Numerically-controlled machine tool thermal error compensation grey neural network modeling method

The invention relates to a numerically-controlled machine tool thermal error compensation grey neural network modeling method. The method mainly comprises the following steps: a. sensors are arranged; b. temperature variables are screened; c. a grey system is established and a thermal error predicted value is obtained; d. a residual sequence is solved; and e. a BP neural network model of the residual sequence is established. According to the invention, the grey system theory and the BP neural network are combined together for machine tool thermal error modeling, so the model prediction accuracy and generalization ability can be improved; accurate fitting prediction can be performed on small sample data, and advantages of simple calculation and fast response can be realized; and by using the neural network method, the system has advantages of high self-learning ability and adaptivity, the complex change of machine tool thermal error can be learned by an operator himself, the change in the machine tool machining process can be reflected, and the advantage of good reliability can be realized.