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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: In this paper, the authors show the activity of a 2-year static and dynamic monitoring activity to check the structural response and actual level of damage of a historic church hit by an earthquake in L'Aquila (Italy) in 2009.
Abstract: The paper shows the activity of a 2-year static and dynamic monitoring activity to check the structural response and the actual level of damage of a historic church hit by earthquake in L'Aquila (Italy) in 2009. Structural health monitoring was carried out with accelerometers and transducers that recorded time histories of the main earthquake-induced ground motions and ambient vibrations. The paper focuses particularly on residual performance and assessment of the ancient church after six earthquake response data set—because of the seismic swarm—via a modal identification of output-only systems by using frequency domain decomposition. In this way, fundamental frequency, mode shapes, damping ratios and displacements can be estimated without knowing the input that has excited the system. The dynamic monitoring provides also a way to check possible drops of tension in the cables and relaxation in the FRP belts used for safety. Efficiency and reliability of modal identification of basilica-type churches, via the dynamic response of macro-elements only in comparison with the whole analysis, are finally proposed. Copyright © 2012 John Wiley & Sons, Ltd.

70 citations

Journal ArticleDOI
TL;DR: In this article, a case history is presented on the application of a simple strain-based Structural Health Monitoring (SHM) approach for monitoring the boron/epoxy patch repair of a critical fatigue crack in an F-111C wing.
Abstract: Although bonded composite patches often offer a far more effective repair than conventional mechanically fastened patches, full credit can not be given for their effectiveness in reducing crack growth when used to repair flight safety structure. This is because of the lack of non-destructive techniques to detect bonds with poor long-term integrity and ability to predict the likelihood and rate of patch disbonding. Structural health monitoring (SHM) may overcome this limitation, since patch health can be monitored on a continuous basis. After discussing some of the requirements and options for structural health monitoring of bonded repair patches, a case history is presented on the application of a simple strain-based SHM approach for monitoring the boron/epoxy patch repair of a critical fatigue crack in an F-111C wing. The effectiveness of the strain-based SHM approach is demonstrated, and improvements which would reduce its limitations and raise its practicality to the level (TRL8) where it could be used for in- flight application are discussed. Conventional strain gauges were used in the SHM system which, although found effective, have several limitations. A study on the option of using Bragg grating optical fibres as strain sensors is briefly described. Finally brief details are provided on an alternative longer-term approach and study to use acousto-ultrasonics as the basis of the SHM system.

69 citations

Journal ArticleDOI
Chung Bang Yun1, Jiyoung Min1
TL;DR: In this article, the state of the art in smart sensors technology is reviewed including optical fiber sensors, piezoelectric sensors, and wireless sensors, which have been carried out on test-road bridges, cable-stayed bridges and railroad bridges, sharing the up-to-date information and promoting the smart sensors and monitoring technologies for applications to civil infrastructures.
Abstract: In this paper, recent research and application activities on smart sensing, monitoring, and damage detection for civil infrastructures are briefly introduced. Emphasis is given to the activities in Korea. First, the state of the art in smart sensors technology is reviewed including optical fiber sensors, piezoelectric sensors, and wireless sensors. Then, a brief overview is given to the recent advances in the structural monitoring/damage detection techniques such as ambient vibration-based bridge health evaluation, piezoelectric sensors-based local damage detection, wireless sensor networks and energy harvesting, and wireless power transmission by laser/optoelectronic devices. Finally, recent collaborative R&D activities on smart structure technologies in Korea are discussed, which have been carried out on test-road bridges, cable-stayed bridges, and railroad bridges, sharing the up-to-date information and promoting the smart sensors and monitoring technologies for applications to civil infrastructures.

69 citations

Journal ArticleDOI
28 Mar 2018-Sensors
TL;DR: A vision-based non-contact bolt loosening detection method that uses a consumer-grade digital camera and is validated through a series of experimental investigations using three laboratory setups including a gusset plate on a cross frame, a column flange, and a girder web.
Abstract: Self-loosening of bolts caused by repetitive loads and vibrations is one of the common defects that can weaken the structural integrity of bolted steel joints in civil structures. Many existing approaches for detecting loosening bolts are based on physical sensors and, hence, require extensive sensor deployment, which limit their abilities to cost-effectively detect loosened bolts in a large number of steel joints. Recently, computer vision-based structural health monitoring (SHM) technologies have demonstrated great potential for damage detection due to the benefits of being low cost, easy to deploy, and contactless. In this study, we propose a vision-based non-contact bolt loosening detection method that uses a consumer-grade digital camera. Two images of the monitored steel joint are first collected during different inspection periods and then aligned through two image registration processes. If the bolt experiences rotation between inspections, it will introduce differential features in the registration errors, serving as a good indicator for bolt loosening detection. The performance and robustness of this approach have been validated through a series of experimental investigations using three laboratory setups including a gusset plate on a cross frame, a column flange, and a girder web. The bolt loosening detection results are presented for easy interpretation such that informed decisions can be made about the detected loosened bolts.

69 citations

Journal ArticleDOI
TL;DR: In this article, the authors present an overview of the most used NDI/SHM technologies for freshwater pipes and sewers, and the methodologies that can be translated into SHM approaches are highlighted.
Abstract: Civil infrastructures such as bridges, buildings, and pipelines ensure society's economic and industrial prosperity. Specifically, pipe networks assure the transportation of primary commodities such as water, oil, and natural gas. The quantitative and early detection of defects in pipes is critical in order to avoid severe consequences. As a result of high-profile accidents and economic downturn, research and development in the area of pipeline inspection has focused mainly on gas and oil pipelines. Due to the low cost of water, the development of nondestructive inspection (NDI) and structural health monitoring (SHM) technologies for fresh water mains and sewers has received the least attention. Moreover, the technical challenges associated with the practical deployment of monitoring system demand synergistic interaction across several disciplines, which may limit the transition from laboratory to real structures. This paper presents an overview of the most used NDI/SHM technologies for freshwater pipes and sewers. The challenges that said infrastructures pose with respect to oil and natural gas pipeline networks will be discussed. Finally, the methodologies that can be translated into SHM approaches are highlighted.

69 citations


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