基于小波包和神经网络激光冲击强化诊断研究

Study on plasma acoustic wave diagnosis of laser shock processing based on wavelet packet and neural networks

为了对激光冲击强化过程进行故障诊断,提出了一种基于小波包和BP神经网络的声学诊断方法,利用小波包提取出了激光冲击强化过程中所采集声波信号在某些频段的能量作为信号特征,并通过神经网络进行训练,能够较好地识别出模拟的故障情况,对于进一步加强声学诊断方法的研究具有重要意义。

In order to carry out fault diagnosis in the laser shock processing, a plasma acoustic wave diagnosis method based on wavelet packet and BP neural networks is proposed. The energy distribution in some frequency range of the acoustic wave extracted by the wavelet packet is taken as the signal feature, and the different fault modes are classified and recognized after the neural networks training. The method is of great importance to further study on the plasma a- coustic wave diagnosis method.