Lamb wave based damage imaging using an adaptive Capon method

As plate-like structures are widely used in railway vehicle systems, structural health monitoring and nondestructive testing of those structures are important. The Lamb wave, as an ultrasonic guided wave propagating in plate-like structures, is an effective tool for fault diagnosis. The Capon method is widely used in Lamb wave based damage imaging due to its superior performance in suppressing background noise compared with the conventional delay-and-sum method. As the conventional Capon method is sensitive to modeling errors like the inaccuracy of the look-direction, diagonal loading is usually adopted to regularize the inverse of the covariance matrix. However, the degree of diagonal loading is related to the accuracy of the given look-direction and is hard to determine accurately. Aimed at improving the imaging quality of the conventional Capon method, an adaptive Capon method with adaptive diagonal loading is proposed. In the proposed method, the dispersion and the amplitude caused by wave diffusion are first compensated for each imaging point using the virtual time reversal technique. The correlations among the compensated waveforms after windowing are used to determine the degree of diagonal loading. In the process of regularizing the inverse of the covariance matrix, a large diagonal loading factor will be applied when the correlations among the compensated waveforms are large. As correlations are closely related to the signal phase, both the amplitude and the phase of scattering signals are utilized in the proposed method. The numerical and experimental validations on an aluminum plate are carried out to verify the effectiveness of the proposed method. The results show that compared with the conventional Capon method, the proposed method can obtain images with higher imaging quality, fewer artifacts, and lower noise.