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Advanced techniques application of on-line partial discharge detection in power cables

机译:电力电缆在线局部放电检测的先进技术应用

摘要

Large numbers of installed medium or high voltage power cables are now of advanced age and have gradual insulation deterioration problems. On-line Partial Discharge (PD) measurement has inherent advantages over the conventional off-line measurement, but it also suffers from a very significant Electro-Magnetic Interference (EMI) problem due to the small PD signal levels being monitored. The large magnitude EMI signal often completely swamps the smaller magnitude PD signal, making it difficult to monitor anything but extremely large PD activity. To monitor cable condition and to be able to assess insulation degradation trends requires advanced techniques. In this thesis, the issues of sensor selection, digital filtering, software based on-line differential technique and wavelet Transform (WT) de-noising techniques are studied. Their applicability, advantages and limitations are discussed with the simulation and high voltage measurement results. The High Frequency Current Transformer (HFCT) type PD sensor is selected after being compared with other sensor in term of sensitivity, universal applicability, frequency response and the installation difficulty. The sinusoidal noise frequency identification and application of the conventional digital filtering are studied. The Least Mean Square (LMS) and Recursive Least Square (RLS) algorithm digital adaptive filters are compared in detail and RLS adaptive filter is selected. Wavelet transform de-noising technique for on-line PD measurement is carefully studied and the applications of noise reduction are developed. A novel WT threshold value selection algorithm is presented in this thesis. The new WT algorithm is compared with the existing wavelet techniques using numerical simulation and laboratory high voltage testing data on cables. The results show that this new fully automatic WT de-noising method has achieved great progress with the capability of detection 30 pC PD signal during on-site on-line measurement where typical noise level is ten times higher in magnitude. On the basis of traditional off-line differential or balanced detection circuit, a software based on-line differential technique is proposed in this thesis. The novel method developed has the capability to process one whole AC cycle of PD data. It enables traditional q-Φ and n-Φ distributions to be obtained as well as PD repetition rates and the usual integrated PD parameters. These techniques are developed for the on-site on-line PD measurement in power cables, but they are not limited to cables. They can also be applied to other high voltage equipment with minor or without modification in the data acquisition procedure.
机译:现在,已安装的大量中压或高压电力电缆已经老化,并且逐渐出现绝缘劣化问题。在线局部放电(PD)测量具有优于常规离线测量的固有优势,但是由于要监视的PD信号电平较小,因此它也存在非常严重的电磁干扰(EMI)问题。大幅度的EMI信号通常会完全淹没小幅度的PD信号,除了非常大的PD活动外,很难监视其他任何东西。要监视电缆状况并能够评估绝缘退化趋势,需要先进的技术。本文研究了传感器选择,数字滤波,基于在线差分技术的软件以及小波变换去噪技术等问题。通过仿真和高压测量结果讨论了它们的适用性,优点和局限性。高频电流互感器(HFCT)型PD传感器是在灵敏度,通用性,频率响应和安装难度等方面与其他传感器进行比较之后才选择的。研究了常规数字滤波的正弦噪声频率识别及其应用。详细比较了最小均方(LMS)和递归最小二乘(RLS)算法数字自适应滤波器,并选择了RLS自适应滤波器。认真研究了在线局部放电测量的小波变换降噪技术,并开发了降噪应用。本文提出了一种新的WT阈值选择算法。使用数值模拟和电缆上的实验室高压测试数据,将新的WT算法与现有的小波技术进行了比较。结果表明,这种新的全自动WT降噪方法取得了巨大进步,能够在现场在线测量过程中检测到30 pC PD信号,而典型噪声水平要高出十倍。本文在传统的离线差分或平衡检测电路的基础上,提出了一种基于在线差分技术的软件。开发的新颖方法具有处理PD数据的整个AC周期的能力。它使得可以获得传统的q-Φ和n-Φ分布以及PD重复率和通常的集成PD参数。这些技术是专为电力电缆中的现场在线局部放电测量而开发的,但不仅限于电缆。它们也可以应用到其他高压设备中,只需对数据采集过程进行较小的改动或不做任何改动。

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