A method for predicting the wear state of ball screw of CNC machine tool

Abstract

The invention discloses a method for predicting abrasion state of a numerically-controlled machine tool ball screw. The method comprises the following steps that three-phase current signals of a motor of a feed shaft of a numerically-controlled machine tool are collected and preprocessed, and then the root-mean-square value IRMS of the three-phase current is calculated; frequency-domain analysis is performed on the root-mean-square value IRMS so as to obtain current signal frequency-domain energy distributions formed before and after the ball screw of the feed shaft is abraded, and the frequency corresponding to current signal mutation is obtained according to the comparison of the current signal frequency-domain energy distributions formed before and after the ball screw of the feed shaft is abraded; and according to the obtained frequency, a wavelet packet is selected for decomposing the layer number,, wavelet packet decomposition is performed on the root-mean-square value IRMS to obtain multiple wavelet packet components, the variance characteristic value of a signal obtained after wavelet packet components on the sensitive segment are reconstructed is calculated, and the abrasion state of the numerically-controlled machine tool ball screw is predicted based on the variance characteristic value. The method has the beneficial effects of being high in prediction speed, low in cost and high in accuracy rate, and the abrasion state of the ball screw can be rapidly evaluated.

Description

technical field [0001] The invention belongs to the field of predicting the wear state of a ball screw, and more particularly relates to a method for predicting the wear state of a ball screw of a numerically controlled machine tool. Background technique [0002] The design life of the ball screw is 10,000 to 15,000 hours. With the development of CNC machine tool processing towards high speed, high acceleration, high precision, and heavy load, the ball screw often fails to reach the design life and is damaged. The most likely form of damage to the ball screw is wear. The wear state of the ball screw in the feed system of the machine tool is predicted to obtain a relatively quantitative index for the wear state of the ball screw, and timely measures can be taken to ensure the processing quality of the workpiece. Reduce scrap rate and improve processing efficiency. [0003] At present, the wear monitoring methods of machine tool equipment are mainly divided into direct monito...

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Problems solved by technology

The direct monitoring method is to directly measure the wear amount. Although the direct monitoring method can accurately measure the wear amount of the worn parts, it is inconvenient to measure. Some parts, such as ball screws, bearings, and guide rails, do not have special instruments for measuring wear. , it is difficult to obtain accurate wear amount

The indirect monitoring method is to monitor the wear state of machine tool components by acquiring machine tool signals and analyzing the signals. The monitoring signals are obtained through different sensors, and the sensors can obtain relatively rich sensing signals. For example, Ryuta SATO of Kobe University uses motor current The signal-assisted speed, position and other signals establish the wear measurement method of the ball screw pair, and the effectiveness of this method is verified by comparing with the measured backlash, but the author believes that the backlash is the wear amount of the ball screw; Another example is Huang Haifeng of Southwest Jiaotong University in 2013. By collecting the current signal and vibration signal of the motor connected to the ball screw, the performance degradation of the ball screw is monitored, but the main method is to construct the current signal, vibration signal and The change of friction coefficient constructs the monitoring method of lead screw wear

[0004] However, further research shows that the above-mentioned prior art still has the following defects or deficiencies: although the above-mentioned method has certain feasibility, it is very inconvenient in engineering application and the test cost is high; although the acquisition of the current signal is relatively simple, However, it is not mentioned in the above method, one is not related to the rapid identification of the machine tool processing state, and the other is not to predict the wear state of the lead screw from the machine tool current signal combined with the change trend of the machine tool excited energy

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