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Applied Sciences
Special Issues
Advanced Technologies in SHM, Performance Evaluation, and Reliabilty Analysis
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Advanced Technologies in SHM, Performance Evaluation, and Reliabilty Analysis

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Civil Engineering".

Deadline for manuscript submissions: 7 October 2024 | Viewed by 900

Special Issue Editor

Dr. Qi-Ang Wang

E-Mail Website
Guest Editor
School of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou 221116, China
Interests: bridge and tunnel engineering; municipal engineering; structural engineering; building and civil engineering
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Structural health monitoring (SHM), as a technique for monitoring and evaluating structural health status, has been widely concerned and applied in recent years. It can not only monitor the vibration and strain of the structure in real time, but also provide an accurate assessment of the health status of the structure, thus providing important data support for decision makers. The performance evaluation of a structure is an important step to ensure its long-term operation and safety. By using SHM technology, we can monitor the vibration characteristics and deformation of the structure in real time, and provide data support for the performance evaluation of the structure. Reliability analysis is an important means to evaluate the stability of structures under different external loads and environmental conditions. With SHM technology, we can monitor the health status of the structure in real time, identify potential faults and fragile points, and propose corresponding improvement measures to improve the reliability and durability of the structure. Potential topics include, but are not limited to: Structural health monitoring; Performance evaluation; Reliability analysis; Application of new sensor technology in structural health monitoring; Application of machine learning to performance evaluation; The development of nondestructive testing technology and its application in reliability analysis.

Dr. Qi-Ang Wang
Guest Editor

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. Applied Sciences 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 2400 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
  • performance evaluation
  • reliability analysis
  • machine learning
  • sensors

Published Papers (2 papers)

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Research

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16 pages, 10223 KiB  
Article
Research on Full-Field Dynamic Deflection Measurement of Beams Based on Dense Feature Matching and Mismatch Removal Method
by Jiayan Zheng, Yichen Tang, Haijing Liu, Zhixiang Zhou and Ji He
Appl. Sci. 2024, 14(8), 3347; https://doi.org/10.3390/app14083347 - 16 Apr 2024
Viewed by 272
Abstract
To solve the problems of measurement errors led by mismatches of dense feature matching in machine vision structural deflection measurement, this paper proposes a dense feature extraction, matching, and dual-step mismatch-removal-based full-field structural dynamic deflection measurement method. First, the of dense feature detection [...] Read more.
To solve the problems of measurement errors led by mismatches of dense feature matching in machine vision structural deflection measurement, this paper proposes a dense feature extraction, matching, and dual-step mismatch-removal-based full-field structural dynamic deflection measurement method. First, the of dense feature detection and matching theory is introduced to extract the SIFT feature points on a structural surface in an image sequence and matched by FLANN to trace the structure movement, and the mechanisms and causes of mismatches are analyzed. Then, a dual-step mismatch removal method combining RANSAC and Structural Displacement Continuity Restriction (SDCR) is introduced to achieve full-field dynamic beam deflection measurement. The proposed method is validated through indoor cantilever beam experiments, and results show that the method can effectively eliminate a large number of SIFT feature mismatches (accounting for approximately 55% of the total matched feature points). The full-field dynamic displacement field of the beam can be measured with the correctly matched dense feature points by converting dense feature point displacements into continuous and uniform spatiotemporal deflections of the structure. A comparison with the GOM Correlate Professional DIC measurement system was conducted, and the maximum measurement error of the cantilever beam dynamic displacement of the proposed method is between 0.024 and 0.053 mm, the root mean squared error of displacement is approximately 0.01 mm, and the correlation coefficient between two deflection–time curves reaches 0.9964. The proposed algorithm is proven to be effective in full-field displacement measurement and has great potential in future structural health monitoring of bridges. Full article
(This article belongs to the Special Issue Advanced Technologies in SHM, Performance Evaluation, and Reliabilty Analysis)
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Review

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18 pages, 12188 KiB  
Review
A Concise State-of-the-Art Review of Crack Monitoring Enabled by RFID Technology
by Sheng-Cai Ran, Qi-Ang Wang, Jun-Fang Wang, Yi-Qing Ni, Zhong-Xu Guo and Yang Luo
Appl. Sci. 2024, 14(8), 3213; https://doi.org/10.3390/app14083213 - 11 Apr 2024
Viewed by 369
Abstract
Cracking is an important factor affecting the performance and life of large structures. In order to maximize personal safety and reduce costs, it is highly necessary to carry out research on crack monitoring technology. Sensors based on Radio Frequency Identification (RFID) antennas have [...] Read more.
Cracking is an important factor affecting the performance and life of large structures. In order to maximize personal safety and reduce costs, it is highly necessary to carry out research on crack monitoring technology. Sensors based on Radio Frequency Identification (RFID) antennas have the advantages of wireless and low cost, which makes them highly competitive in the field of structure health monitoring (SHM). Thus, this study systematically summarizes the research progress of crack monitoring based on RFID technology in recent years. Firstly, this study introduces the causes of cracks and the traditional monitoring methods. Further, this study summarizes several main RFID-based crack monitoring and detection methods, including crack monitoring based on chipless RFID technology, passive RFID technology, and ultra-high-frequency (UHF) RFID technology, including the implementation methods, as well as the advantages and disadvantages of those technologies. In addition, for RFID-based crack monitoring applications, the two most commonly used materials are concrete materials and metal materials, which are also illustrated in detail. In general, this study can provide technical support and a theoretical basis for crack monitoring and detection to ensure the safety of engineering structures. Full article
(This article belongs to the Special Issue Advanced Technologies in SHM, Performance Evaluation, and Reliabilty Analysis)
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