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Metal sheets have good performance and have been widely used. Different kinds of defects can be generated during the preparation and service of metal plates, which will cause the structural performance of the metal plates to decline, thus requiring structural health monitoring (SHM). This study proposes an electromagnetic ultrasonic (EMUS) surface wave detection technique for metal sheet defects via simulation. The numerical results show that after the excitation parameters of the EMUS transducer are optimized through orthogonal experimental design, the amplitude of the EMUS signal generated is increased by about 80%. The power spectrum density (PSD) of the EMUS response signal is used to detect defects. Compared with the peak-to-peak detection, the accuracy is higher, and the reliability is better. The accuracy of the proposed “central zero-point” method for measuring the time delay of the EMUS signal wave packet is higher than that of the “peak-to-peak amplitude” method and the “vibration starting point” method and is close to the accuracy of the “cross-correlation” method.

Insights into Metal Sheet Novelty Detection via Simulated Electromagnetic Ultrasonic Surface Wave