Performance evaluation method for rolling bearing under multiple operating conditions based on geometric measurement

Abstract

The invention relates to a performance evaluation method for a rolling bearing under multiple operating conditions based on geometric measurement. The performance evaluation method comprises the steps of firstly converting rolling bearing vibration signals with different fault degrees under different operating conditions into a recurrence plot, then stable extracting geometric features of the converted recurrence plot by using scale invariant feature transform method, carrying out singular value decomposition on the geometric features extracted from the bearing signals to acquire feature curves of the rolling bearing with different fault degrees under the different operating conditions, and then calculating the similarity of different feature curves by using dynamic time warping so as to work out a health degree of the rolling bearing. Case verification is carried out by using bearing data of the Case Western Reserve University in the United States, and an experimental result shows that the performance evaluation method can evaluate the health degree of the rolling bearing under multiple operating conditions effectively.

Description

technical field [0001] The invention relates to a multi-working-condition rolling bearing performance evaluation method based on geometric measurement, and belongs to the technical field of rolling bearing performance evaluation. Background technique [0002] Rolling bearings are one of the most important components in rotating machinery. Bearing failure or damage often leads to mechanical system failures, and even poses a threat to the safety of workers. The bearing health assessment can obtain the health status of the bearing and prevent the occurrence of failure, so that the equipment can be repaired optimally and avoid the loss caused by unplanned downtime. In addition, reasonable maintenance can not only reduce maintenance costs, but also maximize the efficiency of components. Therefore, it is of great significance to evaluate the performance of rolling bearings in mechanical equipment. [0003] Among various signal processing methods, methods based on vibration signa...

AI Technical Summary

Problems solved by technology

However, EMD has defects such as over-envelope, under-envelope, and endpoint effects; STFT cannot meet the requirements of time and resolution at the same time; WPT needs prior knowledge of the signal to select wavelet packets; WVD is prone to interference from cross items, etc. shortcoming

Images