2024.11.05
Research on Rolling Bearing Operating Life Based on Principal Component Analysis
Bearing is one of the most important components of rotating machinery, but it is also one of the most easily damaged components. According to the statistics at the present stage, about 1/3 of the rotating machinery failures are caused by bearing faults. Therefore, it is of great significance to effectively judge the running state of the bearing [1]. Bearing failure is a multi-state process that gradually evolves from normal to failure. The state existing in this process can not be observed directly, and the measurement signal needs to be analyzed with the help of external equipment [2]. In order to make a reasonable analysis of the bearing operation, the extraction of characteristic parameters is very important.
At present, the time domain parameters are mainly used in the research, including dimensional indicators such as peak-to-peak value, root mean square value and effective value, as well as dimensionless indexes such as skewness factor, wave crest factor, kurtosis and so on. These indexes have their own defects in the whole life cycle of the bearing, which can not fully reflect the state change of the whole operation of the bearing. Therefore, this paper proposes to use principal component analysis to extract new indexes from the existing parameters, and to judge the running state of rolling bearings in the whole life cycle by establishing new quantitative standards.
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