摘要
局部放电既是电力设备绝缘缺陷的表现,同时也会加剧设备绝缘劣化的程度。因此,有效的局部放电定位是电力设备状态监测的重要手段。现有的局部放电定位方法均易受环境影响,定位精度不稳定。提出了基于时间指纹的特高频局部放电定位法,该方法首先使用特高频传感器采集局部放电信号到达时间,以各传感器之间的到达时间差构成该监测点的时间指纹,从而得到被测区域的时间指纹库。当局部放电发生时,将采集到的时间指纹输入到时间指纹库中,使用神经网络算法进行匹配,即可得到局部放电源的定位结果。实验结果表明,在900 m^2的被测区域内,研究的定位方法平均定位误差为1.78 m,可将约60%的定位误差锁定在2 m以内。
Partial discharge is not only a manifestation of electrical equipment insulation defects,but also can aggravate the degree of equipment insulation deterioration.Therefore,effective partial discharge positioning is an important means of monitoring the status of power equipment.The existing partial discharge positioning methods are easily affected by the environment,and the positioning accuracy is unstable.This paper proposes a location method for UHF partial discharge based on time fingerprints.The method first uses UHF sensors to collect the arrival time of the partial discharge signals,and uses the arrival time difference between the sensors to form the time fingerprint of the monitoring point so as to obtain the measured time fingerprint library of the area.When a partial discharge occurs,the collected time fingerprints is input into the time fingerprint library,and the neural network algorithm is used for matching,and then the location result of local discharge power can be obtained.The experimental results show that the average positioning error of the proposed positioning method is 1.78 m within the measured area of 900 square meters,which can lock about 60% of the positioning errors within 2 m.
作者
刘谨
王哲斐
LIU Jin;WANG Zhefei(Pudong Power Supply Company of State Grid Shanghai Electric Power Company,Shanghai 201315,China;Shanghai Siliang Electronic Technology Co.,Ltd.,Shanghai 201315,China)
出处
《湖北电力》
2020年第5期23-28,共6页
Hubei Electric Power
基金
国家电网公司科技项目(项目编号:SGSHJX00KXJS1800777)。
关键词
局部放电
故障定位
时间指纹
神经网络
partial discharge
fault location
time fingerprint
neural networks
