本文關(guān)鍵詞：基于超高頻的局部放電在線監(jiān)測(cè)系統(tǒng)的研究與開發(fā)　出處：《蘭州理工大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 狀態(tài)檢修 局部放電 超高頻 包絡(luò)檢波 小波包分解 核主元分析

【摘要】：隨著國(guó)家電網(wǎng)的發(fā)展,封閉式氣體絕緣組合電器(Gas Isolated Switcher GIS)被大量用在高壓輸配電系統(tǒng)中,它具有受外界影響小,運(yùn)行穩(wěn)定,檢修周期長(zhǎng)等諸多優(yōu)點(diǎn)。對(duì)GIS的運(yùn)行故障長(zhǎng)期調(diào)查顯示：絕緣損壞是造成GIS故障的主要原因。局部放電既是絕緣劣化征兆,又是加速絕緣劣化的主要原因,可以通過(guò)對(duì)局部放電的分析有效的了解GIS的絕緣狀態(tài)。IEEE推薦在線局部放電檢測(cè)是唯一有效絕緣實(shí)驗(yàn),因此對(duì)GIS開展局部放電在線監(jiān)測(cè)具有重要意義。 對(duì)局部放電檢測(cè)常見方法進(jìn)行對(duì)比,確定本文采用超高頻檢測(cè)方法。超高頻檢測(cè)方法具有測(cè)量頻率高,抗干擾性強(qiáng),檢測(cè)靈敏度高等特點(diǎn)在GIS局部放電監(jiān)測(cè)中處于重要位置。從機(jī)理上進(jìn)行分析研究局部放電產(chǎn)生的原因,列舉造成這種現(xiàn)象的主要外在因素。分析電磁波在GIS內(nèi)傳播路徑和基于最小光程差的局部放電定位原理,介紹局部放電表征參數(shù)。 在研究集中式監(jiān)測(cè)系統(tǒng)不足的基礎(chǔ)上,致力于研發(fā)一套采用分布式結(jié)構(gòu)的局部放電檢測(cè)系統(tǒng)。數(shù)據(jù)的采集與處理在就地處理單元完成,在上位監(jiān)測(cè)中心實(shí)現(xiàn)故障類型的判斷,放電位置的定位。各個(gè)就地處理單元功能獨(dú)立,個(gè)別單元的損壞和退出不會(huì)影響到上位機(jī)的正常工作,提高了系統(tǒng)運(yùn)行的穩(wěn)定和檢測(cè)的靈活性。 由于不同故障放電產(chǎn)生的信號(hào)其包絡(luò)曲線不同,數(shù)據(jù)就地處理單元利用包絡(luò)檢波方式對(duì)超高頻信號(hào)進(jìn)行降頻處理,解決超高頻信號(hào)和采集系統(tǒng)之間的矛盾。以高速DSP為核心通過(guò)控制相關(guān)電路完成信號(hào)放大、濾波、采集,存儲(chǔ),并把經(jīng)算法處理的數(shù)據(jù)上傳到上位監(jiān)測(cè)診斷中心。設(shè)計(jì)4種GIS常見放電現(xiàn)象的故障模型進(jìn)行試驗(yàn),采集放電信號(hào)的包絡(luò)波形,以包絡(luò)信號(hào)的特征為基礎(chǔ)展開局部放電的模式識(shí)別和故障診斷。以小波包分解,核主元分析的方法提出包絡(luò)曲線的特征信息,然后用BP神經(jīng)網(wǎng)絡(luò)對(duì)特征信息進(jìn)行分類以驗(yàn)證該方法的有效性。系統(tǒng)軟件開發(fā)分上位和下位兩個(gè)模塊,下位DSP系統(tǒng)的信號(hào)處理算法、控制程序的開發(fā)在CCS集成開發(fā)環(huán)境下以C語(yǔ)言完成,上位診斷分析軟件的開發(fā)以面向?qū)ο蟮目梢暬_發(fā)工具VC++完成。
[Abstract]:With the development of State Grid, Gas Isolated Switcher GIS is widely used in high voltage transmission and distribution system. It has little external influence and stable operation. The long-term investigation of GIS operation fault shows that insulation damage is the main cause of GIS fault and partial discharge is the sign of insulation deterioration. It is also the main reason to accelerate insulation deterioration. It is the only effective insulation experiment to understand the insulation state of GIS effectively by analyzing partial discharge. IEEErecommended on-line partial discharge detection is the only effective insulation experiment. Therefore, it is of great significance for GIS to monitor PD on line. By comparing the common methods of partial discharge detection, it is determined that this paper adopts the ultra-high frequency detection method, which has high measuring frequency and strong anti-interference. The characteristics of high detection sensitivity are very important in GIS partial discharge monitoring. The mechanism of partial discharge is analyzed to study the cause of partial discharge. The main external factors causing this phenomenon are listed, the propagation path of electromagnetic wave in GIS and the principle of partial discharge location based on minimum optical path difference are analyzed, and the characterization parameters of partial discharge are introduced. Based on the lack of centralized monitoring system, a partial discharge detection system with distributed structure is developed. The data acquisition and processing is completed in the local processing unit. The function of each local processing unit is independent, and the damage and exit of individual unit will not affect the normal operation of the host computer. The stability of the system and the flexibility of detection are improved. Because the envelope curves of the signals produced by different fault discharge are different, the data processing unit uses envelope detection to reduce the frequency of UHF signals. To solve the contradiction between the UHF signal and the acquisition system. Using the high-speed DSP as the core, the signal amplification, filtering, acquisition and storage are completed by controlling the related circuit. The data processed by the algorithm is uploaded to the upper monitoring and diagnosis center. Four fault models of common discharge phenomena in GIS are designed and tested to collect the envelope waveform of discharge signals. Based on the characteristics of envelope signal, the pattern recognition and fault diagnosis of partial discharge are carried out, and the characteristic information of envelope curve is presented by wavelet packet decomposition and kernel principal component analysis. Then BP neural network is used to classify the feature information to verify the effectiveness of the method. The system software development is divided into two modules: upper and lower, and the signal processing algorithm of the lower DSP system. The development of the control program is completed in C language under the CCS integrated development environment, and the development of the upper diagnosis and analysis software is accomplished by the object-oriented visual development tool VC.
【學(xué)位授予單位】：蘭州理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TM855;TM595

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