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Gearbox fault diagnosis of rolling mills using multiwavelet sliding window neighboring coefficient denoising and optimal blind deconvolution
Authors:Jing Yuan  ZhengJia He  YanYang Zi  Han Liu
Affiliation:(1) Computer School, Huazhong University of Science &; Technology, Wuhan, Hubei, 430074, P.R. China;(2) Computer School, University of Derby, Derby, UK
Abstract:Fault diagnosis of rolling mills, especially the main drive gearbox, is of great importance to the high quality products and long-term safe operation. However, the useful fault information is usually submerged in heavy background noise under the severe condition. Thereby, a novel method based on multiwavelet sliding window neighboring coefficient denoising and optimal blind deconvolution is proposed for gearbox fault diagnosis in rolling mills. The emerging multiwavelets can seize the important signal proce...
Keywords:multiwavelet denoising  blind deconvolution  gearbox fault diagnosis  rolling mill  
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