CLC number:
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2023-04-25
Cited: 0
Clicked: 1119
Shuiguang TONG, Zilong FU, Zheming TONG, Junjie LI, Feiyun CONG. Fault diagnosis for gearboxes based on Fourier decomposition method and resonance demodulation[J]. Journal of Zhejiang University Science A, 2023, 24(5): 404-418.
@article{title="Fault diagnosis for gearboxes based on Fourier decomposition method and resonance demodulation",
author="Shuiguang TONG, Zilong FU, Zheming TONG, Junjie LI, Feiyun CONG",
journal="Journal of Zhejiang University Science A",
volume="24",
number="5",
pages="404-418",
year="2023",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A2200555"
}
%0 Journal Article
%T Fault diagnosis for gearboxes based on Fourier decomposition method and resonance demodulation
%A Shuiguang TONG
%A Zilong FU
%A Zheming TONG
%A Junjie LI
%A Feiyun CONG
%J Journal of Zhejiang University SCIENCE A
%V 24
%N 5
%P 404-418
%@ 1673-565X
%D 2023
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A2200555
TY - JOUR
T1 - Fault diagnosis for gearboxes based on Fourier decomposition method and resonance demodulation
A1 - Shuiguang TONG
A1 - Zilong FU
A1 - Zheming TONG
A1 - Junjie LI
A1 - Feiyun CONG
J0 - Journal of Zhejiang University Science A
VL - 24
IS - 5
SP - 404
EP - 418
%@ 1673-565X
Y1 - 2023
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A2200555
Abstract: Condition monitoring and fault diagnosis of gearboxes play an important role in the maintenance of mechanical systems. The vibration signal of gearboxes is characterized by complex spectral structure and strong time variability, which brings challenges to fault feature extraction. To address this issue, a new demodulation technique, based on the fourier decomposition method and resonance demodulation, is proposed to extract fault-related information. First, the fourier decomposition method decomposes the vibration signal into Fourier intrinsic band functions (FIBFs) adaptively in the frequency domain. Then, the original signal is segmented into short-time vectors to construct double-row matrices and the maximum singular value ratio method is employed to estimate the resonance frequency. Then, the resonance frequency is used as a criterion to guide the selection of the most relevant FIBF for demodulation analysis. Finally, for the optimal FIBF, envelope demodulation is conducted to identify the fault characteristic frequency. The main contributions are that the proposed method describes how to obtain the resonance frequency effectively and how to select the optimal FIBF after decomposition in order to extract the fault characteristic frequency. Both numerical and experimental studies are conducted to investigate the performance of the proposed method. It is demonstrated that the proposed method can effectively demodulate the fault information from the original signal.
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