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研究生:劉大均
研究生(外文):Ta-Chun Liu
論文名稱:運用經驗模態分解法與包絡線分析於單/雙損傷軸承故障診斷
論文名稱(外文):On empirical mode decomposition and envelope analysis for roller bearing diagnostics in case of single and double defect
指導教授:吳天堯
口試委員:楊學成陳任之
口試日期:2016-07-22
學位類別:碩士
校院名稱:國立中興大學
系所名稱:機械工程學系所
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:2016
畢業學年度:104
語文別:中文
論文頁數:53
中文關鍵詞:軸承故障診斷希爾伯特-黃轉換相對週期譜
外文關鍵詞:Hilbert-Huang transformfault diagnosisrelative period spectrum
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本研究使用包絡譜分析與相對週期譜分析在不同轉速情況下,對軸承之內圈單損壞、外圈單損壞、滾柱單損壞與外圈雙損壞等情況進行故障診斷。首先,經由希爾伯特-黃轉換的經驗模態分解法拆解,將訊號分解成若干個固有模態函數,選取發生振幅調制現象的固有模態函數進行包絡譜分析。接續步驟包含兩部分,第一部分使用快速傅立葉變換取得單損傷頻域特徵;第二部分使用相對週期譜取得雙損傷週期特徵。最後利用支持向量機,來辨識軸承損傷類型。



In this research, the envelope analysis and relative period spectral analysis are utilized to diagnose the different defective classes of bearing under different stationary speed, including the single defect on inner race, outer race, and roller as well as the double defects on outer race. First, the empirical mode decomposition is employed to decompose the signals into a number of intrinsic mode functions. The intrinsic mode functions that have obvious amplitude modulation phenomenon are then selected for envelope analysis. The successional procedure consists of two parts. In the first part, the fast Fourier transform algorithm is used to extract the frequency-domain features for identifying the single-defect classes. In the second part, the relative period spectrum is employed to extract the periodic features for diagnosing the double-defect classes. Finally, the support vector machine is utilized to classify the classes of signle-defect as well as the double-defect.

摘要 i
Abstract ii
目錄 iii
表目錄 vi
圖目錄 vii
第一章 緒論 1
1-1 前言 1
1-2 文獻回顧 3
1-3 研究動機 5
1-4 論文大綱 6
第二章 理論 7
2-1希爾伯特-黃轉換 7
2-2 經驗模態分解 7
2-3固有模態函數 8
2-4包絡線分析 9
2-5相對週期譜 9
2-6 支持向量機 10
2-6-1超平面 11
2-6-2支持向量 14
2-6-3 多分類支持向量機 15
2-7軸承特徵頻率 15
2-8訊號特徵提取流程 17
第三章 實驗架構及實驗方法 23
3-1 實驗架構與儀器 23
3-2實驗儀器與規格 24
3-2-1變頻器及轉速感測器 24
3-2-2馬達 26
3-2-3Keyphasor 26
3-2-4加速規 27
3-2-5 DAQ NI 9234擷取卡 27
3-3 實驗之軸承損壞類型 28
3-3-1正常軸承 28
3-3-2內圈損壞軸承 29
3-3-3滾柱損壞軸承 29
3-3-4外圈單損壞軸承 30
3-3-5外圈複合損傷間隔45度軸承 30
3-3-6外圈複合損傷間隔90度軸承 31
3-3-7外圈複合損傷間隔135度軸承 31
3-3-8外圈複合損傷間隔180度軸承 31
第四章 實驗結果與討論 33
4.1損壞特徵訓練與分類 33
4.2時域訊號分析 33
4.3包絡線頻譜分析 39
4.4相對週期譜分析 42
4.5 特徵提取及支持向量機分類 44
第五章 結論與未來展望 49
5-1 結論 49
5-2 未來展望 49
參考文獻 51



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