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Time-frequency analysis of multi-component nonstationary signals based on MRSECT
Published:2024-06-27 author:MOU Ling, QIN Yingjie, YI Cancan. Browse: 604 Check PDF documents
Time-frequency analysis of multi-component nonstationary signals 
based on MRSECT


MOU Ling1, QIN Yingjie2, YI Cancan2

(1.Hubei Energy Group Renewables Development Co., Ltd., Wuhan 430069, China; 
2.Key Laboratory of Metallurgical 
Equipment and Control, Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081, China)


Abstract:  The time-frequency analysis of multi-component non-stationary signals can obtain the changing rule of signal characteristics with time, and reveal the instantaneous phase and frequency, energy distribution and spectrum evolution of signals. The traditional time-frequency method for processing multi-component signals was limited by its own algorithmic limitations and could not achieve high-resolution time-frequency representation of the signal. Although improved time-frequency methods such as synchro squeezing transform (SST) were gradually derived, their performance in handling strong time-varying frequency modulated multi-component signals under noise interference was still not satisfactory. Comparing to other methods, chirplet transform (CT) had the adaptability of weak amplitude components and robustness to noise for processing non-stationary signals. Chirplet transform (CT) has strong adaptability and noise robustness in handling non-stationary weak amplitude components compared to other methods. Based on this, firstly a theoretical analysis of the multi-resolution chirplet transform (MRCT) derived from CT was conducted. Then, in order to further improve the time-frequency analysis capability, MRCT was optimized based on the principle of synchro extracting transform (SET), the synchro extracting operator (SEO) was introduced, and the multi-resolution synchro extracting chirplet transform (MRSECT) was proposed. Finally, in order to verify the effectiveness of MRSECT when processing complex vibration signals, MRSECT was used to analyze the numerical simulation signals and experimental bearing fault data. The research results demonstrate that MRSECT can effectively extract the time-frequency characteristics of non-stationary signals, and Renyi entropy increases by 25% in analog signal processing and 15.6% in actual bearing fault signal processing. MRSECT has higher time-varying feature information extraction ability compared to other time-frequency algorithms.

Key words:  synchro squeezing transform (SST); chirplet transform (CT); multi-resolution chirplet transform (MRCT); synchro extracting transform (SET); synchro extracting operator (SEO); multiresolution synchro extracting chirplet transform (MRSECT)

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