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Long Term Operational Modal Parameter Identification of Long Span Cable Stayed Bridge

摘要第7-9页
ABSTRACT第9-10页
Chapter 1 Introduction to Bridge Health Monitoring第15-22页
    1.1 Introduction第15页
    1.2 Aim of Bridge Health Monitoring(BHM)第15-16页
    1.3 Advantages of BHM第16-17页
    1.4 Thesis Motivation第17页
    1.5 Scope of Work第17-18页
    1.6 A glimpse of a certain cable stayed bridge(CCSB)第18-19页
    1.7 Thesis Organization第19-22页
Chapter 2 Literature Review第22-37页
    2.1 Data Interpretation第22-26页
        2.1.1 Exploratory Data Analysis第23-24页
        2.1.2 Outlier Analysis第24-25页
        2.1.3 Pauta Criterion第25页
        2.1.4 Auto and Cross Correlation Functions第25-26页
    2.2 Filters第26-29页
        2.2.1 FIR Filters第27-28页
        2.2.2 IIR Filters第28-29页
    2.3 Signal Processing第29-32页
        2.3.1 Background第29-30页
        2.3.2 EMD第30页
        2.3.3 EEMD第30-31页
        2.3.4 CEEMD第31页
        2.3.5 PEEMD第31-32页
    2.4 Stochastic Subspace Identification (SSI)第32-34页
    2.5 Recursive Stochastic Subspace Identification(RSSI)第34-36页
    2.6 Conclusion第36-37页
Chapter 3 Data Interpretation and Pre-Processing第37-49页
    3.1 Reliability of Acquire Data第37-45页
        3.1.1 EDA Application to CCSB第38-43页
        3.1.2 Outlier Analysis第43-44页
        3.1.3 Auto and Cross Correlation Functions第44-45页
    3.2 Application of data pre-processing第45-47页
        3.2.1 FIR filtering of CCSB第45-46页
        3.2.2 IIR filtering of CCSB第46-47页
    3.3 Conclusion第47-49页
Chapter 4 Signal Processing第49-66页
    4.1 Novel Improved Ensemble Empirical Mode Decomposition Method第49-51页
        4.1.1 Addition of White Noise第49-50页
        4.1.2 Decomposition第50-51页
    4.2 Selection and De-Noising of IMF第51-55页
        4.2.1 Cluster Analysis第52-53页
        4.2.2 Principal Component Analysis第53-54页
        4.2.3 Pareto Approach第54-55页
    4.3 Signal Processing for Real Life data of CCSB第55-65页
        4.3.1 Signal processing based on Novel Improved EEMD第55-65页
    4.4 Conclusions第65-66页
Chapter 5 Stochastic Subspace Identification第66-97页
    5.1 Mathematical Representation of state space dynamic system第66-67页
    5.2 CO-SSI第67-69页
    5.3 DATA-SSI第69-70页
    5.4 Pole Discrimination:The Stabilization Diagram第70-72页
    5.5 Simulation based on Real Life data of Bridge第72-82页
        5.5.1 Stabilization diagram for varying Block Rows based on CO-SSI第72-74页
        5.5.2 Stabilization diagram for varying Block Rows based on DATA-SSI第74-77页
        5.5.3 Stabilization diagram for varying Order based on CO-SSI第77-79页
        5.5.4 Stabilization diagram for varying Order based on DATA-SSI第79-82页
    5.6 Simulation of real life data based on data interpretation第82-89页
    5.7 Simulation of real life data based on IIR filters第89-92页
    5.8 Simulation of real life data based on IEEMD第92-96页
    5.9 Conclusions第96-97页
Chapter 6 Recursive Stochastic Subspace Identification第97-133页
    6.1 Covariance Driven Recursive Stochastic Subspace Identification(CO-RSSI)第97-98页
    6.2 Sliding Window Technique(SWT)第98-99页
    6.3 Extended Instrumental Variable Projection Approximation Subspace Tracking第99-100页
    6.4 Implementation of CO-RSSI第100-102页
    6.5 Simulation of Real life data for CO-RSSI based on SWT第102-117页
        6.5.1 Determination of user defined parameters for continuous ldentification第103-110页
        6.5.2 Continuous modal parameters idetification for real life data based on CO-RSSI第110-117页
    6.6 Data Interpretation and Continuous identification for real life data第117-124页
    6.7 IEEMD and Continuous modal parameter identification for real life data第124-131页
    6.8 Conclusions第131-133页
Chapter 7 Conclusions and Recommendations第133-139页
    7.1 Conclusions第133-137页
    7.2 Recommendations第137-139页
Acknowledgement第139-141页
References第141-150页
List of Publications第150-153页
Research Fundings第153-154页
Appendix A Figures for Data Interpretation in Chapter 3第154-200页
    Data Interpretation form 2~(nd) to 12~(th) month第154-200页
Appendix B Figures for SSI in Chapter5第200-212页
    B-1 Stabilization Diagram on original data for remaining months第200-203页
    B-2 Stabilization Diagram after EDA for the remaining months第203-206页
    B-3 Stabilization Diagram after IIR for the remaining months第206-209页
    B-4 Stabilization Diagram after IEEMD for the remaining months第209-212页
Appendix C Figures for RSSI in Chapter6第212-229页
    C-1 Continuous Modal parameters using RSSI for untreated data for the remaining months第212-218页
    C-2 Continuous Modal parameters using RSSI based on Data Interpretation for theremaining months第218-224页
    C-3 Continuous Modal parameters using RSSI based on IEEMD for the remaining months第224-229页

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