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研究生:楚萃瑤
研究生(外文):Tsui-Yao Chu
論文名稱:在馬達的電流波形上使用Fisher’s線性鑑別分析法-辨識馬達的品質類別
論文名稱(外文):Fisher’s Linear Discriminant Analysis Method for Motor Quality Types on Current Waveforms
指導教授:葉雲奇林高洲林高洲引用關係
學位類別:碩士
校院名稱:健行科技大學
系所名稱:電子工程系碩士班
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2014
畢業學年度:102
語文別:中文
論文頁數:35
中文關鍵詞:Fisher’s 線性鍵別分析法特徵點選取直流馬達
外文關鍵詞:Fisher’s LDAfeature selectionDC motor
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本論文提出一個分析馬達電流波形並有效辨識馬達品質類別的方法,稱之為Fisher’s Linear Discriminant Analysis (Fisher’s LDA)法。本論文之Fisher’s LDA法是由下列三大單元所組成,分別為:(1)馬達信號的前置處理:包含馬達電流波形信號的擷取、雜訊的去除、信號的放大、類比/數位信號的轉換、電腦介面電路的設計等;(2)主要特徵點的選取與主要特徵值的統計:本論文以區間交集法(Range-Overlap Method,ROM)在眾多的原始特徵點中選取主要特徵點,並使用統計的方式計算主要特徵點之特徵值範圍,包含特徵值的最小值、最大值、算數平均值等;(3)辨識馬達品質的類別:本論文以Fisher’s LDA演算法辨識馬達品質的類別。依據實際的測試結果,本論文提出之Fisher’s LDA法性能如下:將「好的馬達」辨識成是「好的馬達」之平均正確率是99.92%,將「壞的馬達」正確辨識成是「壞的馬達」的正確率是92.43%,將「壞的馬達」辨識成是「好的馬達」的錯誤率是7.57%,將「好的馬達」辨識成是「壞的馬達」之錯誤率是0.08%。總平均正確辨識率為99.72%。

This study proposes a Fisher’s Linear Discriminant Analysis (Fisher’s LDA) approach to analyze current waveform for determining the motor’s quality types. Fisher’s LDA comprises three main stages: (i) the preprocessing stage for enlarging motor’s current waveforms’ amplitude and eliminating noises; (ii) the qualitative features stage for qualitative feature selection of a motor’s current waveform; (iii) the classification stage for determining motor’s quality types using the Fisher’s LDA. In the experiment, the right rate is 99.92% (92.43%) for right judgment on good (defect) motor to be determined as good (defect), the error rate is 7.57%% (0.08%) for wrong judgment on defect (good) motor to be determined as good (defect). The average right rate is 99.72%.

摘  要 ii
Abstract iii
誌  謝 iv
目  錄 v
表目錄 vi
圖目錄 vii
第一章 緒論 1
1.1 前言 1
第二章 馬達信號的前置處理 3
2.1 電源自動加入裝置(APAD) 4
2.2波形偵測電路(WDC) 6
2.3增益可規劃的放大器(GPA) 6
2.4類比/數位信號轉換器(ADC) 9
第三章 特徵點的選取與特徵值的統計 10
3.1 主要的特徵點選取:區間交集法 11
3.2 主要特徵點的定義與特徵值範圍的統計 14
第四章 辨識馬達的品質類別:Fisher’s 線性鑑別分析法(FLDA)20
5.1 實驗一:測試某一個週期的馬達電流信號 25
5.2 實驗二:測試某一個馬達 27
5.3 實驗三:測試辨識準確度 29
5.4 性能比較 30
第六章 結論 31
參考文獻 32
簡 歷 36



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