For the automation of diamond roller grinding with diamond wheel,it is necessary to accurately identify the grinding contact state.Due to the low material removal rate during the grinding process,the amplitude of the acoustic emission signal does not change significantly and the accuracy of grinding contact state recognition by using only effective value is greatly affected by noise.To solve this problem,the acoustic emission signals were processed by combining modal decomposition and correlation analy-sis,and then the effective values and variance values of each component were calculated to complete feature extraction.Finally,support vector machine was used to identify the grinding contact state.The actual application shows that the recognition accuracy of grinding contact condition of roller is98.3%,and the recognition accuracy of grinding contact condition is realized.
关键词
金刚石滚轮/金刚石砂轮/声发射/模态分解/特征提取/磨削接触状态识别
Key words
Diamond Roller/Diamond Grinding Wheel/Acoustic Emission/Modal Decomposition/Feature Extrac-tion/Grinding Contact State Recognition
维普
万方数据