Dispersion curve analysis method for Lamb wave mode separation

Abstract

The Lamb wave inspection has emerged as a promising method for structural health monitoring and nondestructive testing. However, because of the highly dispersive and multimodal features, the Lamb wave mode separation has become a challenging problem. Based on the dispersion curve analysis, a new signal processing method is proposed in this study to solve this problem. First, a novel function based on the Hessian matrix is constructed to enhance the energy concentration of the dispersion curve in the time–frequency representation to reduce the dispersion effect. Subsequently, the constrained penalty function algorithm is developed for detecting dispersion curves. Finally, a mode reconstruction algorithm is developed to recover Lamb wave modes. The proposed method can separate overlapping wave modes and detect the crack fault by enhancing the time–frequency feature of the Lamb wave signal. Two experiments are carried out to verify the effectiveness of the proposed method for Lamb wave mode separation.