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基于TEV、超聲波聯(lián)合檢測的開關(guān)柜局部放電診斷研究

發(fā)布時(shí)間:2018-05-10 16:50

  本文選題:電力系統(tǒng) + 高壓開關(guān)柜; 參考:《華北電力大學(xué)(北京)》2017年碩士論文


【摘要】:近年來隨著電力系統(tǒng)的快速發(fā)展,入網(wǎng)運(yùn)行的開關(guān)柜數(shù)量不斷增加。但與此同時(shí)開關(guān)柜故障也逐漸增多,對(duì)經(jīng)濟(jì)和社會(huì)造成巨大損失。因此對(duì)開關(guān)柜進(jìn)行不停電檢測具有深遠(yuǎn)意義。TEV法與超聲波法的檢測技術(shù)及特點(diǎn)使其適用于高壓開關(guān)柜局部放電的檢測,論文主要對(duì)這兩種方法的原理及檢測方法進(jìn)行了深入的研究。在對(duì)開關(guān)柜進(jìn)行深入診斷時(shí),所測到的信號(hào)是否為局部放電信號(hào)是其重要工作之一,通過建立局部放電信號(hào)特征提取并建立局部放電典型信號(hào)特征庫,并建立算法對(duì)基于TEV和超聲波的原始信號(hào)進(jìn)行特征提取與識(shí)別。本文主要對(duì)基于TEV、超聲波的典型缺陷局部放電特性及模式識(shí)別進(jìn)行了深入研究,詳細(xì)分析了幾種典型缺陷局部放電特性及模式識(shí)別方法,并對(duì)典型缺陷局部放電的頻譜特性、時(shí)域分析以及開關(guān)柜多源局部放電信號(hào)分離技術(shù)級(jí)應(yīng)用進(jìn)行了深入研究。為了深入研究開關(guān)柜局部放電特性,分析了開關(guān)柜典型局部放電模型。研究發(fā)現(xiàn)對(duì)于基于TEV法的開關(guān)柜局部放電檢測,存在多方面問題,不同的放電其放電特性有所不同。同一放電幅值及重復(fù)率,對(duì)于不同的放電類型,所代表的絕緣狀態(tài)也可能不同。因此對(duì)信號(hào)進(jìn)行放電模式識(shí)別是有必要的,結(jié)果表明利用放電相位特征可以實(shí)現(xiàn)單源放電的模式識(shí)別。本文的信號(hào)分離與聚類技術(shù)不僅能夠區(qū)分不同放電類型,同時(shí)還具有鑒別和分離干擾脈沖的潛力。TEV算法和超聲算法兩者都是基于連續(xù)信號(hào)的分析處理,部分算法可以通用,只是相關(guān)特征參數(shù)不同;诔暦ǖ哪J阶R(shí)別為一般常規(guī)信號(hào)的模式識(shí)別方法,可套用至脈沖電流、超高頻、TEV信號(hào)的模式識(shí)別。最后提出了開關(guān)柜局放聯(lián)合檢測方法。通過創(chuàng)新巡檢模式,提高巡視質(zhì)量;分析開關(guān)柜運(yùn)行工況,建立絕緣狀態(tài)評(píng)價(jià)體系;多技術(shù)聯(lián)合檢測,全面數(shù)據(jù)綜合分析;依據(jù)綜合評(píng)價(jià)結(jié)果,優(yōu)化檢修策略,準(zhǔn)確高效地對(duì)開關(guān)柜內(nèi)部局放位置、程度進(jìn)行深入診斷評(píng)估,并結(jié)合現(xiàn)場實(shí)際檢測案例進(jìn)行分析,證明開關(guān)柜聯(lián)合檢測診斷的可行性和有效性。
[Abstract]:With the rapid development of power system in recent years, the number of switchgear running in network is increasing. But at the same time, switchgear failures also gradually increased, causing huge losses to the economy and society. Therefore, it is of far-reaching significance to detect the non-blackout of switchgear. The detection technology and characteristics of TEV method and ultrasonic method make it suitable for the detection of partial discharge of high voltage switchgear. In this paper, the principles and detection methods of these two methods are studied deeply. In the diagnosis of switchgear, whether the measured signal is partial discharge signal is one of its important work. The characteristic of partial discharge signal is extracted and the characteristic library of partial discharge signal is established. An algorithm is established for feature extraction and recognition of the original signal based on TEV and ultrasonic. In this paper, the partial discharge characteristics and pattern recognition of typical defects based on TEV and ultrasonic wave are studied, and several typical defect partial discharge characteristics and pattern recognition methods are analyzed in detail, and the spectrum characteristics of typical defect partial discharge are analyzed in detail. Time domain analysis and multi-source partial discharge signal separation technology for switchgear are studied. In order to study the characteristics of partial discharge of switchgear, the typical partial discharge model of switchgear is analyzed. It is found that there are many problems in partial discharge detection of switchgear based on TEV method, and different discharge characteristics are different. The same discharge amplitude and repetition rate may represent different insulating states for different discharge types. Therefore, it is necessary to recognize the discharge pattern of the signal. The results show that the single source discharge pattern recognition can be realized by using the discharge phase characteristics. The signal separation and clustering techniques in this paper can not only distinguish different discharge types, but also have the potential of discriminating and separating interference pulses. TEV algorithm and ultrasonic algorithm are both based on continuous signal analysis and processing. Only the correlation characteristic parameters are different. The pattern recognition method based on ultrasonic method is a general pattern recognition method for conventional signals, which can be applied to the pattern recognition of pulse current and ultra-high frequency TEV signals. Finally, the combined detection method of switchgear bureau and discharge is put forward. By innovating the inspection mode, improving the inspection quality; analyzing the operating condition of switchgear, establishing the evaluation system of insulation condition; combining multi-technology detection with comprehensive data analysis; optimizing the maintenance strategy according to the comprehensive evaluation results, The location and degree of internal discharge of switchgear are accurately and efficiently evaluated, and the feasibility and effectiveness of joint detection and diagnosis of switchgear are proved.
【學(xué)位授予單位】:華北電力大學(xué)(北京)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2017
【分類號(hào)】:TM591

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本文編號(hào):1870097


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