Abstract
Abstract
Considering the shortcomings of traditional time-domain and frequency-domain analysis in processing non-stationary signals, this paper proposes to introduce time-frequency into the analysis of a one-dimensional vibration signal and transform it into a two-dimensional time-frequency image to obtain more abundant diagnostic information. At the same time, considering the problem of noise interference under complex working conditions, wavelet denoising is used to preprocess the signal, and the simulation signal is defined. The method of obtaining the time-frequency image verifies the denoising effect. Finally, through the public test data, it is proved that the method can effectively obtain reliable time-frequency images for further bearing fault diagnosis research.
Subject
Computer Science Applications,History,Education
Reference6 articles.
1. A review on signal processing techniques utilized in the fault diagnosis of rolling element bearings[J];Rai;Tribology International,2016
2. A hybrid prognostics approach for estimating the remaining useful life of rolling element bearings[J];Wang,2018
3. Design of online fault diagnosis and early warning system for coal mine rotating machinery[J];Yang;Industry and Mine Automation,2019
4. Fault Severity Monitoring of Rolling Bearings Based on Texture Feature Extraction of Sparse Time-Frequency Images[J];Yan;Applied sciences,2018
5. XJTU-SY Rolling Element Bearing Accelerated Life Test Datasets: A Tutorial[J];Lei;Journal of Mechanical Engineering,2019
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献