An adaptive multiple time domain synchronous averaging method and its application in vibration signal feature enhancement. (2nd February 2022)

• Record Type: Journal Article
• Authors: Yin, Na; Meng, Zong; Guan, Yang; Fan, Fengjie
• Is Part Of: Measurement science & technology. Volume 33:Number 5(2022)
• Publication Date: 2022-02-02
• Subjects: rotating machinery -- feature detection -- time domain synchronous averaging -- auto correlation theory; 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/ac3d08
• Languages: English
• ISSNs: 0957-0233

Abstract

Abstract: The time domain synchronous averaging (TSA) method is a typical time domain signal denoising method, which is widely used in the state detection of rotating machinery. In order to solve the difficult problem of extracting vibration signal features from strong interference, an adaptive multiple time domain synchronous averaging method based on signal period is proposed in this paper. In view of the blindness and randomness of period selection in the TSA method, a new evaluation index of periodic impulse characteristics is proposed. In this method, the signal is resampled then the iteration stop threshold is set, and then the calculation period of interest is determined by two cycle screening. Finally, reconstructed signals with enhanced features are obtained by copying and stitching. Experimental results show that the proposed method is robust and superior in the feature detection of rolling bearing vibration signals.