A condition monitoring method for laser peening based on the correlation between the adjacent aata

As an innovative surface treatment of metal material, laser peening makes greater performance in improving the mechanical property comparing with the conventional shot peening, and it can bring significant contributions to various fields like aerocraft industry. In accordance with the developing pace of its industrialization, the condition monitoring, aiming at maintaining a good working state, is arousing more and more attentions. The acoustic signal with lower cost contains abundant information related to the operating process, and it can be used as non-destructive condition detection of the laser peening. The shock acoustic signal, which is propagating from the original plasma shock wave, was analyzed to extract the valuable characteristics to monitor the process. Considering the nonlinearity of the shock acoustic signal, a new signal processing method was proposed, based on the correlation between the neighbor data in the signal array. On one hand, it was used in analyzing the simulating shock-wave signal; on the other hand, it was applied in studying the practical signal obtained from the laser shock processing. It was shown that the novel method could detect the shock wave signal efficiently with easy and quick operation. It thus has potential in applications.