ETM metal detection system based on ISTA in hybrid excitation

SUN Chun-guang, HE Min, ZENG Xing-xing, FENG Xiao-wei
(College of Logistics Engineering, Shanghai Maritime University, Shanghai 201306, China)

Abstract: Aiming at the problem of poor image reconstruction quality of traditional sensor structures and algorithms in electromagnetic tomography（EMT） metal structure flaw detection, the excitation method and image reconstruction algorithm of the EMT flaw detection system were studied. By analyzing the principle of data collected by EMT, a 6-coil sensor with mixed excitation was designed, and the amount of detection data of mixed excitation and single excitation was compared. According to the mathematical model of EMT technology, the relationship between induced voltage and conductivity distribution was obtained, and the sensitivity matrix under mixed excitation was constructed. The shortcomings of conventional EMT image reconstruction algorithms were analyzed. Based on the non-smooth features of metal defects, an iterative soft threshold algorithm (ISTA) based on wavelet transform was introduced. ANSYS Maxwell software was used as a simulation platform. Experiments with different shape defects using separate excitation and mixed excitation were performed, and the reconstructed image was obtained using different algorithms. A mixed excitation EMT flaw detection system based on iterative soft threshold algorithm was designed. Two excitation methods were used to collect data of different defects. The image reconstruction effects of Tikhonov regularization algorithm, improved Landweber iterative algorithm and iterative soft threshold algorithm were compared. The results indicate that the imaging effect of mixed excitation is better than that of single excitation; under mixed excitation, the image reconstruction quality of ISTA is better than the other two algorithms.

Key words: electromagnetic tomography（EMT）; landweber iterative algorithm; Tikhonov regularization algorithm; iterative soft threshold algorithm (ISTA); metal flaw detection