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Structural health monitoring

About: Structural health monitoring is a research topic. Over the lifetime, 11727 publications have been published within this topic receiving 186231 citations.


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Journal ArticleDOI
TL;DR: The results show that, even for the real data, the proposed method can reliably detect, locate and assess damage of the benchmark structure by inferring substructure stiffness losses using the identified modal parameters from the calibration and monitoring stages.

71 citations

Journal ArticleDOI
TL;DR: In this paper, the authors define and study a benchmark developed by the Task Group on Structural Health Monitoring that was formed in 1999 under the sponsorship of the Dynamics Committee of ASCE and the International Association of Structural Control.
Abstract: The importance of developing robust monitoring systems that can detect and locate progressive deterioration in structures or abrupt damage induced by extreme loading events is well recognized in the aerospace, mechanical, and civil engineering communities. In the case of civil structures such as buildings, bridges, off-shore platforms, or dams, the most commonly used approach for structural health monitoring ~SHM! relies on visual inspections that are labor intensive, often not timely, and may miss hidden damage. A good example of these limitations is found in the fractures induced by the 1994 Northridge earthquake in welded momentresisting beam-column connections in many steel buildings that were not discovered until several months after the earthquake because there was no distress apparent from visual inspections. An alternative to visual inspections and localized testing that is being aggressively investigated in various engineering disciplines is that of structural health monitoring based on vibration signals. A typical SHM system consists of a distributed set of motion sensors ~e.g., accelerometers, velocimeters, or fiber-optic strain gauges! connected through a data acquisition system to a central processing unit that may be in an operator room. For remote real-time monitoring of structures, the processed data must be on-line, possibly through a dedicated line or via an Internet link. The basic idea is well established, namely, the dynamic characteristics of a system ~usually natural frequencies and mode shapes! that can be identified from recorded motions are a function of the physical parameters ~mass and stiffness distributions!. Therefore, changes in physical properties resulting from damage may be inferred from changes in the identified dynamic characteristics using suitable algorithms. Then, in theory, damage may be detected, localized, and assessed through vibration monitoring. In practice, however, realization of the concept has proved to be a very challenging proposition because the inverse problem that must be solved, for typical operating conditions, is poorly conditioned, that is, results are sensitive to measurement noise and modeling errors. An important part of the current effort to affect positive progress in SHM technology in civil engineering structures is the development of well-defined benchmark problems that allow comparison of the performance of various techniques for realistic conditions. This special issue of the Journal of Engineering Mechanics contains eight papers that define and study a benchmark developed by the Task Group on Structural Health Monitoring that was formed in 1999 under the sponsorship of the Dynamics Committee of ASCE and the International Association of Structural Control ~IASC!. These papers expand on some partial and

71 citations

Journal Article
TL;DR: A review of recent advances made in vibration-based Structural Health Monitoring (SHM) using the responses of the structure to an excitation is presented in this article, where the review is divided into parameter and feature estimation, based on linear structural behavior, taking into account the nonlinear structural behaviour, sensor layout and data collection strategies and integration of SHM, with the vibration control of structures, wireless monitoring, and application of LIDAR.

71 citations

Journal ArticleDOI
TL;DR: The damage identification study presented in this paper leveraged a full-scale sub-component experiment conducted in the Charles Lee Powell Structural Research Laboratories at the University of California, San Diego to identify damage in the beam through a finite element model updating procedure.
Abstract: The damage identification study presented in this paper leveraged a full-scale sub-component experiment conducted in the Charles Lee Powell Structural Research Laboratories at the University of California, San Diego. As payload project attached to a quasi-static test of a full-scale composite beam, a high-quality set of low-amplitude vibration response data was acquired from the beam at various damage levels. The Eigensystem Realization Algorithm was applied to identify the modal parameters (natural frequencies, damping ratios, displacement and macro-strain mode shapes) of the composite beam based on its impulse responses recorded in its undamaged and various damaged states using accelerometers and long-gage fiber Bragg grating strain sensors. These identified modal parameters are then used to identify the damage in the beam through a finite element model updating procedure. The identified damage is consistent with the observed damage in the composite beam.

71 citations

Journal ArticleDOI
TL;DR: In this article, a vision-based method applied for in-plane displacement field measurement of cantilever beams is presented, where the deflection curve of the analyzed structure is computed by means of the digital image correlation.
Abstract: Summary Deflection curve can be used to detect and localize damage in civil engineering structures. In this paper, a vision-based method applied for in-plane displacement field measurement of cantilever beams is presented. The deflection curve of the analyzed structure is computed by means of the digital image correlation. Damage is introduced into the structure. Resulting deflection curves are used as an input to the novel damage detection algorithms: line segments method and voting method. The algorithms are then compared with the second derivative method and assessed through the probability of detection procedure. Copyright © 2015 John Wiley & Sons, Ltd.

71 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023600
20221,374
2021776
2020746
2019803
2018708