Modeling method of thermal error least squares support vector machine of numerically-controlled machine tool

Abstract

The invention discloses a modeling method of a thermal error least squares support vector machine of a numerically-controlled machine tool. The method comprises the following steps: (1) selecting a kernel function and determining parameters; and (2) establishing a thermal error model of the machine tool according to least squares support vector machine theory. A compensating system of the invention has the advantages of simple structure and reliable application; and the modeling method of the least squares support vector machine improves the model precision and generalization capability and overcomes defects of the existing prediction methods, such as low precision, low generalization capability and the like. The modeling method has higher prediction precision when the sample size is small and even the sample data are small, thus reducing dependence on experience. Meanwhile, the method improves the self-learning ability of the system, the thermal error model obtained by training can reflect the manufacturing procedure change of the machine tool, and the method has the advantages of adaptability, low hardware requirements for the thermal error compensating system, simple structure and good reliability.

Description

technical field [0001] The invention relates to a thermal error least square support vector machine modeling method of a numerically controlled machine tool. Background technique [0002] Thermal error control of CNC machine tools is one of the basic technologies for precision and ultra-precision machining. The main steps of machine tool thermal error compensation are: detection and analysis of error source, establishment of comprehensive mathematical model of error motion, identification of error element, execution of error compensation and evaluation of error compensation effect. [0003] In thermal error compensation, the establishment of thermal error model is a key step. The experimental modeling method is the most commonly used thermal error modeling method, which uses the thermal error data measured by the experiment and the temperature value of the machine tool and uses the least square principle to perform fitting modeling. However, the thermal error of the machin...

AI Technical Summary

Problems solved by technology

Due to the characteristics of thermal errors, such as time-varying, multi-factor, and working condition uncertainty, the modeling methods developed in recent years have certain limitations.

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