摘要
刀具状态监控对保障生产安全和产品质量具有重要意义。采用声发射(AE)传感器来采集切削过程中发出的AE信号,采用多分辨率分忻法对正常切削、刀具破损、断屑时发出的AE信号进行分析,并提取出反映刀具破损状态的特征量;最后采用BP神经网络实现了刀具破损状态的自动识别。
Tool condition montoring is important to insure safety and product quality. Firstly, the acoustic emis- sion （AE） sensor is adopted to collect the AE signals emitted from the cutting process. Secondly, Multi-Resolution A- nalysis is used to analyze the AE signals emitted from different cutting conditions, such as normal cutting, tool breaking and chip breaking, in order to extract features of the tool breakage condition. At last, tool conditions are recognized au-tomaticlly through BP neural network.
出处
《机械设计与研究》
CSCD
北大核心
2009年第3期87-89,共3页
Machine Design And Research
关键词
刀具破损
声发射
多分辨率分析
tool breakage
acoustic emission
multi-resolution analysis
