姓名 |
林信宏(Hsin-Hung
Lin) |
電子郵件信箱 |
e3503926@pchome.com.tw |
畢業系所 |
營建工程系碩士班(Department
and Graduate Institute of Constrction Engineering) |
畢業學位 |
碩士(Master) |
畢業時期 |
90學年第2學期 |
論文名稱(中) |
應用基因演算法於結構動力參數識別 |
論文名稱(英) |
Application of
Genetic Algorithm to Structural Dynamic Parameter Identification |
檔案 |
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|
論文使用權限 |
使用者自訂權限:校內 0 年後、校外 1
年後公開 |
論文語文/頁數 |
中文/147 |
摘要(中) |
當結構物因地震力作用而產生損壞時,其動力特性也會隨之改變,因此結構物是否還有當初設計時之強度便不得而知。此時若能藉由系統識別的方法來識別結構特性的變化,即可作為對結構物進行修復或補強的參考,並確保人民生命財產之安全。 本文利用基因演算法在時間域上進行系統動力參數之識別,為驗証基因演算法應用於系統動力參數識別之可行性,首先利用數值模擬的方式產生不同系統的輸入和量測反應紀錄,然後利用基因演算法之全域最佳化搜索能力來找尋符合該系統之參數值,並計算量測反應和估測反應之間的誤差指數值以評估識別之結果。 經由數值模擬系統之識別結果可確定基因演算法的可行性,因此本研究接著識別實際結構物-台電大樓主樓,地震來源為台電大樓主樓於331地震時所量測之地震紀錄,並使用單、雙向擾動系統之振態參數識別法進行識別,系統參數亦是經由基因演算法搜索。識別結果顯示331地震時,台電大樓主樓耦合效應並不明顯,因此,為節省電腦運算時間,建議採用單向擾動系統識別即可。 |
摘要(英) |
Structure properties
will be deteriorated and degraded with time in an unexpected way due to
randomness in the environment and loadings over its lifetime. In
particular, when a structure is exposed to strong earthquake ground
motion, the properties of the structure may be changed and its behavior
after an earthquake can be different from that before the earthquake.
Consequently, identification of the state of a structure is necessary
after a certain period of operation, to provide the proper information
for decisions on the maintenance, repair and rehabilitation of the
structure. The system parameter value or state is obtained or
identified by minimizing the accumulated discrepancy between the
recorded response and the identified response. The parameter value
evaluated in such a sequence is called an optimal estimate. In
consequences, system identification problem can also be considered as an
optimization problem. Genetic algorithm (GA) is a search method based on
natural selection and genetics and is different from conventional
optimization methods in several ways. The GA is a parallel and global
search technique that searches multiple points, so it is more likely to
obtain a global solution. In this study, it is intended to propose a new
system identification algorithm, which utilizes GA and is to be
implemented easily, and is robust to the search space. The validity and
the efficiency of the proposed algorithm are explored by simulated
input/output measurements of both SDOF and MDOF dynamic systems.
Finally, the same algorithm is also applied to a real building system.
The real building identified here is the Taiwan Electricity Main
Building located in Taipei. The recorded accelerograms used here are the
data collected on March 31, 2002. The comparison is made between the
predicted acceleration and the measured one for each case. |
關鍵字(中) |
基因演算法
系統識別
誤差指數 |
關鍵字(英) |
Genetic Algorithm
Error Index
System Identification |
指導教授 |
王淑娟
|