An Adaptive Chirp Mode Decomposition-Based Method for Modal Identification of Time-Varying Structures

Xiao-Jun Yao, Yu-Chun Lv, Xiao-Mei Yang (), Feng-Yang Wang and Yong-Xiang Zheng
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Xiao-Jun Yao: Guangdong Provincial Key Laboratory of Intelligent Disaster Prevention and Emergency Technologies for Urban Lifeline Engineering, Dongguan University of Technology, Dongguan 523808, China
Yu-Chun Lv: School of Civil and Transportation Engineering, Hebei University of Technology, Tianjin 300401, China
Xiao-Mei Yang: College of Civil Engineering, Fuzhou University, Fuzhou 350108, China
Feng-Yang Wang: Guangdong Provincial Key Laboratory of Intelligent Disaster Prevention and Emergency Technologies for Urban Lifeline Engineering, Dongguan University of Technology, Dongguan 523808, China
Yong-Xiang Zheng: Key Laboratory of Roads and Railway Engineering Safety Control (Shijiazhuang Tiedao University) Ministry of Education, Shijiazhuang Tiedao University, Shijiazhuang 050043, China

Mathematics, 2024, vol. 12, issue 19, 1-22

Abstract: Modal parameters are inherent characteristics of civil structures. Due to the effect of environmental factors and ambient loads, the physical and modal characteristics of a structure tend to change over time. Therefore, the effective identification of time-varying modal parameters has become an essential topic. In this study, an instantaneous modal identification method based on an adaptive chirp mode decomposition (ACMD) technique was proposed. The ACMD technique is highly adaptable and can accurately estimate the instantaneous frequencies of a structure. However, it is important to highlight that an initial frequency value must be selected beforehand in ACMD. If the initial frequency is set incorrectly, the resulting instantaneous frequencies may lack accuracy. To address the aforementioned problem, the Welch power spectrum was initially developed to extract a high-resolution time–frequency distribution from the measured signals. Subsequently, the time–frequency ridge was identified based on the maximum energy position in the time–frequency distribution plot, with the frequencies associated with the time–frequency ridge serving as the initial frequencies. Based on the initial frequencies, the measured signals with multiple degrees of freedom could be decomposed into individual time-varying components with a single degree of freedom. Following that, the instantaneous frequencies of each time-varying component could be calculated directly. Subsequently, a sliding window principal component analysis (PCA) method was introduced to derive instantaneous mode shapes. Finally, vibration data collected under various operational scenarios were used to validate the proposed method. The results demonstrated the effective identification of time-varying modal parameters in real-world civil structures, without missing modes.

Keywords: modal identification; adaptive chirp mode decomposition; time-varying structure; instantaneous frequency; time–frequency distribution (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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