Modeling method and equipment of machine tool feed system based on dynamics and neural network

Abstract

The invention discloses a modeling method and equipment for a machine tool feed system based on dynamics and a neural network, and belongs to the field of artificial intelligence and computer-aided manufacturing. The method specifically includes the following steps: Firstly, according to the dynamics and kinematic characteristics of each component of the machine tool feed system, the dynamic equation of the feed system is deduced. And build the dynamic simulation model of the feed system according to the dynamic equation. The genetic algorithm is used to identify some parameters of the simulation model, and the accurate values ​​of the parameters are obtained. Finally, the neural network model is used to replace the workbench displacement module, and the output of each module of the original model is used as the input feature of the neural network model, so that the neural network outputs the simulation displacement of the hybrid model. The modeling method realized according to the present invention can improve the nonlinear expression ability of the dynamic model, and improve the simulation accuracy and generalization ability of the model.

Description

technical field [0001] The invention belongs to the field of artificial intelligence and computer-aided manufacturing, and relates to a modeling method and equipment for a machine tool feed system based on dynamics and neural networks, and more particularly, to a modular machine tool feed based on dynamics and neural networks. System Modeling Methods. Background technique [0002] With the development of information technology, virtual manufacturing technology is widely used in various fields of industrial manufacturing, and the basic equipment of the manufacturing process is machine tools, so virtual technology is also inseparable from virtual machine tools. The virtual machine tool is the reproduction of the machine tool in the virtual space of the computer. With the help of virtual machine tools and performing performance simulation and machining simulation on it, it is possible to test the machine tool performance, simulate the machining process, and check the machining...

AI Technical Summary

Problems solved by technology

However, the friction force in a mechanical system is related to many factors, involving mechanics, heat transfer, chemistry, physics and other disciplines, it is difficult to obtain an accurate mathematical model of friction force

In order to solve this problem, the above model ignores the hinge gap, thread gap, temperature change and other conditions in the real environment to approximate the real friction force, thereby reducing the simulation accuracy of the simulation model, so that the simulation effect is consistent with the actual machining. The situation is quite different and cannot accurately reflect the real processing results

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