Method for predicting service life of guide pair of numerical control machine on basis of performance degradation model

Abstract

The invention provides a method for predicting the service life of a guide pair of a numerical control machine on the basis of a performance degradation model. The method comprises the following steps of: acquiring vibration signals, carrying out time-frequency domain analysis, extracting the sensitive characteristic data vectors of the performance degradation of the guide pair, and forming a sensitive characteristic matrix in a time-sequence manner; calculating the load Pi of the guide pair and recording the operating time ti at the same time; calculating the rated life time Lhi, the total time t' that the guide pair has run under the current working condition, and the expected residual life LDi according to Pi, and forming an expected residual life vector T of the expected residual life in a time-sequence manner; and fitting the mapping relation between the inputted sensitive characteristic matrix and the expected residual life vector T by using a degradation model formed by a double-layer dynamic fuzzy neural network, and outputting the prediction result of the service life. By taking the impact on the performance degradation of the guide pair caused by the load change thereof under various working conditions of the numerical control machine into consideration, the method of the invention can achieve the prediction of the residual life when the guide pair is used, and ensure the high prediction accuracy and high value in actual application.

Description

technical field

[0001] The invention belongs to the technical field of numerical control manufacturing of electromechanical integration, and in particular relates to performance degradation evaluation and service life prediction of guide rail pairs of numerical control machine tools. Background technique

[0002] The failure of CNC machine tools seriously affects the processing quality of parts and brings huge economic losses to enterprises. The faults of CNC machine tools include CNC system faults, electrical system faults, mechanical system faults and pneumatic hydraulic system faults, among which the performance degradation of the mechanical system is inevitable and is a key factor affecting product quality. Therefore, real-time monitoring of the mechanical system, discovery of the performance degradation rules of key components such as screw pairs, guide rail pairs, and spindle components during the operation of the machine tool, and real-time evaluation of the remaining...