Sign Coherence Factor-Based Search Algorithm for Defect Localization with Laser Generated Lamb Waves

Techniques based on laser generated Lamb waves (LGLW) and compact array can realize far field, noncontact localization of defects in plate structures. Fully utilizing the information of LGLW signals is beneficial for improving the robustness and image contrast of the localization. However, the classical imaging algorithms are performed by mapping the signal parameters (amplitude, polar sign) into each discrete grid based on the time-of-flight principle. It is time consuming and the performance is sensitive to the frequency. In this study, a sign coherence factor (SCF)-based search algorithm is developed for defect localization with the LGLW signals. In the algorithm, the defect locations are identified by an adaptive search process of individual scatterer. The characteristics of defect localization with compact array-based Lamb waves are analyzed, including the statistical and diversity characteristics, lateral effect of temporal-spatial mapping trajectories. A mathematical model of the individual scatterer and its searching algorithm are designed by incorporating the signal sign with the characteristics. The evolutionary strategy and the clustering algorithm are combined to develop the search algorithm of the individuals in the imaging zone. The SCF of individuals kept based on the analysis with multiple frequencies of LGLW signals are added for high contrast and robustness defect imaging. Two full laser defect detection experiments were carried out to verify the effectiveness of the developed algorithm. Compared with the SCF algorithm, the developed SCF-based search algorithm shows better performance in improving the signal-to-noise ratio of images and its execution time is less affected by the number of discrete grids in the plate.