关键词: 主轴热误差, BP神经网络, 模糊c均值聚类, 普通最小二乘法, 集成模型

Abstract: To solve the problem of instable prediction of single BP neural network model,a thermal error modeling method for CNC machine tool spindle based on ensemble BP neural network was proposed.The Fuzzy c-means Clustering Method (FCM) was adopted to select the temperature sensitive points,which eliminated the multi-collinearity between redundant temperature variables.From the perspective of machine learning,several typical BP neural network models with weak prediction performance were integrated by average method,median method and ordinary least squares method respectively.By taking a horizontal machining center THM6380 as an example,the thermal experiment was carried out.The analysis results of thermal error prediction performance indicated that the prediction accuracy and generalization ability of the ensemble models were better than that of single BP neural network model.The proposed modeling method provided a new idea for the thermal error modeling and subsequent thermal error compensation of machine tool spindle.

Key words: spindle thermal error, BP neural network, fuzzy c-means clustering, ordinary least squares, ensemble model