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Buildings
Special Issues
Recent Advances in Structural Health Monitoring and Maintenance of Buildings
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Recent Advances in Structural Health Monitoring and Maintenance of Buildings

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

Deadline for manuscript submissions: closed (20 February 2024) | Viewed by 2911

Special Issue Editors

Dr. Shieh-Kung Huang

E-Mail Website
Guest Editor
Department of Civil Engineering, National Chung-Hsing University, Taichung 402202, Taiwan
Interests: smart structure; structural health monitoring; structural control; earthquake early warning
Dr. Yuguang Fu

E-Mail Website
Guest Editor
School of Civil and Environmental Engineering, Nanyang Technological University, Singapore 639798, Singapore
Interests: Internet of Things; structural health monitoring; digital twin; artificial intelligence; resilient infrastructure
Special Issues, Collections and Topics in MDPI journals
Dr. Youqi Zhang

E-Mail Website
Guest Editor
Department of Civil Engineering, Aalto University, Espoo, Finland
Interests: structural health monitoring; structural dynamics; finite element method; digital twin
Dr. Ting-Yu Hsu

E-Mail Website
Guest Editor
Department of Civil and Construction Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan
Interests: structural health monitoring; earthquake early warning; earthquake engineering structural dynamics; signal processing and system identification; engineering dynamics; engineering statics

Special Issue Information

Dear Colleagues,

Because of the need to continuously meet operational safety and functionality goals during their long service life, structural health monitoring (SHM) of full-scale civil infrastructures is an inevitable research trend. SHM is an interdisciplinary multi-purpose subject combining signal processing, system identification, damage detection, health evaluation, and several other theories. In the past two decades, with advanced technologies such as sensing networks, data acquisition, communication, signal processing, information management, and intelligent algorithms, SHM technologies and corresponding developments applied to civil infrastructures, especially buildings, have attracted the interest of scientists and engineers. Nowadays, SHM for buildings has been successfully implemented many times. Future research is directed toward the integration of advanced sensing networks, large-scale data management, data mining, information fusion, and intelligent diagnosis.

Therefore, this Special Issue aims to collate the most recent research trends and advanced technologies in buildings SHM to track operational safety and functionality under long-term service and evaluate structural performance. We welcome papers on the following and related topics, including but not limited to:

  • Structural health monitoring of buildings;
  • Sensing networks and optimization;
  • Signal processing;
  • System identification;
  • Damage detection, location, and quantification;
  • Structural performance evaluation;
  • Numerical modeling and model updating;
  • Modal analysis;
  • Artificial intelligence and data-driven approach;
  • Environmental effect.

Dr. Shieh-Kung Huang
Dr. Yuguang Fu
Dr. Youqi Zhang
Dr. Ting-Yu Hsu
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
  • sensing network
  • system identification
  • damage detection
  • signal processing
  • performance evaluation
  • model updating
  • modal analysis
  • artificial intelligence
  • environmental effect

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

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Research

21 pages, 7939 KiB  
Article
Tracking Modal Parameters of Structures Online Using Recursive Stochastic Subspace Identification under Ambient Excitations
by Shieh-Kung Huang, Jin-Quan Chen, Yuan-Tao Weng and Jae-Do Kang
Buildings 2024, 14(4), 964; https://doi.org/10.3390/buildings14040964 - 1 Apr 2024
Viewed by 921
Abstract
Continuous and autonomous system identification is an alternative to regular inspection during operations, which is essential for structural integrity management (SIM) as well as structural health monitoring (SHM). In this regard, online (or real-time) system identification techniques that have recently received considerable attention [...] Read more.
Continuous and autonomous system identification is an alternative to regular inspection during operations, which is essential for structural integrity management (SIM) as well as structural health monitoring (SHM). In this regard, online (or real-time) system identification techniques that have recently received considerable attention can be used to assess the current condition and performance during operations and, in the meantime, can be utilized to detect any damage or deterioration. For example, stochastic subspace identification (SSI), based on recursive formulation, has proven its capability in tracking modal parameters as well as time-variant dynamic behaviors. This study proposes the implementation of recursive SSI (RSSI) using the matrix inversion lemma to track slow time-varying parameter changes under ambient excitations. Subsequently, some investigations for practical implementation are examined and discussed. For verifying the reliability of SHM applications based on the proposed methods, two datasets measured from different experiments are exploited to identify the modal parameters reclusively. The results from both numerical simulations and experimental investigations demonstrated the effectiveness of tracking the modal parameters exhibiting time-varying dynamic characteristics under white noise excitations (or ambient excitations). Full article
(This article belongs to the Special Issue Recent Advances in Structural Health Monitoring and Maintenance of Buildings)
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12 pages, 2074 KiB  
Article
Post-Earthquake Damage Identification of Buildings with LMSST
by Roshan Kumar, Vikash Singh and Mohamed Ismail
Buildings 2023, 13(7), 1614; https://doi.org/10.3390/buildings13071614 - 26 Jun 2023
Cited by 3 | Viewed by 1376
Abstract
The structure is said to be damaged if there is a permanent shift in the post-event natural frequency of a structure as compared with the pre-event frequency. To assess the damage to the structure, a time-frequency approach that can capture the pre-event and [...] Read more.
The structure is said to be damaged if there is a permanent shift in the post-event natural frequency of a structure as compared with the pre-event frequency. To assess the damage to the structure, a time-frequency approach that can capture the pre-event and post-event frequency of the structure is required. In this study, to determine these frequencies, a local maximum synchrosqueezing transform (LMSST) method is employed. Through the simulation results, we have shown that the traditional methods such as the Wigner distribution, Wigner–Ville distributions, pseudo-Wigner–Ville distributions, smoothed pseudo-Wigner–Ville distribution, and synchrosqueezing transforms are not capable of capturing the pre-event and post-event frequency of the structure. The amplitude of the signal captured by sensors during those events is very small compared with the signal captured during the seismic event. Thus, traditional methods cannot capture the frequency of pre-event and post-event, whereas LMSST employed in this work can easily identify these frequencies. This attribute of LMSST makes it a very attractive method for post-earthquake damage detection. In this study, these claims are qualitatively and quantitatively substantiated by comprehensive numerical analysis. Full article
(This article belongs to the Special Issue Recent Advances in Structural Health Monitoring and Maintenance of Buildings)
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