Optimal design method of superconducting magnet used for magnetic resonance imaging (MRI) device

Abstract

An optimal design method of a superconducting magnet used for a magnetic resonance imaging (MRI) device comprises the following steps: obtaining current distribution maps of a primary coil and a screened coil according to magnetically confined conditions and then obtaining the initial cross section of the screened coil based on the current distribution maps; with the magnetic field of the screened coil as a background magnetic field, obtaining the current distribution map of the primary coil again according to magnetically confined conditions, thereby obtaining the initial cross section of the primary coil; based on the initial cross sections of the primary coil and the screened coil, optimizing coil section parameters by adopting hybrid genetic algorithm of simulated annealing to obtain the optimal coil geometries. By the method, the primary and the screened coil can be simultaneously designed.

Description

Technical field [0001] The invention relates to a design method of a superconducting magnet used in a magnetic resonance imaging device. Background technique [0002] Magnetic resonance imaging (MRI) is a high-tech imaging based on the performance characteristics of biological magnetic nuclei (hydrogen nuclei) in a magnetic field. In the past two decades, with the development of magnet technology, engineering electromagnetic field inverse problems, superconducting technology, cryogenic technology, electronic technology, and computers, MRI technology has developed rapidly. With its own technical characteristics and functional advantages, MRI has become an indispensable modern diagnostic equipment in clinical imaging diagnosis. [0003] The magnetic resonance imaging (MRI) system is mainly composed of a magnet system, a spectrometer system, a computer system and an image display system. The magnet system is the most important and costly component of the MRI system. The most importa...

AI Technical Summary

Problems solved by technology

Although these methods have global optimization capabilities, since the optimization problem of the main magnet of magnetic resonance imaging (MRI) is a multi-objective, multi-parameter nonlinear optimization problem, the solution space is complex, and the direct use of random algorithms for coil parameter optimization has great potential. Large blindness reduces algorithm efficiency and even makes optimization difficult

However, in the short-cavity MRI magnet design of this invention, the current density used to directly design the coil will lead to unreasonable results. The current density at both ends of the designed coil is too large, and the local magnetic field is too strong, which often exceeds the current-carrying capacity of the superconducting material.

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