為了獲得更多風能，風力機葉片之設計須格外審慎。然風力機的葉片卻常因為吸收濕氣、材料疲乏、陣風或雷擊等因素而損壞。因此在整個風力機葉片發生毀壞性災變之前，即時偵測葉片損壞，確有其高度重要性。
時頻分析方法在信號處理上是頗受肯定的研究方法，時頻表示法可將一維信號映射在時間和頻率所構成的二維平面，因而在使用時間頻率平面進行信號分析描述時，對於信號頻譜成份及其發生的對應時間掌握，均具有其高度助益。
故本文於進行風機葉片診斷中，輔以數種時頻分析方法分別進行，而由於短時傅立葉轉換之核心函數選擇較無彈性，故本文即研發提出泛用型時間頻寬乘積，並將其與短時傅立葉轉換共同簡化整合，進而將其應用至風力機葉片診斷，以觀察訊號觀測之改善效能。又基於小波轉換所具有之時間與頻率關聯性，本文續將所擷取之信號經由小波轉換之助及研發小波與熵之特性結合，同時觀察信號的時間及頻率變化，期以達成風力機葉片之診斷鑑別。 而為證實本文所提方法之實際可行性，經由模擬不同狀況下的葉片振動信號分析比對，其測試結果應可展現研究方法之參考價值，研究成果並可提供相關工業參考改進之需。

In order to acquire a larger amount of wind power, the design of wind blades must be prudently designed. However, considering that wind turbine blades may be damaged by moisture absorption, fatigue, wind gusts or lightening strikes, the damage detection of the blades before the occurrence of calamity becomes tremendously important.
The time-frequency analysis has emerged to be a useful tool recently for signal-processing study. The time-frequency representations are able to map a one-dimensional signal onto a two-dimensional function of time and frequency. With a representation delineated on a time-frequency plan, it has demonstrated its merit in grasping the spectral components and the time of event.
In the use of different time-frequency methods for the diagnosis of wind blades, the dissertation has proposed the embodiment of generalized time-bandwidth product into short time Fourier transform with simplification. This proposed approach was then applied to the detection of wind blades diagnoses and assess its performance improvement.
Next, based on the time-frequency relationships existed in wavelet transform, the signal acquired from the blades has been further evaluated through the integration of wavelet and entropy, anticipating exhibiting a high identification capability of signal variations.
To confirm the feasibility of methods proposed in this dissertation, several scenarios have been provided. Test results gained from the analysis and comparisons have shown the effectiveness of the approach. They are served as beneficial references for the industry applications that are investigated.

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