Method for Extracting Fault Feature Frequency of Variable Speed ​​Train Rolling Bearings

Abstract

The invention discloses a method for extracting fault characteristic frequencies of train rolling bearings with variable rotational speeds, and belongs to the field of technologies for diagnosing faults and processing signals. The method includes steps of analyzing vibration signals of the bearings with the variable rotational speeds in time and frequency domains, searching local peak values of the vibration signals and extracting instantaneous frequency values corresponding to the rotational speeds at different moments; fitting instantaneous frequencies by the aid of neural networks, acquiring rotational speed curves of reference spindles, re-sampling original signals at uniform angles on the basis of the rotational speed curves and analyzing order ratios of the original signals on the basis of the rotational speed curves; separating signals with mixed order ratio signals by the aid of fixed-point independent component analysis and spectrum peak search technologies to acquire order ratio component characteristics of fault components of the bearings. The method has the advantages that the method is used for estimating the rotational speeds of the train bearings without tachometers in real time, the instable fault bearing signals can be converted into the stable signals in uniform-angle domains, independent order ratio components can be effectively separated from the signals, and the method is favorable for extracting the fault characteristic frequencies of the train bearings and detecting the fault characteristic frequencies of the train bearings in an online manner.

Description

technical field [0001] The invention relates to the technical field of acoustic fault diagnosis of mechanical equipment, in particular to a method for extracting fault characteristic frequencies of train rolling bearings in a state of variable speed. Background technique [0002] Safety is the eternal theme of railway transportation. my country now has more than 600,000 railway wagons. Rolling bearings are important mechanical components. Due to long-term heavy loads and frictional operation, failures such as surface peeling are prone to occur. It is very important to implement online fault diagnosis for vicious accidents such as shaft burning, shaft cutting, derailment and overturning. According to the survey results of the depot, the bearing maintenance process is mainly experienced workers manually turning the outer ring of the bearing to judge whether there is abnormal sound or fault by human ears. This method is greatly affected by subjective factors and is not conduciv...

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Problems solved by technology

[0005] Some research results have been obtained in the extraction of characteristic frequency of bearing faults. However, the above-mentioned research or application systems generally assume that the speed is constant, and cannot be directly applied to the state detection of train rolling bearings under variable speed motion.

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