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博碩士論文 etd-0712107-132711 詳細資訊
Title page for etd-0712107-132711
論文名稱
Title
應用超音波技術於模鑄式變壓器局部放電診斷分析之研究
The Study of Partial Discharges Analysis in Epoxy-Resin Transformers Using Ultrasonic Technology
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
140
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2007-06-13
繳交日期
Date of Submission
2007-07-12
關鍵字
Keywords
超音波、小波、類神經網路、局部放電、模鑄式變壓器
neural network, wavelet, acoustic, epoxy-resin transformer, partial discharge
統計
Statistics
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中文摘要
電機設備絕緣材料的局部放電診斷,是評估絕緣材料之絕緣狀態的重要指標。本文探討非接觸式的超音波檢測法,應用於模鑄式變壓器之局部放電診斷,以建立安全、有效的絕緣狀態診斷技術。首先,本文探討應用超音波檢測法於局部放電檢測之可行性,經實驗室試驗,並且與電氣式脈衝電流法比對實驗結果,確認其正確性。此外,本文並發展出極座標圖譜與放電區間識別圖譜,藉此圖譜與傳統常見之q-φ-t(大小-相位-時間)圖譜,交互比對放電訊號特徵,以確認設備發生之故障瑕疵種類。其次,由於雜訊抑制的成效,關係著局部放電檢測的成效;本文應用小波轉換進行雜訊抑制,藉由小波母函數的比對、濾波門檻的實例測試,選擇出最適當之參數。訊號經抑制雜訊後,將更能強化放電訊息之特徵。最後,本文建立局部放電圖譜資料庫,並且應用倒傳遞類神經網路,學習圖譜之特徵訊息,最後在檢測實例中,提供各種常見之放電類別的發生率指標。研究的成果顯示,針對模鑄式變壓器、配電盤檢測之成效良好,本文所提出之方法可以於消除現場雜訊後,正確識別設備之局部放電瑕疵。
Abstract
The partial discharges (PD) measurement approach in power equipments is a very important inspection technique for insulation deterioration assessment. The PD based approach possesses the greatest potential for further development. This study proposes a noncontact type acoustic measurement system. We first investigate an acoustic measurement method in the laboratory. To prove the accuracy of the acoustic measurements, we proceed with, in the laboratory, signal-pattern comparison between the acoustic measurement method and the pulse current method. This study creates polar-coordinate and discharge type identification patterns. We propose the use of the q-φ-t patterns, the polar-coordinate patterns and discharge type identification patterns, with mutual cross-reference, to identify the discharge type. Then this study applies the wavelet transform to suppress noises; a wavelet mother function most similar to the acoustic PD signals is chosen and then set the filtering threshold value for the wavelet transform. The signals' features will be extracted after the noises are eliminated. The experimental results indicate that the application of wavelet transform can effectively eliminate the field noises. Next, the features will be used to build the training database for the back-propagation neural network (BNN) to construct the discharge patterns' recognition and identification system. Finally, we apply the finished neural networks to field signal-pattern identification. The proposed acoustic measurement system is applied on line to epoxy-resin transformers, power distributors, and the like. The superior measurement results we obtained shall be able to correctly identify power equipment's PD fault types.
目次 Table of Contents
摘要 I
Abstract II
誌謝 IV
目錄 V
圖目錄 IX
表目錄 XII
第一章 緒論 1
1.1 研究動機與背景 1
1.2 研究目的與方法 2
1.3 章節簡述 3
第二章 局部放電原理與檢測方法 5
2.1 前言 5
2.2 模鑄式變壓器之劣化 5
2.3 局部放電 8
2.4 局部放電種類與原理 11
2.4.1 局部放電種類 11
2.4.2 局部放電原理 14
2.5 局部放電模擬 20
2.5.1 前言 20
2.5.2 絕緣體氣隙模型 20
2.6 局部放電檢測 25
2.7 超音波檢測 31
2.7.1 基本概念 31
2.7.2 音射原理 32
2.7.3 音波的傳遞 33
第三章 應用超音波技術於局部放電檢測 36
3.1 前言 36
3.2 研究方法 36
3.3 實驗室驗證 37
3.4 各種放電類別圖譜特徵與檢測案例 45
3.5 瑕疵種類辨識輔助圖譜 53
3.6 本章節結論 60
第四章 雜訊干擾抑制 61
4.1 前言 61
4.2 雜訊干擾的來源 61
4.2.1 雜訊干擾的分類 61
4.2.2 雜訊干擾的途徑 64
4.3 雜訊干擾的抑制 65
4.3.1 雜訊抑制方法 65
4.3.2 頻域開窗 66
4.3.3 時域開窗 66
4.3.4 時-頻分析 67
4.4 小波轉換 67
4.5 最佳小波母函數選擇 71
4.6 濾波門檻選擇設定 75
4.7 小波轉換抑制雜訊成果設定 83
4.8 本章節結論 89
第五章 應用類神經網路於圖譜自動辨識 90
5.1 前言 90
5.2 倒傳遞類神經網路概述 90
5.2.1 類神經網路簡介 90
5.2.2 類神經網路架構與分類 93
5.2.3 倒傳遞神經網路 97
5.3 研究架構 99
5.4 研究方法 102
5.4.1 訓練資料前處理 102
5.4.2 訓練類神經網路 103
5.5 辨識成果與討論 107
5.5 本章節結論 116
第六章 結論與研究展望 117
6.1 結論 117
6.2 未來展望 118
參考文獻 119
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