應用頻率域之遞迴式改良型基因演算法於結構系統識別

Frequency-Domain Recursive Hybrid GA to Structural Dynamic Parameter Identification

李穎睿(Ying-Rui LI)

指導教授 ： 王淑娟

朝陽科技大學/理工學院/營建工程系/碩士(2013年)

摘要

現今預測地震的科技尚未臻成熟，基於安全之考慮，目前只能依照法規進行耐震設計以防患未然。目前台灣地區在各地重要之大樓、學校及橋樑等土木建築物上皆裝有強震儀，可隨時記錄地震發生時之相關資料，利用其地震紀錄來識別對應之結構系統參數，了解結構物的動態行為是耐震分析與分設計中所考慮的重要因素之一。因此，近年來發展了各種不同的系統識別方法與模式，以求得結構系統受震後之動力行為與系統參數的變化進行建築物安全評估，並根據地震後建築物的破壞情形，進行修補工作。近二十年來，很多學者利用系統識別的結果從事結構健康診斷之研究，所謂結構健康診斷是利用比較結構目前之狀態與未受損狀態或基線狀態(Baseline State)之過程來決定建築物受地震或其他型式外力作用下是否有損壞產生，從而決定損壞之位置及程度，進而提出對應不同損壞狀態之損壞指數門檻值。
遞迴式改良型基因演算法是時間域上的改良型基因演算法，可應用於非線性系統識別，其主要是自動式之分段識別，並將各分段之起始位移及速度設定為識別參數，藉由改良型基因演算法之搜索能力進行識別，但在計算反應上需花費較多的時間。為了解決遞迴式改良型基因演算法在時間域上計算反應上需花費較多的時間，因此本研究提出結合頻率域之遞迴式改良型基因演算法，其主要是將地震紀錄做分段，利用傅立葉轉換將分段後之地震紀錄轉換至頻率域上求解，頻率域在運算僅需要利用代數方式進行運算，相較於遞迴式上利用微分方式進行運算較為快速，故能大幅減少運算時間。在此將應用於單自由度及多自由度數值模擬系統之動力特性識別，驗証其可行性；為了更加確定應用於真實建築物之可行性，亦對於含有雜訊的數值模擬地震紀錄及反應進行識別以探討新式識別法之識別效果。最後將本法應用於真實建築物，並且利用最大軟化指標、ASDI指標及MAC指標的方式來判斷建築物之損壞程度，根據兩棟建築物為輕微損壞、一棟建築物的中度損壞及一棟建築物嚴重損壞的損壞狀況，初步設定各損壞指標之門檻值，並推估第五棟建築物的損壞狀況。

關鍵字

系統識別 ； 損壞評估

並列摘要

Although a great deal is known about where earthquakes are likely to occur, there is currently no reliable way to predict the time when an event will occur in any specific location. However, the damages caused by them can be greatly reduced with proper structural design using safer seismic code. In this regard, dynamic behavior of structures under earthquakes should be considered in the process of design. In order to realize the dynamic behavior of structural systems, we can determine the dynamic models and parameters by system identification techniques. However, collecting strong motion data is essential when performing the system identification analysis. Fortunately, the strong motion data recorded by accelerographs, which were installed under the Taiwan Strong-Motion Instrumented Program (TSMIP) since 1993, has accumulated to a remarkable amount. In addition to updating the structural parameters for better response prediction, system identification techniques made possible to monitor the current state or damage state of the structures. The parameters of the structures are identified and referred to the associated baseline states. The current state of a structure’s condition relative to a baseline state is compared and the degree of damage is determined.
In the implementation of the recursive hybrid genetic algorithm in the time domain, numerical integration is essential for solving the differential equation in the time domain. This integration procedure may result in a huge amount of computational time since it is required to apply so many times as long as the evolutionary process is proceded. In order to accelerate the identification process, a recursive hybrid GA in the frequency domain is developed. The time history of the measurement is divided into a series of time intervals, and then the model of equivalent linear system is employed to identify the modal parameters of the system for each time interval. The differential equation can be transformed into the frequency domain by Fourier transform and the response in the frequency domain can be solved by algebraic equations instead of differentials equations. The process of exploring this new algorithm is similar to that of recursive hybrid genetic algorithm in the time-domain, by using the simulated SDOF system and MDOF system considering the effect of noise contamination.
Finally, this new identification strategy is also applied to the identification of the real four buildings. By employing the maximum softening index, Approximate Story Damage Index and Modal Assurance Criterion, we can determine the damage states of these buildings. According to the damaged states of the buildings, a set of the threshold values for damage states can be proposed and then be applied to the damage assessment of a real building.

並列關鍵字

Damage Assessment ； system Identification

參考文獻

【29】 楊維莘及黃烔憲，「數種濾波技術於線性系統識別之可行性探討」，碩士論文，國立交通大學土木工程學系，新竹，2012。

【49】 林沛暘、羅俊雄，「標竿鋼構樓房震動台試驗」，國家地震工程研究中心報告，NCREE-06-020，臺北，2005。

【2】 蔡永勤，「應用頻率域改良型基因演算法與遞迴式改良型基因演算法於結構動力系統識別」，碩士論文，私立朝陽科技大學營建工程研究所，台中(2010)。

【4】 McVerry, G.H., “Structural Identification in the Frequency Domain from Earthquake Records,” Int. Journal of Earthquake Engineering and Structural Dynamics, Vol. 8, pp.161-180, 1980.

【5】 Beck, J.L., and Jennings, P.C., “Structural Identification Using Linear Models and Earthquake Records,” Int. Journal of Earthquake Engineering and Structural Dynamics, Vol. 8, pp.145-160, 1980.