A Judgment Method for Rolling Bearing Performance Degradation Decay Nodes

Abstract

The invention discloses a determination method of performance degradation nodes of rolling bearings and relates to the technical field of detection of performance of bearings. The method comprises thefollowing steps: obtaining vibration acceleration data of different monitoring periods, carrying out Hilbert transformation of the data, solving a power spectrum density maximum value, generating a power spectrum density maximum value curve, generating a first-order derivative curve of the power spectrum density maximum value, defining degradation period nodes, and determining predictable intervals. In the whole bearing service life periods, the extracted performance degradation characteristic quantity variation trends of different bearings have consistency; a trend curve is used for determining operation stages of the bearings and nodes entering the degradation periods so as to determine the predictable intervals; in addition, the method is capable of effectively improving the predictionaccuracy of the remaining lives of the rolling bearings; and the method basis is provided for ensuring safety, availability and efficient operation of the system, reducing maintenance cost and achieving condition maintenance.

Description

technical field [0001] The invention relates to the technical field of bearing performance detection, in particular to a method for judging the performance degradation node of a rolling bearing. Background technique [0002] Different bearings have certain differences in their life values ​​due to their different working conditions and damage types. It is difficult to find an index that reflects the consistency of the variation trend of the performance degradation characteristics of different bearings, which brings difficulties to improve the prediction accuracy of the remaining life of the bearing. The entire working cycle of the bearing can be divided into the running-in stage, the normal stage and the recession stage. The performance decline period should be selected as the prediction interval for the remaining life prediction of the bearing. If an index that reflects the consistency of the change trend of the extracted performance degradation characteristics cannot be fo...

AI Technical Summary

Problems solved by technology

The performance decline period should be selected as the prediction interval for the remaining life prediction of the bearing. If no index can be found to reflect the consistency of the change trend of the extracted performance degradation characteristics, there will be no uniform standard for the division of the bearing's duty cycle.

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