本研究旨在探討使用加速度計量測結構反應並以基因演算法求取結構勁度之非破壞檢測方式。文中基因演算法的適應函數是以加速度計量測反應與結構反應之相似度為基準以求得最佳基因並獲得破壞結構之勁度。研究中並探討不完全量測及具雜訊之處理方式並針對一四層樓結構為例子，包括加速度計數量不完全及量測值包含雜訊之情形，進行實例演算。最後研究亦發現即使加速度計部分損壞導致數量不完全或是量測資料包含雜訊時，基因演算法仍能藉由其它資料求得最佳解。文中亦針對一個鋼筋混凝土實驗模型藉由基因演算法的非破壞檢測做實例分析，落實基因演算法在實際應用上之可行性。

　 由於液流阻尼器的低成本以及不會產生應力增加結構負擔的特性，近年來已逐漸受到重視。雖然結構的行為以線性模擬之，但加裝液流阻尼器結構之數值分析最主要的問題在於其隨著速度而改變的出力為高度非線性行為，也因此導致整個結構的行為呈現非線性。隨機線性法(Stochastic Linearization Technique) 是目前最常被採用的方法，其以一個等值線性阻尼之線性反應取代了原來的非線性結構。在此我們嚐試以近年來常被採用做最佳化搜尋的基因演算法求得滿足運動平衡方程式之最佳解，並求得加裝液流阻尼器結構之非線性反應。最後並針對加裝液流阻尼器結構做非破壞檢測及探討。

The research describes the non-destructive damaged structures using the acceleration sensor measurement data for four-story shear structures, and obtains the optimal solution of story stiffness by genetic algorithm. The fitness function, based on the similarity of measurement-curve derives from the acceleration sensor with responses of the considered structure to find the optimal gene and the stiffness of the damaged structure. The research aims a four-story shear typed structure, including cases with incomplete acceleration sensors. Cases with measurement data noises are also discussed. The simulation results identify the stiffness of damaged-stories using fewer displacement sensors if the sensor location is properly arranged. The genetic algorithm proves that neglecting the noise of incomplete measuring data from other sensing points can still successfully obtains the optimal solution. The current study discusses the experiment case of the four-story reinforced concrete structure, and finds the stiffness reduction by the genetic algorithm.

Fluid dampers have received considerable attention in recent years because of their low cost and usually will not induce additional here in structural systems. However, analysis of structures with fluid damper devices reveals that we are facing a nonlinear dynamic problem because of the relationship between force and velocity of the damper is highly nonlinear, although the structure behaves linearly, the whole damper-structure system has inherent nonlinear properties. The stochastic linearization technique (SLT) is typically performed with a linear system that is statistically equivalent to the nonlinear one. In this paper, an alternative technique, a genetic algorithm (GA), is applied, which is the most used optimal searching method in recent years. The motion equation of the structures is utilized as the objective function. And the non-destructive detection of structure with fluid damper devices are also detected herein.

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