Study Of Dynanic Fingerprint Methodology In Damage Identification Of Bridge Structures

In recent decades, the development of structural damage identification approaches has been accelerating in the fields of civil and aerospace structures. But most of the approaches faced with a number of practical challenges when applied to large structures. There are many problems required to be solved. Because the damage identification based on dynamic test data has latent virtues of long-range and on-line, the dynamical damage identification attracts great attention. In the first content of this thesis, the state-of-art of structural damage identification is depicted. And then the foundational issues of dynamic fingerprints are researched systemically. The main research work is summarized as follows:1. Dynamic fingerprints in the field of damage identification are generalized and classified. They are grouped into four categories: transfer property dynamic fingerprints, complex function dynamic fingerprints, transfer curvature dynamic fingerprints, and character parameter dynamic fingerprints. The computation methods and applicability of dynamic fingerprints are summarized systemically.2. The anti-jamming capability of dynamic fingerprints is researched. At first the noise source of mode parameters is analyzed, and the idealization noise expressions are brought forward. On the basis of probability theory, the noise expressions of dynamic fingerprints are deduced. The damage sensitiveness of dynamic fingerprints is researched based on system sensitiveness theory. In order to provide the definite quantity index for feature selection, the comprehensive performance evaluation criteria for anti-jamming capability of dynamic fingerprints is defined.3. According to feature selection and feature extraction technology in the filed of pattern recognition, the foundation feature storage is transformed with the proper means into the optimization feature storage. And the severability of the optimization feature storage will be improved. The pertinence analysis, genetic algorithm, principal component analysis, fisher discriminant analysis and three spectra analysis technology are researched for feature selection and feature extraction. And the optimization strategies of the foundation feature storage are advanced and provide the effective implementation for the practical application. 4. The structural damage location and damage extent are identified based on pattern classification. Near neighbor method, discriminant analysis method, artificial neural networks (Back-Propogation neural networks, Radial Basis Function neural networks) are researched, and their advantages and disadvantages are analyzed.5. The multistage damage identification method is an effective ways for complex structures, and sub-area's partition is a foundational work. According to fuzzy relation clustering and fuzzy C means clustering, the soft sub-area's partition method is advanced based on the optimization feature storage. It is corresponded with recombining of the optimization feature storage. This method optimizes dynamic fingerprints from feature and pattern, and reduces the difficulty and heightens the precision of structural damage identification.6. The plan of program design for structural damage identification of continuous girder bridge is researched. The main content includes building of the foundation feature storage, sensitiveness analysis, optimization of the feature storage, design of classification methods and so on. The corresponding software system is developed based on MATLAB. Finally, the correctness and feasibility of the presented methodology are demonstrated by a three spans continuous box-girder bridge.