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Locating Partial Discharge Using Particle Swarm Optimisation

机译:使用粒子群算法定位局部放电

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摘要

The use of radio frequency measurement (particularly at UHF) as a means of detecting, diagnosing and locating Partial Discharges in high voltage equipment has advanced considerably in recent years. Partial Discharge location based on UHF signals uses the time-difference-of-arrival of the received pulses at a number of sensors positioned around the equipment exhibiting internal Partial Discharge or arcing in order to establish the location of its source. This method of locating the source is complicated when the line-of-sight path from the Partial Discharge source to each sensor is occluded by internal structures of the equipment under test, as this results in a longer path being taken around the obstruction. In this study, Particle Swarm Optimisation has been applied to the problem of Partial Discharge location in order to assess its effectiveness. This search technique simulates the manner in which a flock of birds searches for food, where the 'birds' (particles) are represented by a vector denoting their position in 3D space and the location of the 'food' is the best location found that satisfies the time-differences-of-arrival of the sensors. The search first sought to minimize a ‿blind' least squares function, which was then extended to assign credit to each sensor's contribution to the error associated with each particle's position due to the path between the particles and the sensors being occluded by objects in the test area. This approach produced locations that were competitive with or slightly better than those obtained by another method of Partial Discharge location which estimates the actual path travelled by the signal using a Cartesian model of the environment in which the Partial Discharge occurs.
机译:近年来,使用射频测量(特别是在UHF上)作为检测,诊断和定位高压设备中局部放电的手段已取得了很大进步。基于UHF信号的局部放电位置利用位于内部呈现局部放电或电弧的设备周围的多个传感器的接收脉冲到达时间差来确定其源位置。当从局部放电源到每个传感器的视线路径被测试设备的内部结构遮挡时,这种定位源的方法很复杂,因为这导致围绕障碍物的路径更长。在这项研究中,粒子群优化已应用于局部放电位置问题,以评估其有效性。这种搜索技术模拟了一群鸟寻找食物的方式,其中“鸟”(颗粒)由表示其在3D空间中位置的矢量表示,“食物”的位置是找到的满足条件的最佳位置传感器的到达时间差。搜索首先尝试最小化一个ƒƒ¢¢â€œ盲盲最小二乘函数,然后将其扩展以为每个传感器对路径导致的与每个粒子位置相关的误差的贡献分配功劳。粒子和传感器之间的距离被测试区域中的物体遮挡。这种方法产生的位置与通过另一种局部放电位置方法获得的位置相比更具竞争性或稍好于后者,后者使用局部放电环境的笛卡尔模型估计信号所经过的实际路径。

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