中国机械工程2024，Vol.35Issue(6)：1052-1063,12.DOI:10.3969/j.issn.1004-132X.2024.06.011
基于VMD-SSA-LSTM考虑刀具磨损的数控铣床切削功率预测模型研究
Research on CNC Milling Machine Cutting Power Prediction Model Considering Tool Wear Based on VMD-SSA-LSTM
摘要
Abstract
Traditional researches of cutting process powers required complex cutting power mod-els and often neglected the influences of tool wear,so a CNC milling machine cutting power prediction model considering tool wear was designed based on VMD,SSA,and LSTM neural network.This model did not require the deconstruction of the energy consumption mechanism during the operation of CNC milling machines,and achieved high-precision prediction of cutting process powers based on his-torical experimental data.Firstly,artificial intelligence machine vision technology was used to analyze and process images of the tool wear,obtaining digital features of the worn tools and determining the maximum wear.Then,the VMD-SSA-LSTM model was established,which considered tool wear in the prediction of CNC milling machine cutting powers.VMD was used to decompose the operational data of CNC milling machines,and then the SSA algorithm optimized the hyperparameters of the LSTM neural network.The decomposed milling machine data components were input into the LSTM neural network,and the predicted values of each component were summed to obtain the cutting power prediction value.Taking face milling as an example,the proposed prediction model was compared and analyzed against BP neural networks,LSTM neural networks,and traditional models,which valida-ted the effectiveness and superiority of the proposed model.关键词
切削过程功率/刀具磨损/麻雀搜索算法/长短时记忆神经网络/变分模态分解/计算机视觉技术Key words
power of cutting process/tool wear/sparrow search algorithm(SSA)/long-short term memory(LSTM)neural network/variational mode decomposition(VMD)/computer vision technology分类
机械制造引用本文复制引用
王秋莲,欧桂雄,徐雪娇,刘锦荣,马国红,邓红标..基于VMD-SSA-LSTM考虑刀具磨损的数控铣床切削功率预测模型研究[J].中国机械工程,2024,35(6):1052-1063,12.基金项目
国家自然科学基金(51765043) （51765043）
江西省自然科学基金(20232BAB204043) （20232BAB204043）
江西省高校人文社会科学研究一般项目(JC22120) （JC22120）
