Train rolling bearing fault and impurity vibration distinguishing method

Abstract

The invention discloses a train rolling bearing fault and impurity vibration distinguishing method. The method includes: utilizing spectral kurtosis to perform filtering processing on an original bearing vibration signal, and adopting an empirical mode decomposition technique to perform step-by-step decomposition on the preprocessed vibration signal to obtain intrinsic mode functions; subjecting the intrinsic mode functions to frequency spectrum and statistic characteristic analysis, extracting a feature vector composed of frequency spectrum center-of-gravity and characteristic frequency energy ratio as input, establishing a support vector machine based classifier model by training, and distinguishing whether a rolling bearing with abnormal noise is faulted or contains impurities in real time. The method is used for distinguishing the fault or impurity-containing state of the train rolling bearing based on vibration signal analysis, the method effectively improves accuracy in bearing fault identification, the problem of overhigh false alarm rate in the bearing vibration diagnosis method caused by impurities is solved, and good technical support is provided for engineering application of the vibration diagnosis method.

Description

technical field [0001] The invention relates to the technical field of equipment fault diagnosis, in particular to a method for distinguishing train rolling bearing faults from impurity-containing operating states. Background technique [0002] Safety is the eternal theme of railway transportation. Rolling bearings are one of the important components of railway wagons. Due to long-term high-speed and heavy-load operation, they are prone to failures such as peeling, so it is very important to detect their failures. According to the research results of the author from Beijing, Xuzhou, Jingzhou and other depots, the domestic inspection and maintenance process mainly involves experienced workers manually turning the outer ring of the bearing to judge whether there is abnormal sound or failure by human ears. This method is subject to subjective factors. It has a great impact and is not conducive to standardized inspection management. In order to reduce their own liability risks,...

AI Technical Summary

Problems solved by technology

There are few literature reports on the problem of misjudgment caused by impurities, but it is a bottleneck problem restricting the engineering application of vibration diagnosis methods

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