期刊
MEASUREMENT
卷 215, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.measurement.2023.112885
关键词
Metal magnetic memory; Defect reconstruction; Magnetic charge model; Particle swarm optimization algorithm
A fast reconstruction method based on the metal magnetic memory technology is proposed for surface defect profiles of ferromagnetic materials. 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.
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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据