Rapid estimation of vibration of peripheral milling process based on bp neural network 神經(jīng)網(wǎng)絡(luò)的立銑加工振動(dòng)快速預(yù)估
Combined with a virtual simulation system of peripheral milling process and cutting force signal obtained in cutting trials , an optimal bp neural network model with 1 - 20 - 1 structure that can be used rapidly to predict vibration in peripheral milling process is trained and established 摘要結(jié)合研制的立銑加工過(guò)程虛擬仿真系統(tǒng)和實(shí)驗(yàn)測(cè)量銑削力信號(hào),訓(xùn)練并建立優(yōu)化的1 - 20 - 1型bp神經(jīng)網(wǎng)絡(luò)模型,快速實(shí)現(xiàn)銑削加工過(guò)程刀具工件系統(tǒng)振動(dòng)狀態(tài)的預(yù)估。
The estimation results of vibration displacement obtained from the bp neural network model have a good agreement with the experimental results , which reveals that neural network technique combined with the virtual simulation system can be used effectively to predict and monitor vibration in peripheral milling process under different cutting parameters 對(duì)比神經(jīng)網(wǎng)絡(luò)模型預(yù)估的振動(dòng)結(jié)果與實(shí)驗(yàn)測(cè)量振動(dòng)信號(hào)可以看出,二者數(shù)據(jù)吻合較好,表明銑削虛擬仿真系統(tǒng)與神經(jīng)網(wǎng)絡(luò)技術(shù)的結(jié)合能夠高效低耗地用于不同銑削加工條件下銑削振動(dòng)狀態(tài)的快速預(yù)估和加工過(guò)程監(jiān)測(cè)。