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Multi-scale chirplet synchroextracting transform for accurate characterization of adjacent fault features in rotating machinery

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成果类型:
期刊论文
作者:
Site Lv;Hongan Wu;Shan Zeng*;Chen Yu;Ke Yang
通讯作者:
Shan Zeng
作者机构:
[Site Lv; Shan Zeng; Chen Yu; Ke Yang] School of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan, Hubei 430023, China
[Hongan Wu] Hubei Key Laboratory for Efficient Utilization and Agglomeration of Metallurgic Mineral Resources, Wuhan University of Science and Technology, Wuhan 430081, China
通讯机构:
[Shan Zeng] S
School of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan, Hubei 430023, China
语种:
英文
期刊:
Mechanical Systems and Signal Processing
ISSN:
0888-3270
年:
2025
卷:
234
页码:
112826
基金类别:
CRediT authorship contribution statement Site Lv: Writing – original draft, Methodology. Hongan Wu: Writing – review & editing, Methodology. Shan Zeng: Validation, acquisition, Data curation. Chen Yu: Investigation, Conceptualization. Ke Yang: Validation, Formal analysis.
机构署名:
本校为第一且通讯机构
院系归属:
数学与计算机学院
摘要:
When mechanical equipment fails, the fault characteristics are often interfered by adjacent components. Therefore, how to well characterize the time-varying laws of multi-component signals containing adjacent components has always been a difficulty and research hotspot in the application of time–frequency analysis (TFA) technologies in mechanical fault diagnosis. In this paper, a new TFA method is proposed, called the Multi-scale chirplet synchroextracting transform (MCSET). On the basis of chirplet transform (CT), by using two additional para...

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