槓桿式勁度可控式隔震系統之系統識別

Parametric Identification of Structures with Leverage-type Stiffness Controllable Isolation System

曾文佐(WEN-TSO TSENG)

指導教授 ： 王淑娟

朝陽科技大學/理工學院/營建工程系/碩士(2019年)

摘要

近年來結構健康監測技術逐漸受到重視，許多建物長時間受到多次地震、風力及時間等影響，造成建築物之材料老化、內部結構損壞而引起結構物之動態反應特性發生改變，而這種改變是目視難以察覺的。在這種情況下，可以採用系統識別技術來幫助專業人員獲得結構物之各種參數，以便更好地判斷結構物動力特性之現況。
而在經歷過921集集大地震後，國內的耐震設計法規標準紛紛提高設計地震力，而導致建築所需的成本大幅增加，使得傳統的耐震設計難以滿足現代的設計需求，因此必須考慮到消能減震、隔震器等新式防震科技。現今使用的消能器提供之阻尼，以及隔震器提供之勁度等均屬於非線性系統，近年來的重要建築物皆已將這些科技導入建築物內使用，而加裝了這些防震系統，會使結構系統動力行為與原先有所差異，因此建築物真正之強度便不得而知。在這種情況下，進行系統識別時也必須將這一些消能、隔震等系統的非線性行為加入考慮，如此一來就必須修改原本的反應方程式，才能有效的對加裝了消能、隔震等系統之建築物進行參數識別。
傳統(被動)隔震系統因設計參數固定，當隔震結構遭受非設計地震力時，隔震效果可能會不如預期，因此發展出了主動控制系統及半主動隔震系統。主動控制系統可以降低遭受不同地震時的結構反應，但在實際應用中所需的控制能量較大，限制了其應用，而半主動隔震系統因施加力量在隔震元件而改變隔震元件特性，故可改善上述主動控制與被動隔震系統之問題。
本研究參考葉士瑋【1】「最小輸入能量法於勁度可控式隔震系統之應用研究」之論文，而槓桿式勁度可控式隔震系統(Leverage-type Stiffness Controllable Isolation System, LSCIS)為一半主動控制之非線性隔震系統，採用之控制律為最小輸入能量法(Least Input Energy Method, LIEM)，由於勁度為一可隨時間改變的時變參數，故LSCIS為一非線性系統。依其數值分析方法及控制律建立數值分析模式，撰寫計算反應之程式。而後匯入改良型基因演算法中，以系統識別方法識別出其有意義之物理參數，藉此判斷隔震建築之結構狀況。數值模擬結果顯示，利用改良型基因演算法可成功識別出原先所設定之系統參數。而在模擬之資訊含有雜訊的情況下，所設定之參數仍有相當正確的識別結果。最後使用葉士瑋【1、2】提供之實際量測模型所得之真實數據進行參數識別以驗證識別系統程式是否也能識別出誤差在合理範圍內之反應及合理的參數，並於識別參數中加入初始速度及位移，嘗試增加識別之準確性。後續將控制律參數加入識別參數中，測試是否也能成功識別出正確之控制律參數。

關鍵字

改良型基因演算法 ； 系統識別 ； 半主動隔震系統

並列摘要

During past few decades, structural health monitoring has attracted a lot attention. Structures may be subjected to seismic forces, wind loads and other effects over its lifetime use. Therefore, the structural parameters may be deviated from the design values due to the yielding or the fatigue of the material strength. In this regard, the dynamic characteristics may also be changed due to the damage of the structure. In order to realize the dynamic behavior of structural systems, we can determine the dynamic models and parameters by system identification techniques. System identification techniques also made possible to monitor the current state of the structure.
The traditional approach to earthquake resistant design is to design structures with sufficient strength capacity and the ability to deform in a ductile manner. Alternatively, newer concepts of structural control, including both passive and active control systems, have been growing in acceptance and may preclude the necessity of allowing for inelastic deformations in the structural system. A compromise between passive and active control systems has been developed recently in the form of semi-active control systems. Semi-active control systems maintain the reliability of passive control systems while taking advantage of the adjustable parameter characteristics of an active control system.
Yeh et al. proposed a control law called “Least Input Energy Method” (LIEM). The goal of LIEM is to minimize the input seismic energy to the superstructure by adjusting the isolation stiffness, so that the dynamic response of the structure can be mitigated. The proposed LIEM control law is applied to a semi-active isolation system called “Leverage-type Stiffness Controllable Isolation System” (LSCIS), and the isolation stiffness of the LSCIS can be controlled on-line by varying the pivot of its leverage [1].
In order to capture the behavior of LSCIS, this study builds up a numerical analysis program based on the numerical analysis method of LSCIS proposed by Yeh [1]. The validity of the proposed program is demonstrated by comparing the results of this study with the theoretical results of the LSCIS provided by Yeh [1].
A hybrid Genetic Algorithm developed by Wang [3] and Hong [4] is required to be applied to the identification of both the device and structural system. Accordingly, a hybrid Genetic Algorithm, merging the numerical analysis program associated with the LSCIS device has been developed in this study. By this hybrid computational strategy we can perform the parametric identification of the LSCIS device it self, and then implementing the identification techniques to the structure equipped with LSCIS.
The proposed algorithm has been applied to identify the system parameters of both the simulated LSCIS device and the simulated structure equipped with LSCIS device with or without noise contamination. Accordingly, the feasibility of the proposed new method has been verified. Finally, this identification algorithm has also been applied to the measured data from the experiments performed by Yeh [1, 2]. The comparisons has been made between the predicted response and the measured one for both the device and structural system equipped with those devices.

並列關鍵字

Hybrid Genetic Algorithm ； System Identification ； Semi-active Isolation System

參考文獻

【1】 葉士瑋，「最小輸入能量法於勁度可控式隔震系統之應用研究」，碩士論文，國立高雄第一科技大學營建工程研究所，高雄，2009，指導教授：盧煉元。

【2】 Lu, L. Y., Chu, S. Y., Yeh, S. W and Chung, L. L., “Seismic Test of Least-input-energy Control with Ground Velocity Feedback for Variable-stiffness Isolation Systems,” Journal of Sound and Vibration, Vol. 331, No.4, pp. 767-784, 2012.

【3】 Wang, G. S., “Application of Hybrid Genetic Algorithm to System Identification,” Structural Control and Health Monitoring, Vol. 16(2), pp. 125-153, 2009.

【4】 洪忠儀，「結合基因演算法與局部搜索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，臺中，2005，指導教授：王淑娟。

【5】 http://www3.nstm.gov.tw/earthquake/A_1_4_a.htm