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系統識別號 U0026-0508201914033200
論文名稱(中文) 資料型隨機子空間識別法於非定常環境振動下之模態參數識別
論文名稱(英文) Identification of Modal Parameters under Nonstationary Ambient Vibration by Data-driven Stochastic Subspace Identification
校院名稱 成功大學
系所名稱(中) 航空太空工程學系
系所名稱(英) Department of Aeronautics & Astronautics
學年度 107
學期 2
出版年 108
研究生(中文) 鍾旻軒
研究生(英文) Min-Hsuan Chung
學號 P46061160
學位類別 碩士
語文別 中文
論文頁數 104頁
口試委員 指導教授-江達雲
口試委員-楊世銘
口試委員-崔兆棠
口試委員-林章生
中文關鍵字 模態參數識別  隨機子空間識別法  非定常  穩態圖 
英文關鍵字 Identification of Modal Parameters  Stochastic Subspace identification  Nonstationary  Stabilization Diagram 
學科別分類
中文摘要 在環境振動之模態分析中,由於環境激勵的隨機性,前人往往會將激勵假設為定常白訊,然而實際環境振動大部分為非定常訊號,即其訊號統計值會隨時間改變。吾人利用時域法之資料型隨機子空間識別法探討非定常環境振動問題,由於此法基礎建立在狀態空間模型上,其為一定常時間序列模型。為了研究非定常環境振動之參數識別,吾人利用前人所提之曲線擬合法,將輸出響應轉為近似定常訊號之響應,並加以改良使之適用性更廣,以利對非定常環境振動進行模態參數識別。資料型隨機子空間識別法是利用奇異值分解判別系統階數後再進一步計算模態參數。但針對受非定常地震訊號激勵之系統識別時,奇異值分布無明顯跳躍點,於是本文引入穩態圖協助判斷系統階數並訂定準則及提取參數之流程,成功提取模態參數。
英文摘要 In most modal analysis of ambient vibrations, it is usually assumed that excitation is a stationary white noise because of the randomness of ambient excitation. However, most of the realistic ambient vibrations are nonstationary signals that statistics change over time. In this thesis, Data-driven Stochastic Subspace Identification (SSI-Data) method is employed to study the nonstationary ambient vibration problems. This identification method is based on the state subspace model which is a stationary time series model. In order to identify nonstationary vibrations, this thesis improves the curve fitting method proposed by previous studies, which convert the output responses to the approximate stationary responses. In the SSI-Data method, the order of a system is determined by singular value decomposition and the modal parameters are then calculated. However, for the identification of realistic nonstationary vibrations, there is no obvious jump point in the singular value decomposition diagram. Therefore, this thesis adopts stabilization diagram to determine the orders of the system, and then formulates the criterions and procedures to extract the modal parameters.
論文目次 摘要 I
目錄 VI
第一章 緒論 1
1-1 前言 1
1-2 模態分析與系統識別 2
1-3 文獻回顧 4
1-3-1 模態參數識別 4
1-3-2 時域法 5
1-3-3 隨機子空間識別法 7
1-4 研究動機與目的 8
1-5 本文架構 10
第二章 環境振動之基礎理論 12
2-1 引言 12
2-2 隨機過程及隨機振動 12
2-2-1 定常與非定常過程 13
2-2-2 全態過程 16
2-2-3 隨機外力過程的模擬 16
2-3 確定性動力分析 20
2-3-1 結構系統之自由振動分析 20
2-3-2 結構系統之單位脈衝響應分析 22
2-4 受定常外力之振動分析 23
2-5 受非定常外力之振動分析 25
第三章 時域法模態參數識別 27
3-1 引言 27
3-2 資料型隨機子空間識別法 28
3-2-1 狀態空間模型 28
3-2-2 數據矩陣 32
3-2-3 正交投影 34
3-2-4 奇異值分解 36
3-2-5 求解模態參數 37
3-3 模態參數提取 39
3-3-1 穩態圖 40
3-3-2 模態參數之篩選及提取 41
第四章 數值模擬 43
4-1 曲線擬合改良 43
4-2 受非定常乘法模型激勵之系統模態參數識別 44
4-3 受美濃大地震實測訊號激勵之系統模態參數識別 50
4-4 受九二一大地震實測訊號激勵之系統模態參數識別 54
第五章 結論 59
參考文獻 62
參考文獻 [1] Ewins, D. J., Modal Testing: Theory and Practice, Research Studies Press, 1984.
[2] Eykhoff, P., System Identification: Parameter and State Estimation, London, England: Wiley-Interscience, 1974.
[3] Den Hartog, J. P., Mechanical Vibration, New York, U.S.A: McGraw-Hill, 1962.
[4] Ibrahim, S. R., and Pappa, R. S., “Large Survey Testing Using the Ibrahim Time Domain (ITD) Model Identification Algorithm,” Journal of Spacecraft and Rockets, Vol. 19, pp. 459-465, 1982.
[5] Ibrahim, S. R. and Mikulcik, E. C., “A Method for the Direct Identification of Vibration Parameters from Free Response,” Shock and Vibration Bulletin, Vol. 47, Part. 4, pp. 183-198, 1977.
[6] Ibrahim, S. R., Brincker, R. and Asmussen, J. C., “Modal Parameter Identification from Response of General Unknown Random Inputs,” Proceedings of 14th International Modal Analysis Conference, pp. 446-452, 1995.
[7] Juang, J. N. and Pappa, R. S., “An Eigensystem Realization Algorithm for Modal Parameter Identification and Modal Reduction,” Journal of Guidance and Control Dynamics AIAA, Vol.8, No. 5, pp. 620-627, 1985.
[8] Juang, J. N. and Pappa, R. S., “Effects of Noise on Modal Parameter Identification by the Eigensystem Realization Algorithm,” Journal of Guidance and Control Dynamics AIAA, Vol. 9, No. 3, pp. 294-303, 1986.
[9] Juang, J. N., Cooper, J. E. and Wright, J. R., “An Eigensystem Realization Algorithm using Data Correlations (ERA/DC) for Modal Parameter Identification,” Control Theory and Advanced Technology, Vol. 4, No. 1, pp. 5-14, 1988.
[10] Carne, T. G., Lauffer, J. P. and James, G. H., “The Natural Excitation Technique for Modal Parameter Extraction from Operating Wind Turbines,” SAND92-1666.UC-261, Sandia National Laboratories, 1993.
[11] Carne, T. G., Lauffer, J. P., Gomez, A. J. and Benjannet, H., “Modal Testing an Immense Flexible Structure Using Natural and Artificial Excitation,” The International Journal of Analytical and Experimental Modal Analysis, The Society of Experimental Mechanics, pp. 117-122, 1988.
[12] Chiang, D. Y. and Lin, C. S., “Identification of Modal Parameters from Nonstationary Ambient Vibration Data Using Correlation Technique,” AIAA Journal, Vol. 46, No. 11, pp. 2752-2759, 2008.
[13] 蘇芳禾,特徵系統實現法於定常環境振動之模態參數識別研究,碩士論文,國立成功大學航空太空工程學研究所, 2006.
[14] Van, O. P., and De, M. B., “Subspace Algorithm for the Stochastic Identification Problem.” In Proceedings of the 30th IEEE Conference on Decision and Control, pp. 1321-1326, 1991.
[15] Peeters, B., and Roeck, G.D., “Reference-based Stochastic Subspace Identification for Output-only Modal Analysis,” Mechanical System Signal Processing, Vol. 13, pp. 855-878. 1999.
[16] Kompalka, A. S., Reese, S., and Bruhns, O. T., “Experimental Investigation of Damage Evolution by Data-Driven Stochastic Subspace Identification and Iterative Finite Element Model Updating,” Archive of Applied Mechanics, Vol. 77, pp. 559-573, 2007.
[17] Mevel, L., Basseville, M., and Goursat, M., “Stochastic Subspace-Based Structural Identification and Damage Detection Application to the Steel-Quake Benchmark,” Mechanical System Signal Processing, Vol.17, pp. 91-101, 2003.
[18] Yu, D. J., and Ren, W. X., “EMD-Based Stochastic Subspace Identification of Structures from Operational Vibration Measurements,” Engineering Structure, Vol. 27, pp. 1741-175, 2005.
[19] 王建智,資料型隨機子空間法於系統之模態參數識別研究, 碩士論文,國立成功大學航空太空工程學研究所, 2017.
[20] 張竣發,資料型隨機子空間識別法於環境振動下之系統模態參數識別,碩士論文,國立成功大學航空太空工程學研究所, 2018.
[21] 高紫光 , 路磊, “非平穩時間序列的狀態空間建模與預測”, 系統工程, 第16卷第3期, 1998.
[22] Luis, E. A., Luis, D. A. V., and Edilson, D. T., “Diagonal Time Dependent State Space Models for Modal Decomposition of Non-Sationary Signals,” Mechanical System Signal Processing, Vol.147, pp. 208-223, 2018.
[23] Bendat, J. S. and Piersol, A. G., Random Data: Analysis and Measurement Procedures, 4th edition, New York: Wiley, 2010
[24] 林章生,非定常環境振動之系統模態參數識別,博士論文,國立成功大學航空太空工程學研究所, 2011.
[25] Peeters, B. and Roeck, G.D., “Stochastic System Identification for Operational Modal Analysis: A Review,” Journal of Dynamic Systems, Measurement, and Control, Vol. 123, pp. 659-667, 2001.
[26] Priori, C., Angelis, D., and Betti, R., “On the Selection of User-Defined Parameters in Data-Driven Stochastic Subspace Identification,” Mechanical System Signal Processing, Vol.100, pp. 501-523, 2018
[27] Nicholson, W. K., Linear Algebra with Applications, 6th edition, New York, U.S.A: McGraw-Hill, 2009.
[28] 陳豹,現代控制理論,臺北市:科技圖書股份有限公司,1992.
[29] Chang, J., Zhang, Q. W., and Sun, L. M., “Identified Method of Arch Bridge Modal Parameters Based on Stochastic Subspace Combined with Stabilization Diagram, ”Journal of Architecture and Civil Engineering, Vol.24, No.1, 2007.
[30] Bathe, K. J., Finite Element Procedures in Engineering Analysis, Prentic-Hall, Chap.9, 1982.
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