Thermal error prediction method and device for machine tool feed shaft and storage medium

Abstract

The invention belongs to the technical field of machine tool thermal error compensation, and particularly relates to a thermal error prediction method and device for a machine tool feed shaft and a storage medium, and the thermal error prediction method comprises the following steps: S1, collecting thermal error measurement values of the machine tool feed shaft according to a time sequence, and forming a thermal error training set; s2, establishing an ARMA model; S3, optimizing parameter variables p and q and vectors alpha i and beta j by using a genetic algorithm; and S4, substituting the parameter variables p and q and the vectors alpha i and beta j obtained by optimization in the step S3 into an ARMA model to obtain a GA-ARMA model, and performing thermal error prediction on the machine tool feed shaft by using the GA-ARMA model. The prediction method provided by the invention is high in prediction efficiency, high in accuracy and good in stability.

Description

technical field [0001] The invention belongs to the technical field of thermal error compensation of machine tools, and in particular relates to a thermal error prediction method, device and storage medium of a feed axis of a machine tool. Background technique [0002] The main sources of errors of CNC machine tools are geometric errors, thermal errors and other errors. Thermal errors account for 40% to 70% of the total errors of machine tools. Therefore, reducing thermal errors can effectively improve the machining accuracy of machine tools. The methods to reduce the thermal error of the machine tool are: thermal error prevention method and thermal error compensation method. [0003] The thermal error prevention method can reduce the original error by using materials with good thermal stability to manufacture machine tools, but this method leads to a substantial increase in production costs. The thermal error compensation method reduces the thermal error of the machine too...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the problem of low prediction efficiency and low prediction accuracy of thermal error prediction using the ARMA model as a thermal error model, the present invention provides a thermal error prediction method, device, and storage device with high prediction efficiency and high accuracy for the feed axis of a machine tool. Media and Computer Equipment

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