Research on Thermal Error of CNC Machine Tool Based on DBSCAN Clustering and BP Neural Network Algorithm
作者： Huanzhao Li , Aimei Zhang , Xuewei Pei
DOI: 10.1109/ICIASE45644.2019.9074094
关键词: Artificial neural network 、 Artificial intelligence 、 Numerical control 、 Basis (linear algebra) 、 Pearson product-moment correlation coefficient 、 Machine tool 、 Pattern recognition 、 DBSCAN 、 Displacement (vector) 、 Point (geometry) 、 Computer science
摘要: To reduce the influence of thermal error on accuracy CNC machine tool this paper proposed a temperature sensor measuring point optimization method based DBSCAN clustering algorithm and BP neural network modeling for tool. Pearson correlation coefficient reduced measurement from 16 to 5. Established spindle displacement, score model up 0.99, which provided an important theoretical basis compensation.
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