摘要
为了对变压器中的局部放电源进行精确定位,文中提出了一种基于自然选择自适应粒子群算法(Natural Selection-Adaptive Particle Swarm Optimization,NS-APSO)的超声定位方法。在自适应粒子群算法的基础上融入自然选择的思想,每次迭代都对种群中的粒子进行“优胜劣汰”处理,用好的粒子替换差的粒子从而提高种群的整体质量。为了增强算法的实用性,基于Matlab中的GUI模块开发了一款能够对不同尺寸变压器内部局部放电源进行定位的软件。将定位结果与标准PSO算法得到的结果进行对比,结果表明基于NS-APSO算法的变压器超声定位方法具有更高的定位精度和全局搜索能力。
In order to accurately locate the partial discharge source in the transformer,a method of ultrasonic location based on natural selection adaptive particle swarm optimization(NS-APSO)is proposed in this paper.The idea of natural selection is integrated into the adaptive particle swarm optimization algorithm,the particles in the population are treated as“survival of the fittest”in each iteration,and the poor particles are replaced by the good ones to improve the overall quality of the population.In order to enhance the practicability of the algorithm,a kind of software is developed based on the graphical user interface(GUI)module of MATLAB,which can locate the local discharge power inside transformers of different sizes.The results show that the ultrasonic positioning method based on NS-APSO algorithm has higher positioning accuracy and global search ability.
作者
周晶
罗日成
黄军
梁新福
党世轩
Zhou Jing;Luo Richeng;Huang Jun;Liang Xinfu;Dang Shixuan(School of Electrical and Information Engineering,Changsha University of Science&Technology,Changsha 410004,China)
出处
《电测与仪表》
北大核心
2022年第8期155-160,共6页
Electrical Measurement & Instrumentation
基金
湖南省教育厅科研资助项目(15C0031)。
关键词
粒子群算法
自适应参数调整
超声波定位
局部放电
Matlab-GUI
particle swarm optimization algorithm
adaptive parameter adjusting
ultrasonic localization
partial discharge
Matlab-GUI
