 Bolt loosening detection in a jointed beam using empirical mode decomposition–based nonlinear system identification methodChao Xu, Chen-Chen Huang and Wei-Dong Zhu International Journal of Distributed Sensor Networks, 2019, vol. 15, issue 9, 1550147719875656 Abstract: In this work, a state-of-art nonlinear system identification method based on empirical mode decomposition is utilized and extended to detect bolt loosening in a jointed beam. This nonlinear system identification method is based on identifying the multi-scale dynamics of the underlying system. Only structural dynamic response signals are needed to construct a reduced-order model to represent the system concerned. It makes the method easy to use in practice. A new bolt loosening identification procedure based on the constructed system nonlinear reduced-order model is proposed. A new damage feature to indicate bolt loosening is presented. Experimental works are carried out to validate the proposed method. The results show that the proposed damage detection method can detect bolt loosening effectively, and the proposed damage feature values increase with the increase of bolt torques. The damage feature calculated from the response solution of the reduced-order model can give robust and sensitive indication of bolt loosening. Keywords: Bolt loosening; nonlinear system identification; reduced-order model; empirical mode decomposition; damage diagnosis (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:15:y:2019:i:9:p:1550147719875656 Access Statistics for this article More articles in International Journal of Distributed Sensor Networks |
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