A weighted sparse reconstruction-based ultrasonic guided wave anomaly imaging method for composite laminates

Abstract

Ultrasonic guided wave is a promising tool for structural health monitoring and nondestructive testing. Numerous signal processing methods have been proposed to detect and localize anomalies based on ultrasonic guided waves for plate-like structures. However, imaging performance is limited in these methods, such as large spot size and significant artifacts. To achieve a better imaging performance of Lamb waves, a weighted sparse reconstruction-based anomaly imaging method is proposed for plate-like structures. Scattering signals are sparsely decomposed in a dictionary pre-constructed from Lamb wave propagation and scattering models. The pixel value at each location of the imaging region can be obtained by solving a weighted sparse reconstruction problem. To verify the accuracy and effectiveness of the proposed method, experiments on a carbon fiber reinforced plastic with and without additional mass are conducted. The experimental results show that the proposed method can achieve anomaly imaging with smaller spot size and fewer artifacts.