Research On Thermal Error Compensation Techniques Of CNC Machine Tools

With the rapid development of science and techinology. and improvement of industrial manufacturing level, more and more requirements of the machining accuracy of CNC machine tools were put forward by modern equipment manufacturing. However, as the improvement of machine too Is’ manufacturing accuracy, the thermal error caused by thermal deformation of the machine’s parts gradually becomes the main factor that affects the improvement of the machining accuracy of CNC machine tools. Reducing or even eliminating the thermal error has received extensive attention of domestic and foreign research scholars. On the basis of analyzing the thermal error compensation technology of CNC machine tools researched by the domestic and foreign research scholars, this paper mainly studied the machine temperature and thermal deformation detection technology, the identification of temperature measurement points placed on the machine tools and thermal error compensation modeling techniques. The specific contents are divided into the following aspects:(1) Firstly, this subject analyzed the structural characteristics, heat source and the main forms of thermal deformation of the CNC machine tool used in the experiment, which provided a theoretical basis for arrangement of the temperature sensors and the thermal error detection on the CNC machine tools, and also expatiated on the operating principle of the data acquisition system. By analyzing the machine tool temperature and thermal deformation data from data acquisition system, there is a strong correlation showed between the temperature measurement points that need to be optimized.(2) Secondly, on the basis of analyzing the machine tool’s temperature field, temperature measurement points optimization method of the CNC machine tools was proposed based on fuzzy C-means clustering (FCM) algorithm, gray-fuzzy clustering algorithm and particle swarm optimization (PSO). The number of the temperature measurement points of the machine tool was reduced from20to4, and the mutual coupling effects between them were eliminated through optimization.(3) Thirdly, thermal error compensation models of CNC machine tool based on RBF neural network, least squares support vector machine were studied on the basis of the previously selected critical temperature points. And then the thermal error compensation models of CNC machine tool based on particle swarm optimization and least squares support vector machine, multiple quadratic nonlinear regression and multiple cube nonlinear regression were proposed. Finally, the compensation results of all models were analyzed and compared, the best compensation method was obtained.