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Fault diagnosis method of elevator traction wheel bearing based on angular domain resampling and VMD

Published:2023-10-19 author:WEI Yi-min, LIU Hui, YANG Le-hong. Browse: 310 Check PDF documents

Fault diagnosis method of elevator traction wheel bearing based on

angular domain resampling and VMD

WEI Yi-min, LIU Hui, YANG Le-hong

(Zhejiang Key Laboratory of Mechanical and Electrical Product Reliability Technology, Zhejiang

SciTech University, Hangzhou 310018, China)

Abstract: Aiming at the problem that the fault diagnosis effect of traction wheel bearing was easily affected by variable speed working conditions and environmental noise, a fault diagnosis method of traction wheel bearing based on angle resampling method for estimating traction wheel speed based on car running acceleration, and a fault diagnosis method of traction wheel bearing based on sparrow search algorithm for optimizing variational mode decomposition parameters were proposed. Firstly, the method of estimating the speed of the traction pulley was used to realize the angular resampling of the vibration signal of the traction wheel bearing. Then, the sparrow search algorithm (SSA) was used to optimize the variational mode decomposition (VMD) parameters, the vibration signal was decomposed and the components were selected according to the maximum kurtosis criterion, and the fault characteristics of the traction wheel bearing were extracted. Finally, the elevator test bench was built to carry out the fault injection test, and a variety of classification models were constructed to verify the fault diagnosis method of traction wheel bearing based on angle resampling and the method of SSA-VMD. The research results show that, the diagnostic effect of angular resampling is obviously better than that of non-angular resampling, and the fault recognition rate is increased by more than 5%. The SSA-VMD method can accurately extract the fault features of the traction wheel bearing under the experimental conditions, and the fault recognition rate reaches 95%.

Key words: traction wheel bearings; fault diagnosis; equal angle domain resampling; variational modal decomposition (VMD); sparrow search algorithm (SSA)

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