Profile Prediction of Screw Rotor Milling Based on BiLSTM-LSSVM
Aiming at the problem of profile prediction in the machining process of screw rotor disc milling cutter,a screw profile prediction method based on Bi-directional long short-term memory and least square-support vector machines(BiLSTM-LSSVM)was proposed.Firstly,the vibration signals in the processing process are collected and pre-processed for noise reduction.The signals after noise reduction are down-sam-pled and then input into BILSTM for time series prediction.Secondly,feature extraction is carried out on the signal after time series prediction,and the extracted feature vector is input into LSSVM for profile pre-diction.Finally,the BiLSTM-LSSVM model is verified by orthogonal experiment,and the error compensa-tion experiment is carried out for the predicted profile.The experimental results show that the proposed screw profile prediction model based on BiLSTM-LSSVM can accurately predict the screw profile machining of the screw rotor disc milling cutter,and then provide support for the screw rotor profile compensation.
screw rotorbi-directional long short-term memoryleast square support vector machinespro-file prediction
万方数据
维普
