Improved sparse representation localization method for pipeline weld cracks with bud-shaped Electromagnetic acoustic transducer

The shear horizontal (SH) guided wave has the ability to detect small cracks, which is crucial for ensuring pipeline safety. However, the traditional SH guided wave electromagnetic acoustic transducer (EMAT) faces significant limitations in the directivity of the excitation signal. This reduces the signal-to-noise ratio and presents challenges for signal processing and defect localization. In this paper, an improved dictionary construction method for pipeline defect localization is proposed based on a new bud-shaped coil structure design with a periodic permanent magnet (PPM) EMAT configuration. The method involves four primary steps: First, an SH guided wave propagating circumferentially along the pipeline is generated using the proposed bud-shaped EMAT. Then, an over-complete dictionary is established that combines the wave number and the weakly damped attenuation characteristics of the SH wave. Next, a convex optimization model for the echo signal is established, and the Split Augmented Lagrangian Shrinkage Algorithm (SALSA) is used to compute the sparse coefficient and reconstruct the signal. Finally, the defect is localized based on the reconstructed signals. Experimental results show that the proposed method localizes defects with high precision. The average error is about 3.1 mm with theoretical velocity and under 1 mm with actual velocity, even with overlapping packets and simulated weld noise. The proposed method provides a novel approach for extracting SH waves traveling through a pipe and localizing defects.