文章基本信息

标题：A Fourier Series-Neural Network Based Real-Time Compensation Approach for Geometric and Thermal Errors of CNC Milling Machines
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作者：Wei Wang ; Yi Zhang ; Kaiguo Fan 等
期刊名称：Advances in Mechanical Engineering
印刷版ISSN：1687-8140
电子版ISSN：1687-8140
出版年度：2013
卷号：2013
DOI：10.1155/2013/357920
出版社：Sage Publications Ltd.
摘要：In order to improve the accuracy and efficiency of the real-time error compensation, a Fourier Series-Neural Network (FS-NN) based compensation methodology is developed to reduce the thermally induced geometric errors of CNC milling machines under varying conditions. Firstly, an error model is presented based on the principle of Fourier series with fast calculation and higher precision, which is regarded as the error base of original geometric errors. Secondly, the relationships between the slopes related to different error curves and the temperatures of key thermal points are figured out by using neural networks when concerning thermal effects. Then, a combined error model is established which is suitable for reducing axis positioning errors at any thermal status. Finally, a real-time dynamic error compensation system is developed featuring automatic error modeling and multiaxis synchronous compensation. The experimental results prove that the proposed methodology has satisfactory modeling accuracy and robustness to frequently changing working conditions.