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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.


Papers
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Journal ArticleDOI
TL;DR: In this article, a frequency-domain maximum likelihood estimator is used to automate the modal identification process and a fuzzy clustering algorithm is used for mode selection and mode-tracking.

135 citations

Reference BookDOI
31 Aug 2011
TL;DR: In this article, structural health monitoring of long span suspension bridges is discussed and a case study of the Tsing Ma suspension bridge in Hong Kong is presented to examine their effectiveness in the operational performance of a real bridge.
Abstract: Long span suspension bridges cost billions. In recent decades, structural health monitoring systems have been developed to measure the loading environment and responses of these bridges in order to assess serviceability and safety while tracking the symptoms of operational incidents and potential damage. This helps ensure the bridge functions properly during a long service life and guards against catastrophic failure under extreme events. Although these systems have achieved some success, this cutting-edge technology involves many complex topics that present challenges to students, researchers, and engineers alike. Systematically introducing the fundamentals and outlining the advanced technologies for achieving effective long-term monitoring, Structural Health Monitoring of Long-Span Suspension Bridges covers: - The design of structural health monitoring systems - Finite element modelling and system identification - Highway loading monitoring and effects - Railway loading monitoring and effects - Temperature monitoring and thermal behaviour - Wind monitoring and effects - Seismic monitoring and effects - SHMS-based rating method for long span bridge inspection and maintenance - Structural damage detection and test-bed establishment These are applied in a rigorous case study, using more than ten years' worth of data, to the Tsing Ma suspension bridge in Hong Kong to examine their effectiveness in the operational performance of a real bridge. The Tsing Ma bridge is the world's longest suspension bridge to carry both a highway and railway, and is located in one of the world’s most active typhoon regions. Bridging the gap between theory and practice, this is an ideal reference book for students, researchers, and engineering practitioners.

135 citations

Proceedings ArticleDOI
07 Apr 2008
TL;DR: In this paper, structural health monitoring (SHM) techniques were used during a fatigue test of a 9 meter glass-poxy and carbon-epoxy wind turbine blade, and the SHM system was implemented by teams from NASA Kennedy Space Center, Purdue University and Virginia Tech.
Abstract: As electric utility wind turbines increase in size, and correspondingly, increase in initial capital investment cost, there is an increasing need to monitor the health of the structure. Acquiring an early indication of structural or mechanical problems allows operators to better plan for maintenance, possibly operate the machine in a de-rated condition rather than taking the unit off-line, or in the case of an emergency, shut the machine down to avoid further damage. This paper describes several promising structural health monitoring (SHM) techniques that were recently exercised during a fatigue test of a 9 meter glass-epoxy and carbon-epoxy wind turbine blade. The SHM systems were implemented by teams from NASA Kennedy Space Center, Purdue University and Virginia Tech. A commercial off-the-shelf acoustic emission (AE) NDT system gathered blade AE data throughout the test. At a fatigue load cycle rate around 1.2 Hertz, and after more than 4,000,000 fatigue cycles, the blade was diagnostically and visibly failing at the out-board blade spar-cap termination point at 4.5 meters. For safety reasons, the test was stopped just before the blade completely failed. This paper provides an overview of the SHM and NDT system setups and some current test results.

134 citations

Journal ArticleDOI
TL;DR: In this paper, a 22-storey reinforced concrete building is used to trace the variation of its modal frequencies, which are identified using the Bayesian spectral density approach with the ambient vibration data.

133 citations

Journal ArticleDOI
TL;DR: An on-line adaptive tracking technique, based on the least-square estimation, to identify the system parameters and their changes of non-linear hysteretic structures and demonstrate the application and effectiveness of the proposed technique in detecting the structural damages.
Abstract: System identification and damage detection based on vibration data have received considerable attention recently because of their importance to structural health monitoring. Various technical approaches have been proposed in the literature; however, the on-line identification of the changes of parameters for non-linear structures due to damages is still a challenging problem. In this paper, we propose an on-line adaptive tracking technique, based on the least-square estimation, to identify the system parameters and their changes of non-linear hysteretic structures. The method proposed is capable of tracking abrupt or slow changes of the system parameters from which the damage event and the severity of the structural damage can be detected and evaluated. Simulation results for tracking the parametric changes of non-linear hysteretic structures are presented to demonstrate the application and effectiveness of the proposed technique in detecting the structural damages.

133 citations


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