臺灣博碩士論文加值系統

本論文將小波包絡函數應用在振動訊號之奇異性分析，藉以探討機械系統之損壞。因為在機械系統的振動訊號中會發生振幅調變現象，所以採用小波包絡函數將可應用於解調變振動訊號中，並且由於小波包絡函數可由高截止頻率、低截止頻率和比例參數等三參數調整函數特性。因此，可藉由選擇高截止頻率和低截止頻率，小波包絡函數就能任意地選擇頻帶進行包絡線轉換，可提供奇異分析的方便性。此外，為適當決定分析振動訊號奇異性之訊號區間，將提出一個理論分析以減少分析振動訊號之數學運算量，可應用小波包絡函數之奇異性分析出奇異指數的大小藉以有效地診斷出軸承損壞。因此，一整體奇異性指數可由計算振動訊號的數個奇異性指數而獲得，並可做為機械系統損壞診斷的一項明確指標。當應用於分析一個軸承系統振動訊號時，整體奇異性指數被證實可有效應用於軸承損壞診斷。
本文在實驗中採用TI TMS320C32訊號處理晶片，用以實現本文所提出的小波包絡函數奇異性分析。此外，透過網際網路來傳送小波包絡函數奇異性分析值資料傳送到遠端電腦；最後達到遠端監控機械系統損壞診斷。

In the thesis, the singularity exponent analysis is proposed and derived from a wavelet-based enveloping function. According to the singularity exponent of the vibration signal, the defect of a mechanical system is studied. Because of the occurrence of amplitude modulation in the vibration signal of mechanical system, a wavelet-based enveloping function is applied to demodulate the vibration signal. The wavelet-based enveloping function has three parameters to adjust the function characteristics, which are the high-cutoff frequency, the low-cutoff frequency and the scale. The passband of wavelet-based enveloping function can be arbitrarily designated by simply setting the parameters of high-cutoff frequency and the low-cutoff frequency, and could also provide the convenience in the singularity analysis. For determining the interval of vibration signal to calculate the singularity exponent of the vibration signal, a theoretical study is proposed to reduce the requirement of computation. Accordingly, a global singularity exponent could be derived from calculating the singularity exponents of the vibration signal and would be an explicit index for the defect diagnosis of a mechanical system. When applied in the analysis of vibration signal for a bearing system, the global singularity exponent is capable of diagnosing of the bearing defects.
The proposed method is implemented in a TMS320C32 DSP interface card in the diagnosis of bearing defect to apply the singularity analysis with the wavelet-based envelope function. Thus, the singularity exponents derived from the wavelet-based enveloping function could be applied in the remote diagnosis of a mechanical system through the internet.

摘要………………………………………………………………………………I
Abstract………………………………………………………………………II
誌謝……………………………………………………………………………IV
目次…………………………………………………………………………... V
表目錄………………………………………………………………………... VII
圖目錄………………………………………………………………………... VIII

第一章 緒論…………………………………………………........... 1
1.1 前言………………………………………………………..... 1
1.2 文獻回顧…………………………………..…………………… 2
1.3 研究方向……………………………………………………….. 4

第二章 訊號分析與方法………………………………………….........5
2.1 簡介……………………………………………………………... 5
2.2 振動訊號之奇異性分析………………………………………... 6
2.2.1 小波奇異性指數理論分析. ………………................. 6
2.3 小波包絡函數應用於奇異性分析…………………………….. 8
2.3.1 小波包絡函數…………………………………………….... 8
2.3.2 小波奇異性分析範圍……………………………………… 10
2.3.3 小波包絡函數之計算奇異性……………………………… 13
2.4 實際應用考量…………………………………………………... 17

第三章 遠端診斷架構……………………………………............ 19
3.1 遠端監控原理…………………………………………………... 19
3.2 網路結構的類型………………………………………………... 20
3.3 TCP、UDP、IP通訊協定簡介…………………………………... 22
3.4 遠端機械損壞診斷監測………………………………………... 24
3.4.1 遠端診斷監測功能………………………………………… 24
3.4.2 機械損壞診斷狀態監測…………………………………… 25
3.4.3 遠端之損壞診斷監測……………………………………… 26
3.5 遠端監測介面、架構選擇與安置……………………………… 27
3.6 Socket介面設計與建構方式…………………………………... 28
3.6.1 Socket元件…………………………………………………. 28

第四章 實驗分析與結果………………………………............... 31
4.1 實驗方法與過程………………………………………………... 31
4.1.1 訊號量測設備……………………………………………… 34
4.1.2 系統架構…………………………………………………… 34
4.2 實驗結果…………………………………………………………. 35

第五章 結論與討論……………………………………………………….. 50

參考文獻……………………………………………………………………... 52

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