Research on Background Noise Separation of Reducers Based on VMD and FastICA

The NVH noise performance of electric vehicles greatly affects driving comfort, and the NVH performance has become a key indicator for verifying the quality of their products; strengthening the research can greatly promote the high-quality development of reducers. Aiming at the problem that the nois...

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Main Authors: Li Weilin, Jiang Yangming, Zhang Zhongjie, Liu Ting, Lin Ting, Cheng Xu, Chen Feng, Wang Keyu, Zeng Hao
Format: Article
Language:zho
Published: Editorial Office of Journal of Mechanical Transmission 2024-11-01
Series:Jixie chuandong
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Online Access:http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2024.11.023
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author Li Weilin
Jiang Yangming
Zhang Zhongjie
Liu Ting
Lin Ting
Cheng Xu
Chen Feng
Wang Keyu
Zeng Hao
author_facet Li Weilin
Jiang Yangming
Zhang Zhongjie
Liu Ting
Lin Ting
Cheng Xu
Chen Feng
Wang Keyu
Zeng Hao
author_sort Li Weilin
collection DOAJ
description The NVH noise performance of electric vehicles greatly affects driving comfort, and the NVH performance has become a key indicator for verifying the quality of their products; strengthening the research can greatly promote the high-quality development of reducers. Aiming at the problem that the noise data acquisition environment of the noise test stand is highly disturbed and difficult to be eliminated, a noise signal decomposition based on variational modal decomposition (VMD) and fast independent component analysis (FastICA) and a background noise component identification and noise reduction method based on signal correlation analysis were proposed. The method firstly adopted the VMD to decompose the speed reducer mixed signal into multiple modal components, and then further separated and demixed the obtained modal components through the FastICA to obtain the multidimensional independent components. Finally, the multidimensional independent components were identified and filtered out by using the signal correlation analysis to reduce the noise and complete the separation of the background noise in the test. The results show that the proposed VMD-FastICA can correctly separate the background noise signal in the mixed signal, and effectively separate the noise. Through the reducer noise test stand 9 000 r/min speed conditions of operation test comparison, the decomposition filters out the background noise and reduces the sound pressure level by an average of 3.09 dB(A), with an average error of 0.32 dB(A), to further optimize new energy vehicle gearbox noise performance test methods, and to enhance the accuracy of the gearbox noise test to provide a technical guarantee.
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spelling doaj-art-38de89e19d7d4aa2891043c557b253272025-01-10T15:01:58ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392024-11-014816216877639539Research on Background Noise Separation of Reducers Based on VMD and FastICALi WeilinJiang YangmingZhang ZhongjieLiu TingLin TingCheng XuChen FengWang KeyuZeng HaoThe NVH noise performance of electric vehicles greatly affects driving comfort, and the NVH performance has become a key indicator for verifying the quality of their products; strengthening the research can greatly promote the high-quality development of reducers. Aiming at the problem that the noise data acquisition environment of the noise test stand is highly disturbed and difficult to be eliminated, a noise signal decomposition based on variational modal decomposition (VMD) and fast independent component analysis (FastICA) and a background noise component identification and noise reduction method based on signal correlation analysis were proposed. The method firstly adopted the VMD to decompose the speed reducer mixed signal into multiple modal components, and then further separated and demixed the obtained modal components through the FastICA to obtain the multidimensional independent components. Finally, the multidimensional independent components were identified and filtered out by using the signal correlation analysis to reduce the noise and complete the separation of the background noise in the test. The results show that the proposed VMD-FastICA can correctly separate the background noise signal in the mixed signal, and effectively separate the noise. Through the reducer noise test stand 9 000 r/min speed conditions of operation test comparison, the decomposition filters out the background noise and reduces the sound pressure level by an average of 3.09 dB(A), with an average error of 0.32 dB(A), to further optimize new energy vehicle gearbox noise performance test methods, and to enhance the accuracy of the gearbox noise test to provide a technical guarantee.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2024.11.023Electric vehicle reducerBackground noiseVMDFastICA
spellingShingle Li Weilin
Jiang Yangming
Zhang Zhongjie
Liu Ting
Lin Ting
Cheng Xu
Chen Feng
Wang Keyu
Zeng Hao
Research on Background Noise Separation of Reducers Based on VMD and FastICA
Jixie chuandong
Electric vehicle reducer
Background noise
VMD
FastICA
title Research on Background Noise Separation of Reducers Based on VMD and FastICA
title_full Research on Background Noise Separation of Reducers Based on VMD and FastICA
title_fullStr Research on Background Noise Separation of Reducers Based on VMD and FastICA
title_full_unstemmed Research on Background Noise Separation of Reducers Based on VMD and FastICA
title_short Research on Background Noise Separation of Reducers Based on VMD and FastICA
title_sort research on background noise separation of reducers based on vmd and fastica
topic Electric vehicle reducer
Background noise
VMD
FastICA
url http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2024.11.023
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