Gaussian process regression model incorporated with tool wear mechanism  

作　　者：Dehua LI Yingguang LI Changqing LIU 

机构地区：[1]National Key Laboratory of Science and Technology on Helicopter Transmission,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China

出　　处：《Chinese Journal of Aeronautics》2022年第10期393-400,共8页中国航空学报（英文版）

基　　金：National Natural Science Foundation Project of China(Nos.51925505,51921003)。

摘　　要：Cutting tool condition directly affects machining quality and efficiency.In order to avoid severely worn tools used during machining process and fully release the remaining useful life in the meanwhile,a reliable evaluation method of remaining useful life of cutting tools is quite necessary.Due to the variation of cutting conditions,it is a challenge to predict remaining useful life of cutting tools by a unified model.In order to address this issue,this paper proposes a method for predicting the remaining useful life of cutting tools in variable cutting conditions based on Gaussian process regression model incorporated with tool wear mechanism,where the predicted value at adjacent moments is constrained to a linear relationship by the covariance matrix of Gaussian model based on the assumption of progressive tool wear process,so the wear process under continuous changing conditions can be modelled.In addition to that,the input feature space and the output of the model are also enhanced by considering the tool wear mechanism for improving prediction accuracy.Machining experiments are performed to verify the proposed method,and the results show that the proposed could improve the prediction of tool remaining useful life significantly.

关 键 词：Remaining useful life Cutting condition Tool wear Wear mechanism Gaussian process regression 

分 类 号：V46[航空宇航科学与技术—航空宇航制造工程] V26