2015Unpublished venueRequires access

Magnetic dipole model in the near-field

Yupeng Ren, Chao Hu, Sheng Xiang, Zhongqing Feng

Open publisher page 21 citations

Abstract

Magnetic dipole model is significant to calculate the magnetic strength of the magnet source. However, a restriction is that the distance from the testing position to the magnet's position must be much farther than the size of the magnet. The magnetic dipole model is not suitable for the near-filed around the magnet. Here, we propose a modified method for the correction of the near-field by introducing some coefficients to correct the magnetic dipole model. We divide the magnet's field into several regions according to the distance respect to the magnet size. We carried out experiments to measure the magnet's field, and then searched the suitable coefficients for each region to minimize the errors which between the measurements of magnetic strength and the presumed model values. In this paper, we investigated the magnetic field distribution for three types of magnets, Hollow Cylindrical Magnet Magnetized in Axially, Filled Cylindrical Magnet Magnetized in Axially and Hollow Cylindrical Magnet Magnetized in Radial. We use the modified magnetic dipole model to calculate the magnetic strength distribution for these magnets. Experimental results show that the modified method is effective to improve the accuracy of the magnet's near-field model.

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What this paper is about

Magnetic dipole model is significant to calculate the magnetic strength of the magnet source. However, a restriction is that the distance from the testing position to the magnet's position must be much farther than the size of the magnet. The magnetic dipole model is not suitable for the near-filed around the magnet. Here, we propose a modified method for the correction of the near-field by introducing some coefficients to correct the magnetic dipole model. We divide the magnet's field into several regions according to the distance respect to the magnet size. We carried out experiments to measure the magnet's field, and then searched the suitable coefficients for each region to minimize the errors which between the measurements of magnetic strength and the presumed model values. In this paper, we investigated the magnetic field distribution for three types of magnets, Hollow Cylindrical Magnet Magnetized in Axially, Filled Cylindrical Magnet Magnetized in Axially and Hollow Cylindrical Magnet Magnetized in Radial. We use the modified magnetic dipole model to calculate the magnetic strength distribution for these magnets. Experimental results show that the modified method is effective to improve the accuracy of the magnet's near-field model.

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Available abstract

Magnetic dipole model is significant to calculate the magnetic strength of the magnet source. However, a restriction is that the distance from the testing position to the magnet's position must be much farther than the size of the magnet. The magnetic dipole model is not suitable for the near-filed around the magnet. Here, we propose a modified method for the correction of the near-field by introducing some coefficients to correct the magnetic dipole model. We divide the magnet's field into several regions according to the distance respect to the magnet size. We carried out experiments to measure the magnet's field, and then searched the suitable coefficients for each region to minimize the errors which between the measurements of magnetic strength and the presumed model values. In this paper, we investigated the magnetic field distribution for three types of magnets, Hollow Cylindrical Magnet Magnetized in Axially, Filled Cylindrical Magnet Magnetized in Axially and Hollow Cylindrical Magnet Magnetized in Radial. We use the modified magnetic dipole model to calculate the magnetic strength distribution for these magnets. Experimental results show that the modified method is effective to improve the accuracy of the magnet's near-field model.

Key concepts: Dipole, Magnetic field, Magnetic dipole, Physics, Nuclear magnetic resonance, Computer science, Quantum mechanics

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