近幾年結構系統健康監測逐漸受到重視，許多建物結構由於材料老化、地震的損壞以及其他人為因素造成結構物之動態行為改變。如果損壞是發生於結構內部的，專業技師很難進行目視檢查。在這種情況下，可以採用系統識別技術來幫助專業技師獲得定量參考資訊，以便更好地進行判斷。系統識別即利用量測之結構物動態資料，對系統特性進行識別。本文運用之系統識別方法為遞迴最小平方識別法(Recursive Least Square method, RLS)，其利用當步階計算之估測參數與量測資料，即可估算下一個步階之系統參數，故遞迴最小平方法可以識別各個時間點之系統參數。本文首先整理「核三廠一、二號機第三次十年整體安全評估審查報告」，並對其識別結果進行探討，以呈現遞迴最小平方法實際應用案例。同時建立一系列單自由度系統，探討遞迴最小平方法參數設定與雜訊對識別成效之影響，並驗證識別方法之正確性。進一步建立雙線性隔震建築等值模型進行模擬，以探討遞迴最小平方法對於時變系統與非時變系統之識別成效，並說明遞迴最小平方法之可行性。

Structural health monitoring is gradually attracting the attention of the public. Lots of structures are subject to degradation due to aging of materials, damageto strong earthquakes, and other human-induced factors. If the damages are embedded inside of the structure, it is difficult for professional engineers to perform visual survey. In this case, system identification technology can be adopted to assist professional engineers to get a quantitative reference for better judgement. System identification technologycan identify important structural parameters by using the measured records due to earthquakes. The system identification method used in this thesis is called the recursive least squares(RLS) method.The identified parameters are obtained sequentially in real-time. It is desirable to perform theidentification tasks recursively to reduce computation time and to be able to observe thetime-varying behavior. In order to verify the feasibility of RLS method,a set of single degree of freedom systems are used to investigate the parameter settings of the RLS method and the signal-to-noise ratio of the measured data are also considered. Further mover, an equivalent bilinear base-isolated building model is adopted to illustrate the effectiveness of the RLS method for the identification of the bilinear system.

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