Fault Diagnosis for Rolling Bearing of Combine Harvester Based on Composite-Scale-Variable Dispersion Entropy and Self-Optimization Variational Mode Decomposition Algorithm

Because of the influence of harsh and variable working environments, the vibration signals of rolling bearings for combine harvesters usually show obvious characteristics of strong non-stationarity and nonlinearity. Accomplishing accurate fault diagnosis using these signals for rolling bearings is a...

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Bibliographic Details
Published in:	Entropy (Basel, Switzerland) Vol. 25; no. 8; p. 1111
Main Authors:	Jiang, Wei, Shan, Yahui, Xue, Xiaoming, Ma, Jianpeng, Chen, Zhong, Zhang, Nan
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 25.07.2023 MDPI
Subjects:	Agricultural machinery Algorithms Analysis Artificial intelligence Bearing strength Bearings combine harvester Combine harvesters Decomposition Dispersion dispersion entropy Entropy Farm equipment Fault diagnosis Machine learning Optimization Research methodology Roller bearings rolling bearing Signal analysis Signal processing Vibration VMD Wavelet transforms
ISSN:	1099-4300, 1099-4300
Online Access:	Get full text
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