【摘要】：GIS設備(氣體絕緣金屬封閉開關設備)因其集成度高、運維方便、占地面積小等優(yōu)點,應用程度越來越高,雖然運行可靠性較高,但是一旦發(fā)生故障,后果相當嚴重,檢修工作繁雜,停電時間長,停電范圍波及非故障元件。因此,必須加強GIS智能化和信息化建設,實現設備狀態(tài)智能診斷,最終指導制定相應檢修策略。GIS設備的智能化和信息化,主要是通過靈敏的狀態(tài)監(jiān)測手段、可靠的評價手段來判斷GIS設備的運行狀態(tài),并且在設備運行狀態(tài)出現異常時對設備進行故障分析,對故障部位、嚴重程度做出判斷,并識別診斷故障初期征兆。目前國內外已應用的GIS設備狀態(tài)帶電檢測和在線監(jiān)測設備,多數采用單一種類的傳感器對單一物理量進行檢測和診斷,較少采用多參量綜合檢測的方法去研究GIS設備在運行過程中絕緣狀態(tài)的變化過程與規(guī)律,如超聲、特高頻等。如何應用多種類型傳感器,并有機地整合傳感器和相應的數據采集、信號傳輸系統,對設備進行高效狀態(tài)分析和故障診斷將是一個重要研究方向。本論文重點研究和探索基于聲、電等信號傳感器陣列實現GIS設備狀態(tài)監(jiān)測和智能評估診斷的方法和關鍵技術。首先,本文針對特高頻和超聲波信號在GIS設備中的傳播特性以及設備中的絕緣盆、L型彎、T型分支等常見結構對于信號的影響,給信號檢測和定位增加的復雜性進行了分析。第三章研究了基于高階累積量和雙譜估計的信號時延估計算法,通過以雙指數振蕩衰減函數模擬局部放電信號驗證了該時延估計算法的準確性,最終利用該時延算法計算出實測特高頻信號的時延,并將該時延序列應用于GIS設備局部放電定位,預測出局部放電源的空間位置。第四章研究了GIS狀態(tài)診斷技術平臺的設計,包括超聲、特高頻傳感器及其陣列優(yōu)化、監(jiān)測IED裝置架構設計、多通道同步采集裝置研制,并研究了綜合考慮時域脈沖和統計圖譜的局放類型識別方法,通過分別利用主成分分析方法、信息增益方法及支持向量機回歸消去方法等特征選擇方法來降低特征空間維數,提高模式識別的效率,然后通過狀態(tài)信息可視化監(jiān)控平臺實現GIS狀態(tài)信息及故障類型預判展示。最后,通過建立GIS模擬實驗平臺,設計了 5種典型絕緣缺陷模型,利用本文設計的診斷平臺進行模擬實驗測試,對聲電聯合的局放精確定位算法進行了實物實驗驗證,并取得了主要故障類型指紋圖譜和典型缺陷包絡特征。
[Abstract]:Because of its advantages of high integration, convenient operation and maintenance, small area and so on, GIS equipment (gas insulated metal closed switchgear) is being applied more and more highly, although its operation reliability is high, but once it breaks down, the consequences are quite serious. Overhauling work, long blackout time, power failure range and non-fault components. Therefore, it is necessary to strengthen the construction of GIS intelligence and information, to realize the intelligent diagnosis of equipment status, and finally to guide the establishment of the corresponding maintenance strategy, the intelligence and information of GIS equipment, mainly through the sensitive state monitoring means. The reliable evaluation method is used to judge the running state of GIS equipment, and to analyze the fault of the equipment when it is abnormal, to judge the fault location and severity, and to identify the early symptoms of the fault diagnosis. At present, most of the existing GIS equipment used at home and abroad are used to detect and diagnose the single physical quantity by using a single kind of sensor. The method of multi-parameter comprehensive detection is seldom used to study the changing process and law of insulation state of GIS equipment during operation, such as ultrasonic, UHF and so on. How to apply various types of sensors and integrate sensors with corresponding data acquisition and signal transmission systems is an important research direction for efficient state analysis and fault diagnosis of equipment. This paper focuses on the research and exploration of the methods and key technologies of GIS equipment condition monitoring and intelligent evaluation and diagnosis based on acoustic and electrical signal sensor array. Firstly, this paper analyzes the influence of UHF and ultrasonic signal propagation characteristics in GIS equipment and the influence of the common structures such as the insulation basin L bending T branch on the signal, and the complexity of signal detection and localization is analyzed. In chapter 3, the time-delay estimation algorithm based on high-order cumulant and bispectral estimation is studied, and the accuracy of the time-delay estimation algorithm is verified by simulating partial discharge signals with double-exponential oscillation attenuation function. Finally, the delay of UHF signal is calculated by using the delay algorithm, and the delay sequence is applied to the location of partial discharge of GIS equipment, and the spatial position of local discharge power supply is predicted. The fourth chapter studies the design of GIS status diagnosis technology platform, including ultrasonic, UHF sensor and its array optimization, monitoring IED device architecture design, multi-channel synchronous acquisition device development. The method of partial discharge type recognition considering time domain pulse and statistical spectrum is studied. The feature space dimension is reduced by using principal component analysis method, information gain method and support vector machine regression elimination method, respectively. The efficiency of pattern recognition is improved, and then the GIS state information and fault type prediction are displayed through the state information visual monitoring platform. Finally, through the establishment of GIS simulation experiment platform, five kinds of typical insulation defect models are designed and tested by using the diagnostic platform designed in this paper. The fingerprint of main fault types and the envelope features of typical defects are obtained.
【學位授予單位】：山東大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TM595

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