The objective of this study is the loosening detection of bolted joints without human involvement by applying the concept of structural health monitoring. The smart washer which consists of the flexible cantilever beam enables to detect bolt loosening by using self-sensing and actuation functions of piezoelectric material. The basic principle of how to detect bolt loosening is to the dynamics characteristics of a smart washer system which varies depending on bolt tightening axial tension. The natural frequency of the smart washer was identified by using the subspace state space identification method described in previous papers. However, the previous method has the problems that The identification and modeling error degrade the fault detection accuracy. This paper proposes a bolt loosening detection method based on the model-based Fault Detection and Isolation technique. The numerical simulations and the experiments results were performed to verify the possibility of the loosening detection by using the smart washer with observer-based supervisor. Improvement of bolt loosening detection accuracy is confirmed by comparing the proposed method with the previous method.
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ASME 2008 Conference on Smart Materials, Adaptive Structures and Intelligent Systems
October 28–30, 2008
Ellicott City, Maryland, USA
Conference Sponsors:
- Aerospace Division
ISBN:
978-0-7918-4332-1
PROCEEDINGS PAPER
Adopting Supervisor for Bolt Loosening Detection by Using Smart Washer
Tohru Tanaka,
Tohru Tanaka
Kobe University, Kobe, Hyogo, Japan
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Masayuki Okugawa
Masayuki Okugawa
Gifu National College of Technology, Motosu, Gifu, Japan
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Tohru Tanaka
Kobe University, Kobe, Hyogo, Japan
Masayuki Okugawa
Gifu National College of Technology, Motosu, Gifu, Japan
Paper No:
SMASIS2008-481, pp. 151-158; 8 pages
Published Online:
July 13, 2009
Citation
Tanaka, T, & Okugawa, M. "Adopting Supervisor for Bolt Loosening Detection by Using Smart Washer." Proceedings of the ASME 2008 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. Smart Materials, Adaptive Structures and Intelligent Systems, Volume 2. Ellicott City, Maryland, USA. October 28–30, 2008. pp. 151-158. ASME. https://doi.org/10.1115/SMASIS2008-481
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