摘要
为了开发一种有效的激光冲击强化工艺故障诊断系统,基于声学诊断原理,对激光冲击强化过程中采集到的声信号进行小波包分析,提取出能够指示故障状态的声学特征信息,并验证了其有效性。最后将提取的特征信息结合人工神经网络,建立了激光冲击强化的故障诊断系统模型。
In order to develop an efficient fault diagnosis system of laser shock processing, based on the theory of acoustic fault diagnosis, some useful parameters combined with the fault were exacted from the acoustic signal using the wavelet packet analysis and testified by some faults. Combined with the neural network with the signal characteristics, a fault diagnosis system model was established finally.
出处
《应用激光》
CSCD
北大核心
2012年第3期202-207,共6页
Applied Laser
基金
西安市科技计划资助项目(项目编号:CXY1116(6))
陕西省自然科学基金资助秒年个米微(项目编号:2010JM6012)
关键词
激光冲击强化
故障诊断
小波包分析
神经网络
系统模型
laser shock processing
fault diagnosis
wavelet packet analysis
neural network
system model
