臺灣博碩士論文加值系統

本文針對電腦風扇葉片缺損的振動特徵，利用希爾伯特-黃轉換 (Hilbert-Huang Transform, HHT)進行分析與檢測。HHT是一種適用於非平穩與非線性訊號的時頻分析工具，其分析流程首先將待分析訊號用經驗模態分解法(Empirical Mode Decomposition,EMD)分解出數個本質模態函數 (Intrinsic Mode Functions, IMFs)。其次再利用Hilbert轉換(Hilbert Transform, HT)求得該待測訊號之瞬時頻率、瞬時振福，進而建立兼具時-頻-能量三者的分佈圖，稱為希爾伯特時頻譜(Hilbert Spectrum)。文中利用此數據，將風扇旋轉頻率上之平均能量除以振動總能量定義為損傷程度，以此作為破壞檢測指標之一。此外並比較不同破壞程度之希爾伯特時頻譜與偏度之歐式距離當作另一個破壞檢測指標。實驗部分將風扇分成無損壞、輕微損壞及嚴重損壞三種情況，分別量測並分析其希爾伯特時頻譜，再計算其診斷指標，用以判斷其破壞程度，依據分析結果：以平均能量除以振動總能量為診斷指標其準確度為87.5%；以不同破壞程度之希爾伯特時頻譜與偏度之歐式距離為診斷指標，轉速為3100(RPM)之風扇其準確度為85.42%，轉速為2500(RPM)之風扇其準確度為58.33%，轉速為2000(RPM)之風扇其準確度為60.42%。

The current study investigates the property of vibration on the damaged cooling fans via Hilbert-Huang Transform (HHT) method. HHT is a time-frequency analysis tool commonly used to test the nonstationary and nonlinear signals. HHT consists of two procedures when applied to the analysis: (a) The utilization of Empirical Mode Decomposition (EMD) to extract Intrinsic Mode Functions (IMFs) from signals to be processed. (b) The utilization of Hilbert Transform (HT) to obtain Instantaneous frequency and Instantaneous amplitude from signals to be processed. Base on data, the degree of damage is defined as the average energy of fan rotation frequency divided by total energy of vibration. The degree of damage, thus, is used as the indicator for damage detecting. Being classified into undamaged, slightly damaged and seriously damaged, the cooling fans with different classification are compared via Hilbert spectrum to fulfill the damage detecting in the current study. According to the analysis, by considering the result of average energy of fan rotation frequency divided by total energy of vibration as the indicator for damage detecting, the accuracy is 87.5%. With the indicator for damage detecting defined as the distance between Hilbert spectrum of different classification of cooling fans and skewness, the accuracy is 85.42% when the rotation speed of cooling fan is 3100(RPM), 58.33% when the rotation speed of cooling fan is 2500(RPM), and 60.42% when the rotation speed of cooling fan is 2000(RPM).

摘要 I
Abstract II
目錄 III
圖目錄 V
表目錄 VII
第一章 緒論 1
1.1 研究動機 1
1.2 文獻回顧 2
1.3 研究內容及大綱 5
第二章 HHT基礎理論 6
2.1 瞬時頻率與解析訊號 6
2.2 希爾伯特黃轉換(Hilbert-Huang Transform, HHT) 13
2.2.1 本質模態函數(Intrinsic Mode Functions, IMF) 13
2.2.2 經驗模態分解法(Empirical Mode Decomposition, EMD) 14
2.2.3 希伯特頻譜 18
2.3 總體經驗模態分解法(Ensemble EMD,EEMD) 18
2.4 遮罩訊號法(MASK SIGNAL) 20
2.5 希爾伯特黃轉換之特性 21
第三章損壞診斷指標 23
3.1 旋轉頻率之能量比值(指標一) 23
3.2 相似度(指標二) 24
3.2.1 頻譜之歐式距離 24
3.2.2 偏度(skewness)之歐式距離 25
第四章 實驗設備與系統架構 26
4.1 實驗設備與流程 26
4.2 訊號量測儀器 27
4.3 訊號量測過程 29
第五章 實驗設計與結果分析 32
5.1 實驗設計 32
5.2 各轉速風扇與其指標 33
5.2.1 轉速3100(RPM)風扇 33
5.2.2 轉速2000(RPM)風扇 37
5.2.3 轉速2000(RPM)風扇 40
5.3 以各特徵設立診斷指標 44
5.3.1 以c值為特徵設立診斷指標 44
5.3.2 以頻譜相似度為特徵設立診斷指標 46
第六章 結論及未來展望 51
6.1 結論 51
6.2 未來展望 52
參考文獻 53

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