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With the rapid development of science and technology, higher requirements are placed on the machining accuracy and reliability of various CNC machine tools and machining centers. In such high-speed, precision machine tools, the problem of thermal deformation has become increasingly prominent, and an effective way to solve this problem is to perform thermal monitoring and compensation. In the thermal error control compensation technology of CNC machine tools, it is the key to reasonably select the temperature measurement point and the position of the control source to establish a reasonable and practical mathematical model between temperature rise and thermal error of the temperature measurement point. Practice shows that the temperature rise of the surface of the CNC machine tool and the internal points have different influences on the thermal error of the machine tool. There are always some heat source propagation points. The temperature rise of these points will cause the machine to change the thermal error in different directions. As long as the temperature rise of these points is effectively controlled, the thermal error of the CNC machine tool is basically controlled. We call these points the key points affecting the thermal error of the CNC machine tool. The effective identification of the key points is the key to the thermal compensation technology. It not only directly affects the compensation effect, but also has certain guiding significance for the overall layout and structural design of CNC machine tools. This paper proposes a general method for identifying the key points of thermal error of CNC machine tools by basic artificial neural network. The method uses the measured data of temperature rise of each temperature measurement point and the displacement of the measuring point of each end of the spindle, and applies the neural network in Matlab. The toolbox establishes a neural network model between temperature rise and displacement, and then obtains the partial derivative of each output of the network model for each input, and determines the effect of the temperature rise of the temperature measurement point on the displacement of the displacement measurement point according to the magnitude of the partial derivative. The point with large derivative is the key point of thermal deformation, which should be paid attention to and applied in thermal monitoring and compensation. This method is used in CNC machine tools, and its identification results are in line with reality. Identification of key points of thermal error CNC machine tools are a complex hot state system. Many factors are affected. The development of modern computer technology and the application of neural network toolbox make the establishment of temperature rise and displacement models and the identification of key points not only possible. And convenient and precise. (Finish)
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