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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/43341完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 羅俊雄 | |
| dc.contributor.author | Chia-Hui Chen | en |
| dc.contributor.author | 諶佳慧 | zh_TW |
| dc.date.accessioned | 2021-06-15T01:50:41Z | - |
| dc.date.available | 2009-07-16 | |
| dc.date.copyright | 2009-07-16 | |
| dc.date.issued | 2009 | |
| dc.date.submitted | 2009-07-03 | |
| dc.identifier.citation | 1. A. D. Steltzner and D. C. Kammer, 'Input force estimation using an inverse structural filter,' Proc. Proceedings of the International Modal Analysis Conference - IMAC, 1999), pp. 954-960.
2. Z. R. Lu and S. S. Law, 'Force identification based on sensitivity in time domain,' Journal of Engineering Mechanics, 132:10 (2006), 1050-1056. 3. Z. R. Lu and S. S. Law, 'Identification of system parameters and input force from output only,' Mechanical Systems and Signal Processing, 21:5 (2007), 2099-2111. 4. J. J. Liu, C. K. Ma, I. C. Kung, and D. C. Lin, 'Input force estimation of a cantilever plate by using a system identification technique,' Computer Methods in Applied Mechanics and Engineering, 190:11-12 (2000), 1309-1322. 5. C. K. Ma, P. C. Tuan, J. M. Chang, and D. C. Lin, 'Adaptive weighting inverse method for the estimation of input loads,' International Journal of Systems Science, 34:3 (2003), 181-194. 6. C. K. Ma and C. C. Ho, 'An inverse method for the estimation of input forces acting on non-linear structural systems,' Journal of Sound and Vibration, 275:3-5 (2004), 953-971. 7. C. H. Loh, A. L. Wu, J. N. Yang, C. H. Chen, and T. S. Ueng, 'Input force identification using kalman filter techniques: Application to soil-pile interaction,' Proc. Proceedings of SPIE - The International Society for Optical Engineering, 2008. 8. S. Granger and L. Perotin, 'An inverse method for the identification of a distributed random excitation acting on a vibrating structure part 1: Theory,' Mechanical Systems and Signal Processing, 13:1 (1999), 53-65. 9. J. H. Lin, X. L. Guo, H. Zhi, W. P. Howson, and F. W. Williams, 'Computer simulation of structural random loading identification,' Computers and Structures, 79:4 (2001), 375-387. 10. R. Panneer Selvam and S. K. Bhattacharyya, 'Parameter identification of a compliant nonlinear SDOF system in random ocean waves by reverse MISO method,' Ocean Engineering, 28:9 (2001), 1199-1223. 11. S. Narayanan and S. C. S. Yim, 'Modeling and identification of a nonlinear SDOF moored structure, part 1 - Hydrodynamic models and algorithms,' Journal of Offshore Mechanics and Arctic Engineering, 126:2 (2004), 175-182. 12. S. C. S. Yim and S. Narayanan, 'Modeling and identification of a nonlinear SDOF moored structure, part 2 - Comparisons and sensitivity study,' Journal of Offshore Mechanics and Arctic Engineering, 126:2 (2004), 183-190. 13. M. S. Cho and K. J. Kim, 'Indirect input identification in multi-source environments by principal component analysis,' Mechanical Systems and Signal Processing, 16:5 (2002), 873-883. 14. A. K. Chopra, Dynamics of structures: theory and applications to earthquake engineering, Prentice Hall, Upper Saddle River, NJ :, 2001. 15. 黃謝恭,運用適應性卡氏過濾理論即時系統損壞識別,臺灣大學,2007. 16. M. I. Friswell and J. E. Mottershead, Finite element model updating in structural dynamics Kluwer Academic Publishers, Dordrecht, 1995. 17. A. N. Tikhonov, 'Solution of incorrectly formulated problems and the regularization method,' Soviet Math. Dokl., 4 (1963), 1035-1038. 18. J. S. Bendat and A. G. Piersol, Random data, Wiley, New York :, 2000. 19. D. C. Lay, Linear algebra and its applications, 2 ed., Addison-Wesley, Reading, Mass. :, 1996. 20. R. L. Wiegel, Earthquake engineering, Prentice-Hall, Englewood Cliffs, NJ : , 1970. 21. 翁作新、陳家漢、曾永成,'振動台砂土試體土壤液化及土壤-基樁-結構互制反應之探討(II)',國家地震工程研究中心研究計畫,計畫編號:NCREE-06097A1010。 22. 翁作新、陳家漢、彭立先、李偉誠,'大型振動台剪力盒土壤液化試驗(II)-大型砂試體之準備與振動台初期試驗',國家地震工程研究中心報告,報告編號:NCREE-03-042,2003。 23. N. Kalouptsidis, Signal Processing Systems : Theory and Design, John Wiley & sons, New York :, 1997. 24. R. W. Clough, Dynamics of structures, McGraw-Hill, New York :, 1975. 25. 辜琪媜,利用小波轉換技術於結構振動訊號之解析,臺灣大學,2005。 | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/43341 | - |
| dc.description.abstract | 本研究介紹不同之外力識別法,以藉由量測所得之系統反應評估作用於系統之外力歷時。本文推導之時域褶積識別法,假設外力由傅立葉級數組成,藉由建立系統之褶積向量,並結合Matlab之最佳化工具,以識別外力。並採用遞迴式卡氏過濾理論(RLS-KF Method)識別外力,並與時域褶積識別法進行比較。不同於前述之方法,外力參數之敏感度識別法假設外力由正弦波組成,藉由建立系統反應對外力參數之敏感度矩陣,以識別外力參數。外力參數之最佳化以Matlab之最佳化工具取代敏感度矩陣,以改善外力參數之敏感度識別法之效率。功率譜密度函數識別法則是以系統反應之交叉功率譜密度函數識別外力之交叉功率譜密度函數。由於有限的量測資料,本文介紹卡氏重建器與結合分段式立方Hermite型插值多項式之奇異值分解重建法,以重建未量測點之反應歷時,以利進行部分量測系統之外力識別。
首先,由數值模擬建立一多自由度之系統、輸入隨機外力與系統反應,以驗證外力識別法。接著,將驗證之外力識別法與反應重建法應用於振動台之土壤-樁基礎互制實驗中。對土壤-樁基礎系統施予白噪音並量測系統反應,並以系統識別技術建立樁基礎之系統矩陣。最後,以介紹之外力識別法評估土壤與樁基礎之作用力。本研究最終証明,可先由量測之反應進行系統識別後,由識別之系統與本文介紹之外力識別法間接求得作用於系統之外來刺激力。 | zh_TW |
| dc.description.abstract | In this study several input force identification methods is presented using the direct response meausrements. First, by assuming the input force as a summation of sine and cosine functions, the time domain convolution method is derived. Based on the system convolution vector and the optimization scheme are presented for identifying the input forces. Then a different input force identification approach which employs the Recursive Least Square with Kalman Filter (RLS-KF) method is used for comparison. Different to the above two proposed methods, a sensitivity method with respect to the input force parameters is also presented for identify the force parameters by estabilishing sensitivity matrix of dynamic response. Optimization with respect to the force parameters can improve the efficiency of sensitivity method is also investigated. PSD method for identifying cross power spectral density of distributed excitation force is discussed by calculating cross power spectral density of measured response. Due to the limited number of measurements on the response data, both Kalman Estimator technique and Singular Value Decomposition (SVD) incopoerated with piecewise cubic Hermite Polynomial curve fitting method are used to reconstruct the unmeasured reponses and establish the full response measurement.
The proposed input force identification methods were verified first using numerical simulation of a MDOF system subjected to limited number of input forces. Second, data from the shaking table tests of soil-pile interaction are used to idrntify the interaction forces. For this large-scale shaking table test, the ambient vibration measurements of the pile are used to estabilish the structural system matrix. Based on the proposed identification methods in this study, soil-pile force is identified. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T01:50:41Z (GMT). No. of bitstreams: 1 ntu-98-R96521218-1.pdf: 4594819 bytes, checksum: 1dfcda1c56ac13ca11608da4ce7e005f (MD5) Previous issue date: 2009 | en |
| dc.description.tableofcontents | 誌 謝 I
摘 要 II ABSTRACT III 目 錄 V 表目錄 IX 圖目錄 XI 第一章 緒論 1 1.1 研究動機 1 1.2 文獻回顧 1 1.3 本文內容 2 第二章 識別理論 4 2.1 狀態空間方程式 4 2.2 時域褶積識別法(TIME DOMAIN CONVOLUTION METHOD FOR INPUT FORCE IDENTIFICATION) 5 2.2.1 振態疊加法 5 2.2.2 動力反應 8 2.2.3 外力參數識別 10 2.2.4 流程 11 2.3 遞迴式卡氏過濾理論識別法(RLS-KF METHOD) 12 2.3.1 卡氏過濾理論 12 2.3.2 遞迴式最小平方估測法 13 2.4 外力參數之敏感度識別法 16 2.4.1 動力反應 17 2.4.2 動力反應之敏感度 17 2.4.3 外力參數識別 18 2.4.4 流程 19 2.5 外力參數之最佳化 20 2.6 功率譜密度函數識別法 21 2.6.1 外力之正交化分解 21 2.6.2 振態反應之功率譜密度函數識別 22 2.6.3 振態外力之功率譜密度函數識別 23 2.6.4 外力之功率譜密度函數識別 25 2.6.5 流程 26 2.7 部分量測之反應重建法 26 2.7.1 卡氏重建器(Kalman Estimator) 26 2.7.2 奇異值分解重建法 27 第三章 數值模擬 29 3.1 模擬之系統 29 3.2 部分量測之反應重建 31 3.2.1 卡氏重建器 31 3.2.2 奇異值分解重建法 32 3.2.3 重建法之比較 33 3.3 CASE 1 34 3.3.1 時域褶積識別法 34 3.3.2 RLS-KF識別法 36 3.3.3 外力參數之敏感度識別法 37 3.3.4 外力參數之最佳化 38 3.3.5 功率譜密度函數識別法 38 3.4 CASE 2 39 3.4.1 時域褶積識別法 40 3.4.2 RLS-KF識別法 40 3.4.3 外力參數之敏感度識別法 41 3.4.4 外力之最佳化 42 3.4.5 功率譜密度函數識別法 42 3.5 CASE 3 43 3.5.1 時域褶積識別法 43 3.5.2 RLS-KF識別法 44 3.5.3 外力參數之敏感度識別法 44 3.5.4 外力之最佳化 45 3.5.5 功率譜密度函數識別法 46 3.6 識別法之比較與討論 46 第四章 土壤-樁基礎互制實驗分析 49 4.1 土壤-樁基礎互制原理 49 4.2 實驗配置 49 4.3 系統識別 50 4.3.1 Test 1-1 51 4.3.2 Test 2 53 4.4 CASE 1之外力識別 54 4.4.1 時域褶積識別法 55 4.4.2 RLS-KF識別法 56 4.4.3 外力參數之最佳化 57 4.4.4 功率譜密度函數識別法 57 4.4.5 識別結果之比較 58 4.5 CASE 2之外力識別 62 4.5.1 奇異值分解重建法 63 4.5.2 時域褶積識別法 64 4.5.3 RLS-KF識別法 65 4.5.4 外力參數之最佳化 66 4.5.5 功率譜密度函數識別法 67 4.5.6 識別結果之比較 67 第五章 結論與未來工作 70 5.1 結論 70 5.2 未來工作 72 參考文獻 73 附錄A RLS-KF識別法之推導流程 163 A.1 卡氏過濾理論 163 A.2 遞迴式最小平方估測法 166 附錄B 小波包轉換 170 | |
| dc.language.iso | zh-TW | |
| dc.subject | 反應重建法 | zh_TW |
| dc.subject | 卡氏過濾理論 | zh_TW |
| dc.subject | 外力識別法 | zh_TW |
| dc.subject | 土壤-樁基礎互制實驗 | zh_TW |
| dc.subject | 遞迴式最小平方估測法 | zh_TW |
| dc.subject | 系統識別法 | zh_TW |
| dc.subject | soil-pile interaction | en |
| dc.subject | response reconstruction | en |
| dc.subject | Input identification | en |
| dc.subject | Kalman filter | en |
| dc.subject | recursive least-squares estimator | en |
| dc.subject | system identification | en |
| dc.title | 利用系統識別技術進行外力評估:遞迴式卡氏過濾理論與時域褶積法 | zh_TW |
| dc.title | Input Force Estimation Using System Identification Techniques: Kalman Filter with Recursive Least Square Method versus Time Domain Convolution Method | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 97-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 田堯彰,翁作新,卿建業 | |
| dc.subject.keyword | 外力識別法,系統識別法,反應重建法,卡氏過濾理論,遞迴式最小平方估測法,土壤-樁基礎互制實驗, | zh_TW |
| dc.subject.keyword | Input identification,system identification,response reconstruction,Kalman filter,recursive least-squares estimator,soil-pile interaction, | en |
| dc.relation.page | 172 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2009-07-03 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 土木工程學研究所 | zh_TW |
| 顯示於系所單位: | 土木工程學系 | |
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