Magnetic model of magnetic objects based on genetic algorithm

Some magnetic objects such as steel hull submarines have complex geometry and so their magnetizations are usually inhomogeneous. In many areas, it is interesting to build a magnetic model of a magnetic object with measurement data of the magnetic field. This is an inverse problem. The paper considers the condition number of the coefficient matrix as the objective function and uses genetic algorithm to search the position of magnetic dipoles. At the same time, the fitness error between measurements and calculations is monitored so that when the objective function reaches the optimum, the fitness error can meet the requirement. The magnetic model of a submarine’s mock-up is obtained using its measured data. The result shows that the magnetic model built with our method is high accurate and strong robust.