基于NS-APSO算法的变压器局部放电超声定位方法

为了对变压器中的局部放电源进行精确定位,本文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。

Ultrasonic location method of partial discharge in transformer based on NS-APSO algorithm

In order to accurately locate the partial discharge source in the transformer, a method of ultrasonic location based on NS-APSO (natural selection adaptive particle swarm optimization) is proposed in this paper. The idea of natural selection is integrated into the adaptive particle swarm optimization algorithm, in each iteration, the particles in the population are treated as "survival of the fitte 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 software is developed based on the GUI(graphical user interface) module of MATLAB, which can locate the local discharge power in different sizes of transformer. Comparing the positioning results with the results of the standard PSO algorithm, shows that the transformer ultrasonic positioning method based on NS-APSO algorithm has higher positioning accuracy and global search ability.