采用随机微粒群算法的舰船消磁系统优化调整

随着舰船消磁技术的发展,消磁线圈的数目越来越多,用于调整消磁系统的常规方法越来越难以实施.为解决这一问题,采用随机微粒群算法对舰船消磁系统进行了优化调整,给出了优化调整数学模型及优化结果.计算例子表明随机微粒群算法在舰船消磁磁场特征均方根最小和峰值最小方面均比常规方法更有优势,而且这种方法还能用于优化与舰船磁场特征相关的任意一个或多个参数.因此,利用这种新方法可以将舰船消磁系统调整到最优状态,从而能够保证舰船的磁性安全.另外,随机微粒群算法具有算法直观,编程简单,计算速度快的优点,可以方便地应用于工程实际.

Optimal calibration of ship degaussing system using stochastic particle swarm optimization

With the development of ship degaussing technology,more and more degaussing coils are being adopted.Thus,conventional methods to calibrate the degaussing system are increasingly difficult to implement.To solve this problem,the stochastic particle swarm optimization was applied to the optimal calibration of a ship degaussing system.The mathematical model and results are presented,which show that the stochastic particle swarm optimization has more advantages than conventional ones in terms of minimizing the root mean square and peak of the ship degaussing magnetic field signature,and that this method can be used to optimize one or more parameters relating to the ship's magnetic field signature.Hence,using this new method,the ship degaussing system is calibrated to an optimal state,and the ship's magnetic safety is ensured.Furthermore,the stochastic particle swarm optimization is expediently used to calibrate the ship degaussing system due to the simple program,intuitional algorithm,and high calculating speed.