Abstract
The ultrasonic guided wave method is a main technology used in structural health monitoring; guided wave signal processing is an important component. Guided waves exhibit inherently dispersive multi-mode characteristics. The inevitable reflection and transmission in the propagation process make the received signal particularly complex. In addition, interference of environmental noise can further increase the difficulty of analysis. Considering the typical multi-component signal processing problem of guided waves, this study proposes an enhanced sparse representation strategy based on the differential norm penalty, with the goal of mode separation to find a more effective method for sparse component recognition. The proposed method was verified through simulations and experiments. The results show that sparse representation with a differential norm penalty can extract the mode components in the guided wave signal more efficiently, with a higher recovery accuracy than existing methods.
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