plate is not obvious. The results of this study can provide data and theoretical support for the layout optimization of the nickel steel flat bolt connection structure, and help to improve reliability analysis and health monitoring in complex assembly fields such as large complex equipment and aerospace. Full article
Show Figures

Figure 1

11 pages, 3729 KiB  
Article
Modification and Evaluation of Attention-Based Deep Neural Network for Structural Crack Detection
by Hangming Yuan, Tao Jin and Xiaowei Ye
Sensors 2023, 23(14), 6295; https://doi.org/10.3390/s23146295 - 11 Jul 2023
Cited by 2 | Viewed by 887
Abstract
Cracks are one of the safety-evaluation indicators for structures, providing a maintenance basis for the health and safety of structures in service. Most structural inspections rely on visual observation, while bridges rely on traditional methods such as bridge inspection vehicles, which are inefficient [...] Read more.
Cracks are one of the safety-evaluation indicators for structures, providing a maintenance basis for the health and safety of structures in service. Most structural inspections rely on visual observation, while bridges rely on traditional methods such as bridge inspection vehicles, which are inefficient and pose safety risks. To alleviate the problem of low efficiency and the high cost of structural health monitoring, deep learning, as a new technology, is increasingly being applied to crack detection and recognition. Focusing on this, the current paper proposes an improved model based on the attention mechanism and the U-Net network for crack-identification research. First, the training results of the two original models, U-Net and lrassp, were compared in the experiment. The results showed that U-Net performed better than lrassp according to various indicators. Therefore, we improved the U-Net network with the attention mechanism. After experimenting with the improved network, we found that the proposed ECA-UNet network increased the Intersection over Union (IOU) and recall indicators compared to the original U-Net network by 0.016 and 0.131, respectively. In practical large-scale structural crack recognition, the proposed model had better recognition performance than the other two models, with almost no errors in identifying noise under the premise of accurately identifying cracks, demonstrating a stronger capacity for crack recognition. Full article
Show Figures

Figure 1

12 pages, 5740 KiB  
Article
Enhancing Fire Detection Technology: A UV-Based System Utilizing Fourier Spectrum Analysis for Reliable and Accurate Fire Detection
by Cong Tuan Truong, Thanh Hung Nguyen, Van Quang Vu, Viet Hoang Do and Duc Toan Nguyen
Appl. Sci. 2023, 13(13), 7845; https://doi.org/10.3390/app13137845 - 04 Jul 2023
Cited by 4 | Viewed by 1933
Abstract
This study proposes a low-cost and reliable smart fire alarm system that utilizes ultraviolet (UV) detection technology with an aspherical lens to detect fires emitting photons in the 185–260 nm range. The system integrates the aspherical lens with an accelerator and a digital [...] Read more.
This study proposes a low-cost and reliable smart fire alarm system that utilizes ultraviolet (UV) detection technology with an aspherical lens to detect fires emitting photons in the 185–260 nm range. The system integrates the aspherical lens with an accelerator and a digital compass to determine the fire source’s direction, allowing for safe evacuation and effective firefighting. Artificial intelligence is employed to reduce false alarms and achieve a low false alarm rate. The system’s wide detection range and direction verification make it an effective fire detection solution. Upon detecting a fire, the system sends a warning signal via Wi-Fi or smartphone to the user. The proposed system’s advantages include early warning, a low false alarm rate, and detection of a wide range of fires. Experimental results validate the system’s design and demonstrate high accuracy, reliability, and practicality, making it a valuable addition to fire management and prevention. The proposed system utilizes a parabolic mirror to collect UV radiation into the detector and a simple classification model that uses Fourier transform algorithm to reduce false alarms. The results showed accuracies of approximately 95.45% and 93.65% for the flame and UVB lamp, respectively. The system demonstrated its effectiveness in detecting flames in the range of up to 50 m, making it suitable for various applications, including small and medium-sized buildings, homes, and vehicles. Full article
Show Figures

Figure 1

12 pages, 5130 KiB  
Article
Ultrasonic Nonlinearity Experiment due to Plastic Deformation of Aluminum Plate Due to Bending Damage
by Junpil Park, Mohammed Aslam and Jaesun Lee
Materials 2023, 16(12), 4241; https://doi.org/10.3390/ma16124241 - 08 Jun 2023
Cited by 1 | Viewed by 971
Abstract
The nonlinear ultrasonic evaluation technique is useful for assessing micro-defects and microstructure changes caused by fatigue or bending damage. In particular, the guided wave is advantageous for long-distance testing such as piping and plate. Despite these advantages, the study of nonlinear guided wave [...] Read more.
The nonlinear ultrasonic evaluation technique is useful for assessing micro-defects and microstructure changes caused by fatigue or bending damage. In particular, the guided wave is advantageous for long-distance testing such as piping and plate. Despite these advantages, the study of nonlinear guided wave propagation has received relatively less attention compared to bulk wave techniques. Furthermore, there is a lack of research on the correlation between nonlinear parameters and material properties. In this study, the relationship between nonlinear parameters and plastic deformation resulting from bending damage was experimentally investigated using Lamb waves. The findings indicated an increase in the nonlinear parameter for the specimen, which was loaded within the elastic limit. Inversely, regions of maximum deflection in specimens with plastic deformation exhibited a decrease in the nonlinear parameter. This research is expected to be helpful for maintenance technology in the nuclear power plant and aerospace fields that require high reliability and accuracy. Full article
Show Figures

Figure 1

4 pages, 168 KiB  
Editorial
Moving towards Preventive Maintenance in Wind Turbine Structural Control and Health Monitoring
by Jersson X. Leon-Medina and Francesc Pozo
Energies 2023, 16(6), 2730; https://doi.org/10.3390/en16062730 - 15 Mar 2023
Cited by 1 | Viewed by 1159
Abstract
In recent years, the scope of structural health monitoring in wind turbines has broadened due to the development of innovative data-driven methodologies [...] Full article
17 pages, 2923 KiB  
Article
On Cointegration Analysis for Condition Monitoring and Fault Detection of Wind Turbines Using SCADA Data
by Phong B. Dao
Energies 2023, 16(5), 2352; https://doi.org/10.3390/en16052352 - 01 Mar 2023
Cited by 2 | Viewed by 1451
Abstract
Cointegration theory has been recently proposed for condition monitoring and fault detection of wind turbines. However, the existing cointegration-based methods and results presented in the literature are limited and not encouraging enough for the broader deployment of the technique. To close this research [...] Read more.
Cointegration theory has been recently proposed for condition monitoring and fault detection of wind turbines. However, the existing cointegration-based methods and results presented in the literature are limited and not encouraging enough for the broader deployment of the technique. To close this research gap, this paper presents a new investigation on cointegration for wind turbine monitoring using a four-year SCADA data set acquired from a commercial wind turbine. A gearbox fault is used as a testing case to validate the analysis. A cointegration-based wind turbine monitoring model is established using five process parameters, including the wind speed, generator speed, generator temperature, gearbox temperature, and generated power. Two different sets of SCADA data were used to train the cointegration-based model and calculate the normalized cointegrating vectors. The first training data set involves 12,000 samples recorded before the occurrence of the gearbox fault, whereas the second one includes 6000 samples acquired after the fault occurrence. Cointegration residuals—obtained from projecting the testing data (2000 samples including the gearbox fault event) on the normalized cointegrating vectors—are used in control charts for operational state monitoring and automated fault detection. The results demonstrate that regardless of which training data set was used, the cointegration residuals can effectively monitor the wind turbine and reliably detect the fault at the early stage. Interestingly, despite using different training data sets, the cointegration analysis creates two residuals which are almost identical in their shapes and trends. In addition, the gearbox fault can be detected by these two residuals at the same moment. These interesting findings have never been reported in the literature. Full article
Show Figures

Figure 1

14 pages, 24656 KiB  
Article
Wrinkle Detection in Carbon Fiber-Reinforced Polymers Using Linear Phase FIR-Filtered Ultrasonic Array Data
by Tengfei Ma, Yang Li, Zhenggan Zhou and Jia Meng
Aerospace 2023, 10(2), 181; https://doi.org/10.3390/aerospace10020181 - 15 Feb 2023
Cited by 6 | Viewed by 2087
Abstract
Carbon fiber-reinforced polymers (CFRP) are extensively used in aerospace applications. Out-of-plane wrinkles frequently occur in aerospace CFRP parts that are commonly large and complex. Wrinkles acting as failure initiators severely damage the mechanical performance of CFRP parts. Wrinkles have no significant acoustic impedance [...] Read more.
Carbon fiber-reinforced polymers (CFRP) are extensively used in aerospace applications. Out-of-plane wrinkles frequently occur in aerospace CFRP parts that are commonly large and complex. Wrinkles acting as failure initiators severely damage the mechanical performance of CFRP parts. Wrinkles have no significant acoustic impedance mismatch, reflecting weak echoes. The total focusing method (TFM) using weak reflection signals is vulnerable to noise, so our primary work is to design discrete-time filters to relieve the noise interference. Wrinkles in CFRP composites are geometric defects, and their direct detection requires high spatial precision. The TFM method is a time-domain delay-and-sum algorithm, and it requires that the time information of filtered signals has no change or can be corrected. A linear phase filter can avoid phase distortion, and its filtered signal can be corrected by shifting a constant time. We first propose a wrinkle detection method using linear phase FIR-filtered ultrasonic array data. Linear phase filters almost do not affect the wrinkle geometry of detection results and can relieve noise-induced dislocation. Four filters with different bandwidths have been designed and applied for wrinkle detection. The 2 MHz bandwidth filter is recommended as an optimum choice. Full article
Show Figures

Figure 1

22 pages, 7491 KiB  
Article
FEM Simulation-Based Adversarial Domain Adaptation for Fatigue Crack Detection Using Lamb Wave
by Li Wang, Guoqiang Liu, Chao Zhang, Yu Yang and Jinhao Qiu
Sensors 2023, 23(4), 1943; https://doi.org/10.3390/s23041943 - 09 Feb 2023
Cited by 1 | Viewed by 1329
Abstract
Lamb wave-based damage detection technology shows great potential for structural integrity assessment. However, conventional damage features based damage detection methods and data-driven intelligent damage detection methods highly rely on expert knowledge and sufficient labeled data for training, for which collecting is usually expensive [...] Read more.
Lamb wave-based damage detection technology shows great potential for structural integrity assessment. However, conventional damage features based damage detection methods and data-driven intelligent damage detection methods highly rely on expert knowledge and sufficient labeled data for training, for which collecting is usually expensive and time-consuming. Therefore, this paper proposes an automated fatigue crack detection method using Lamb wave based on finite element method (FEM) and adversarial domain adaptation. FEM-simulation was used to obtain simulated response signals under various conditions to solve the problem of the insufficient labeled data in practice. Due to the distribution discrepancy between simulated signals and experimental signals, the detection performance of classifier just trained with simulated signals will drop sharply on the experimental signals. Then, Domain-adversarial neural network (DANN) with maximum mean discrepancy (MMD) was used to achieve discriminative and domain-invariant feature extraction between simulation source domain and experiment target domain, and the unlabeled experimental signals samples will be accurately classified. The proposed method is validated by fatigue tests on center-hole metal specimens. The results show that the proposed method presents superior detection ability compared to other methods and can be used as an effective tool for cross-domain damage detection. Full article
Show Figures

Figure 1

35 pages, 50389 KiB  
Review
Developments in 3D Visualisation of the Rail Tunnel Subsurface for Inspection and Monitoring
by Thomas McDonald, Mark Robinson and Gui Yun Tian
Appl. Sci. 2022, 12(22), 11310; https://doi.org/10.3390/app122211310 - 08 Nov 2022
Cited by 4 | Viewed by 2735
Abstract
Railway Tunnel SubSurface Inspection (RTSSI) is essential for targeted structural maintenance. ‘Effective’ detection, localisation and characterisation of fully concealed features (i.e., assets, defects) is the primary challenge faced by RTSSI engineers, particularly in historic masonry tunnels. Clear conveyance and communication of gathered information [...] Read more.
Railway Tunnel SubSurface Inspection (RTSSI) is essential for targeted structural maintenance. ‘Effective’ detection, localisation and characterisation of fully concealed features (i.e., assets, defects) is the primary challenge faced by RTSSI engineers, particularly in historic masonry tunnels. Clear conveyance and communication of gathered information to end-users poses the less frequently considered secondary challenge. The purpose of this review is to establish the current state of the art in RTSSI data acquisition and information conveyance schemes, in turn formalising exactly what constitutes an ‘effective’ RTSSI visualisation framework. From this knowledge gaps, trends in leading RTSSI research and opportunities for future development are explored. Literary analysis of over 300 resources (identified using the 360-degree search method) informs data acquisition system operation principles, common strengths and limitations, alongside leading studies and commercial tools. Similar rigor is adopted to appraise leading information conveyance schemes. This provides a comprehensive whilst critical review of present research and future development opportunities within the field. This review highlights common shortcomings shared by multiple methods for RTSSI, which are used to formulate robust criteria for a contextually ‘effective’ visualisation framework. Although no current process is deemed fully effective; a feasible hybridised framework capable of meeting all stipulated criteria is proposed based on identified future research avenues. Scope for novel analysis of helical point cloud subsurface datasets obtained by a new rotating ground penetrating radar antenna is of notable interest. Full article
Show Figures

Figure 1

18 pages, 9290 KiB  
Article
Prediction of Traffic Vibration Environment of Ancient Wooden Structures Based on the Response Transfer Ratio Function
by Cheng Zhang, Nan Zhang, Yunshi Zhang and Xiao Liu
Sensors 2022, 22(21), 8414; https://doi.org/10.3390/s22218414 - 02 Nov 2022
Cited by 2 | Viewed by 1286
Abstract
Traffic−induced vibration is increasingly affecting people’s lives, which necessitates scrutiny of the environmental vibrations caused by traffic. This paper proposed a vibration prediction method suitable for the ancient wooden structures subjected to traffic−induced vibrations based on the multi−point response transfer ratio function. The [...] Read more.
Traffic−induced vibration is increasingly affecting people’s lives, which necessitates scrutiny of the environmental vibrations caused by traffic. This paper proposed a vibration prediction method suitable for the ancient wooden structures subjected to traffic−induced vibrations based on the multi−point response transfer ratio function. The accuracy of the proposed approach was also checked by comparing the predicted results with the measured results in the context of both the time domain and frequency domain. Subsequently, the environmental vibrations due to heavy−duty trucks passing at various speeds were measured, and the measurements were utilized as the input vibration excitation to assess the structural vibration of the Feiyun Pavilion. The structural safety was evaluated according to the “Technical specifications for protecting historic buildings against man−made vibration”. In order to meet the structural safety requirements of the Feiyun Pavilion, it is strongly recommended to limit the type and speed of vehicles in the nearby area. Full article
Show Figures

Figure 1

18 pages, 7149 KiB  
Article
Application of Fiber Optic Sensing System for Predicting Structural Displacement of a Joined-Wing Aircraft
by Yang Meng, Ying Bi, Changchuan Xie, Zhiying Chen and Chao Yang
Aerospace 2022, 9(11), 661; https://doi.org/10.3390/aerospace9110661 - 27 Oct 2022
Cited by 4 | Viewed by 1741
Abstract
This work aims to achieve real-time monitoring of strains and structural displacements for the target Joined-Wing aircraft. To this end, a Fiber Optic Sensing System (FOSS) is designed and deployed in the aircraft. The classical modal method, which is used for Strain-to-Displacement Transformation [...] Read more.
This work aims to achieve real-time monitoring of strains and structural displacements for the target Joined-Wing aircraft. To this end, a Fiber Optic Sensing System (FOSS) is designed and deployed in the aircraft. The classical modal method, which is used for Strain-to-Displacement Transformation (SDT), is improved to adapt to different boundary conditions by introducing extra constraint equations. The method is first verified by numerical studies on a cantilever beam model and the high-fidelity finite element model of the Joined-Wing aircraft. Ground static tests are then carried out to further demonstrate the capability of the developed FOSS and SDT algorithm in practical application. The results have shown that the improved modal method is able to predict structural deformation under different boundary conditions by using only free–free modes. In addition, the errors between the predicted displacement and the reference in the ground test are within 10%, which proves the FOSS has reasonable accuracy and the potential for future flight tests. Full article
Show Figures

Figure 1

40 pages, 1440 KiB  
Review
Review of Machine-Learning Techniques Applied to Structural Health Monitoring Systems for Building and Bridge Structures
by Alain Gomez-Cabrera and Ponciano Jorge Escamilla-Ambrosio
Appl. Sci. 2022, 12(21), 10754; https://doi.org/10.3390/app122110754 - 24 Oct 2022
Cited by 24 | Viewed by 4580
Abstract
This review identifies current machine-learning algorithms implemented in building structural health monitoring systems and their success in determining the level of damage in a hierarchical classification. The integration of physical models, feature extraction techniques, uncertainty management, parameter estimation, and finite element model analysis [...] Read more.
This review identifies current machine-learning algorithms implemented in building structural health monitoring systems and their success in determining the level of damage in a hierarchical classification. The integration of physical models, feature extraction techniques, uncertainty management, parameter estimation, and finite element model analysis are used to implement data-driven model detection systems for SHM system design. A total of 68 articles using ANN, CNN and SVM, in combination with preprocessing techniques, were analyzed corresponding to the period 2011–2022. The application of these techniques in structural condition monitoring improves the reliability and performance of these systems. Full article
Show Figures

Figure 1

18 pages, 13238 KiB  
Article
Mechanic-Electric-Thermal Directly Coupling Simulation Method of Lamb Wave under Temperature Effect
by Xiaofei Yang, Zhaopeng Xue, Hui Zheng, Lei Qiu and Ke Xiong
Sensors 2022, 22(17), 6647; https://doi.org/10.3390/s22176647 - 02 Sep 2022
Cited by 3 | Viewed by 1436
Abstract
Lamb Wave (LW)-based structural health monitoring method is promising, but its main obstacle is damage assessment in varying environments. LW simulation based on piezoelectric transducers (referred to as PZTs) is an efficient and low-cost method. This paper proposes a multiphysics simulation method of [...] Read more.
Lamb Wave (LW)-based structural health monitoring method is promising, but its main obstacle is damage assessment in varying environments. LW simulation based on piezoelectric transducers (referred to as PZTs) is an efficient and low-cost method. This paper proposes a multiphysics simulation method of LW propagation with the PZTs under temperature effect. The effect of temperature on LW propagation is considered from two aspects. On the one hand, temperature affects the material parameters of the structure, the adhesive layers and the PZTs. On the other hand, it is considered that the thermal stress caused by the inconsistency of thermal expansion coefficients among the structure, the adhesive layers, and the PZTs affect the piezoelectric constant of the PZTs. Based on the COMSOL Multiphysics, the mechanic–electric–thermal directly coupling simulation model under temperature effect is established. The simulation model consists of two steps. In the first step, the thermal-mechanic coupling is carried out to calculate the thermal stress, and the thermal stress effect is introduced into the piezoelectric constant model. In the second step, mechanic–electric coupling is carried out to simulate LW propagation, which considers the piezoelectric effect of the PZTs for the LW excitation and reception. The simulation results at −20 °C to 60 °C are obtained and compared to the experiment. The results show that the A0 and S0 mode of simulation signals match well with the experimental measurements. Additionally, the effect of temperature on LW propagation is consistent between simulation and experiment; that is, the amplitude increases, and the phase velocity decreases with the increment of temperature. Full article
Show Figures

Figure 1

25 pages, 4154 KiB  
Review
A Review on Rail Defect Detection Systems Based on Wireless Sensors
by Yuliang Zhao, Zhiqiang Liu, Dong Yi, Xiaodong Yu, Xiaopeng Sha, Lianjiang Li, Hui Sun, Zhikun Zhan and Wen Jung Li
Sensors 2022, 22(17), 6409; https://doi.org/10.3390/s22176409 - 25 Aug 2022
Cited by 16 | Viewed by 3979
Abstract
Small defects on the rails develop fast under the continuous load of passing trains, and this may lead to train derailment and other disasters. In recent years, many types of wireless sensor systems have been developed for rail defect detection. However, there has [...] Read more.
Small defects on the rails develop fast under the continuous load of passing trains, and this may lead to train derailment and other disasters. In recent years, many types of wireless sensor systems have been developed for rail defect detection. However, there has been a lack of comprehensive reviews on the working principles, functions, and trade-offs of these wireless sensor systems. Therefore, we provide in this paper a systematic review of recent studies on wireless sensor-based rail defect detection systems from three different perspectives: sensing principles, wireless networks, and power supply. We analyzed and compared six sensing methods to discuss their detection accuracy, detectable types of defects, and their detection efficiency. For wireless networks, we analyzed and compared their application scenarios, the advantages and disadvantages of different network topologies, and the capabilities of different transmission media. From the perspective of power supply, we analyzed and compared different power supply modules in terms of installation and energy harvesting methods, and the amount of energy they can supply. Finally, we offered three suggestions that may inspire the future development of wireless sensor-based rail defect detection systems. Full article
Show Figures

Figure 1

20 pages, 6594 KiB  
Article
Thermal Analysis and Prediction Methods for Temperature Distribution of Slab Track Using Meteorological Data
by Qiangqiang Zhang, Gonglian Dai and Yu Tang
Sensors 2022, 22(17), 6345; https://doi.org/10.3390/s22176345 - 23 Aug 2022
Cited by 1 | Viewed by 1298
Abstract
The structural temperature distribution, especially temperature difference caused by solar radiation, has a great impact on the deformation and curvature of the concrete slab tracks of high-speed railways. Previous studies mainly focused on the temperature prediction of slab tracks, while how the temperature [...] Read more.
The structural temperature distribution, especially temperature difference caused by solar radiation, has a great impact on the deformation and curvature of the concrete slab tracks of high-speed railways. Previous studies mainly focused on the temperature prediction of slab tracks, while how the temperature distribution is affected by environmental conditions has been rarely investigated. Based on the integral transformation method, this work presents an analytical method to determine and decompose the temperature distribution of the concrete slab track. A field temperature test of a half-scaled specimen of concrete slab track was conducted to validate the developed methodology. In the proposed method, we decompose the temperature distribution of the slab track into an initial temperature component and a boundary temperature component. Then, the boundary temperature components caused by solar radiation and atmospheric temperature are investigated, respectively. The results show that the solar radiation plays a significant role in the nonlinear temperature distribution, while the atmospheric temperature has little effect. By contrast, the temperature change in the slab surface resulting from the atmospheric temperature accounts on average for only 5% in the hot weather condition. The proposed method establishes a relation between the structural temperature and meteorological parameters (i.e., the solar radiation and atmospheric temperature). Consequently, the temperature distribution of the concrete slab track is predicted via the meteorological parameters. Full article
Show Figures

Figure 1

17 pages, 6981 KiB  
Article
Research on Mechanical Properties and Damage Evolution of Pultruded Sheet for Wind Turbine Blades
by Ying He, Yuanbo Wang, Hao Zhou, Chang Li, Leian Zhang and Yuhuan Zhang
Materials 2022, 15(16), 5719; https://doi.org/10.3390/ma15165719 - 19 Aug 2022
Cited by 1 | Viewed by 1410
Abstract
In order to explore the mechanical properties, failure mode, and damage evolution process of pultruded sheets for wind turbine blades, a tensile testing machine for pultruded sheets for wind turbine blades was built, and the hydraulic system, mechanical structure, and control scheme of [...] Read more.
In order to explore the mechanical properties, failure mode, and damage evolution process of pultruded sheets for wind turbine blades, a tensile testing machine for pultruded sheets for wind turbine blades was built, and the hydraulic system, mechanical structure, and control scheme of the testing machine were designed. The feasibility of the mechanical structure was verified by numerical simulation, and the control system was simulated by MATLAB software. Then, based on the built testing machine, the static tensile test of the pultruded sheet was carried out to study the mechanical properties and failure mode of the pultruded sheet. Finally, an infrared thermal imager was used to monitor the temperature change on the surface of the test piece, and the temperature change law and damage evolution process of the test piece during the whole process were studied. The results show that the design scheme of the testing machine was accurate and feasible. The maximum stress occurred in the beam after loading the support, the maximum stress was 280.18 MPa, and the maximum displacement was 0.665 mm, which did not exceed its structural stress-strain limit. At the same time, the control system met the test requirements and had a good follow-up control effect. The failure load of the pultruded sheet was 800 kN. The failure deformation form included three stages of elasticity, yield, and fracture, and the finite element analysis data were in good agreement with the test results. The failure modes were fiber breakage, delamination, and interfacial debonding. The surface temperature of the specimen first decreased linearly, and then continued to increase. The strain and temperature trend were consistent with time. Full article
Show Figures

Figure 1

31 pages, 8471 KiB  
Review
Piezoelectric Impedance-Based Structural Health Monitoring of Wind Turbine Structures: Current Status and Future Perspectives
by Thanh-Cao Le, Tran-Huu-Tin Luu, Huu-Phuong Nguyen, Trung-Hau Nguyen, Duc-Duy Ho and Thanh-Canh Huynh
Energies 2022, 15(15), 5459; https://doi.org/10.3390/en15155459 - 28 Jul 2022
Cited by 12 | Viewed by 3621
Abstract
As an innovative technology, the impedance-based technique has been extensively studied for the structural health monitoring (SHM) of various civil structures. The technique’s advantages include cost-effectiveness, ease of implementation on a complex structure, robustness to early-stage failures, and real-time damage assessment capabilities. Nonetheless, [...] Read more.
As an innovative technology, the impedance-based technique has been extensively studied for the structural health monitoring (SHM) of various civil structures. The technique’s advantages include cost-effectiveness, ease of implementation on a complex structure, robustness to early-stage failures, and real-time damage assessment capabilities. Nonetheless, very few studies have taken those advantages for monitoring the health status and the structural condition of wind turbine structures. Thus, this paper is motivated to give the reader a general outlook of how the impedance-based SHM technology has been implemented to secure the safety and serviceability of the wind turbine structures. Firstly, possible structural failures in wind turbine systems are reviewed. Next, physical principles, hardware systems, damage quantification, and environmental compensation algorithms are outlined for the impedance-based technique. Afterwards, the current status of the application of this advanced technology for health monitoring and damage identification of wind turbine structural components such as blades, tower joints, tower segments, substructure, and the foundation are discussed. In the end, the future perspectives that can contribute to developing efficient SHM systems in the green energy field are proposed. Full article
Show Figures

Figure 1

15 pages, 3107 KiB  
Communication
Torsional Low-Strain Test for Nondestructive Integrity Examination of Existing High-Pile Foundation
by Yunpeng Zhang, M. Hesham El Naggar, Wenbing Wu and Zongqin Wang
Sensors 2022, 22(14), 5330; https://doi.org/10.3390/s22145330 - 16 Jul 2022
Cited by 6 | Viewed by 1427
Abstract
Low-strain tests are widely utilized as a nondestructive approach to assess the integrity of newly piled foundations. So far, the examination of existing pile foundations is becoming an indispensable protocol for pile recycling or post-disaster safety assessment. However, the present low-strain test is [...] Read more.
Low-strain tests are widely utilized as a nondestructive approach to assess the integrity of newly piled foundations. So far, the examination of existing pile foundations is becoming an indispensable protocol for pile recycling or post-disaster safety assessment. However, the present low-strain test is not capable of testing existing pile foundations. In this paper, the torsional low-strain test (TLST) is proposed to overcome this drawback. Both the upward and downward waves are considered in the TLST wave propagation model established in this paper so that a firm theoretical basis is grounded for the test signal interpretations. A concise semi-analytical solution is derived and its rationality is verified by comparisons with the existing solutions for newly piled foundations and the finite element results. The main conclusions of this study can be drawn as follows: (1). by placing the sensors where the incident wave is applied, the number of reflected signals can be minimized; (2). the defects can be more evidently identified if the incident wave/sensors are input/installed close to the superstructure/pile head. Full article
Show Figures

Figure 1

19 pages, 7813 KiB  
Article
Carbon Nanofibers Grown in CaO for Self-Sensing in Mortar
by Lívia Ribeiro de Souza, Matheus Pimentel, Gabriele Milone, Juliana Cristina Tristão and Abir Al-Tabbaa
Materials 2022, 15(14), 4951; https://doi.org/10.3390/ma15144951 - 15 Jul 2022
Cited by 7 | Viewed by 1770
Abstract
Intelligent cementitious materials integrated with carbon nanofibers (CNFs) have the potential to be used as sensors in structural health monitoring (SHM). The difficulty in dispersing CNFs in cement-based matrices, however, limits the sensitivity to deformation (gauge factor) and strength. Here, we synthesise CNF [...] Read more.
Intelligent cementitious materials integrated with carbon nanofibers (CNFs) have the potential to be used as sensors in structural health monitoring (SHM). The difficulty in dispersing CNFs in cement-based matrices, however, limits the sensitivity to deformation (gauge factor) and strength. Here, we synthesise CNF by chemical vapour deposition on the surface of calcium oxide (CaO) and, for the first time, investigate this amphiphilic carbon nanomaterial for self-sensing in mortar. SEM, TEM, TGA, Raman and VSM were used to characterise the produced CNF@CaO. In addition, the electrical resistivity of the mortar, containing different concentrations of CNF with and without CaO, was measured using the four-point probe method. Furthermore, the piezoresistive response of the composite was quantified by means of compressive loading. The synthesised CNF was 5–10 μm long with an average diameter of ~160 nm, containing magnetic nanoparticles inside. Thermal decomposition of the CNF@CaO compound indicated that 26% of the material was composed of CNF; after CaO removal, 84% of the material was composed of CNF. The electrical resistivity of the material drops sharply at concentrations of 2% by weight of CNF and this drop is even more pronounced for samples with 1.2% by weight of washed CaO. This indicates a better dispersion of the material when the CaO is removed. The sensitivity to deformation of the sample with 1.2% by weight of CNF@CaO was quantified as a gauge factor (GF) of 1552, while all other samples showed a GF below 100. Its FCR amplitude can vary inversely up to 8% by means of cyclic compressive loading. The method proposed in this study provides versatility for the fabrication of carbon nanofibers on a tailored substrate to promote self-sensing in cementitious materials. Full article
Show Figures

Figure 1

17 pages, 3622 KiB  
Article
Assessment of Cracking in Masonry Structures Based on the Breakage of Ordinary Silica-Core Silica-Clad Optical Fibers
by Sergei Khotiaintsev and Volodymyr Timofeyev
Appl. Sci. 2022, 12(14), 6885; https://doi.org/10.3390/app12146885 - 07 Jul 2022
Cited by 1 | Viewed by 1601
Abstract
This paper presents a study on the suitability and accuracy of detecting structural cracks in brick masonry by exploiting the breakage of ordinary silica optical fibers bonded to its surface with an epoxy adhesive. The deformations and cracking of the masonry specimen, and [...] Read more.
This paper presents a study on the suitability and accuracy of detecting structural cracks in brick masonry by exploiting the breakage of ordinary silica optical fibers bonded to its surface with an epoxy adhesive. The deformations and cracking of the masonry specimen, and the behavior of pilot optical signals transmitted through the fibers upon loading of the test specimen were observed. For the first time, reliable detection of structural cracks with a given minimum value was achieved, despite the random nature of the ultimate strength of the optical fibers. This was achieved using arrays of several optical fibers placed on the structural element. The detection of such cracks allows the degree of structural danger of buildings affected by earthquake or other destructive phenomena to be determined. The implementation of this technique is simple and cost effective. For this reason, it may have a broad application in permanent damage-detection systems in buildings in seismic zones. It may also find application in automatic systems for the detection of structural damage to the load-bearing elements of land vehicles, aircraft, and ships. Full article
Show Figures

Figure 1

17 pages, 9222 KiB  
Article
Structural Responses Estimation of Cable-Stayed Bridge from Limited Number of Multi-Response Data
by Namju Byun, Jeonghwa Lee, Joo-Young Won and Young-Jong Kang
Sensors 2022, 22(10), 3745; https://doi.org/10.3390/s22103745 - 14 May 2022
Cited by 5 | Viewed by 2102
Abstract
A cable-stayed bridge is widely adopted to construct long-span bridges. The deformation of cable-stayed bridges is relatively larger than that of conventional bridges, such as beam and truss types. Therefore, studies regarding the monitoring systems for cable-stayed bridges have been conducted to evaluate [...] Read more.
A cable-stayed bridge is widely adopted to construct long-span bridges. The deformation of cable-stayed bridges is relatively larger than that of conventional bridges, such as beam and truss types. Therefore, studies regarding the monitoring systems for cable-stayed bridges have been conducted to evaluate the performance of bridges based on measurement data. However, most studies required sufficient measurement data for evaluation and just focused on the local response estimation. To overcome these limitations, Structural Responses Analysis using a Limited amount of Multi-Response data (SRALMR) was recently proposed and validated with the beam and truss model that has a simple structural behavior. In this research, the structural responses of a cable-stayed bridge were analyzed using SRALMR. The deformed shape and member internal forces were estimated using a limited amount of displacement, slope, and strain data. Target structural responses were determined by applying four load cases to the numerical model. In addition, pre-analysis for initial shape analysis was conducted to determine the initial equilibrium state, minimizing the deformation under dead loads. Finally, the performance of SRALMR for cable-stayed bridges was analyzed according to the combination and number of response data. Full article
Show Figures

Figure 1

16 pages, 3114 KiB  
Article
Angular Displacement Control for Timoshenko Beam by Optimized Traveling Wave Method
by Huawei Ji, Chuanping Zhou, Jiawei Fan, Huajie Dai, Wei Jiang, Youping Gong, Chuzhen Xu, Ban Wang and Weihua Zhou
Aerospace 2022, 9(5), 259; https://doi.org/10.3390/aerospace9050259 - 11 May 2022
Cited by 1 | Viewed by 1704
Abstract
The vibration of flexible structures in spacecraft, such as large space deployable reflectors, solar panels and large antenna structure, has a great impact on the normal operation of spacecraft. Accurate vibration control is necessary, and the control of angular displacement is a difficulty [...] Read more.
The vibration of flexible structures in spacecraft, such as large space deployable reflectors, solar panels and large antenna structure, has a great impact on the normal operation of spacecraft. Accurate vibration control is necessary, and the control of angular displacement is a difficulty of accurate control. In the traditional control method, the mode space control has a good effect on suppressing low-order modes, but there is control overflow. The effect of traveling wave control on low-order modes is worse than the former, but it has the characteristics of broadband control. It can better control high-order modes and reduce control overflow. In view of the advantages and disadvantages of the two control methods, based on Timoshenko beam theory, this paper uses vector mode function to analyze the modal of spacecraft cantilever beam structure, establishes the system dynamic equation, and puts forward an optimized traveling wave control method. As a numerical example, three strategies of independent mode space control, traditional traveling wave control and optimized traveling wave control are used to control the active vibration of beam angle. By comparing the numerical results of the three methods, it can be seen that the optimal control method proposed in this paper not only effectively suppresses the vibration, but also improves the robustness of the system, reflecting good control performance. An innovation of this paper is that the Timoshenko beam model is adopted, which considers the influence of transverse shear deformation and moment of inertia on displacement and improves the accuracy of calculation, which is important for spacecraft accessory structures with high requirements for angle control. Another innovation is that the optimized traveling wave control method is exquisite in mathematical processing and has good results in global and local vibration control, which is not available in other methods. Full article
Show Figures

Figure 1

18 pages, 4000 KiB  
Article
Improvement of Lightweight Convolutional Neural Network Model Based on YOLO Algorithm and Its Research in Pavement Defect Detection
by Fu-Jun Du and Shuang-Jian Jiao
Sensors 2022, 22(9), 3537; https://doi.org/10.3390/s22093537 - 06 May 2022
Cited by 33 | Viewed by 4527
Abstract
To ensure the safe operation of highway traffic lines, given the imperfect feature extraction of existing road pit defect detection models and the practicability of detection equipment, this paper proposes a lightweight target detection algorithm with enhanced feature extraction based on the YOLO [...] Read more.
To ensure the safe operation of highway traffic lines, given the imperfect feature extraction of existing road pit defect detection models and the practicability of detection equipment, this paper proposes a lightweight target detection algorithm with enhanced feature extraction based on the YOLO (You Only Look Once) algorithm. The BIFPN (Bidirectional Feature Pyramid Network) network structure is used for multi-scale feature fusion to enhance the feature extraction ability, and Varifocal Loss is used to optimize the sample imbalance problem, which improves the accuracy of road defect target detection. In the evaluation test of the model in the constructed PCD1 (Pavement Check Dataset) dataset, the mAP@.5 (mean Average Precision when IoU = 0.5) of the BV-YOLOv5S (BiFPN Varifocal Loss-YOLOv5S) model increased by 4.1%, 3%, and 0.9%, respectively, compared with the YOLOv3-tiny, YOLOv5S, and B-YOLOv5S (BiFPN-YOLOv5S; BV-YOLOv5S does not use the Improved Focal Loss function) models. Through the analysis and comparison of experimental results, it is proved that the proposed BV-YOLOv5S network model performs better and is more reliable in the detection of pavement defects and can meet the needs of road safety detection projects with high real-time and flexibility requirements. Full article
Show Figures

Figure 1

16 pages, 7115 KiB  
Article
Analysis of the Effect of Velocity on the Eddy Current Effect of Metal Particles of Different Materials in Inductive Bridges
by Wei Li, Shuang Yu, Hongpeng Zhang, Xingming Zhang, Chenzhao Bai, Haotian Shi, Yucai Xie, Chengjie Wang, Zhiwei Xu, Lin Zeng and Yuqing Sun
Sensors 2022, 22(9), 3406; https://doi.org/10.3390/s22093406 - 29 Apr 2022
Cited by 2 | Viewed by 1593
Abstract
A method for analyzing the influence of velocity changes on metal signals of different materials in oil detection technology is proposed. The flow rate of metal contaminants in the oil will have a certain impact on the sensitivity of the output particle signal [...] Read more.
A method for analyzing the influence of velocity changes on metal signals of different materials in oil detection technology is proposed. The flow rate of metal contaminants in the oil will have a certain impact on the sensitivity of the output particle signal in terms of electromagnetic fields and circuits. The detection velocity is not only related to the sensitivity of the output particle signal, but also to the adaptability of high-speed and high-throughput in oil online monitoring. In this paper, based on a high-sensitivity inductive bridge, the eddy current effect of velocity in a time-harmonic magnetic field is theoretically analyzed and experimentally verified, the phenomenon of particle signal variation with velocity for different materials is analyzed and discussed, and finally the effect of velocity on the output signal of the processing circuit is also elaborated and experimentally verified. Experiments show that under the influence of the time-harmonic magnetic field, the increase of the velocity enhances the detection sensitivity of non-ferromagnetic metal particles and weakens the detection sensitivity of non-ferromagnetic particles. Under the influence of the processing circuit, different velocities will produce different signal gains, which will affect the stability of the signal at different velocities. Full article
Show Figures

Figure 1

19 pages, 3889 KiB  
Article
Horizontal Vibration Characteristics of a Tapered Pile in Arbitrarily Layered Soil
by Xiaoyan Yang, Guosheng Jiang, Hao Liu, Wenbing Wu, Guoxiong Mei and Zijian Yang
Energies 2022, 15(9), 3193; https://doi.org/10.3390/en15093193 - 27 Apr 2022
Cited by 4 | Viewed by 1377
Abstract
A tapered pile (TP) is a new type of pile with a good bearing capacity, and scholars have conducted in-depth research on its static bearing characteristics. However, there is relatively little research on its dynamic bearing characteristics. In this paper, the horizontal vibration [...] Read more.
A tapered pile (TP) is a new type of pile with a good bearing capacity, and scholars have conducted in-depth research on its static bearing characteristics. However, there is relatively little research on its dynamic bearing characteristics. In this paper, the horizontal vibration behavior of a tapered pile in arbitrarily layered soil is studied. Utilizing the Winkler foundation model and Timoshenko beam model to simulate pile-surrounding soil (PSS) and a tapered pile, respectively, the horizontal vibration model of a tapered pile embedded in layered soil was built. The analytical solutions for the horizontal displacement (HD), bending moment (BM), and shear force (SF) of a tapered pile were derived, and then the solutions for the horizontal dynamic impedance (HDI), rocking dynamic impedance (RDI), and horizontal-rocking coupling dynamic impedance (HRDI) of pile head were obtained. Using the present solutions, the effects of soil and pile properties on the horizontal vibration characteristics of a tapered pile were systemically studied. The ability of a tapered pile–soil system to resist horizontal vibration can be improved by strengthening the upper soil, but this ability cannot be further improved by increasing the thickness of the strengthened upper soil if its thickness is greater than the critical influence thickness. Full article
Show Figures

Figure 1

20 pages, 6222 KiB  
Article
Design of a Chipless RFID Tag to Monitor the Performance of Organic Coatings on Architectural Cladding
by Tim Savill and Eifion Jewell
Sensors 2022, 22(9), 3312; https://doi.org/10.3390/s22093312 - 26 Apr 2022
Cited by 4 | Viewed by 2051
Abstract
Coating degradation is a critical issue when steel surfaces are subject to weathering. This paper presents a chipless, passive antenna tag, which can be applied onto organically coated steel. Simulations indicated that changes associated with organic coating degradation, such as the formation of [...] Read more.
Coating degradation is a critical issue when steel surfaces are subject to weathering. This paper presents a chipless, passive antenna tag, which can be applied onto organically coated steel. Simulations indicated that changes associated with organic coating degradation, such as the formation of defects and electrolyte uptake, produced changes in the backscattered radar cross section tag response. This may be used to determine the condition of the organic coating. Simulating multiple aging effects simultaneously produced a linear reduction in tag resonant frequency, suggesting coating monitoring and lifetime estimation may be possible via this method. For coatings thinner than calculations would suggest to be optimum, it was found that the simulated response could be improved by the use of a thin substrate between the coated sample and the antenna without vastly affecting results. Experimental results showed that changes to the dielectric properties of the coating through both the uptake of water and chemical degradation were detected through changes in the resonant frequency. Full article
Show Figures

Figure 1

18 pages, 6402 KiB  
Article
Fault Detection of Aero-Engine Sensor Based on Inception-CNN
by Xiao Du, Jiajie Chen, Haibo Zhang and Jiqiang Wang
Aerospace 2022, 9(5), 236; https://doi.org/10.3390/aerospace9050236 - 25 Apr 2022
Cited by 13 | Viewed by 2725
Abstract
The aero-engine system is complex, and the working environment is harsh. As the fundamental component of the aero-engine control system, the sensor must monitor its health status. Traditional sensor fault detection algorithms often have many parameters, complex architecture, and low detection accuracy. Aiming [...] Read more.
The aero-engine system is complex, and the working environment is harsh. As the fundamental component of the aero-engine control system, the sensor must monitor its health status. Traditional sensor fault detection algorithms often have many parameters, complex architecture, and low detection accuracy. Aiming at this problem, a convolutional neural network (CNN) whose basic unit is an inception block composed of convolution kernels of different sizes in parallel is proposed. The network fully extracts redundant analytical information between sensors through different size convolution kernels and uses it for aero-engine sensor fault detection. On the sensor failure dataset generated by the Monte Carlo simulation method, the detection accuracy of Inception-CNN is 95.41%, which improves the prediction accuracy by 17.27% and 12.69% compared with the best-performing non-neural network algorithm and simple BP neural networks tested in the paper, respectively. In addition, the method simplifies the traditional fault detection unit composed of multiple fusion algorithms into one detection algorithm, which reduces the complexity of the algorithm. Finally, the effectiveness and feasibility of the method are verified in two aspects of the typical sensor fault detection effect and fault detection and isolation process. Full article
Show Figures

Figure 1

32 pages, 20624 KiB  
Article
Research on Damage Localization of Steel Truss–Concrete Composite Beam Based on Digital Orthoimage
by Rui Luo, Zhixiang Zhou, Xi Chu, Xiaoliang Liao and Junhao Meng
Appl. Sci. 2022, 12(8), 3883; https://doi.org/10.3390/app12083883 - 12 Apr 2022
Cited by 2 | Viewed by 1533
Abstract
Most structural health monitoring is carried out for a limited number of key measurement points of a bridge, and incomplete measurement data lead to incomplete mechanical equation inversion results, which is a key problem faced in bridge damage identification. The ability of digital [...] Read more.
Most structural health monitoring is carried out for a limited number of key measurement points of a bridge, and incomplete measurement data lead to incomplete mechanical equation inversion results, which is a key problem faced in bridge damage identification. The ability of digital images to holographically describe structural morphology can effectively alleviate the problem of damage identification due to incomplete test data. Based on digital image processing technology, a matrix similarity damage identification method based on a structural digital orthoimage was proposed. Firstly, a steel truss–concrete composite beam specimen with a complex support bar system was designed and fabricated in the laboratory, and the digital orthoimage of the test beam was obtained by the perspective transformation of the original image of the test beam. The body contour of the structure was extracted from the digital orthoimage of the test beam, and wavelet threshold denoising was performed on the lower edge profile to obtain the deflection curves of the structure under different working conditions. The verification results show that the maximum error of the deflection curve is 3.42%, which proves that the digital orthoimage can accurately and completely reflect the deformation of the structure. Finally, based on the digital orthophoto of the test beam, a matrix similarity test before and after the damage was carried out, and the results show that the singularities of the similarity distribution are consistent with the location of the damage; furthermore, the accurate positioning of the damage in different working conditions is achieved. Full article
Show Figures

Figure 1

19 pages, 3910 KiB  
Article
Damage Detection of Continuous Beam Bridge Based on Maximum Successful Approximation Approach of Wavelet Coefficients of Vehicle Response
by Kai Liu, Haopeng Qi and Zengshou Sun
Appl. Sci. 2022, 12(8), 3743; https://doi.org/10.3390/app12083743 - 08 Apr 2022
Cited by 1 | Viewed by 1660
Abstract
In view of problems such as closed traffic, the large number of sensors required, and the labor-intensive and time-consuming nature of previous bridge detection, this paper analyzes the dynamic response of the vehicle body of the continuous girder bridge under the action of [...] Read more.
In view of problems such as closed traffic, the large number of sensors required, and the labor-intensive and time-consuming nature of previous bridge detection, this paper analyzes the dynamic response of the vehicle body of the continuous girder bridge under the action of vehicle load. Based on theoretical analysis and formula derivation, a new method of bridge damage detection based on coupled vehicle–bridge vibration is conceived. This method can accurately identify the location of bridge damage and approximately estimate the degree of bridge damage. The method is as follows: Taking the continuous beam bridge as an example, first, use the tractor inspection vehicle model to drive over the continuous beam bridge before and after the damage, and collect the acceleration response of the vehicle body. Then, the acceleration response difference is transformed by wavelet transform. Furthermore, perform the innovative use of the maximum successive approximation approach to process wavelet transform coefficients, which can identify the location of the bridge damage. Additionally, study the impact of vehicle speed, vehicle weight, road surface roughness, and noise on this damage detection method. In addition, a method for judging bridge damage degree based on wavelet transform coefficients is proposed, and the judgment error basically meets the requirements. Full article
Show Figures

Figure 1

26 pages, 8503 KiB  
Article
Experimental Research on Vibration-Damping Effect of Combined Shear Hinge Prefabricated Steel Spring Floating Slab Track
by Zhiping Zeng, Xudong Huang, Zhuang Li, Weidong Wang, Zixiao Shi, Yu Yuan and Abdulmumin Ahmed Shuaibu
Sensors 2022, 22(7), 2567; https://doi.org/10.3390/s22072567 - 27 Mar 2022
Cited by 6 | Viewed by 1898
Abstract
Objective: The cast-in-place steel spring floating slab track (SSFST) is difficult to maintain and repair, while the mechanical strength of the end of the traditional prefabricated SSFST is poor. In order to overcome the above shortcomings, a shear-hinge-combined prefabricated SSFST was developed, and [...] Read more.
Objective: The cast-in-place steel spring floating slab track (SSFST) is difficult to maintain and repair, while the mechanical strength of the end of the traditional prefabricated SSFST is poor. In order to overcome the above shortcomings, a shear-hinge-combined prefabricated SSFST was developed, and an indoor test was carried out to analyze its vibration-damping effect. Methods: A combined shear hinge SSFST connection model with two length sizes was established. The dynamic response amplitude and frequency response characteristics of the foundation (ground) under different isolator installations and fatigue loads were studied, and the vibration-damping performance of two sizes of combined shear hinge SSFST was evaluated. Results: The vibration-damping effect of the steel spring vibration isolator mainly acts in the middle and low-frequency bands of 16–400 Hz, and the vibration near 10 Hz will be aggravated after the vibration isolator is installed. The vibration index and variation law of the two sizes of SSFST are similar, and the vibration response of 4.8 m SSFST is slightly less than 3.6 m SSFST. There is almost no change in each index when the load is 5 million times, and there is a certain range of change when the load is 10 million times, but the overall change is small. Conclusions: The combined shear hinge prefabricated SSFST can have an excellent isolation effect on vibration and can still maintain good vibration-damping ability within 10 million fatigue loads (about 5 years); 4.8 m SSFST should be laid in straight sections with higher train speeds, while 3.6 m SSFST should be applied in curved sections to ensure smooth lines. Full article
Show Figures

Figure 1

15 pages, 1384 KiB  
Perspective
Concept of Placement of Fiber-Optic Sensor in Smart Energy Transport Cable under Tensile Loading
by Monssef Drissi-Habti, Neginhal Abhijit, Manepalli Sriharsha, Valter Carvelli and Pierre-Jean Bonamy
Sensors 2022, 22(7), 2444; https://doi.org/10.3390/s22072444 - 22 Mar 2022
Cited by 10 | Viewed by 2072
Abstract
Due to the exponential growth in offshore renewable energies and structures such as floating offshore wind turbines and wave power converters, the research and engineering in this field is experiencing exceptional development. This emergence of offshore renewable energy requires power cables which are [...] Read more.
Due to the exponential growth in offshore renewable energies and structures such as floating offshore wind turbines and wave power converters, the research and engineering in this field is experiencing exceptional development. This emergence of offshore renewable energy requires power cables which are usually made up of copper to transport this energy ashore. These power cables are critical structures that must withstand harsh environmental conditions, handling, and shipping, at high seas which can cause copper wires to deform well above the limit of proportionality and consequently break. Copper, being an excellent electric conductor, has, however, very weak mechanical properties. If plasticity propagates inside copper not only will the mechanical properties be affected, but the electrical properties are also disrupted. Constantly monitoring such large-scale structures can be carried out by providing continuous strain using fiber-optic sensors (FOSs). The embedding of optical fibers within the cables (not within the phase) is practiced. Nevertheless, these optical fibers are first introduced into a cylinder of larger diameter than the optical fiber before this same fiber is embedded within the insulator surrounding the phases. Therefore, this type of embedding can in no way give a precise idea of the true deformation of the copper wires inside the phase. In this article, a set of numerical simulations are carried-out on a single phase (we are not yet working on the whole cable) with the aim of conceptualizing the placement of FOSs that will monitor strain and temperature within the conductor. It is well known that copper wire must never exceed temperatures above 90 °C, as this will result in shutdown of the whole system and therefore result in heavy maintenance, which would be a real catastrophe, economically speaking. This research explores the option of embedding sensors in several areas of the phase and how this can enable obtaining strain values that are representative of what really is happening in the conductor. It is, therefore, the primary objective of the current preliminary model to try to prove that the principle of embedding sensors in between copper wires can be envisaged, in particular to obtain an accurate idea about strain tensor of helical ones (multi-parameter strain sensing). The challenge is to ensure that they are not plastically deformed and hence able to transport electricity without exceeding or even becoming closer to 90 °C (fear of shutdown). The research solely focuses on mechanical aspects of the sensors. There are certainly some others, pertaining to sensors physics, instrumentation, and engineering, that are of prime importance, too. The upstream strategy of this research is to come up with a general concept that can be refined later by including, step by step, all the aspects listed above. Full article
Show Figures

Figure 1

19 pages, 2567 KiB  
Article
SDFormer: A Novel Transformer Neural Network for Structural Damage Identification by Segmenting the Strain Field Map
by Zhaoyang Li, Ping Xu, Jie Xing and Chengxing Yang
Sensors 2022, 22(6), 2358; https://doi.org/10.3390/s22062358 - 18 Mar 2022
Cited by 7 | Viewed by 2357
Abstract
Damage identification is a key problem in the field of structural health monitoring, which is of great significance to improve the reliability and safety of engineering structures. In the past, the structural strain damage identification method based on specific damage index needs the [...] Read more.
Damage identification is a key problem in the field of structural health monitoring, which is of great significance to improve the reliability and safety of engineering structures. In the past, the structural strain damage identification method based on specific damage index needs the designer to have rich experience and background knowledge, and the designed damage index is hard to apply to different structures. In this paper, a U-shaped efficient structural strain damage identification network SDFormer (structural damage transformer) based on self-attention feature is proposed. SDFormer regards the problem of structural strain damage identification as an image segmentation problem, and introduces advanced image segmentation technology for structural damage identification. This network takes the strain field map of the structure as the input, and then outputs the predicted damage location and level. In the SDFormer, the low-level and high-level features are smoothly fused by skip connection, and the self-attention module is used to obtain damage feature information, to effectively improve the performance of the model. SDFormer can directly construct the mapping between strain field map and damage distribution without complex damage index design. While ensuring the accuracy, it improves the identification efficiency. The effectiveness and accuracy of the model are verified by numerical experiments, and the performance of an advanced convolutional neural network is compared. The results show that SDFormer has better performance than the advanced convolutional neural network. Further, an anti-noise experiment is designed to verify the anti-noise and robustness of the model. The anti-noise performance of SDFormer is better than that of the comparison model in the anti-noise experimental results, which proves that the model has good anti-noise and robustness. Full article
Show Figures

Figure 1

16 pages, 4010 KiB  
Article
Numerical Simulation of Aging by Water-Trees of XPLE Insulator Used in a Single Hi-Voltage Phase of Smart Composite Power Cables for Offshore Farms
by Drissi-Habti Monssef, Manepalli Sriharsha, Neginhal Abhijit, Carvelli Valter and Bonamy Pierre-Jean
Energies 2022, 15(5), 1844; https://doi.org/10.3390/en15051844 - 02 Mar 2022
Cited by 4 | Viewed by 2085
Abstract
Submarine power cables are expected to last 20 years without maintenance to be considered technologically reliable enough and economically beneficial. One of the main issues facing this target is the development of what is called commonly water-trees (nanometer-sized flaws filled with residual humidity), [...] Read more.
Submarine power cables are expected to last 20 years without maintenance to be considered technologically reliable enough and economically beneficial. One of the main issues facing this target is the development of what is called commonly water-trees (nanometer-sized flaws filled with residual humidity), that form within XLPE (cross-linked Polyethylene) insulators and then migrate towards copper, thus leading to its corrosion and further to possible shut-down. Water trees are resulting from the coalescence of nanovoids filled with residual humidity that migrate towards copper under the combined effects of electrical forces and plastic deformation. The nanovoids are originated during manufacturing, shipping, handling and embedding in deep seas. The formation of these nanovoids leads to the degradation of the service lifetime of submarine power cables. Current research is intended to come up with a way to go a little further towards the generalization of coalescence of n nanovoids. In the perspective of multi-physics modeling, a preliminary 3D finite element model was built. Although water voids are distributed randomly inside XLPE, in this study, two extreme cases where the voids are present parallel and perpendicular to the copper surface, were considered for simplification. This will enable checking the electric field effect on neighbouring voids, in both cases as well as the influence of the proximity of the conductor on the plasticity of voids, that further leads to their coalescence. It is worthwhile to note that assessing water-trees formation and propagation through an experimental campaign of ageing tests may extend over decades. It would therefore be an exceptional opportunity to be able to get insight into this mechanism through numerical modeling that needs a much shorter time. The premilinary model suggested is expected to be extended in the future so that to include more variables (distribution and shapes of nano-voids, water pressure, molecular modeling, electric discharge. Full article
Show Figures

Figure 1

23 pages, 6261 KiB  
Article
Gearbox Fault Diagnosis Based on Improved Variational Mode Extraction
by Yuanjing Guo, Shaofei Jiang, Youdong Yang, Xiaohang Jin and Yanding Wei
Sensors 2022, 22(5), 1779; https://doi.org/10.3390/s22051779 - 24 Feb 2022
Cited by 12 | Viewed by 2346
Abstract
Gearboxes are widely used in drive systems of rotating machinery. The health status of gearboxes considerably influences the normal and reliable operation of rotating machinery. When a gearbox experiences tooth failure, a vibration signal with impulse features is excited. However, these impulse features [...] Read more.
Gearboxes are widely used in drive systems of rotating machinery. The health status of gearboxes considerably influences the normal and reliable operation of rotating machinery. When a gearbox experiences tooth failure, a vibration signal with impulse features is excited. However, these impulse features tend to be relatively weak and difficult to extract. To solve this problem, a novel approach for gearbox fault feature extraction and fault diagnosis based on improved variational mode extraction (VME) is proposed. Since the initial value of the desired mode center frequency and the value of the penalty parameter in VME must be assigned, a short-time Fourier transform (STFT) was performed, and a new index, the standard deviation of differential values of envelope maxima positions (SDE), is proposed. The feasibility and effectiveness of the proposed approach was verified by a simulation signal and two datasets associated with a gearbox test bench. The results demonstrate that the VME-based approach outperforms the variational mode decomposition (VMD) approach. Full article
Show Figures

Figure 1

15 pages, 3920 KiB  
Article
Guided Wave Phase Velocity Dispersion Reconstruction Based on Enhanced Phased Spectrum Method
by Vykintas Samaitis and Liudas Mažeika
Materials 2022, 15(4), 1614; https://doi.org/10.3390/ma15041614 - 21 Feb 2022
Cited by 1 | Viewed by 1745
Abstract
Fibre-reinforced composite laminates are frequently used in various engineering structures, due to their increased weight-to-stiffness ratio, which allows to fulfil certain regulations of CO2 emissions. Limited inter-laminar strength makes composites prone to formation of various defects, which leads to progressive degradation of [...] Read more.
Fibre-reinforced composite laminates are frequently used in various engineering structures, due to their increased weight-to-stiffness ratio, which allows to fulfil certain regulations of CO2 emissions. Limited inter-laminar strength makes composites prone to formation of various defects, which leads to progressive degradation of residual strength and fatigue life of the structure. Using ultrasonic guided waves is a common technique for assessing the structural integrity of composite laminates. Phase velocity is one of the fundamental characteristics of guided waves and can be used for defect detection, material property estimation, and evaluation of dispersion. In this paper, a phase velocity reconstruction approach, based on the phase-shift method, was proposed, which uses frequency sweep excitation to estimate velocity at specific frequency harmonics. In contrast to the conventional phase spectrum technique, the proposed approach is applicable to the narrowband piezoelectric transducers and suitable for the reconstruction of dispersion curves for direct, converted, and multiple co-existing modes with high accuracy. The proposed technique was validated with finite element simulations and experiments, both on isotropic and anisotropic structures, analysing the direct, converted, and overlapped modes. The results demonstrated that, using the proposed technique, the phase velocity dispersion can be reconstructed at −20 dB level bandwidth of the transducer, with a relative error of ±4%, compared to the theoretical velocity predictions. Full article
Show Figures

Figure 1

13 pages, 2331 KiB  
Article
Percussion-Based Pipeline Ponding Detection Using a Convolutional Neural Network
by Dan Yang, Mengzhou Xiong, Tao Wang and Guangtao Lu
Appl. Sci. 2022, 12(4), 2127; https://doi.org/10.3390/app12042127 - 18 Feb 2022
Cited by 7 | Viewed by 1620
Abstract
Pipeline transportation is the main method for long-distance gas transportation; however, ponding in the pipeline can affect transportation efficiency and even cause corrosion to the pipeline in some cases. A non-destructive method to detect pipeline ponding using percussion acoustic signals and a convolution [...] Read more.
Pipeline transportation is the main method for long-distance gas transportation; however, ponding in the pipeline can affect transportation efficiency and even cause corrosion to the pipeline in some cases. A non-destructive method to detect pipeline ponding using percussion acoustic signals and a convolution neural network (CNN) is proposed in this paper. During the process of detection, a constant energy spring impact hammer is used to apply an impact on the pipeline, and the percussive acoustic signals are collected. A Mel spectrogram is used to extract the acoustic feature of the percussive acoustic signal with different ponding volumes in the pipeline. The Mel spectrogram is transferred to the input layer of the CNN and the convolutional kernel matrix of the CNN realizes the recognition of pipeline ponding volume. The recognition results show that the CNN can identify the amount of pipeline ponding with the percussive acoustic signals, which use the Mel spectrogram as the acoustic feature. Compared with the support vector machine (SVM) model and the decision tree model, the CNN model has better recognition performance. Therefore, the percussion-based pipeline ponding detection using the convolutional neural network method proposed in this paper has high application potential. Full article
Show Figures

Figure 1

17 pages, 32376 KiB  
Article
A New Design of the Dual-Mode and Pure Longitudinal EMAT by Using a Radial-Flux-Focusing Magnet
by Xu Zhang, Weiwen Li, Bo Li, Jun Tu, Chunhui Liao, Qiao Wu, Sheng Feng and Xiaochun Song
Sensors 2022, 22(4), 1316; https://doi.org/10.3390/s22041316 - 09 Feb 2022
Cited by 6 | Viewed by 2225
Abstract
An electromagnetic acoustic transducer (EMAT) is suitable for measuring the propagation time more accurately without causing abrasion to the transducer during testing due to the principle of its excitation. This work designs a flux-concentrating EMAT with a radial-flux-focusing permanent magnet to significantly enhance [...] Read more.
An electromagnetic acoustic transducer (EMAT) is suitable for measuring the propagation time more accurately without causing abrasion to the transducer during testing due to the principle of its excitation. This work designs a flux-concentrating EMAT with a radial-flux-focusing permanent magnet to significantly enhance static magnetic field strength. Through theoretical analysis and finite element simulation, two kinds of coils are designed according to the concentration areas of the horizontal and vertical components of the magnetic field. One is used to generate pure longitudinal waves, and the other is used to generate both longitudinal waves and shear waves. The experimental comparison shows that the amplitudes of the pure longitudinal wave and the dual-mode wave excited by the two kinds of coils with the radial-flux-focusing magnet are more than two times higher than those with the ordinary magnet. Therefore, the flux-concentrating EMAT with the appropriate coil provides an insight into realizing more accurate detection where longitudinal wave detection is required. Full article
Show Figures

Figure 1

15 pages, 8063 KiB  
Article
A Filtering Method for Suppressing the Lift-Off Interference in Magnetic Flux Leakage Detection of Rail Head Surface Defect
by Yinliang Jia, Yichen Lu, Longhui Xiong, Yuhua Zhang, Ping Wang and Huangjian Zhou
Appl. Sci. 2022, 12(3), 1740; https://doi.org/10.3390/app12031740 - 08 Feb 2022
Cited by 7 | Viewed by 1751
Abstract
Magnetic flux leakage (MFL) detection is a common nondestructive detection method which is usually used to detect the surface defects of steel pipes and rails. To suppress the interference of lift-off on the detection signal of the defects in rail head surfaces, a [...] Read more.
Magnetic flux leakage (MFL) detection is a common nondestructive detection method which is usually used to detect the surface defects of steel pipes and rails. To suppress the interference of lift-off on the detection signal of the defects in rail head surfaces, a filtering method is proposed according to the distribution characteristics of the defect leakage magnetic field (LMF) in different directions. The sensor array is used to confirm the reference signal according to the difference between the signals in x and z directions. The installation mode of the sensors is deduced according to the distribution of the defect LMF. The experimental results show that this method can effectively suppress the lift-off interference in the MFL signal of the defects in the rail head surfaces. Full article
Show Figures

Figure 1

14 pages, 5446 KiB  
Article
Verification of Tensile Force Estimation Method for Temporary Steel Rods of FCM Bridges Based on Area of Magnetic Hysteresis Curve Using Embedded Elasto-Magnetic Sensor
by Won-Kyu Kim, Junkyeong Kim, Jooyoung Park, Ju-Won Kim and Seunghee Park
Sensors 2022, 22(3), 1005; https://doi.org/10.3390/s22031005 - 27 Jan 2022
Cited by 2 | Viewed by 2559
Abstract
The free cantilever method (FCM) is a bridge construction method in which the left and right segments are joined in sequence from a pier without using a bottom strut. To support the imbalance of the left and right moments during construction, temporary steel [...] Read more.
The free cantilever method (FCM) is a bridge construction method in which the left and right segments are joined in sequence from a pier without using a bottom strut. To support the imbalance of the left and right moments during construction, temporary steel rods, upon which tensile force is applied that cannot be managed after construction, are embedded in the pier. If there is an excessive loss of tensile force applied to the steel rods, the segments can collapse owing to the unbalanced moment, which may cause personal and property damage. Therefore, it is essential to monitor the tensile force in the temporary steel rods to prevent such accidents. In this study, a tensile force estimation method for the temporary steel rods of an FCM bridge using embedded Elasto-Magnetic (EM) sensors was proposed. After the tensile force was applied to the steel rods, the change in tensile force was monitored according to the changing area of a magnetic hysteresis curve, as measured by the embedded EM sensors. To verify the field applicability of the proposed method, the EM sensors were installed in an FCM bridge pier under construction. The three sensors were installed in conjunction with a sheath tube, and the magnetic hysteresis curve was measured over nine months. Temperature data from the measurement period were used to compensate for the error due to daily temperature fluctuations. The estimated tensile force was consistent with an error range of ±4% when compared with the reference value measured by the load cell. Based on the results of this experiment, the applicability of the proposed method was demonstrated. Full article
Show Figures

Figure 1

17 pages, 7747 KiB  
Article
Crack Detection in Frozen Soils Using Infrared Thermographic Camera
by Yang Zhao, Yufan Han, Cheng Chen and Hyungjoon Seo
Sensors 2022, 22(3), 885; https://doi.org/10.3390/s22030885 - 24 Jan 2022
Cited by 7 | Viewed by 2526
Abstract
Frozen soils are encountered on construction sites in the polar regions or regions where artificial frozen ground (AFG) methods are used. Thus, efficient ways to monitor the behavior and potential failure of frozen soils are currently in demand. The advancement of thermographic technology [...] Read more.
Frozen soils are encountered on construction sites in the polar regions or regions where artificial frozen ground (AFG) methods are used. Thus, efficient ways to monitor the behavior and potential failure of frozen soils are currently in demand. The advancement of thermographic technology presents an alternative solution as deformation occurring in frozen soils generate heat via inter-particle friction, and thus a subsequent increase in temperature. In this research, uniaxial compression tests were conducted on cylindrical frozen soil specimens of three types, namely clay, sand, and gravel. During the tests, surface temperature profiles of the specimens were recorded through an infrared video camera. The thermographic videos were analyzed, and subsequent results showed that temperature increases caused by frictional heat could be observed in all three frozen soil specimens. Therefore, increases in temperature can be deemed as an indicator for the potential failure of frozen soils and this method is applicable for monitoring purposes. Full article
Show Figures

Figure 1

13 pages, 5236 KiB  
Article
A Characterization Method for Pavement Structural Condition Assessment Based on the Distribution Parameter of the Vehicle Vibration Signal
by Weiguo Wang, Shishi Zhou and Qun Yang
Appl. Sci. 2022, 12(2), 683; https://doi.org/10.3390/app12020683 - 11 Jan 2022
Cited by 5 | Viewed by 1395
Abstract
A pavement structural survey plays a vital role in road maintenance and management. This study was intended to explore the feasibility of a non-stop pavement structure assessment method by analyzing the vibration data from a vehicle sensor. In this study, three falling weight [...] Read more.
A pavement structural survey plays a vital role in road maintenance and management. This study was intended to explore the feasibility of a non-stop pavement structure assessment method by analyzing the vibration data from a vehicle sensor. In this study, three falling weight deflectometer (FWD) tests and four vehicle vibration tests were conducted on five pavement structures. The FWD test results show that the continuously reinforced composite pavement has a higher structural stiffness than the semi-rigid base asphalt pavement. According to the statistical distribution of vehicle acceleration, a distribution parameter, the peak probability density (PPD), was proposed. The correlation coefficient (−0.722) of the center deflection (D1) and PPD indicates a strong correlation between the two variables. Therefore, PPD is strongly correlated with pavement structural stiffness. This study proposed a novel characterization method for pavement structural conditions based on the distribution parameter of the vehicle vibration signal. Full article
Show Figures

Figure 1

15 pages, 3629 KiB  
Article
The Dependence of Ultrasonic Velocity in Ultra-Low Expansion Glass on Temperature
by Wenqing Wei, Yongfeng Zhang, Zongzheng Du, Minwei Song, Yuanyuan Zhang and Hong Liu
Appl. Sci. 2022, 12(2), 577; https://doi.org/10.3390/app12020577 - 07 Jan 2022
Cited by 1 | Viewed by 1617
Abstract
The coefficient of thermal expansion (CTE) is an important property of ultra-low expansion (ULE) glass, and the ultrasonic velocity method has shown excellent performance for the nondestructive measurement of CTE in large ULE glass. In this method, the accurate acquisition of the ultrasonic [...] Read more.
The coefficient of thermal expansion (CTE) is an important property of ultra-low expansion (ULE) glass, and the ultrasonic velocity method has shown excellent performance for the nondestructive measurement of CTE in large ULE glass. In this method, the accurate acquisition of the ultrasonic velocity in ULE glass is necessary. Herein, we present a correlation method to determine the ultrasonic TOF in ULE glass and to further obtain the ultrasonic longitudinal wave velocity (cL) indirectly. The performance of this method was verified by simulations. Considering the dependence of cL on temperature (T), we carried out the derivation of the analytical model between cL and T. Based on reasonable constant assumptions in the physical sense, a cLT exponential model was produced, and some experimental results support this model. Additional experiments were carried out to validate the accuracy of the cLT exponential model. The studies we conducted indicate that the cLT exponential model can reliably predict the ultrasonic velocity in ULE glass at different temperatures, providing a means for the nondestructive CTE measurement of large ULE glass at a specified temperature. Full article
Show Figures

Figure 1

42 pages, 3178 KiB  
Review
A Review of Infrared Thermography for Delamination Detection on Infrastructures and Buildings
by Ko Tomita and Michael Yit Lin Chew
Sensors 2022, 22(2), 423; https://doi.org/10.3390/s22020423 - 06 Jan 2022
Cited by 39 | Viewed by 4854
Abstract
This paper provides a comprehensive review on the use of infrared thermography to detect delamination on infrastructures and buildings. Approximately 200 pieces of relevant literature were evaluated, and their findings were summarized. The factors affecting the accuracy and detectability of infrared thermography were [...] Read more.
This paper provides a comprehensive review on the use of infrared thermography to detect delamination on infrastructures and buildings. Approximately 200 pieces of relevant literature were evaluated, and their findings were summarized. The factors affecting the accuracy and detectability of infrared thermography were consolidated and discussed. Necessary measures to effectively capture latent defects at the early stage of delamination before crack formation were investigated. The results of this study could be used as the benchmarks for setting standardized testing criteria as well as for comparison of results for future works on the use of infrared thermography for detection of delamination on infrastructures and buildings. Full article
Show Figures

Figure 1

11 pages, 3810 KiB  
Article
Improvement of Performance for Raman Assisted BOTDR by Analyzing Brillouin Gain Spectrum
by Qiang Huang, Junqiang Sun, Wenting Jiao and Li Kai
Sensors 2022, 22(1), 116; https://doi.org/10.3390/s22010116 - 24 Dec 2021
Cited by 2 | Viewed by 2151
Abstract
We propose a simplified partitioned Brillouin gain spectrum (BGS) analysis method to enhance the spatial resolution and measurement accuracy of a Brillouin optical time-domain reflectometer (BOTDR) assisted by a first-order Raman pump. We theoretically derive the mathematical model of the partitioned BGS and [...] Read more.
We propose a simplified partitioned Brillouin gain spectrum (BGS) analysis method to enhance the spatial resolution and measurement accuracy of a Brillouin optical time-domain reflectometer (BOTDR) assisted by a first-order Raman pump. We theoretically derive the mathematical model of the partitioned BGS and analyze the superposition process of sub-Brillouin signals within a theoretical spatial resolution range. We unified all the unknown constant parameters of the calculation process to simplify the partitioned BGS analysis method and the value of the uniform parameter is attained through the system test data and numerical analysis. Moreover, to automate data processing, the starting point of the temperature/strain change is determined by the first occurrence of the maximum Brillouin frequency shift (BFS), then the position where the partitioned BGS analysis method calculation begins is obtained. Using a 100 ns probe pulse and partitioned BGS analysis method, we obtain a spatial resolution of 0.4 m in the 78.45-km-long Raman-assisted BOTDR system, and the measurement accuracy is significantly improved. In addition, we achieve a strain accuracy of 5.6 με and a spatial resolution of 0.4 m in the 28.5-km-long BOTDR without Raman amplification. Full article
Show Figures

Figure 1