本文主要應用經驗模態分解法於渦輪幫浦軸承故障診斷。研究初期設計軸承 缺陷模擬訊號進行技術開發及驗證，接著以放電加工與細孔加工方法製作軸承內 環及外環缺陷，分別實現在雙面轉子系統及渦輪幫浦實驗平台，用以確認技術之 實用性。研究中藉由經驗模態分解法不需定義其基本函數及轉換式之特性，改善 傳統帶通濾波包絡解調法缺點，避免實驗對象之結構共振頻率求取不易與帶通濾 波範圍選取容易受到主觀影響並造成包絡譜分析結果之差異。最後，比較以經驗 模態分解改良之包絡譜分析方法及傳統包絡譜分析方法之分析結果，進而探討兩 者間之優劣。本文說明發展在線式軸承監測診斷方法之實用性，未來可應用於其 他旋轉機器之故障診斷。 This thesis applies empirical mode decomposition in fault diagnosis of turbo-pump bearings. In the initial stage design simulation signals of fault bearing and do technical development as well as verify, next by electrical discharge machining and electrical discharge machining of deep hole in inner-ring and outer-ring of bearing to make defects technique for realizing the technique of breakdown diagnosis on two-plane rotor system and turbo-pump platform. Empirical mode decomposition no need to define basic function and transformation, which cause the defect of conventional envelope analysis with band-pass filtering could be improved during the research. With this character could the following phenomena be avoid: first, the hard obtainment about resonance frequency of subject; second, range of band-pass filtering could be easily influenced by subject in the time of choosing and result in the difference to result of envelope analysis. In the end compare the analysis from envelope analysis algorithm of empirical mode decomposition and the technique of conventional envelope analysis, then to discuss the advantage and deficiency between them. This thesis explains the practicality in development of on-line diagnosis technique of bearing monitoring, and in the future could be applied to other rotating machines for fault diagnosis.