請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/48256完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 柯文俊(Wen-Jiunn Ko) | |
| dc.contributor.author | Jia-Yu Chen | en |
| dc.contributor.author | 陳佳郁 | zh_TW |
| dc.date.accessioned | 2021-06-15T06:50:22Z | - |
| dc.date.available | 2014-02-20 | |
| dc.date.copyright | 2011-02-20 | |
| dc.date.issued | 2011 | |
| dc.date.submitted | 2011-02-17 | |
| dc.identifier.citation | [1] Ibrahim, S. R. and Mikulcik, E. C., “A Method for the Direst Identification of Vibration Parameters from Free Response,” Shock and Vibration Bulletin, Vol. 47, 1977, Pt. 4, pp. 183-198.
[2] Ibrahim, S. R. and Mikulcik, E. C., “The Experimental Determination of Vibration Parameters from Free Response,” Shock and Vibration Bulletin, Vol. 46, 1976, Pt. 5, pp. 183-198. [3] Code, H. A. Jr., “Methods and Apparatus for Measuring the Damping Characteristics of a Structure by the Random Decrement Technique,” United States Patent, No.3, 622, 069, 1971. [4] Vandiver, J. R., Dunwoody, R. B., Campbell and Cook, M. F., “A Mathematical Basis for the Random Decrement Vibration Signature Analysis Technique,” Journal of Mech. Des., Vol. 104, 1982, pp. 307-313. [5] Ibrahim, S.R., “Modal Confidence Factor in Vibration Testing,” Journal of Spacecraft and Rockets, Vol. 15, Spet-Oct. 1978, pp. 313-316. [6] Ku, C.J., Cermak, J.E. and Chou, L.S., “Biased Modal Estimates from Random Decrement Signatures of Forced Acceleration Response,” Journal of Structural Engineering, Aug. 2007, pp. 1180-1185. [7] 曹松華,隨機遞減法於非定常環境振動模態參數識別之應用,國立成功大學航太太空工程研究所碩士論文,2004。 [8] Huang, C. S., Yang, Y. B., Lu, L. Y. and Chen, C. H. “Dynamic Testing and System Identification of a Multi-Span Highway Bridge,” Earthquake Engineering and Structural Dynamics, Vol. 28, 1999, pp. 857-878. [9] Ahmed, A.E., Mahmoud, R.H. and Marzouk, H. “Identification of The Excitation and Reaction Forces on Offshore Platforms Using the Random Decrement Technique,” Ocean Engineering, 2009, pp.521-528. [10] Tamura, Y., Zhang, L., Yoshida, A., Nakata, S., and Itoh, T., “Ambient Vibration Test and Modal Identification of Structures by FDD and 2DOF-RD Technique,” SEWC, Yokohama, Japan, 2009. [11] Pandit, S. M. and Wu, S. M., Time Series and System Analysis with Applications, John wiley, New York, 1983. [12] 洪振發、戴志豪與柯文俊,利用量測鑑定模態參數以直接法修正結構分析模型的質量與勁度矩陣。中國造船輪機工程學刊第十九卷第三期,民國八十九年,pp. 1-12。 [13] Lardies, J., “Analysis of Multivariate Autoregressive Process,” Mechanical System and Signal Processing, Vol. 10, No. 6, 1996, pp. 747-761. [14] Baillie, D. C. and Mathew, J., “A Comparison of Autoregressive Modeling Techniques for Fault Diagnosis of Rolling Element Bearing,” Mechanical System and Signal Processing, Vol. 10, No. 1, 1996, pp. 1-19. [15] Pandit, S. M. and Wu, S. M., Modal and Spectrum Analysis: Data Dependent System in State Space, John Wiley & Sons, Inc. 1991. [16] Lardies, J., “Modal Parameters Identification from Output-Only Measurements,” Mechanics Research Communications, Vol. 24, No. 5, 1997, pp. 521-528. [17] Juang, J.-N., Applied System Identification, Prentice Hall PTR, Englewood Cliffs, New Jersey 07632, 1994. [18] Ljung, L., System Identification: Theory for the User. Prentice-Hall, Englewood Cliffs, New Jersey, 1987. [19] Ko, W.J. and Hung, C.F., “Extraction of Structural System Matrices from An Identified State-Space System Using the Combined Measurements of DVA,” Accepted by Sound and Vibration, 2001. [20] Meirovitch, L., “Elements of Vibration Analysis,” McGraw-Hill book company [21] Julius, S. B. and Allan, G.P., “Random Data: Analysis and Measurement Procedures,” Second Edition. [22] Lin, Y. K., “Probabilitstic Theory of Structural Dynamics,” McGraw-Hill, New York, 1967. [23] Ibrahim, S. R., Brincker, R. and Asmussen, J. C., “Modal Parameter Identification from Responses of General Unknown Random Inputs,” Proceeding of the 14th International Model Analysis Conference, Vol. 1, 1996, pp. 446-452. [24] Bedewi, N. E., “The Mathematical Foundation of the Auto and Cross-Random Decrement Techniques and the Development of Structural Deterioration,” Ph. D Thesis, University of Maryland College Park, 1986. [25] James, G. H., Carne. T. G. and Lauffer, J. P., “The Natural Excitation Technique for Modal Parameter Extraction from Operating Wind Turbines,” SAND92-1666. UC-261, Sandia National Laboratories, 1993. [26] Larbi, N. and Lardies, J., “Experimental Modal Analysis of a Structure Excited by a Random Force,” Mechanical System and Signal Processing, Vol.14, No.2, 2000, pp.181-192. [27] Hung, C. F. and Ko, W. J., “Identification of Dynamic System from Data Compose by Combination of Their Response Compoments,” Engineering Structures, 2002, pp.1441-1450. [28] 謝宗佑,應用小波轉換法從結構自由響應中辨識等效自然頻率及阻尼比之研究,國立台灣大學工程科學及海洋工程研究所碩士論文,2008。 [29] 林罡亦,應用含外變數的非線性自我迴歸模型估算非線性系統之線性模態參數,國立台灣大學工程科學及海洋工程研究所碩士論文,2009。 [30] 徐國翔,應用描述子狀態空間系統之次空間演算法識別結構模態參數,國立台灣大學工程科學及海洋工程研究所碩士論文,2009。 | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/48256 | - |
| dc.description.abstract | 結構系統具有其獨特的特性,其輸出入資料隱含著結構特徵,因此將結構動態現象量測所得的輸出入資料,建立數學模型,並由此數學模型估算出此結構系統的特性,稱為結構系統識別。結構系統之模態參數,可藉由激勵訊號與響應訊號進行識別。而在真實世界中,結構系統受環境振動影響下,卻只能獲得其輸出響應訊號,因此如何在沒有激勵訊號的量測而直接由輸出響應訊號獲得模態參數,為本文探討之重點。
本文由漫散衰減響應與自由振動衰減訊號之數學公式的演算,發現輸出響應訊號經漫散衰減法處理後,漫散衰減訊號與自由振動衰減訊號有相似之數學形式,並用電腦模擬檢驗其正確性。接著利用自我迴歸模型估算出結構系統之自然頻率、阻尼比和模態振型。為驗證漫散衰減法為前處理輔助估算模態參數可有效應用於自由響應及漫散響應資料的識別,文中透過單自由度及三自由度具阻尼系統加入不同程度的雜訊下以測試漫散衰減法的能力。最後探討兩組實驗例,一為懸臂鋼樑試驗,另一為國家地震工程中心所進行之五層樓縮尺鋼結構受地震波衝擊之試驗。實驗資料分析結果可驗證漫散衰減法之前處理在輔助自我迴歸模型的識別能力。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2021-06-15T06:50:22Z (GMT). No. of bitstreams: 1 ntu-100-R97525053-1.pdf: 5408829 bytes, checksum: 050597c3eccd33bf28c8dd2918277929 (MD5) Previous issue date: 2011 | en |
| dc.description.tableofcontents | 中文摘要 I
英文摘要II 目錄IV 圖目錄VII 表目錄 XI 簡稱術語對照表 XIII 符號說明 XIV 第一章 導論 1 1.1 研究背景與目的 1 1.2 文獻回顧 2 1.3 論文架構 4 第二章 結構系統及訊號處理之相關理論 7 2.1 構型及運動空間運動方程式 7 2.2 連續/離散時間狀態空間轉換 10 2.3 離散時間等效狀態方程組 12 2.4 自由振動系統響應 16 2.5 漫散訊號 17 2.6 互相關函數 19 第三章 漫散衰減法之理論 25 3.1 漫散衰減法之基本原理 25 3.2 漫散衰減法之數學基礎 27 3.3 漫散衰減法訊號與自由衰減振動響應之關係 28 3.4 單自由度漫散衰減法之實現 32 3.5 多自由度漫散衰減法之實現 34 第四章 時間序列模型之結構系統識別理論 36 4.1 時間序列 36 4.2 自我迴歸模型 36 4.3 轉換至離散時間狀態空間系統 39 4.4 系統特徵根篩選 41 第五章 數值模擬例 43 5.1 單自由度系統模擬 43 5.1.1 單自由度具阻尼系統之自由振動 44 5.1.2 單自由度具阻尼含雜訊系統之自由振動 48 5.1.3 單自由度具阻尼系統之漫散振動 54 5.1.4 單自由度具阻尼含雜訊系統之漫散振動 58 5.2 三自由度系統模擬 65 5.2.1 三自由度具阻尼系統之自由振動 65 5.2.2 三自由度具阻尼在不同初始條件下之自由振動 70 5.2.3 三自由度具阻尼系統之漫散振動 74 5.2.4 三自由度具阻尼在不同初始條件下之漫散振動 79 第六章 實際結構識別 83 6.1 垂直懸臂鋼樑實驗 83 6.1.1 懸臂鋼樑理論分析 84 6.1.2 懸臂鋼樑識別與結果探討 87 6.2 國家地震工程中心之五層樓縮尺鋼架結構實驗 95 6.2.1 國家地震工程中心之五層樓縮尺鋼架結構識別與結果探討 103 第七章 結論與未來展望 112 7.1 結論 112 7.2 未來展望 113 參考文獻 115 | |
| dc.language.iso | zh-TW | |
| dc.subject | 模態參數 | zh_TW |
| dc.subject | 系統識別 | zh_TW |
| dc.subject | 漫散衰減 | zh_TW |
| dc.subject | 自我迴歸數學模型 | zh_TW |
| dc.subject | modal parameters | en |
| dc.subject | autoregressive model | en |
| dc.subject | random decrement | en |
| dc.subject | system identification | en |
| dc.title | 應用漫散衰減法與自我迴歸模型在識別結構模態參數之研究 | zh_TW |
| dc.title | Application of Random Decrement Method and Autoregressive Model for Identifying the Modal Parameters of Structures | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 99-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 程安邦,劉德源,徐培譽,薛文証 | |
| dc.subject.keyword | 系統識別,漫散衰減,自我迴歸數學模型,模態參數, | zh_TW |
| dc.subject.keyword | system identification,random decrement,autoregressive model,modal parameters, | en |
| dc.relation.page | 117 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2011-02-17 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 工程科學及海洋工程學研究所 | zh_TW |
| 顯示於系所單位: | 工程科學及海洋工程學系 | |
文件中的檔案:
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-100-1.pdf 未授權公開取用 | 5.28 MB | Adobe PDF |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。
