An approach to the calculation of multilayer magnetic shielding using artificial neural network |
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| Authors: | S Koroglu N Umurkan O Kilic F Attar |
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| Affiliation: | 1. Departamento de Electrónica, Automática e Informática Industrial, UPM, Ronda de Valencia 3, 28012 Madrid, Spain;2. Departamento de Ingeniería Eléctrica, Electrónica y de Control, UNED, Juan del Rosal, 12 – Ciudad Universitaria, 28040 Madrid, Spain;1. Department of Power, School of Electrical Engineering-UCV, Los Chaguaramos, 1040 Caracas, Venezuela;2. Department of Electrical Engineering, ETSEIB-UPC, Av. Diagonal 647, 08028 Barcelona, Spain;1. Institute of Electrostatic & Electromagnetic Protection, Mechanical Engineering College, Shijiazhuang 050003, China;2. State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Wuhan 430070, China;3. The 33rd Institute of China Electronics Technology Group Corporation, Taiyuan 030006, China;1. Centro Atómico Bariloche and Instituto Balseiro, San Carlos de Bariloche, Argentina;2. Laboratorio de Colisiones Atómicas, Departamento de Física, UTFSM, Valparaíso, Chile;1. AGH University of Science and Technology, Faculty of Physics and Applied Computer Science, 30-059 Kraków, Poland;2. The H. Niewodniczański Institute of Nuclear Physics, Polish Academy of Sciences, 31-342 Kraków, Poland;3. Institute of Physics, Jan Kochanowski University, 25-406 Kielce, Poland |
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| Abstract: | The electromagnetic interference has many undesired effects to the office equipments and the performance of technological devices. Therefore, electrical devices should have field protection mechanism against magnetic fields. The shielding mechanism prevents external magnetic field emitted from the device to the vicinity area. This work attempts to apply artificial neural network in order to estimate shielded magnetic field for multilayer shielding application. The multilayer magnetic shielding performances of cylindrical shaped ferromagnetic shields under extremely low frequency are investigated. For this purpose, three different ferromagnetic materials in cylindrical shape are chosen for magnetic shielding. The shielding performances of these materials are measured and a selected set of data is used to train and test an artificial neural network. The proposed neural network model achieves an intelligent decision for the shielded magnetic field level based on distance, unshielded magnetic field value, number of shield layer and skin-depth of the shield. |
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