對於維持電氣設備正常運行所需之維護保養工作，早期的維護工作是在設備發生事故後才進行，但這樣的維修方式，易造成龐大的直接與間接經濟損失，因此，後來維修工作更改為定期維修的方式。定期維修對於減少事故發生以及發現設備缺陷可以達到一定的成效，但無法預知設備的實際絕緣或運轉狀況，可能導致過度的維修，造成人力及物力資源的浪費。因此，目前國際最新發展趨勢聚焦在電氣設備故障診斷與線上狀態監測的技術與研究，期望能提高設備的維護水準及避免突發事故發生。

本研究旨在開發基於模糊法之感應電動機故障診斷以及運轉狀態監測系統。首先，運用電氣分析法以及振動分析法量測馬達電氣以及振動訊號。其次，計算國際規範之電氣相關指標及記錄振動軸軌跡圖譜，透過指標適切性評估以及分形理論擷取特徵值。進而設計基於模糊法的故障診斷以及運轉狀態監測系統，評估馬達各類型故障發生的機率以及馬達的運轉狀態等級。最後，並以健康及馬達常見(定子、轉子、軸承及偏心)四種故障瑕疵模型及模擬案例以評估其可行性。

In terms of the maintenance work for keeping normal operation of electrical equipments, the maintenance work was implemented after the equipment was in trouble in early stages, but this maintenance mode was likely to cause heavy direct and indirect economic losses. Therefore, the maintenance work was changed to periodic maintenance. The periodic maintenance is effective on reducing accidents and finding equipment defects to some extent, but the actual insulation or operating condition of equipment cannot be predicted, there may be excessive maintenance, wasting manpower and material resources. Therefore, the latest international development trend aims at the technology and study of electrical equipment fault diagnosis and on-line condition monitoring, hoping to upgrade the equipment maintenance levels and prevent sudden accidents.

This study aims to develop a fuzzy-based induction motor fault diagnosis and condition monitoring system. First, the electrical and vibration signals of motor are measured by using electrical analysis and vibration analysis methods. Secondly, the electrical indexes of international specifications are calculated and the vibrating shaft trajectory pattern is recorded. The feature values are extracted by index fitness evaluation and fractal theory then design the fuzzy-based fault diagnosis and condition monitoring system to evaluate the probability of various types of motor faults and the motor operating state level. Finally, the feasibility is evaluated by using health and common motor (stator, rotor, bearing and eccentric) fault defect models and simulation cases.

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