A method of 2D defect profile reconstruction from magnetic flux leakage signals based on improved particle filter

Abstract

Defect profile reconstruction in magnetic flux leakage (MFL) testing means the reconstruction of defect profiles and parameters according to inspected MFL signals, and it is the key point in realising MFL inversion. In this paper, the inversion problem is described as a classical discrete-time tracking problem based on state and measurement equations. A state-space approach is adopted to solve the inversion problem by establishing the state-space model of defect profile and MFL signals, and apply the improved particle filter algorithm to the defect profile reconstruction. The results indicate that the improved particle filter-based inversion algorithm is an effective and feasible new method of MFL inversion due to its accuracy and robustness against noise. Meanwhile, the improved resampling algorithm further improves the efficiency.