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Advanced Devices and Data Analysis in Vibration Control and Structural Health Monitoring

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

Deadline for manuscript submissions: closed (20 May 2025) | Viewed by 7844

Special Issue Editors

Dr. Yinghao Zhao

E-Mail Website
Guest Editor
School of Civil Engineering, Guangzhou Maritime University, Guangzhou 510725, China
Interests: structural health monitoring; seismic fragility analysis; structural damage detection; deep learning; computer vision
Dr. Zeyu Wang

E-Mail Website
Guest Editor
School of Civil Engineering, Tsinghua University, Beijing 100084, China
Interests: machine learning; structural reliability; uncertainty quantification; Bayesian updating; surrogate modeling
Special Issues, Collections and Topics in MDPI journals
Dr. Xijun Ye

E-Mail Website
Guest Editor
School of Civil Engineering, Guangzhou University, Guangzhou 510006, China
Interests: structural health monitoring; modal analysis; structural damage diagnosis; deep learning

Special Issue Information

Dear Colleagues,

Introduction

Structural health monitoring (SHM) is a vital function of modern large-scale structures and infrastructure systems. This technology, along with data-driven simulation and analysis, can ensure the safety, reliability and durability of infrastructures. As sensor technology has matured, there has been a surging increase in the number of studies performed in the field of SHM to enrich more functionalities for health monitoring. Many efficient methods such as image recognition for cracks, pattern recognition for structural vibration, etc., can be computationally efficient. However, the problems of SHM are still challenging, and therefore still need to be addressed with more advanced devices and data analysis techniques. In line with the practical purpose of SHM, methods that can simultaneously investigate state-of-the-practice engineering models and data-driven analysis methods should be investigated and devised. This Special Issue aims to provide a platform for researchers, practitioners, and engineers to share their latest findings, innovations, and developments in advanced devices, new data analysis strategies, artificial intelligence, deep learning, uncertainty quantification and engineering optimization for SHM.

Scope

This Special Issue focuses on the latest advances in advanced devices, innovative data analysis strategies, optimization methods, uncertainty quantification, Bayesian methods and artificial intelligence techniques for SHM. It covers research works related to sensors, data acquisition systems, wireless sensor networks, data analysis techniques, signal processing algorithms and optimization strategies for SHM and applications. This issue also covers the application of advanced devices, innovative data analysis strategies, artificial intelligence and deep learning in practical scenarios.

Topics of Interest

The topics of interest for this Special Issue include, but are not limited to, the following:

  1. Advanced sensors and data acquisition systems for SHM and engineering optimization;
  2. Wireless sensor networks for SHM;
  3. Innovative data analysis strategies for SHM and engineering optimization;
  4. Signal processing and machine learning techniques for SHM and engineering optimization;
  5. Non-destructive testing and evaluation for SHM;
  6. Experimental and numerical studies on SHM and engineering optimization;
  7. Applications of advanced devices, innovative data analysis strategies, artificial intelligence and deep learning in real-world scenarios;
  8. Health monitoring of large-scale structures such as bridges, wind turbines and buildings;
  9. Uncertainty quantification with advanced numerical methods and simulations;
  10. Risk-informed decision-making for SHM of infrastructure systems.

Dr. Yinghao Zhao
Dr. Zeyu Wang
Dr. Xijun Ye
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. 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
  • structural damage detection
  • risk-informed decision making
  • advanced devices
  • data analysis strategies
  • structural reliability
  • control system
  • Bayesian updating
  • deep learning
  • computer vision

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Published Papers (5 papers)

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Research

28 pages, 11410 KiB  
Article
A Study on the Amplification Effect and Optimum Control of the Intermediate Column–Lever Negative Stiffness Viscous Damper
by Qiang Zhou, Wen Pan, Xiang Lan and Zuwei Li
Appl. Sci. 2024, 14(17), 7627; https://doi.org/10.3390/app14177627 - 29 Aug 2024
Viewed by 1211
Abstract
Currently, the energy dissipation efficiency of intermediate column dampers is extremely low, and traditional lever amplification damping systems occupy a large space in buildings. Aiming at solving these problems, this paper puts forward a new intermediate column–lever negative stiffness viscous damper (CLNVD), which [...] Read more.
Currently, the energy dissipation efficiency of intermediate column dampers is extremely low, and traditional lever amplification damping systems occupy a large space in buildings. Aiming at solving these problems, this paper puts forward a new intermediate column–lever negative stiffness viscous damper (CLNVD), which has the characteristics of small impact on building space and significant amplification of the damper displacement. The CLNVD consists of the following four parts: the viscous damper, the negative stiffness device, the lever, and the intermediate column. This paper introduces the displacement amplification coefficient (fd) to assess the CLNVD’s displacement amplification effect and introduces the energy dissipation coefficient (fE) to assess the CLNVD’s energy dissipation effect. The expressions for fd and fE are derived according to the geometric magnification coefficient and effective displacement factor. Moreover, the impacts of multiple factors including the CLNVD’s position, the lever’s amplification coefficient, the bending line stiffness of beam, the negative stiffness, the damping coefficient, the damping index, and the inter-story displacement on the CLNVD’s fd and fE are elaborated. The analysis results reveal the following: when the CLNVD is located in the middle of the span, the fd and fE of the CLNVD will be maximized, and fE will increase first and then decrease as the beam’s bending line stiffness increases. Meanwhile, the amplification capability of the CLNVD increases as the lever’s amplification coefficient χ rises. When the negative stiffness does not exist, there exists an optimum lever’s amplification coefficient χ that maximizes fE. When the combination of damping coefficient c and index α satisfies a specific relationship, fE of the CLNVD reaches its largest value. When the negative stiffness and the loss stiffness of VD are within the region proposed in this paper, the CLNVD will achieve a higher fd and avoid providing significant negative stiffness. Subsequently, this paper proposes an optimization design method of the CLNVD. Finally, the amplification effect of CLNVD as well as the effectiveness of its optimization design method are verified through examples. In the case study, the CLNVD offers a larger damping ratio under the circumstance of fortification earthquakes. Under fortification and rare earthquakes, the inter-story displacement of Scheme 1 has been decreased by half roughly. According to the above-mentioned results, the CLNVD provides a brand-new approach for designers in the seismic design of buildings. Furthermore, this paper will provide beneficial reference for the damping design of other amplification devices equipped with negative stiffness dampers. Full article
(This article belongs to the Special Issue Advanced Devices and Data Analysis in Vibration Control and Structural Health Monitoring)
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20 pages, 3884 KiB  
Article
Structural Damage Detection through Dual-Channel Pseudo-Supervised Learning
by Tianjie Hu, Kejian Ma and Jianchun Xiao
Appl. Sci. 2024, 14(16), 7377; https://doi.org/10.3390/app14167377 - 21 Aug 2024
Viewed by 923
Abstract
Structural damage detection is crucial for maintaining the health and safety of buildings. However, achieving high accuracy in damage detection remains challenging, especially in noisy environments. To improve the accuracy and noise robustness of damage detection, this study proposes a novel method that [...] Read more.
Structural damage detection is crucial for maintaining the health and safety of buildings. However, achieving high accuracy in damage detection remains challenging, especially in noisy environments. To improve the accuracy and noise robustness of damage detection, this study proposes a novel method that combines the Conformer model and the dual-channel pseudo-supervised (DCPS) learning strategy for structural damage detection. The DCPS learning strategy improves the stability and accuracy of the model in noisy environments. It enables the model to input acceleration signals with different noise levels into each branch of the dual-channel network, thereby learning noise-robust features. The Conformer model, as the backbone network, integrates the advantages of convolutional neural networks (CNNs) and Transformers to effectively extract both local and global features from acceleration signals. The proposed method is validated using a four-story single-span steel-frame building model and the IASC-ASCE simulated benchmark structure. The results show that the proposed method achieves a higher classification accuracy than existing structural damage detection methods. Compared to the single Conformer-based method, this method improves the accuracy by 1.57% and 4.93% for the two validation structures, respectively. Moreover, the proposed method benefits from the DCPS learning strategy’s ability to achieve superior noise robustness compared to other methods. The proposed method holds potential value for improving the accuracy of damage detection and noise robustness in scenarios such as maintenance and extreme events. Full article
(This article belongs to the Special Issue Advanced Devices and Data Analysis in Vibration Control and Structural Health Monitoring)
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13 pages, 2058 KiB  
Article
Updating Durability Models for Concrete Structures in Chlorine Environment Based on Detection Information
by Hui Gu and Zhaobo Meng
Appl. Sci. 2024, 14(11), 4516; https://doi.org/10.3390/app14114516 - 24 May 2024
Viewed by 1121
Abstract
The assessment of concrete structure durability in chlorine environments is significantly impacted by the uncertainty inherent in existing durability models. It introduces an integrated approach for updating these models based on the detection information of existing structures. This approach narrows the gap between [...] Read more.
The assessment of concrete structure durability in chlorine environments is significantly impacted by the uncertainty inherent in existing durability models. It introduces an integrated approach for updating these models based on the detection information of existing structures. This approach narrows the gap between theoretical predictions and observed structural durability. Specifically, we refined the probability model of critical chloride content by analyzing steel bar corrosion sample proportions using Bayesian theory for greater accuracy. The enhanced model enables more reliable life expectancy prediction, forming a solid foundation for maintaining and strengthening existing structures. This method was demonstrated through a case study of a reinforced concrete industrial building with a service life of 12 years. Full article
(This article belongs to the Special Issue Advanced Devices and Data Analysis in Vibration Control and Structural Health Monitoring)
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14 pages, 2784 KiB  
Article
Laboratory Study of Effective Stress Coefficient for Saturated Claystone
by Fanfan Li, Weizhong Chen, Zhigang Wu, Hongdan Yu, Ming Li, Zhifeng Zhang and Fusheng Zha
Appl. Sci. 2023, 13(19), 10592; https://doi.org/10.3390/app131910592 - 22 Sep 2023
Cited by 1 | Viewed by 1294
Abstract
Claystone is potentially the main rock formation for the deep geological disposal of high-level radioactive nuclear waste. A major factor that affects the deformation of the host medium is effective stress. Therefore, studying the effective stress principle of claystone is essential for a [...] Read more.
Claystone is potentially the main rock formation for the deep geological disposal of high-level radioactive nuclear waste. A major factor that affects the deformation of the host medium is effective stress. Therefore, studying the effective stress principle of claystone is essential for a stability analysis of waste disposal facilities. Consolidated drained (CD) tests were carried out on claystone samples to study their effective stress principle in this paper. Firstly, two samples were saturated under a specified confining pressure and pore pressure for about one month. Secondly, the confining pressure and pore pressure were increased to a specified value simultaneously and then reverted to the previous stress state (the deformations of the samples were recorded during the whole process). Different incremental combinations of the confining pressure and pore pressure were tried at this step. Finally, the effective stress coefficients of the samples were obtained through a back analysis. Furthermore, some potential influencing factors (the neutral stress and loading rate) of the effective stress coefficient were also studied through additional tests. Some interesting results are worth mentioning: (1) the effective stress coefficient of claystone is close to one; (2) the neutral stress and loading rate may have little effect on the effective stress coefficient of claystone. Full article
(This article belongs to the Special Issue Advanced Devices and Data Analysis in Vibration Control and Structural Health Monitoring)
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21 pages, 7505 KiB  
Article
Evaluation of Mechanical Performance of a New Disc Spring-Cable Counter Pressure Shock Absorber
by Yanfeng Wang, Xiaohui Wu, Shaofeng Ji, Faping Xiao and Dayang Wang
Appl. Sci. 2023, 13(15), 8718; https://doi.org/10.3390/app13158718 - 28 Jul 2023
Cited by 1 | Viewed by 2292
Abstract
Mechanical performance evaluation of a new disc spring-cable counter pressure shock absorber is focused on in this study. The proposed shock absorber is always in a compressive working state with energy dissipation capacity under both tension and compression loadings. The design formulas of [...] Read more.
Mechanical performance evaluation of a new disc spring-cable counter pressure shock absorber is focused on in this study. The proposed shock absorber is always in a compressive working state with energy dissipation capacity under both tension and compression loadings. The design formulas of its axial bearing capacity, vertical stiffness, deformation energy of the shock absorber were derived, and the corresponding specific design process was provided in detail. Experimental and numerical investigations of the mechanical performance were conducted under static and dynamic loadings. The parameters influencing the laws of the mechanical performance of the shock absorber, including loading frequency, pre-compression deformation and loading amplitude, were investigated. The rationality of the proposed shock absorber was firstly verified through comparative analysis using experimental, numerical and theoretical calculations. The shock absorber with a friction coefficient of 0.005 between disc springs, and a friction coefficient of 0.3 between the disc spring and cover plate has the smallest error between experiment and theory for the flattening force. The bearing capacity of the shock absorber exhibits a linear relationship with the loading displacement in static loading. In dynamic loading, however, the bearing capacity shows a trend of slow growth followed by rapid growth. The energy dissipation capacity of the shock absorber shows an increase with the increase of loading displacement. The minimum equivalent damping ratio of all of the dynamic test cases is 7%, with a maximum up to 15.3%. Under the same loading frequency, the equivalent stiffness and equivalent damping ratio have a linear amplification trend with the increase of pre-compression deformation, and the maximum increase of equivalent stiffness is equal to 41.37%. Under the same loading frequency and pre-compression deformation, the energy consumption capacity can be improved by increasing the loading amplitude. Full article
(This article belongs to the Special Issue Advanced Devices and Data Analysis in Vibration Control and Structural Health Monitoring)
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