Bolt loosening detection in a jointed beam using empirical mode decomposition–based nonlinear system identification method
Links to Files
Author/Creator
Author/Creator ORCID
Date
Type of Work
Department
Program
Citation of Original Publication
Xu, C., Huang, C.-C. and Zhu, W.-D. (2019) ‘Bolt loosening detection in a jointed beam using empirical mode decomposition–based nonlinear system identification method’, International Journal of Distributed Sensor Networks. doi: 10.1177/1550147719875656.
Rights
This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
Attribution 4.0 International (CC BY 4.0)
Attribution 4.0 International (CC BY 4.0)
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.