Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
3.1
3.8
Journals
Buildings
Special Issues
Advances in Structural Health Monitoring and Damage Identification
share announcement

Advances in Structural Health Monitoring and Damage Identification

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Building Structures".

Deadline for manuscript submissions: 31 May 2024 | Viewed by 3107

Special Issue Editors

Dr. Shuli Fan

E-Mail Website
Guest Editor
State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China
Interests: structural health monitoring; earthquake engineering; finite element modeling; experimental testing; vulnerability assessment
Special Issues, Collections and Topics in MDPI journals
Dr. Weijie Li

E-Mail Website
Guest Editor
School of Civil Engineering, Dalian University of Technology, Dalian 116024, China
Interests: structural health monitoring; smart materials and structures

Special Issue Information

Dear Colleagues,

We are pleased to invite you to contribute to the Special Issue "Advances in Structural Health Monitoring and Damage Identification".

Structural health monitoring (SHM) enables us to implement damage identification strategies for civil engineering structures using sensory systems. It provides additional information to evaluate the safety of structures throughout their life. Recent advances in sensors, intelligent data analytic tools and damage identification methods have opened a new paradigm for SHM as a data drive remedy for structural safety with the benefits of cost-effectiveness and real-time operation.

The aim of this Special Issue is to bring together original research and review articles discussing new smart sensors, sensor networks, intelligent SHM techniques, approaches to damage detection, model updating and safety evaluation, and the design and implementation of SHM systems for practical civil infrastructure.

Potential topics include, but are not limited to, the following:

  1. Smart sensors, piezoelectric sensors, and other types of sensors used in SHM.
  2. Innovative sensing technologies, the optimal placement of sensors, and sensor networks for SHM.
  3. Advanced data processing techniques, big data, and intelligent monitoring techniques for SHM.
  4. Qualitative or quantitative evaluation methods based on monitoring databases.
  5. Multisensor, multisource information fusion techniques for SHM.
  6. Object identification, damage identification, loading identification, and modal identification.

Dr. Shuli Fan
Dr. Weijie Li
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. Buildings is an international peer-reviewed open access monthly 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

  • structural health monitoring
  • non-destructive technology
  • damage identification
  • smart sensors
  • intelligent monitoring
  • multisource information fusion
  • ultrasonic-based SHM
  • piezoelectric-based smart sensors
  • machine learning for damage detection
  • digital twins for damage detection

Published Papers (4 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

19 pages, 16246 KiB  
Article
Multi-Span Box Girder Bridge Sensitivity Analysis in Response to Damage Scenarios
by Marame Brinissat, Richard Paul Ray and Rajmund Kuti
Buildings 2024, 14(3), 667; https://doi.org/10.3390/buildings14030667 - 02 Mar 2024
Viewed by 489
Abstract
Due to their distinct features, including structural simplicity and exceptional load-carrying capacity, steel box girder bridges play a critical role in transportation networks. However, they are categorized as fracture-critical structures and face significant challenges. These challenges stem from the overloading and the relentless [...] Read more.
Due to their distinct features, including structural simplicity and exceptional load-carrying capacity, steel box girder bridges play a critical role in transportation networks. However, they are categorized as fracture-critical structures and face significant challenges. These challenges stem from the overloading and the relentless effects of corrosion and aging on critical structural components. As a result, these bridges require thorough inspections to ensure their safety and integrity. This paper introduces generalized approaches based on vibration-based structural health monitoring in response to this need. This approach assesses the condition of critical members in a steel girder bridge and evaluates their sensitivity to damage. A rigorous analytical evaluation demonstrated the effectiveness of the proposed approach in evaluating the Szapáry multi-span continuous highway bridge under various damage scenarios. This evaluation necessitates extensive vibration measurements, with piezoelectric sensors capturing ambient vibrations and developing detailed finite element models of the bridge to simulate the structural behavior accurately. The results obtained from this study showed that bridge frequencies are sufficiently sensitive for identifying significant fractures in long bridges. However, the mode shape results show a better resolution when compared to the frequency changes. The findings are usually sensitive enough to identify damage at the affected locations. Amplitude changes in the mode shape help determine the location of damage. The modal assurance criterion (MAC) served to identify damage as well. Finally, the results show a distinct pattern of frequency and mode shape variations for every damage scenario, which helps to identify the damage type, severity, and location along the bridge. The analysis results reported in this study serve as a reference benchmark for the Szapáry Bridge health monitoring. Full article
(This article belongs to the Special Issue Advances in Structural Health Monitoring and Damage Identification)
►▼ Show Figures

Figure 1

23 pages, 9845 KiB  
Article
Research on Damage Identification of Arch Bridges Based on Deflection Influence Line Analytical Theory
by Yu Zhou, Meng Li, Yingdi Shi, Chengchao Xu, Dewei Zhang and Mingyang Zhou
Buildings 2024, 14(1), 6; https://doi.org/10.3390/buildings14010006 - 19 Dec 2023
Cited by 2 | Viewed by 706
Abstract
There is no analytical solution to the deflection influence line of catenary hingeless arches nor an explicit solution to the deflection influence line difference curvature of variable section hingeless arches. Based on the force method equation, a deflection influence line analytical solution at [...] Read more.
There is no analytical solution to the deflection influence line of catenary hingeless arches nor an explicit solution to the deflection influence line difference curvature of variable section hingeless arches. Based on the force method equation, a deflection influence line analytical solution at any location before and after structural damage is obtained, and then an explicit solution of the deflection influence line difference curvature of the structural damage is obtained. The indexes suitable for arch structure damage identification are presented. Based on analytical theory and a finite element model, the feasibility of identifying damage at a single location and multiple locations of an arch bridge is verified. This research shows that when a moving load acts on a damaged area of an arch structure, the curvature of the deflection influence line difference will mutate, which proves theoretically that the deflection influence line difference curvature can be used for the damage identification of hingeless arch structures. This research has provided theoretical support for hingeless arch bridge design and evaluation. Combined with existing bridge monitoring methods, the new bridge damage identification method proposed in this paper has the potential to realize normal health status assessments of existing arch bridges in the future. Full article
(This article belongs to the Special Issue Advances in Structural Health Monitoring and Damage Identification)
►▼ Show Figures

Figure 1

18 pages, 3915 KiB  
Article
Detection of Structural Damage in a Shaking Table Test Based on an Auto-Regressive Model with Additive Noise
by Quanmao Xiao, Daopei Zhu, Jiazheng Li and Cai Wu
Buildings 2023, 13(10), 2480; https://doi.org/10.3390/buildings13102480 - 29 Sep 2023
Viewed by 479
Abstract
Damage identification plays an important role in enhancing resilience by facilitating precise detection and assessment of structural impairments, thereby strengthening the resilience of critical infrastructure. A current challenge of vibration-based damage detection methods is the difficulty of enhancing the precision of the detection [...] Read more.
Damage identification plays an important role in enhancing resilience by facilitating precise detection and assessment of structural impairments, thereby strengthening the resilience of critical infrastructure. A current challenge of vibration-based damage detection methods is the difficulty of enhancing the precision of the detection results. This problem can be approached through improving the noise reduction performance of algorithms. A novel method based partially on the errors-in-variables (EIV) model and its total least-squares (LS) algorithm is proposed in this study. Compared with a classical damage detection approach involving adoption of auto-regressive (AR) models and the least-squares (LS) method, the proposed method accounts for all the observation errors as well as the relationships between them, especially in an elevated level of noise, which leads to a better accuracy. Accordingly, a shaking table test and its corresponding finite element simulation of a full-scale web steel structure were conducted. The acceleration time-series output data of the model after suffering from different seismic intensities were used to identify damage using the presented detection method. The response and identification results of the experiment and the finite element analysis are consistent. The finding of this paper indicated that the presented approach is capable of detecting damage with a higher accuracy, especially when the signal noise is high. Full article
(This article belongs to the Special Issue Advances in Structural Health Monitoring and Damage Identification)
►▼ Show Figures

Figure 1

20 pages, 9124 KiB  
Article
Identification of Tension Force in Cable Structures Using Vibration-Based and Impedance-Based Methods in Parallel
by Minh-Huy Nguyen, Tran-De-Nhat Truong, Thanh-Cao Le and Duc-Duy Ho
Buildings 2023, 13(8), 2079; https://doi.org/10.3390/buildings13082079 - 16 Aug 2023
Viewed by 1014
Abstract
For cable structures, the tension force is one of the main factors showing the structure’s health. If the tension force falls below a safe level during construction or operation, it can lead to partial or complete the structural failure, posing a risk to [...] Read more.
For cable structures, the tension force is one of the main factors showing the structure’s health. If the tension force falls below a safe level during construction or operation, it can lead to partial or complete the structural failure, posing a risk to the people’s safety. In this study, a parallel structural health monitoring approach of the vibration-based and impedance-based methods is proposed to identify the tension force in cable structures. Firstly, a cable structure including the anchorage is simulated using a finite element model to obtain the vibration and impedance responses. The numerical results are verified with the experimental ones of the previous studies. Then, the parallel approach combining the above two methods is presented to determine the tension force. For the vibration-based method, the tension force is estimated by the natural frequencies. For the impedance-based method, the tension force is estimated by the mean absolute percentage deviation (MAPD) index and the artificial neural network (ANN). Finally, the tension force estimation results are compared and assessed. By using the parallel approach, the reliability and accuracy of the tension force identification results are guaranteed. Full article
(This article belongs to the Special Issue Advances in Structural Health Monitoring and Damage Identification)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-4
Back to TopTop