基于遗传算法优化小波神经网络数控机床热误差建模

doi:10.3901/JME.2019.21.215

机械工程学报 ›› 2019, Vol. 55 ›› Issue (21): 215-220.doi: 10.3901/JME.2019.21.215

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基于遗传算法优化小波神经网络数控机床热误差建模

李彬, 张云, 王立平, 李学崑

清华大学精密超精密制造装备及控制北京市重点实验室北京 100084

收稿日期:2018-12-05 修回日期:2019-07-22 出版日期:2019-11-05 发布日期:2020-01-08
作者简介:李彬,男,1984年出生。主要研究方向为数控机床热误差分析。E-mail:xc_lib@126.com
基金资助:
国家重大科技专项资助项目（2014ZX04001051-06）。

Modeling for CNC Machine Tool Thermal Error Based on Genetic Algorithm Optimization Wavelet Neural Networks

LI Bin, ZHANG Yun, WANG Liping, LI Xuekun

Beijing Key Lab of Precision/Uitra-precision Manufacturing Equipment and Control, Tsinghua University, Beijing 100084

Received:2018-12-05 Revised:2019-07-22 Online:2019-11-05 Published:2020-01-08

摘要/Abstract

摘要： 数控机床的热误差已经成为影响其加工精度的一个关键因素，为最大限度提高数控机床热误差补偿的精度和效率，结合遗传算法自适应全局优化搜索能力和小波神经网络良好的时频局部特性的优点，提出一种基于遗传算法优化小波神经网络的机床热误差补偿模型。以某型号五轴摆动卧式加工中心为试验对象，以机床温度变量和热误差为数据输入样本，建立小波神经网络模型热误差预测模型，然后用遗传算法优化小波神经网络权值、阈值，最终建立热误差预测模型。通过与传统人工神经网络和普通小波神经网络进行对比分析及试验论证表明，该补偿模型具有精度高、抗扰动能力和鲁棒性强等优点，有望在实际加工场合的数控机床的热误差预测和补偿研究中得到更大的推广应用。

关键词: 热误差, 误差补偿, 数控机床, 小波神经网络, 遗传算法优化

Abstract: Thermal error has been a significant factor influencing the accuracy of CNC machine tools,in order to maximize the accuracy and efficiency of thermal error compensation for CNC machine tools, a novel thermal error compensation model based on genetic algorithm for optimizing wavelet neural network is presented by combining the advantages of adaptive global optimization searching ability of genetic algorithm and good time-frequency local characteristics of wavelet neural network. Taking a five-axis swing horizontal machining center as the test object, the thermal error prediction model of wavelet neural network model is established with the temperature variables and thermal errors of machine tools as input samples. Then the weights and thresholds of wavelet neural network are adjusted by genetic algorithm, and the thermal error prediction model is finally established. Compared with traditional artificial neural network and ordinary wavelet neural network, the new compensation model has the advantages of high precision, strong anti-disturbance ability and robustness. This model is expected to be used in thermal error prediction and comp-ensation of the complex industrial applications.

Key words: thermal error, error compensation, machine tool, wavelet neural networks, genetic algorithm optimization

中图分类号:

TG502

李彬, 张云, 王立平, 李学崑. 基于遗传算法优化小波神经网络数控机床热误差建模[J]. 机械工程学报, 2019, 55(21): 215-220.

LI Bin, ZHANG Yun, WANG Liping, LI Xuekun. Modeling for CNC Machine Tool Thermal Error Based on Genetic Algorithm Optimization Wavelet Neural Networks[J]. Journal of Mechanical Engineering, 2019, 55(21): 215-220.

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基于遗传算法优化小波神经网络数控机床热误差建模

Modeling for CNC Machine Tool Thermal Error Based on Genetic Algorithm Optimization Wavelet Neural Networks

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