Submit to Sensors Review for Sensors Propose a Special Issue

Journal Menu

Journal Browser

► Journal Browser

Sensors for Vibration Control and Structural Health Monitoring

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Keywords
Published Papers

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 8322

Share This Special Issue

Special Issue Editors

Dr. Fook Fah Yap

E-Mail Website
Guest Editor

School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore
Interests: vehicle dynamics; micro-mobility; dynamics of damped structures and vibration control using magneto-rheological fluid damping technology; structural dynamics and vibrations; flywheel energy storage systems; virtual prototyping and simulation of complex mechanical systems
Special Issues, Collections and Topics in MDPI journals

Dr. Nader Vahdati

E-Mail Website
Guest Editor

Mechanical Engineering Department, Healthcare Engineering Innovation Center (HEIC), SAN Campus, Khalifa University, Abu Dhabi 127788, United Arab Emirates
Interests: vibrations; acoustics; SHM; sensors

Special Issue Information

Dear Colleagues,

Vibration, strain, and temperature sensors are often essential for condition and structural health monitoring (SHM). Today's sensors can be highly sensitive, ruggedized, miniaturized, distributed, wireless, telemetric, and ultra-low-power consumption. They enable a huge amount of data to be tracked in real time, over vast distances, and often in hostile environments. Much research is ongoing in sensor and condition monitoring technologies.

Industries that can benefit from the use of advanced sensors are those that operate and maintain machinery, vehicles, buildings, bridges, railways, and other infrastructure. Monitoring and analysis can help to determine the root cause of failure of a piece of equipment or structure. In predictive maintenance, condition monitoring is often used to warn of an impending problem so corrective measures can be taken early to prevent failure.

We invite you to submit original research articles to a new Special Issue, entitled "Sensors for Vibration Control and Structural Health Monitoring", in our open-access journal Sensors. The Special Issue aims to highlight advances in sensor technologies for vibration control and SHM. It also aims to share novel sensor applications to solve challenging condition monitoring problems.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) applications in the following:

Oil and gas
Renewable power
Transportation
Manufacturing
Processing

We look forward to receiving your contributions.

Dr. Fook Fah Yap
Dr. Nader Vahdati
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

condition monitoring
structural health monitoring
vibration
accelerometers
predictive maintenance
damage detection
optical fiber sensors
wireless sensors

Published Papers (7 papers)

Download All Papers

Order results

Result details

Show export options Show export options

Select all

Export citation of selected articles as:

Research

15 pages, 4120 KiB

Open AccessArticle

Study of the Prediction of Vibrations in Soft Soil Foundations Based on Field Tests

by Jiaxin Lin, Nan Zhang and Yunshi Zhang

Sensors 2024, 24(8), 2564; https://doi.org/10.3390/s24082564 - 17 Apr 2024

Viewed by 440

Abstract

To explore the prediction of vibrations in soft soil foundations, in light of the construction of laboratories with microvibration requirements on soft soil foundations which are subject to the limitations of urban land planning, field testing was conducted, and the soil surface vibration responses were recorded at different distances from a road under various highway traffic loads. By analyzing the data which summarize the characteristics of soft soil foundations, it is clarified that the vibration response of soft soil foundations mainly occurs at low frequencies, and the vibration response under road traffic loads is prone to resonance at the natural frequency of soft soil foundations. Subsequently, a new vibration prediction method based on the vibration transmission ratio is proposed, and its effectiveness and accuracy based on transmissibility are verified. This research study provides a reference for laboratories constructed on soft soil and for surrounding traffic planning. Full article

(This article belongs to the Special Issue Sensors for Vibration Control and Structural Health Monitoring)

► Show Figures

Figure 1

25 pages, 10207 KiB

Open AccessArticle

Study on the Equivalence Transformation between Blasting Vibration Velocity and Acceleration

by Chong Yu, Jiajun Wu, Haibo Li, Yongan Ma and Changjian Wang

Sensors 2024, 24(6), 1727; https://doi.org/10.3390/s24061727 - 7 Mar 2024

Viewed by 603

Abstract

The evaluation of blasting vibrations primarily hinges on two physical quantities: velocity and acceleration. A significant challenge arises when attempting to reference the two types of vibration data in relation to one another, such as different types of seismometers, noise, etc., necessitating a method for their equivalent transformation. To address this, a transformation method is discussed in detail with a case study, and equations for the ratio (Ra) of the particle peak velocity (PPV) to the particle peak acceleration (PPA) are proposed. The findings are twofold: (1) The conventional data conversion processes often suffer from low accuracy due to the presence of trend terms and noise in the signal. To mitigate this, the built-in MATLAB function is used for trend term elimination, complemented by a combined approach that integrates CEEMDAN with WD/WDP for noise reduction. These significantly enhance the accuracy of the transformation. (2) This analysis reveals a positive power function correlation between Ra and the propagation distance of the blast vibrations, contrasted by a negative correlation with the maximum charge per delay. Intriguingly, the Ra values observed in pre-splitting blasting operations are consistently lower than those in bench blasting. The established Ra equations offer a rapid, direct method for assessing the transformation between the PPV and PPA, providing valuable insights for the optimization of blasting design. Full article

(This article belongs to the Special Issue Sensors for Vibration Control and Structural Health Monitoring)

► Show Figures

Figure 1

20 pages, 6457 KiB

Open AccessArticle

Shape Sensing in Plate Structures through Inverse Finite Element Method Enhanced by Multi-Objective Genetic Optimization of Sensor Placement and Strain Pre-Extrapolation

by Emiliano Del Priore and Luca Lampani

Sensors 2024, 24(2), 608; https://doi.org/10.3390/s24020608 - 18 Jan 2024

Cited by 1 | Viewed by 727

Abstract

The real-time reconstruction of the displacement field of a structure from a network of in situ strain sensors is commonly referred to as “shape sensing”. The inverse finite element method (iFEM) stands out as a highly effective and promising approach to perform this task. In the current investigation, this technique is employed to monitor different plate structures experiencing flexural and torsional deformation fields. In order to reduce the number of installed sensors and obtain more accurate results, the iFEM is applied in synergy with smoothing element analysis (SEA), which allows the pre-extrapolation of the strain field over the entire structure from a limited number of measurement points. For the SEA extrapolation to be effective for a multitude of load cases, it is necessary to position the strain sensors appropriately. In this study, an innovative sensor placement strategy that relies on a multi-objective genetic algorithm (NSGA-II) is proposed. This approach aims to minimize the root mean square error of the pre-extrapolated strain field across a set of mode shapes for the examined plate structures. The optimized strain reconstruction is subsequently utilized as input for the iFEM technique. Comparisons are drawn between the displacement field reconstructions obtained using the proposed methodology and the conventional iFEM. In order to validate such methodology, two different numerical case studies, one involving a rectangular cantilevered plate and the other encompassing a square plate clamped at the edges, are investigated. For the considered case studies, the results obtained by the proposed approach reveal a significant improvement in the monitoring capabilities over the basic iFEM algorithm with the same number of sensors. Full article

(This article belongs to the Special Issue Sensors for Vibration Control and Structural Health Monitoring)

► Show Figures

Figure 1

23 pages, 8436 KiB

Open AccessArticle

Sensitivity of Mass Geometry Parameters on E-Scooter Comfort: Design Guide

by Juan David Cano-Moreno, José Manuel Arenas Reina, Victorina del Carmen Parra Lanillos and Manuel Enrique Islán Marcos

Sensors 2024, 24(2), 399; https://doi.org/10.3390/s24020399 - 9 Jan 2024

Viewed by 842

Abstract

E-scooter vibrations are a problem recently studied. Theoretical models based on dynamic simulations and also real measurements have confirmed the high impact of e-scooter vibrations on driver comfort and health. Some authors recommend improving e-scooter damping systems, including tyres. However, it has not been suggested nor has any research been published studying how to improve e-scooter frame design for reducing driver vibrations and improving comfort. In this paper, we have modelled a real e-scooter to have a reference. Then, we have developed a multibody dynamic model for running dynamic simulations studying the influence of mass geometry parameters of the e-scooter frame (mass, centre of gravity and inertia moment). Acceleration results have been analysed based on the UNE-2631 standard for obtaining comfort values. Based on results, a qualitative e-scooter frame design guide for mitigating vibrations and increasing the comfort of e-scooter driver has been developed. Some application cases have been running on the multibody dynamic simulation model, finding improvements of comfort levels higher than 9% in comparison with the e-scooter reference model. The dynamic model has been qualitatively validated from real measurements. In addition, a basic sensor proposal and comfort colour scale is proposed for giving feedback to e-scooter drivers. Full article

(This article belongs to the Special Issue Sensors for Vibration Control and Structural Health Monitoring)

► Show Figures

Figure 1

24 pages, 7103 KiB

Open AccessArticle

A Developed Jerk Sensor for Seismic Vibration Measurements: Modeling, Simulation and Experimental Verification

by Mostafa M. Geriesh, Ahmed M. R. Fath El-Bab, Wael Khair-Eldeen, Hassan A. Mohamadien and Mohsen A. Hassan

Sensors 2023, 23(12), 5730; https://doi.org/10.3390/s23125730 - 20 Jun 2023

Cited by 2 | Viewed by 1710

Abstract

Acceleration-based sensors are widely used in indicating the severity of damage caused to structural buildings during dynamic events. The force rate of change is of interest when investigating the effect of seismic waves on structural elements, and hence the calculation of the jerk is necessary. For most sensors, the technique used for measuring the jerk (m/s³) is based on differentiating the time–acceleration signal. However, this technique is prone to errors especially in small amplitude and low frequency signals, and is deemed not suitable when online feedback is required. Here, we show that direct measurement of the jerk can be achieved using a metal cantilever and a gyroscope. In addition, we focus on the development of the jerk sensor for seismic vibrations. The adopted methodology optimized the dimensions of an austenitic stainless steel cantilever and enhanced the performance in terms of sensitivity and the jerk measurable range. We found, after several analytical and FE analyses, that an L-35 cantilever model with dimensions 35 × 20 × 0.5 (mm³) and a natural frequency of 139 (Hz) has a remarkable performance for seismic measurements. Our theoretical and experimental results show that the L-35 jerk sensor has a constant sensitivity value of 0.05 ((deg/s)/(G/s)) with ±2% error in the seismic frequency bandwidth of 0.1~40 (Hz) and for amplitudes in between 0.1 and 2 (G). Furthermore, the theoretical and experimental calibration curves show linear trends with a high correlation factor of 0.99 and 0.98, respectively. These findings demonstrate the enhanced sensitivity of the jerk sensor, which surpasses previously reported sensitivities in the literature. Full article

(This article belongs to the Special Issue Sensors for Vibration Control and Structural Health Monitoring)

► Show Figures

Figure 1

14 pages, 4341 KiB

Open AccessArticle

Quaternion Wavelet Transform and a Feedforward Neural Network-Aided Intelligent Distributed Optical Fiber Sensing System

by Lei Fan, Yongjun Wang, Hongxin Zhang, Chao Li, Xingyuan Huang, Qi Zhang and Xiangjun Xin

Sensors 2023, 23(7), 3637; https://doi.org/10.3390/s23073637 - 31 Mar 2023

Cited by 2 | Viewed by 1328

Abstract

In this paper, aiming at a large infrastructure structural health monitoring network, a quaternion wavelet transform (QWT) image denoising algorithm is proposed to process original data, and a depth feedforward neural network (FNN) is introduced to extract physical information from the denoised data. A Brillouin optical time domain analysis (BOTDA)-distributed sensor system is established, and a QWT denoising algorithm and a temperature extraction scheme using FNN are demonstrated. The results indicate that when the frequency interval is less than 4 MHz, the temperature error is kept within ±0.11 °C, but is ±0.15 °C at 6 MHz. It takes less than 17 s to extract the temperature distribution from the FNN. Moreover, input vectors for the Brillouin gain spectrum with a frequency interval of no more than 6 MHZ are unified into 200 input elements by linear interpolation. We hope that with the progress in technology and algorithm optimization, the FNN information extraction and QWT denoising technology will play an important role in distributed optical fiber sensor networks for real-time monitoring of large-scale infrastructure. Full article

(This article belongs to the Special Issue Sensors for Vibration Control and Structural Health Monitoring)

► Show Figures

Figure 1

28 pages, 10435 KiB

Open AccessArticle

Cost-Effective Corrosion Detection Sensor for Above-Ground Oil and Gas Flowlines

by Nader Vahdati, Oleg Shiryayev, Shahid M. Parapurath, Fook F. Yap and Haider Butt

Sensors 2022, 22(21), 8489; https://doi.org/10.3390/s22218489 - 4 Nov 2022

Cited by 2 | Viewed by 1881

Abstract

A sensor for monitoring of the external corrosion of small-diameter aboveground oil and gas pipelines (called flowlines), based on fiber-optic strain sensing, is proposed. The working principle of our proposed sensor relies on the use of a pre-stressed sacrificial structure made of the same material as the pipeline and monitoring changes in the measured strain that occur due to deterioration caused by corrosion to the structure. We present the development of analytical equations that allow designing the sensor structure to achieve the desired strain values. The analysis was verified using commercial finite element analysis (FEA) software. The proposed sensor is simple and cost-effective and can be easily manufactured. It can be deployed on existing overground pipelines without any modification to the pipeline structure. While it is not capable of measuring the corrosion rate continuously, it can provide a measurement of the average corrosion rate over the life span of its sacrificial metal structure. Full article

(This article belongs to the Special Issue Sensors for Vibration Control and Structural Health Monitoring)

► Show Figures

Journal Menu

Journal Browser

Sensors for Vibration Control and Structural Health Monitoring

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Published Papers (7 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI