利用辐射射频检测技术研究噪声对局部放电定位精度的影响

O. El Mountassir, B. Stewart, S. McMeekin, A. Ahmadinia
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引用次数: 6

摘要

局部放电是高压电站绝缘系统在降解过程中发生的放电现象。在完全故障之前,pd提供了即将发生的设备故障的早期预警,同时也加速了故障过程。辐射射频(RF)测量方法是可用于定位PD源的众多其他检测方法之一。该方法使用至少4个接收天线来检测辐射的PD RF信号,由此可以使用迭代或非迭代定位算法计算PD源的三维位置。本文利用本地定制的四个天线位置的“Y”形排列,评估高斯噪声对具有不同频谱和信号强度特性的两种不同PD源的定位精度的影响。在对数百个实验射频信号进行测量的基础上,利用累积能量计算不同天线之间的到达时间差(TDOA),然后利用迭代双曲最小二乘(HLS)算法确定PD源的位置。结果表明,确定两种不同PD源位置的精度和能力取决于信号的信噪比(SNR)质量以及信号的强度。此外,结果表明,平均tdoa可能不会提供一个收敛的解决方案,而平均单个tdoa的位置提供一个更好的解决方案。
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Effect of noise on the location accuracy of partial discharges using radiated RF detection techniques
Partial discharges (PD) are electric discharges that occur when the insulation system of high voltage plant is in the process of degradation. Prior to complete breakdown, PDs provide an early warning of imminent equipment failure, while also accelerating the breakdown process. Radiated radio frequency (RF) measurement methods are one of numerous other detection methods which may be employed to locate PD sources. This method uses at least 4 receiving antennas to detect the radiated PD RF signals from which the three dimensional position of the PD source can be calculated using iterative or non-iterative location algorithms. This paper evaluates the effect of Gaussian noise on the location accuracy of two different PD sources which have different frequency spectra and signal strength characteristics using a locally customised “Y shaped” arrangement of four antenna positions. Based on measurements of hundreds of experimental RF signals, the time-differences-of-arrival (TDOA) between the different antennas is calculated using cumulative energy and then the location of the PD source determined by applying the iterative hyperbolic least squares (HLS) algorithm. The results demonstrate that the accuracy and the ability to determine the position of the two different PD sources depends on the signal-to-noise ratio (SNR) quality as well as the strength of the signals. Also, results show that averaging the TDOAs may not provide a converged solution, while averaging the locations of the individual TDOAs provide a better solution.
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