Study On Modal Parameter Identification And Damage Recognition Methods For Bridge Structures

Long-span bridges are important part of national infrastructures. During the period of bridge's service life, different degree levels of damages will occur. Therefore study on techniques for health monitoring of bridges and build a Predicting, warning and timely maintaining system based on identifying the abnormal change of structural dynamic characteristic parameters and inspecting the hidden trouble of structural damages are essential and has great significance to ensure structural safety, prolong structural service life and avoid the occurrence of disastrous accidents.The parameter identification and the damage recognition are one of health monitoring system's core technologies and theoretical Foundation. The system recognition technology of big-scale Engineering structures is still in the development phase and need further discussing and consummating because of many uncertain factors as follows: huge volume quality, complex boundary condition, bad environmental factor, difficulty of drive signal survey, large quantity of testing data and low Signal-To-Noise Ratio, et al. At present, research in this domain needs to be further strengthened. Existing methods of parameter identification and damage recognition are insufficient in precision, efficiency, robust and economical performance index. They have many difficulties need to overcome in the actual project application: such as slow convergence rate in solving complicated structure, bad noise immunity, low computational accuracy by using low order mode or incomplete survey information et al. New theory and method needs urgently to solve online monitoring parameters identification and damage recognition questions of large-scale civil engineering structures.This dissertation starts from the key problems of further development of the health monitoring system for large bridges. Computation intelligent methods and modern signal processing technologies such as PSO, SVD, WT, and Power Spectrum Analysis are applied synthetically and systematically thorough research is carried out in parameter identification and damage recognition domain. The main research results and innovations are as follows:1. Firstly, the theory significance, the application background, the present development and research results have obtained of structural modal parameter identification, physical parameter identification and damage recognition methods are commented in detail. Main Insufficient and disadvantages of several recognition methods be Applied widely in health monitoring technology are analyzed. Then the studying contents and work achievement are introduced.2. A new method which can identify the structural modal parameters exactly based on Singular Value Decomposition and Wavelet Transform is put forward. The wavelet transform and the SVD filter are unified. And the MATLAB software is using in the value simulation signal processing of a three-degree of freedom structure. The results show that the method based on the SVD and WT has overcome the insufficiency of the sole wavelet method. It can distinguish the modal information in the signal's time-frequency diagram obviously, extract the Wavelet ridge of the structure conveniently and exactly. And can obtain a high recognition precision of the frequency and the damping ratio by synthetic judgment according to the information of many test sensors.3. In view of the modal parameter identification when only has the output signals of the system under ambient excitations has difficulty, a new method of structural modal parameters identification based on singular Value decomposition of the power spectrum is put forward. The response power spectral density matrix which can obtained through the survey is replaced the frequency response function matrix. The eigenfunction matrix of the system is separated through the singular value decomposition to the power spectral density function. Then the eigenvalue and the eigenvector of the eigenmatrix were solved to realize the system's modal parameter identification. This method is used in the modal parameter identification of a cable stayed bridge under ambient excitations, and the identification frequency is compared with the finite element computation frequency. The results indicated that this method overcome the subjectivity in modal selection of frequency domain pick-peaking method, choose eigenfrequency and identify close modal accurately and objectively. With the advantages of practical, processing simply and quickly, It can be applied widely in actual engineering projects.4. A method of structural modal parameters identification based on the finite element time-history analysis is put forward. Take a single tower cable-stayed bridge as the project object, using the ANSYS software, the finite element modal analysis and the non-linear time-history analysis has been carried on by different combinatorial seismic input model. The structural modal parameters be distinguished through processing the node acceleration time-history response data is close with the computation value of the finite element modal analysis in the low frequency band, the error of the high frequency band does not surpass 6%, the two results fit well. It may be further shown that the method proposed can solve modal parameter recognition questions under the earthquake drive effectively.5. A new structural physics parameter recognition method based on Particle Swarm Optimization (PSO) algorithm is proposed. The rigidity parameter recognition in different situations (without noise, with 0.1% noise, with 0.3% noise, with insufficient survey information, and with incomplete modal frequency et al.) has simulated separately using a three-tiers Frame value simulation model. The simulation result has proved that the improved PSO algorithm with stochastic inertia weight proposed in this dissertation can distinguish the unknown parameters of structures accurately. It overcomes the precocious phenomenon of primitive PSO algorithm. It has quicker computation convergence rate and better stability, and has more superiority in solving parameters recognition with insufficient survey information and incomplete modal frequency especially.6. A structural damage recognition method based on SVD and proved PSO algorithm is proposed. The WT and the SVD filter are unified to simulate the damage of a simple beam numerical model. And the improved PSO algorithm is used to distinguish the damage parameters under many kinds of operating mode. The findings indicated: The odd and break points of damage signals are amplified through singular value decomposition of the wavelet coefficient matrix, the position and the extent of structural damage can be distinguished precisely. The improved PSO algorithm may distinguish the damage position accurately of structures under the applied loads. It can obtained higher precision of the sensitive parameters of the damage, quicker convergence rate and more stable recognition result. So this method has validity and feasibility in engineering application.