Abstract
In this paper, a fast reconstruction method for surface defect profiles of ferromagnetic materials is proposed based on the metal magnetic memory technology. An improved magnetic charge model that can adapt to rectangular and V-shaped defect profiles and a new particle swarm optimization algorithm based on a chaotic initial distribution, sigmoid inertia weight coefficient, and sine cosine acceleration coefficients are established as the forward model and iterative means of the method, respectively. The proposed method is verified with theoretical and experimental data, and the influence of noise is considered. The reconstruction method has good accuracy, repeatability, and robustness.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
