Bridge Health Monitoring And Operational Modal Analysis:Thoery,Application And Implementation

As an important part of transportation civil engineering, the operational safety of bridge structures is of great meaning. With the development of science and technology, the bridges are heading torward the directions of "long span","new material" and "new structure system", which also brings new chanllenges to the design, construction and operational management of bridges. The already happened bridge failures always remind us the importance of operational safety of civil structures. Under this background, the vibration-based structural health monitoring (SHM) becomes a continuing research topic of recent years. The quick development of industrial manufactory and instrumentation greatly improved the precision of sensors, making them not be a barrier of SHM anymore, while the biggest problem of damage detection in SHM is the transformation from theoretical to application. This dissertation mainly focuses on the signal processing and operational modal analyis in bridge SHM and the related theory, application and implementation are investigated in following aspects:1. The state-of-the-art of bridge SHM is summarized based on the existing literatures. The signal processing methods for bridge SHM are studied. The preprocessing methods, stationary spectrum analysis based on Fast Fourier Transform (FFT) and time-frequency analysis are introduced respectively. The Hilbert-Huang Transform (HHT) is especially introduced for the analysis of non-stationary bridge dynamic test signals. Through mathematical simulation and test signal analysis, it is proved that HHT has advantages in dealing with non-stationary and nonlinear signals. Also, the existing problems of HHT are pointed out.2. The common used methods for modal parameter identification from ambient vibration test are studied. The stochastic subspace identification (SSI) is systematically investigated following the sequence of "structure stochastic state-space model","system matrices identification","modal parameter identification", and "uncertainty analysis". A weighting judge method is proposed for determining model order in SSI. For the problem of evaluating the accuracy of identified modal parameters, an uncertainty calculation method based on sensitive analysis is introduced. A system modal parameter uncertainty quantification procedure is established. The confidence intervals of modal parameters are constructed. Through a simulation example of a two degree of freedom system, the effectiveness and robustness of SSI and the proposed methods are illustrated.3. The effects of initial conditions in operational modal analysis (OMA) are considered for the first time. One biggest problem of OMA, which is the high bending and torsion modes are difficult to identify from output-only data because the frequency content of ambient excitation is usually narrow-banded, is solved. Firstly, the accuracy of output correlation sequence by considering large-amplitude initial conditions is studied. Secondly, the influences of sampling time, initial conditions and damping ratios and many other parameters on the accuracy of OMA are analyzed through a simulation example of a single degree of freedom system based on Monte Carlo Analysis. Finally, a full scale application is presented where the modal parameters of a high speed railway bridge are determined from output-only data. It is found that some additional high bending and torsion modes can be identified with good accuracy when considering initial conditions.4. The application of empirical mode decomposition (EMD) in modal parameter identification is studied. Firstly, a modal analysis method based on EMD and random decrement technique (RDT) is introduced. Secondly, in order to deal with the problem of mode mixing of EMD and spurious modes of SSI, a bandwidth restricted EMD based SSI method is proposed for OMA. The test dynamic signals are first decomposed into a series of intrinsic mode functions (IMFs), each of which represents only one frequency component, and then SSI is performed on IMFs to extract modal parameters. The spurious modes in stabilization diagram are greatly restricted. Through the OMA of Songtoujiang railway bridge, the proposed method is proved to be very effective.5. The bridge SHM software, HBHM1.0is developed based on Visual studio2010. The overall design and each function mode of HBHM are introduced. The data construction and database are also introduced. A simulated data acquisition system is proposed to the early stage development of the software and also for the debugging. This paper mainly focuses on the implementation of the function modes of signal processing and modal parameter identification. For the completeness of the theory, the function mode of the damage detection and multi-level structure condition assessment are also introduced. As HBHM considered different data interface, it can serve for different bridge SHM projects. At last, the running of the HBHM is fulfilled by the dynamic test of Yichang Yangtze river bridge.Finally, the main research contents of the thesis and the basic conclusions are summarized. The outlook for future research is also made.