A priori Bayesian Information for Inverse Resolution of Integral Formulation applied to Thin Regions Magnetization Identification

Gireg Chavin-Collin (1, 2) , Didier Cavallera (2) , Olivier Chadebec (1) , Gérard Meunier (1) , Olivier Pinaud (1) , Nicolas Galopin (1) , Laure Line Rouve (1)

1 G2ELab - Laboratoire de Génie Electrique de Grenoble
2 Naval Group

An algorithm for the reconstruction of the magnetization inside an iron sheet is proposed. The magnetization distribution is reconstructed from magnetic measurements made on sensors placed in the surrounding air region. The problem consists in identifying magnetic charges thanks to Bayesian a priori information. The charges derive from the divergence of the flux density through element facets. The efficiency of the method is demonstrated with a numerical application.

Mots clés: Bayesian inference; magnetization identification; magnetostatic inverse problem; volume integral method; thin magnetic region

Domaines: Energie électrique

Gireg Chavin-Collin, Didier Cavallera, Olivier Chadebec, Gérard Meunier, Olivier Pinaud, et al.. A priori Bayesian Information for Inverse Resolution of Integral Formulation applied to Thin Regions Magnetization Identification. The 2020 19thBiennial IEEE Conference on Electromagnetic Field Computation (CEFC'2020), Nov 2020, Pisa, Italy. ⟨hal-03051630⟩