• 沒有找到結果。

第六章 結論與未來展望

6.2 未來展望

6.2.2 未來展望

大樓,由原本的6 層樓在往上擴建 7 層樓,共 13 層樓大樓,且原 6 層為鋼筋混 凝土建築物,上面7 層為鋼結構建築物,會認為頻率會不太一樣,但從 5 層與 13 層之FFT 來看,其頻率峰值皆有出現,雖然最高峰值 5 層與 13 層不同,但兩張 圖峰值頻率都有,因此進行配置時,可以得到最佳感測器配置位置。

綜合上述數值模型以及六棟結構物,推論本文所提出最佳配置可信度高,以 最少顆感測器獲得較為精準之中低模態頻率,並用數值模擬當建築物受到災害使 其勁度折減時,其原先配置依然能得到較為精準之中低模態頻率,也就是建築物 受損後,用最佳感測器配置法所得出最佳配置位置,依然能找到較為精準之模態 頻率,並與原先之模態頻率比較,瞭解建築物之模態頻率是否下降,進而進行更 進一步的安全檢測,確保結構之安全與穩定性。

態頻率,須將各層樓感測器從單顆改成雙顆,並量測同一方向。測得時間歷時資 料後,兩兩相減,得到扭轉向之時間歷時,才可以進行最佳化配置。

由於扭轉向須建立3D 數值模型進行模擬,無法用簡單的剪力構架進行計算,

可作為之後再討論之空間。真實量測時因扭轉向感測器變成兩倍,不見得能達到 減少花費成本與設置時間,且在紀錄上,因感測器數變多,所遇到的問題也相對 地變多,因此如何單獨討論扭轉向之模態頻率最佳配置是一個須深入研究的題目。

由於結構物的模態頻率無法確切知道,都只能借助模擬或者檢測後進行方式去求 得,本文以討論了很多去除遇到非結構物頻率的方式,但實際上,應該還會有很 多問題存在,如何得到更精確的模態頻率,增進結構的安全性是未來需要發展的 目標,以最少顆感測器得到最精準之模態頻率,是本文需要追求的目標。

參考文獻

Bakir, P. G. (2011). “Evaluation of optimal sensor placement techniques for parameter identification in buildings.” Mathematical and Computational Applications, 16(2), 456-466.

Bandara, R. P., Chan, T. H. T., & Thambiratnam, D. P. (2014). “Frequency response function based damage identification using principal component analysis and pattern recognition technique.” Engineering Structures, 66, 116-128.

Bao, Y., Tang, Z., Li, H., & Zhang, Y. (2018). “Computer vision and deep learning–

based data anomaly detection method for structural health monitoring.”

Structural Health Monitoring, 18(2), 401-421.

Bendat, J. S., & Piersol, A. G. (2011). Random Data: Analysis and Measurement procedures.”NewYork, NY: John Wiley & Sons.

Brincker, R., & Andersen, P. (2006). “Understanding stochastic subspace identification.”

Paper presented at the Conference Proceedings: IMAC-XXIV: A Conference &

Exposition on Structural Dynamics.

Celebi, M., & Liu, H.-P. (1998). “Before and after retrofit–response of a building during ambient and strong motions.” Journal of Wind Engineering and Industrial Aerodynamics, 77, 259-268.

Chang, J., Limin, S. U. N., & Qi, W. (2007). “Identified method of arch bridge modal parameters based on stochastic subspace combined with stabilization diagram.” Journal of Architecture and Civil Engineering, 24(1), 21-25.

Chen, J.-D., & Loh, C.-H. (2017). “Tracking modal parameters of building structures from experimental studies and earthquake response measurements.” Structural Health Monitoring, 16(5), 551-567.

Chen, J.-D., & Loh, C.-H. (2018). “Two-stage damage detection algorithms of structure using modal parameters identified from recursive subspace identification.”

Earthquake Engineering & Structural Dynamics, 47(3), 573-593.

Cho, S., Yun, C.-B., Lynch, J. P., Zimmerman, A. T., Spencer Jr, B. F., & Nagayama, T.

(2008). “Smart wireless sensor technology for structural health monitoring of civil structures.” Steel Structures, 8(4), 267-275.

Concha, A., & Alvarez-Icaza, L. (2018). “Parameter and State Estimation of Shear Buildings Using Spline Interpolation and Linear Integral Filters.” Shock and Vibration, 2018, 1-21.

Conforto, S., & D'Alessio, T. (1999). “Optimal estimation of power spectral density by means of a time-varying autoregressive approach.” Signal Processing, 72(1), 1-14.

Deraemaeker, A., Reynders, E., De Roeck, G., & Kullaa, J. (2008). “Vibration-based structural health monitoring using output-only measurements under changing environment.” Mechanical Systems and Signal Processing, 22(1), 34-56.

Doebling, S. W., Farrar, C. R., & Prime, M. B. (1998). “A summary review of vibration-based damage identification methods.” Shock and vibration digest, 30(2), 91-105.

Elmer, W., Stafsudd, J. Z., & Taciroglu, E. (2010). “Performance of equilibrium-based system identification algorithms with incomplete state data.” Engineering Structures, 32(2), 483-497.

Fan, K. Q., Ni, Y., & Gao, Z. M. (2004). “Improved stochastic system identification approach with its application in bridge condition monitoring.” Zhongguo Gonglu Xuebao/China Journal of Highway and Transport, 17(4), 70-78.

Farrar, C. R., Doebling, S. W., & Nix, D. A. (2001). “Vibration–based structural damage identification.” Philosophical Transactions of the Royal Society of London.

Series A, 359(1778), 131-149.

Farrar, C. R., Park, G., Allen, D. W., & Todd, M. D. (2006). “Sensor network paradigms for structural health monitoring.” Structural Control and Health Monitoring, 13(1), 210-225.

Gao, Y., Spencer, B. F., & Ruiz-Sandoval, M. (2006). “Distributed computing strategy for structural health monitoring.” Structural Control and Health Monitoring, 13(1), 488-507.

Giraldo, D. F., Song, W., Dyke, S. J., & Caicedo, J. M. (2009). “Modal identification through ambient vibration: comparative study.” Journal of Engineering Mechanics, 135(8), 759-770.

Godfrey, K., McCormack, A., & Flower, J. (1994). “Applying system identification using commercially available software and hardware.” Control Engineering Practice, 3, 1081-1086.

Guo, H. Y., Zhang, L., Zhang, L. L., & Zhou, J. X. (2004). “Optimal placement of sensors for structural health monitoring using improved genetic algorithms.”

Smart Materials and Structures, 13(3), 528-534.

Hackmann, G., Sun, F., Castaneda, N., Lu, C., & Dyke, S. (2012). “A holistic approach to decentralized structural damage localization using wireless sensor networks.”

Computer Communications, 36(1), 29-41.

Hegde, G., & Sinha, R. (2008). “Method of modal identification of torsionally-coupled buildings using earthquake responses.” Paper presented at the Proceedings of the The 14th World Conference on Earthquake Engineering.

Holland, J. H. (1975). Adaptation in Natural and Artificial Systems. USA : University of Michigan Press

Jezequel, L., & Argoul, P. (1986). “A new integral transform for linear systems identification.” Journal of Sound and Vibration, 111(2), 261-278.

Kammer, D. C. (1991). “Sensor placement for on-orbit modal identification and correlation of large space structures.” Journal of Guidance, Control, and Dynamics, 14(2), 251-259.

Kang, J. S., Park, S.-K., Shin, S., & Lee, H. S. (2005). “Structural system identification in time domain using measured acceleration.” Journal of Sound and Vibration, 288(1-2), 215-234.

Kasper, K., Mathelin, L., & Abou-Kandil, H. (2015). “A machine learning approach for constrained sensor placement.” Paper presented at the 2015 American Control Conference (ACC).

Kaya, Y., Kocakaplan, S., & Şafak, E. (2015). “System identification and model calibration of multi-story buildings through estimation of vibration time histories at non-instrumented floors.” Bulletin of Earthquake Engineering, 13(11), 3301-3323.

Koh, C. G., Hong, B., & Liaw, C. Y. (2003). “Substructural and progressive structural identification methods.” Engineering Structures, 25(12), 1551-1563.

Hong, L. L., Huang, L.H., & Jhou, W. Y. (2009). “Identification and variation of story lateral stiffness in buildings.” Structural Control and Health Monitoring, 16(2), 200-222.

Limongelli, M. P. (2003). “Optimal location of sensors for reconstruction of seismic responses through spline function interpolation.” Earthquake Engineering &

Structural Dynamics, 32(7), 1055-1074.

Limongelli, M. P. (2004). “Modeling of unknown seismic responses of partially instrumented bridge structure.” Paper presented at the 13th world conference on earthquake engineering, Vancouver, Canada.

Liu, W., Gao, W. C., Sun, Y., & Xu, M. J. (2008). “Optimal sensor placement for spatial lattice structure based on genetic algorithms.” Journal of Sound and Vibration, 317(1-2), 175-189.

Liu, Y.-C., Loh, C.-H. and Ni, Y.-Q. (2013), “Stochastic subspace identification for output-only modal analysis: application to super high-rise tower under abnormal loading condition.” Earthquake Engineering Structure Dynamic, 42, 477-498.

Loh, C. H., & Chen, J. D. (2017). “Tracking modal parameters from building seismic response data using recursive subspace identification algorithm.” Earthquake Engineering & Structural Dynamics, 46(13), 2163-2183.

Loh, C. H., J. H. Weng, C. H. Chen, and K. C. Lu. (2013). “System Identification of Mid Story Isolation Building Using `Both Ambient and Earthquake Response Data.” Structural Control and Health Monitoring 20 (2): 139-155.

Loh, C. H., & Tou, I. C. (1995). “A system identification approach to the detection of changes in both linear and non‐linear structural parameters.” Earthquake Engineering & Structural Dynamics, 24(1), 85-97.

López‐Almansa, F., Barbat, A., & Rodellar, J. (1988). “SSP algorithm for linear and non‐linear dynamic response simulation.” International Journal for Numerical Methods in Engineering, 26(12), 2687-2706.

Meo, M., & Zumpano, G. (2005). “On the optimal sensor placement techniques for a

Minami, Y., Yoshitomi, S., & Takewaki, I. (2013). “System identification of super high-rise buildings using limited vibration data during the 2011 Tohoku (Japan) earthquake.” Structural Control and Health Monitoring, 20(11), 1317-1338.

Papadimitriou, C. (2004). “Optimal sensor placement methodology for parametric identification of structural systems.” Journal of Sound and Vibration, 278(4-5), 923-947.

Papadopoulos, M., & Garcia, E. (1998). “Sensor Placement Methodologies for Dynamic Testing.” AIAA Journal, 36(2), 256-263.

Park, S., Ahmad, S., Yun, C. B., & Roh, Y. (2006). “Multiple Crack Detection of Concrete Structures Using Impedance-based Structural Health Monitoring Techniques.” Experimental Mechanics, 46(5), 609-618.

Peeters, B., & De Roeck, G. (1999). “Reference-based stochastic subspace identification for output-only modal analysis.” Mechanical Systems and Signal Processing, 13(6), 855-878.

Peeters, B. (2000), System Identification and Damage Detection in Civil Engineering, Katholieke Universiteit Leuven, Leuven.

Pintelon, R., & Schoukens, J. (2012). System Identification: a Frequency Domain Approach. NewYork, NY: John Wiley & Sons.

Rama Mohan Rao, A., Lakshmi, K., & Krishnakumar, S. (2014). “A Generalized Optimal Sensor Placement Technique for Structural Health Monitoring and System Identification.” Procedia Engineering, 86, 529-538.

Rao, S. S. (2019). Engineering Optimization: Theory and Practice. NewYork, NY: John Wiley & Sons.

Reynders, E., & Roeck, G. D. (2008). “Reference-based combined deterministic–

stochastic subspace identification for experimental and operational modal analysis.” Mechanical Systems and Signal Processing, 22(3), 617-637.

Richards, J. A., & Richards, J. A. (1999). Remote Sensing Digital Image Analysis. Berlin, Germany: springer.

Shin R., Okada Y., Yamamoto K. (2022) “Application of C-LSTM Networks to Automatic Labelling of Vehicle Dynamic Response Data for Bridges.” Sensors, 22, 3486.

Shin R., Okada Y. and Yamamoto K. (2021) “Field Experiments and Predicting using C-LSTM Networks of Bridge Position Estimation.”, Proceeding of World Congress on Engineering 2021, July 7-9, London, U.K., pp.351-355.

Şafak, E. (1991). “Identification of linear structures using discrete-time filters.” Journal of Structural Engineering, 117(10), 3064-3085.

Serhat Erdogan, Y., Necati Catbas, F., & Gundes Bakir, P. (2014). “Structural identification (St-Id) using finite element models for optimum sensor configuration and uncertainty quantification.” Finite Elements in Analysis and Design, 81, 1-13.

Soyoz, S., Taciroglu, E., Orakcal, K., Nigbor, R., Skolnik, D., Lus, H., & Safak, E.

(2013). “Ambient and Forced Vibration Testing of a Reinforced Concrete Building before and after Its Seismic Retrofitting.” Journal of Structural Engineering, 139(10), 1741-1752.

Su, W.-C., & Huang, C.-S. (2017). “Identification of structural stiffness parameters via wavelet packet from seismic response.” Procedia Engineering, 199, 1032-1037.

Ta, M.-N., Lardies, J., & Marc, B. (2006). “Natural frequencies and modal damping ratios identification of civil structures from ambient vibration data.” Shock and Vibration, 13(4, 5), 429-444.

Tan, R., & Cheng, W. (1993). “System identification of a non-classically damped linear system.” Computers & Structures, 46(1), 67-75.

Tomizuka, M., Liu, Y.-C., & Loh, C.-H. (2011). “Stochastic subspace identification for output-only modal analysis: accuracy and sensitivity on modal parameter estimation.” Paper presented at the Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2011.

Tomizuka, M., Lu, K.-C., Loh, C.-H., & Weng, J. H. (2010). “Development of smart sensing system for structural health monitoring.” Paper presented at the Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2010.

Udwadia, F. E. (1994). “Methodology for optimum sensor locations for parameter identification in dynamic systems.” Journal of Engineering Mechanics, 120(2), 368-390.

Van Overschee, P., & De Moor, B. (1996). Subspace Identification for Linear Systems:

Theory—Implementation—Applications. Berlin/Heidelberg, Germany:

Springer Science & Business Media.

Welch, P. (1967). “The use of fast Fourier transform for the estimation of power spectra:

a method based on time averaging over short, modified periodograms.” IEEE Transactions on audio and electroacoustics, 15(2), 70-73.

Worden, K., Cross, E. J., Dervilis, N., Papatheou, E., & Antoniadou, I. (2015).

“Structural health monitoring: from structures to systems-of-systems.” IFAC-papersonline, 48(21), 1-17.

Xiao, H., Bruhns, O. T., Waller, H., & Meyers, A. (2001). “An Input/Output-Based Procedure for Fully Evaluating and Monitoring Dynamic Properties of Structural Systems Via a Subspace Identification Method.” Journal of Sound and Vibration, 246(4), 601-623.

Yang, J. N., Lei, Y., Pan, S., & Huang, N. (2003a). “System identification of linear structures based on Hilbert-Huang spectral analysis. Part 1: normal modes.”

Earthquake Engineering & Structural Dynamics, 32(9), 1443-1467.

Yang, J. N., Lei, Y., Pan, S., & Huang, N. (2003b). “System identification of linear structures based on Hilbert-Huang spectral analysis. Part 2: Complex modes.”

Earthquake Engineering & Structural Dynamics, 32(10), 1533-1554.

Health Monitoring of Civil Infrastructures.” International Journal of Distributed Sensor Networks, 8(8).

Yi, T.-H., Li, H.-N., & Gu, M. (2011a). “Optimal Sensor Placement for Health Monitoring of High-Rise Structure Based on Genetic Algorithm.” Mathematical Problems in Engineering, 2011, 1-12.

Yi, T.-H., Li, H.-N., & Gu, M. (2011b). “Optimal sensor placement for structural health monitoring based on multiple optimization strategies.” The Structural Design of Tall and Special Buildings, 20(7), 881-900.

Yu, D.-J., & Ren, W.-X. (2005). “EMD-based stochastic subspace identification of structures from operational vibration measurements.” Engineering Structures, 27(12), 1741-1751.

Yuan, P., Wu, Z., & Ma, X. (1998). “Estimated mass and stiffness matrices of shear building from modal test data.” Earthquake Engineering & Structural Dynamics, 27(5), 415-421.

Yuen, K.-V., & Kuok, S.-C. (2010). “Ambient interference in long-term monitoring of buildings.” Engineering Structures, 32(8), 2379-2386.

Yun, C.-B., & Shinozuka, M. (2007). “Identification of Nonlinear Structural Dynamic Systems.” Journal of Structural Mechanics, 8(2), 187-203.

Zhu, S., Zhang, X.-H., Xu, Y.-L., & Zhan, S. (2013). “Multi-type sensor placement for multi-scale response reconstruction.” Advances in Structural Engineering, 16(10), 1779-1797.

李宗憲(2016),「反應量測為主之結構動態特性識別與損傷檢驗」,國立臺灣大 學土木工程學研究所碩士論文,台北市。

李育謙(2011),「濾波技巧於橋梁頻率間接量測法之應用」,國立臺灣大學土木 工程學研究所碩士論文,台北市。

林珮涓(2014),「應用子空間識別法於長期結構物之地震反應解析」,國立臺灣 大學土木工程學研究所碩士論文,台北市。

林智勇(2004),「利用微振實驗資料識別橋梁及建築物之動力參數」,國立臺灣 大學土木工程學研究所碩士論文,台北市。

唐嘉明(2010),「隨機子空間識別方法在結構損壞預警之應用」,國立臺灣大學 土木工程學研究所碩士論文,台北市。

翁健煌(2010),「子空間識別法於系統識別及結構損壞診斷之應用」,國立臺灣 大學土木工程學研究所博士論文,台北市。

馬俊強 (1979),「樓房微動之自然頻率」,國立台灣大學土木工程學研究所碩士論 文碩士論文,台北市。

許維廷(2015),「自動型操作模態分析應用於隨機子空間識別法」,國立臺灣大 學土木工程學研究所碩士論文,台北市。