地動特性預測模組與智慧型隔減震控制系統之研發

Development of Ground Motion Characteristics Prediction Module and its Application to the Control of Intelligent Isolation System

10.6849/SE.202009_35(3).0002

蕭迦恩(Chia-En Hsiao)；林光奕(Kuang-Yi Lin)；林子剛(Tzu-Kang Lin)；盧煉元(Lyan-Ywan Lu)

地表運動特性 ； 支持向量機 ； 隔減震控制 ； 基因演算法 ； 模糊控制 ； Ground motion characteristics ； Support vector machine ； Structural control ； Genetic algorithm ； Fuzzy control

結構工程

35卷3期（2020 / 09 / 01）

39 - 62

繁體中文

近年來隔減震控制與地震預警的研究愈加受到重視，在地震工程領域中，地表運動特性除了常見的加速度、速度與位移的極值，還可分類為近斷層地表運動（near-fault ground motion）與遠域地表運動（far-field ground motion）。根據過去結構隔減震控制的相關研究，不同地表運動特性對於結構反應之控制結果影響甚鉅，故此研究試圖提出地表運動特性之預測模組，於地震主震波到來前預測此地震之地表運動特性，以優化隔減震之即時控制成效。本研究建立近斷層地表運動與遠域地表運動之資料庫，利用六項初達波特徵參數以及地表動態頻譜的高頻能量累加參數，以監督式機器學習—支持向量機建立地表運動特性預測模組。為了進一步開發智慧型隔減震即時控制系統，研究中採用槓桿式可變勁度隔震系統（Leverage-type Stiffness Controllable Isolation System, LSCIS）作為隔減震原型機構，此半主動控制機構可透過調整其控制律之控制參數，改變有效隔震勁度以即時控制結構動態反應。本研究亦將數個相異類型且具指標性的地表運動所對應之控制參數透過基因演算法最佳化，並以模糊控制建立地表運動與控制參數之關係模型，開發出智慧型隔減震即時控制系統。

In recent years, researches on structural control combining earthquake early warning have been widely studied. In the field of seismic engineering, ground motions can be mainly classified into near-fault and far-field ground motions. While the ground motion characteristics have a great influence on control performance; however, the existing earthquake early warning system can only predict the peak ground acceleration, and the optimal control efficiency cannot be promptly achieved. Therefore, a prediction module for ground motion characteristics is proposed in this study. A database of near-fault ground motions and far-field ground motions is first collected, and the six p-wave features and the high-frequency energy accumulations of the ground dynamic spectrum are used to establish the ground motion characteristic prediction module by utilizing support vector machine. In order to develop the intelligent structural control system, the Leverage-type Stiffness Controllable Isolation System (LSCIS) is used as the structural control mechanism. The effective isolation stiffness of the LSCIS can be swiftly changed to control the dynamic response of the structure. The control parameters corresponding to different types of ground motion are optimized by genetic algorithm, and fuzzy control is adopted for the intelligent isolation system.

1. 劉政嘉,林子剛,盧煉元,蕭迦恩(2019)。考量強地動特性之可變勁度隔震系統研發與應用。結構工程，34(1)，77-104。
   連結：
2. Baker, J. W.(2007).Quantitative Classification of Near-Fault Ground Motions Using Wavelet Analysis.Bulletin of the Seismological Society of America,97(5),1486-1501.
3. Böse, M.,Heaton, T.,Hauksson, E.(2012).Rapid Estimation of Earthquake Source and Ground-Motion Parameters for Earthquake Early Warning Using Data from a Single Three-Component Broadband or Strong-Motion Sensor.Bulletin of the Seismological Society of America,102(2),738-750.
4. Boser, B.,Guyon, I.,Vapnik, V.(1996).A Training Algorithm for Optimal Margin Classifier.Proceedings of the Fifth Annual ACM Workshop on Computational Learning Theory
5. Bozorgnia, Y.,Abrahamson, N. A.,Atik, L. A.,Ancheta, T. D.,Atkinson, G. M.,Baker, J. W.,Youngs, R.(2020).NGA-West2 Research Project.Earthquake Spectra,30(3),973-987.
6. Davoodi, M.,Jafari, M. K.,Hadiani, N.(2013).Seismic response of embankment dams under near-fault and far-field ground motion excitation.Engineering Geology,158,66-76.
7. Hoseini Vaez, S. R.,Sharbatdar, M. K.,Ghodrati Amiri, G.,Naderpour, H.,Kheyroddin, A.(2013).Dominant pulse simulation of near fault ground motions.Earthquake Engineering and Engineering Vibration,12(2),267-278.
8. Lu, L.-Y.,Chu, S.-Y.,Yeh, S.-W.,Chung, L.-L.(2012).Seismic test of least-input-energy control with ground velocity feedback for variable-stiffness isolation systems.Journal of Sound and Vibration,331(4),767-784.
9. Lu, L.-Y.,Lin, T.-K.,Yeh, S.-W.(2010).Experiment and analysis of a leverage-type stiffness-controllable isolation system for seismic engineering.Earthquake Engineering & Structural Dynamics,39(15),1711-1736.
10. Meirovitch, L.(1990).Dynamics and control of structures.John Wiley & Sons.
11. Moustafa, A.,Takewaki, I.(2010).Characterization and modeling of near-fault pulse-like strong ground motion via damage-based critical excitation method.Structural Engineering and Mechanics,34(6),755-778.
12. Satriano, C.,Wu, Y.-M.,Zollo, A.,Kanamori, H.(2011).Earthquake early warning: Concepts, methods and physical grounds.Soil Dynamics and Earthquake Engineering,31(2),106-118.
13. Scholkopf, B.,Smola, A. J.,Williamson, R. C.,Bartlett, P. L.(2000).New support vector algorithms.Neural computation,12(5),1207-1245.
14. Sehhati, R.,Rodriguez-Marek, A.,ElGawady, M.,Cofer, W. F.(2011).Effects of near-fault ground motions and equivalent pulses on multi-story structures.Engineering Structures,33(3),767-779.
15. Somerville, P.(2005).Engineering characterization of near fault ground motions.2005 NZSEE Conference
16. Soyluk, K.,Karaca, H.(2017).Near-fault and far-fault ground motion effects on cable-supported bridges.Procedia Engineering,199,3077-3082.
17. Vapnik, V. N.(2000).The Nature of Statistical Learning Theory.New York, NY, USA:Springer.
18. Zhang, S.,Wang, G.(2013).Effects of near-fault and far-fault ground motions on nonlinear dynamic response and seismic damage of concrete gravity dams.Soil Dynamics and Earthquake Engineering,53,217-229.
19. 陳啟仁,林子剛,盧煉元(2015)。考量位能效應之可變勁度隔震系統研發與應用。結構工程，30(3)，91-102。