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  1. NTU Theses and Dissertations Repository
  2. 工學院
  3. 工程科學及海洋工程學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/41141
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor柯文俊
dc.contributor.authorTsung-Yu Hsiehen
dc.contributor.author謝宗佑zh_TW
dc.date.accessioned2021-06-14T17:19:38Z-
dc.date.available2010-07-30
dc.date.copyright2008-07-30
dc.date.issued2008
dc.date.submitted2008-07-24
dc.identifier.citation[1] Paul S. Addison, 'The Illustrated Wavelet Transform Handbook', Institute of Physics, 2002.
[2] S. Mallat, 'A Wavelet Tour in Signal Processing', Academic Press, San Diego, 1998.
[3] Jaideva C. Goswami and Andrew K. Chan, 'Fundamentals of Wavelets: Theory, Algorithms, and Applications', John Wiley & Sons, Inc., 1999
[4] M. Ruzzene, A. Fasana, L. Garibaldi, B. Piombo, 'Natural Frequencies and Dampings Identification Using Wavelet Transform:Application to Real Data', Mechanical Systems and Signal Processing, 1997, pp.207-218.
[5] W.J Staszewski, 'Identification of damping in mdof systems using time-scale decomposition', Journal of Sound and Vibration, Vol. 203, 1997, pp. 283–305
[6] S. Gouttebroze and J. Lardies, 'On using the wavelet transform in modal analysis', Mechanics Research Communications, Vol.28, 2001, pp. 561-569
[7] J. Lardies and S. Gouttebroze, 'Identification of modal parameters using the wavelet transform', International Journal of Mechanical Sciences, Vol. 44, 2002, pp. 2263-2283.
[8] J. Lardies, M,N. Ta, M.Berthillier, 'Modal parameter estimation based on the wavelet transform of output data', Archive of Applied Mechanics 73 (2004) 718-733
[9] J. Slavic, I. Simonovski, M. Boltezar, 'Damping Identification Using A Continuous Wavelet Transform: Application to Real Data, Journal of Sound and Vibration, Vol. 262, 2003, pp. 291-307
[10] M. Boltezar, J. Slavic, 'Enhancements to the continuous wavelet transform for damping identifications on short signals', Mechanical Systems and Signal Processing, Vol. 18, 2004, pp. 1065-1076
[11] T. Kijewski, A. Kareem, 'On the presence of end effects and there melioration on in wavelet-based analysis', Journal of Sound and Vibration, Vol.256, 2002, pp. 980-988
[12] A. Kareem, T. Kijewski, 'Time-frequency analysis of wind effects on structures', Journal of Wind Engineering and Industrial Aerodynamics, Vol.90, 2002, pp 1435-1452
[13] B.F. Yan, A. Miyamoto, E. Brühwiler, 'Wavelet transform-based modal parameter identification considering uncertainty', Journal of Sound and Vibration, Vol.291, 2006, pp. 285-301
[14] M. Haase, J. Widjajakusuma, 'Damage identification based on ridges and maxima lines of the wavelet transform', International Journal of Engineering Science, Vol.41, 2003, pp. 1423-1443
[15] Kaiping Yu, Jiyuan Ye, Jingxiang Zou, Bingyuan Yang, Hua Yang, ' Missile flutter experiment and data analysis using wavelet transform', Journal of Sound and Vibration, Vol.269, 2004, pp. 899-912

[16]
B. A. D. Piombo, A. Fasana, S. Marchesiello, M. Ruzzene, 'Modelling and identification of the dynamic response of a supported bridge', Mechanical Systems and Signal Processing, Vol.14, 2000, pp. 75-89
[17] Van Overschee, P. and De Moor, B., Subspace Identification for Linear Systems: Theory, Implementation and Applications, Kluwer Academic Publishers, 1996.
[18] Van Overschee, P. and De Moore, B., 'N4SID: Subspace Algorithm for the Identification of Combined Deterministic Stochastic System, Automatica, Special Issue on Statistical Signal Processing and Control, Vol. 30, No. 1, 1994, pp. 75-93.
[19] Van Overschee P. and De Moor, B., 'Subspace Algorithm for the Stochastic Identification Problem,' Automatica J. IFAC, Vol. 29, No. 3, 1993, pp. 649-660.
[20] Van Overschee P. and De Moor, B., 'A Unifying Theorem for Three Subspace System Identification Algorithms,' Special Issue on trends in System Identification,' Automatica J. IFAC, Vol. 31, No. 11, 1995, pp. 1853-1864.
[21] Swindlehurst, A., Roy, R., Ottersten, B. and Kailath, T., 'A Subspace Fitting Method for Identification of State-Space Models,' IEEE Transaction on Automatica Control, Vol. 40, No. 2, 1995, pp. 311-316.
[22] Viberg, M., 'Subspace-Based Methods for the Identification of Linear Time Invariant Systems,' Special Issue on Trends in System Identification, Automatica J. IFAC, Vol. 31, No. 12, 1995, pp. 1835-1851.
[23] Cho, Y. M. and Kailath, T., 'Fast Subspace-Based System Identification: An Instrumental Variable Approach,' Automatica J. IFAC, Vol. 31, No. 6, 1995, pp. 903-905.
[24] Chou, C. T. and Verhaegen, M., 'Subspace Algorithm for the Identification of Multivariate Dynamic Error-in-Variables Models,' Automatica J. IFAC, Vol. 33, No. 10, 1997, pp. 1857-1869.
[25] Stoica, P. and Jansson, M., 'MIMO System Identification: State-Space and Subspace Approximations versus transfer Function and Instrumental Variables,' IEEE Transaction on Signal Processing, Vol. 48, No. 11, 2000, pp. 3087-3099.
[26] Mitra, S. K., 'Digital Signal Processing ', McGraw-Hill, International edition, 2002.
[27] Simon HayKin and Barry Van Veen, 'Signal and Systems', John Wiley & Sons, Inc., International edition, 2002.
[28] 'Curve Fitting Toolbox User’s Guide', Version 1.2, The Mathworks, Inc., 2007.
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/41141-
dc.description.abstract小波轉換為一種針對訊號分析所發展的時頻分析工具,與短時間傅立葉轉換相較之下,時頻解析度可依照小波函數的伸縮進行自適應調變,因此具備優良的非平穩訊號分析能力,同時小波函數的帶通特性亦能分離訊號中各頻率成分。本文發展以小波轉換為基礎之結構系統識別法,利用結構系統之自由響應轉換後所建構出的時間-尺度平面,一一將響應所帶有之頻率成分分解於平面上,根據轉換後各模態的脊線趨勢,進而識別出結構模態參數之等效自然振頻與等效阻尼比,並以功率頻譜密度圖及時譜圖來輔助識別流程。
為了驗證小波轉換可被應用於從結構之自由響應資料中辨識出結構之等效自然振頻與等效阻尼比,本文首先以一個單自由度系統進行討論,將自由響應加入不同程度的雜訊後分為前後半段分別進行識別,並且討論小波頻寬參數對於識別結果的影響。隨後利用一個三自由度系統,檢視小波對於多自由度系統的識別能力。最後探討兩組不同的結構實驗例,分別為懸臂樑以及機車車架結構,用以檢驗小波在未知雜訊干擾以及結構特性之識別能力。本文所有數值模擬例及實驗例,同時以數值次空間運算法(N4SID)的識別結果加以比較分析探討。
zh_TW
dc.description.provenanceMade available in DSpace on 2021-06-14T17:19:38Z (GMT). No. of bitstreams: 1
ntu-97-R95525046-1.pdf: 6264751 bytes, checksum: c9ae2e5741e16e7b7b1ce4806a0f98b7 (MD5)
Previous issue date: 2008
en
dc.description.tableofcontents中文摘要 I

英文摘要 II

簡稱術語對照表 III

目錄 IV

圖目錄 VI

表目錄 XII

符號說明 XIII

第一章:緒論 1
1.1 研究目的.......................................... 1
1.2 文獻回顧.......................................... 2
1.3 論文架構.......................................... 4

第二章:時頻分析 6
2.1傅立葉分析......................................... 6
2.2短時間傅立葉分析................................... 11
2.3小波轉換........................................... 13
2.3.1小波函數......................................... 14
2.3.2連續小波轉換..................................... 20

第三章:小波應用於系統識別研究概述 25
3.1 複數形式Morlet小波................................ 25
3.2 修正型複數形式Morlet小波.......................... 27
3.3 邊界效應.......................................... 30
3.4 小波熵............................................ 31
3.5 模態參數識別流程.................................. 32

第四章:數值模擬例 38
4.1單自由度系統模擬例................................. 38
4.1.1最佳頻寬參數選擇................................. 40
4.1.2不同雜訊下小波識別法之評估能力................... 49
4.2三自由度系統....................................... 61

第五章:實際結構識別應用 80
5.1 懸臂樑............................................ 80
5.1.1懸臂樑理論分析................................... 81
5.1.2懸臂樑識別結果探討............................... 83
5.2 機車車架結構...................................... 92
5.2.1 機車車架結構識別結果探討........................ 100

第六章:結論與展望 102
6.1結論............................................... 102
6.2展望............................................... 104

參考文獻 105
dc.language.isozh-TW
dc.subject結構系統識別zh_TW
dc.subject小波轉換zh_TW
dc.subject模態參數zh_TW
dc.subjectwavelet transformen
dc.subjectmodal parametersen
dc.subjectStructural system identificationen
dc.title應用小波轉換法從結構自由響應中辨識等效自然振頻及阻尼比之研究zh_TW
dc.titleEstimating the equivalent natural frequencies and damping ratios from the free responses of structure using the wavelet transformen
dc.typeThesis
dc.date.schoolyear96-2
dc.description.degree碩士
dc.contributor.oralexamcommittee甯攸威,林君穎,薛文証
dc.subject.keyword結構系統識別,模態參數,小波轉換,zh_TW
dc.subject.keywordStructural system identification,modal parameters,wavelet transform,en
dc.relation.page106
dc.rights.note有償授權
dc.date.accepted2008-07-27
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
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