本文探討連續小波轉換於模態參數識別之應用。分別對系統自由響應、簡諧響應與定常響應轉化為近似自由響應的訊號經小波轉換獲得之時頻解析，然後利用系統模態參數表現於時頻解析之峰脊特徵中，進而識別出各模態的模態參數，即自然頻率，阻尼比及振形。由於各模態的參數是從時頻譜中的峰脊識別而得，而相近模態頻率在時頻解析圖中又容易互相干擾而影響識別結果。本文針對連續小波轉換於參數識別的相關理論與技術提出一套系統化的識別流程，並對相近頻率所造成的識別問題提出解決方法。經數值模擬結果顯示，系統的自由響應、簡諧響應與近似自由響應在本文所提之識別法下可得到良好的模態參數識別結果。

This thesis presents a technique for modal-parameter identification based on continuous wavelet transformation. Through adequate processing methods, the stationary ambient vibration data is transformed approximately to the free vibration of the analyzed system. The modal-parameter of the system (including natural frequencies, damping ratios and mode shapes) are then identified from the ridges in the time-frequency spectrum obtained by the wavelet analysis. As the modal parameters are identified from the ridges, and the close modes will interfere with each other and affect the result of modal identification. The modal-parameter identification based on the continuous wavelet transformation of proposed systematic method and close modes caused by the identification of problems for solutions. Through numerical simulations, applicability and effectiveness of the proposed wavelet-based method of modal parameter identification from vibration data is demonstrated.

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