Generalized dispersive mode decomposition: Algorithm and applications

被引：50
作者：
Chen, Shiqian [1 ]
Wang, Kaiyun [1 ]
Peng, Zhike [2 ]
Chang, Chao [1 ]
Zhai, Wanming [1 ]
机构：
[1] Southwest Jiaotong Univ, State Key Lab Tract Power, Chengdu 610031, Peoples R China
[2] Shanghai Jiao Tong Univ, State Key Lab Mech Syst & Vibrat, Shanghai 200240, Peoples R China
来源：
JOURNAL OF SOUND AND VIBRATION | 2021年 / 492卷
基金：
中国国家自然科学基金;
关键词：
Group delay; Dispersion curve; Fault diagnosis; Lamb wave; Time-frequency (TF);
D O I：
10.1016/j.jsv.2020.115800
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
Dispersive signals known for frequency-dependent characteristics have been frequently encountered in various fields like nondestructive testing, underwater acoustics, etc. Such signals often exhibit frequency-varying group delays (GDs) and consist of multiple modes overlapped in the time-frequency (TF) domain, which brings challenges to existing signal processing methods. In this paper, a generalized dispersive mode decomposition (GDMD) method is proposed to accurately estimate GDs and fully separate overlapped modes of dispersive signals. Specifically, a generalized dispersive signal model is defined in the frequency domain at first. Then, based on the defined model, the mode decomposition issue is formulated as an optimal dispersion compensation problem where the method simultaneously searches for the optimal modes and their GDs, with which the dispersion effects of all the modes can be fully eliminated. In addition, according to the output results of the GDMD, a high-quality TF distribution can be constructed to clearly reveal the TF pattern of a multimodal dispersive signal. Simulated examples and real-life applications to railway wheel fault diagnosis and Lamb wave analysis are carried out to show the effectiveness of the GDMD. (C) 2020 Elsevier Ltd. All rights reserved.
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页数：16
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