【作者】 武媛；

【导师】 杜伯学；

【作者基本信息】 天津大学 ， 高电压与绝缘技术， 2007， 硕士

【摘要】 近年来,通过测量局部放电(PD)信号对高压电气设备进行在线检测的技术取得了很大的进步。局部放电在线检测系统中的放电类型的模式识别,能够及时发现绝缘内部局部缺陷及放电发展程度,防止事故发生。因此,通过分析放电脉冲特征评估电力设备的绝缘状况并正确识别出放电类型对于绝缘系统的诊断是一项重要工作。在以往的研究中,大家习惯于应用传统的φ-q-n三维谱图(即指纹法,描述局部放电的重要特征量:相角φ,放电量q和单位时间内的放电次数n)对局放模型进行识别,在研究中也得到了比较好的识别效果。但是,在识别中我们遇到了较多的实际困难。首先,由于高压设备现场较为复杂,各种噪声对信号的干扰和湮没要求我们具有较好的消噪方法。其次,φ-q-n三维谱图包含的信息量大,要求较高的处理设备配置和软件设置,在某些特定的现场和设备中,实现较为困难。同时,对特定高压设备的局放模式,如发电机,变压器等可根据其特有的局放类型提取特征最明显的信息,可以通过一些比较简单的特征参数对其进行识别。本文针对发电机定子特有的局放类型,槽放电,端部放电,绝缘内部放电和磨耗放电四种特定类型,构建相应的局放模型[1];研究适用于高频率小电流信号的Rogowski线圈,调试线圈的结构和参数;将消噪效果考虑在内,选取Dmey小波提取实验模拟的电机局放信号的极性特征;通过比较不同局放类型的正负极性信号的统计特征达到识别局放类型的目的;对相应的局放类型提出可行性的后续操作建议。实验结果表明,该方法相较于传统的φ-q-n三维谱图在保留了其原有的识别能力前提下,计算更为简便,更为直观有效。更多还原

【Abstract】 In recent years, great improvements have been made in on-line monitoring of high voltage (HV) apparatus by detection of partial discharge (PD) signals. In this method, it is essential to investigate the characteristics of the PD pulses to evaluate insulation conditions. Recognition of PD types is fundamental for insulation system diagnosis. In former researches, the traditionalφ-q-n 3-Dimentional (3-D) plots are usually applied to recognize the PD pattern, which received obvious recognition results in researches. But it is rather difficult to use in practice.Firstly, because of the complex environment of HV apparatus, signals are buried in various noises, which requires better denoised method. Secondly,φ-q-n 3-D plots contain excessive information, which need more advanced hardware and software of signal process. In some of the specific detection scene and practical facility, it might be hard to create the 3-D plot. Meanwhile, the specific PD patterns in certain type of HV apparatus, such as generators, transformers, etc, can be recognized by some indexes or 2-D plots instead of 3-D plots with less calculation.This paper creates four relevant PD models upon the peculiar PD patterns of generator stators. The four PD patterns are slot discharge, end-winding discharge, inner discharge and abrasion discharge. The Rogowski coil is designed and rejusted to test the low high frequency current in the experiment. The signals are decomposed and reconstructed using mother wavelet Dmey of wavelet packet (WP) theory. In this way, the noises are removed and polarity characteristics are abstracted. The plots of negative and positive discharge signals differ between different PD patterns. Accordingly, the feasible operation suggestions are given out to certain PD types. The results show that this method is much simpler compared to the traditionalφ-q-n 3-D plots but remains the accuracy of pattern-recognition.更多还原