A novel patch-matching 2D denoising method for fault diagnosis of roller bearings. (23rd September 2020)

• Record Type: Journal Article
• Authors: Wang, Mengjiao; Chen, Yangfan; Shenglong Yu, Samson; Zhang, Xinan; Ho-Ching Iu, Herbert; Li, Zhijun; Zeng, Yicheng
• Is Part Of: Measurement science & technology. Volume 31:Number 11(2020)
• Publication Date: 2020-09-23
• Subjects: vibration signal -- fault diagnosis -- patch-matching 2D -- empirical modal decomposition -- envelope analysis; Physical measurements -- Periodicals; Scientific apparatus and instruments -- Periodicals; Equipment and Supplies -- Periodicals; Science -- instrumentation -- Periodicals; Technology -- instrumentation -- Periodicals; Mesures physiques -- Périodiques; Physical measurements; Scientific apparatus and instruments; Periodicals; 502.87
• DOI: 10.1088/1361-6501/aba071
• Languages: English
• ISSNs: 0957-0233

Abstract

Abstract: The vibration signal of roller bearings contains important information, but the strong background noise makes fault diagnosis difficult. In this paper, inspired by the idea of a block-matching 3D algorithm, using local and nonlocal correlation of vibration signal, a patch-matching 2D (PM2D) denoising method is proposed for the first time to suppress noise in vibration signals. The proposed denoising method constructs similarity matrices of component modules, which are used for threshold processing to determine the coefficients of the 2D discrete cosine transform, so as to achieve optimal denoising performance. Then, empirical mode decomposition and envelope analysis are employed to perform fault diagnosis. The proposed PM2D denoising method and fault diagnosis strategies are applied to both simulated and measured signals. A comparison study shows the superiority of the proposed method over the other existing denoising methods.