1.School of Mechatronics Engineering, Henan University of Science and Technology, Luoyang 471003, China
2.Innovation Institute for Robot and Intelligent Equipment (Luoyang), CASIA, Luoyang 471003, China
Abstract：The multi-information data acquisition system of tool wear condition of CNC lathe is built by acquiring the acoustic emission and vibration acceleration signals. The data of acoustic emission and vibration acceleration signals during the process of CNC machine tool processing under the conditions of different tool wear degree and different cutting condition is acquired and analyzed using the orthogonal experimental method. The optimum characteristic frequency band of acoustic emission and vibration acceleration signals were extracted by the wavelet envelope decomposition method so as to recognize tool wear condition as the characteristic parameters. The characteristic information of acoustic emission and vibration acceleration signals during the process of CNC machine tool processing were fused. And the intelligent recognition of tool wear condition during the process of machine tool processing was researched.
收稿日期: 2016-09-29
出版日期: 2017-10-28
引用本文:
徐彦伟1 陈立海1 袁子皓1,2 颉潭成1. 基于信息融合的刀具磨损状态智能识别[J]. 振动与冲击, 2017, 36(21): 257-264.
Xu Yanwei1 Chen Lihai1 Yuan Zihao1,2 Xie Tancheng1 . Intelligent Recognition of Tool Wear Condition Based on Information Fusion. JOURNAL OF VIBRATION AND SHOCK, 2017, 36(21): 257-264.
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