Studies On Methods For Structural Parameter Identification System Based On Vibration Signal

The key issues of structural parameter identification system in health monitoring,mainly including the fields of wireless sensing technology and identification algorithms,are studied via theoretical analysis, numerical simulation and experimental research inthis thesis. The main research work and contribution are as follows.(1) The mobile wireless sensor network (MWSN) aided by the magnet-wheelclimbing robot is developed to collect vibration signal for structural parameteridentification system. The design of MWSN consists of mechanical design, hardwareand software design. The hammer impact experiment of steel portal frame is carried outin the laboratory. The difference between acceleration data collected separately fromMWSN and static sensor is small. The comparison of frame's modal parameteridentified separately from time history of acceleration data collected by MWSN andfinite element method shows that the MWSN could offer reliable, flexible and adaptivespatial resolutions for SHM that can overcome the limitation of high cost of sensors,limited power supply of current sensor networks.(2) Extended Eigensystem realization algorithm (EERA) is proposed and derivedfor structural modal parameter identification, which could be used for the measuredforced response. Any kind of time history of acceleration, velocity or displacement isavailable for EERA. The accuracy and stability of EERA are demonstrated, and it'ssuggested to use the time history of acceleration to identify higher modes of structures.The problems of mode mixing and endpoint effect in Hilbert-Huang Transform (HHT)for modal parameter identification are solved by adopting Chebyshev I type filter andremoving endpoints. And the format of mode shapes of proportional-damping-ratiostructure is achieved. The accuracy and robustness of the two proposed algorithms aredemonstrated by numerical simulation and shaking table test of frame.(3) The improved Berman-Baruch method (IBB) is proposed and derived toidentify structural physical parameters for finite element model updating. One constraintof Berman-Baruch method that the normalized modes with mass matrix are requiredcould be released with the diagonal mass matrix. The updated model via IBB is morephysical meaning and keeps the characters of band and sparse of system matrices. The structural physical parameters under3kinds of different damage scenarios are identifiedseparately by minimizing4kinds of different objective functions by genetic algorithm(GA), the comparison among those sets of identified parameters shows model updatingbased on GA is sensitive to the chosen objective functions, and it's suggested to use thecombination objective function proposed in this thesis in order to obtain the accurateand robust detection when the kind of structural damage is unknown. The DifferenceModel Updating (DMU) is presented by adding the known blocks to the structure andits characteristics are concluded that it's one kind of complete algorithm for modelupdating, the physical properties could be preserved, the computational cost could belower, the qualification of added mass block is easy to satisfy, and parameteridentification based on incomplete set of complex modes also can be achieved whileidentification based on noise-contaminated modes seems inefficiency.(4) The Improved Unscented Kalman Filter (IUKF) is proposed and derived by thefollowing two changes, using the Singular Value Decomposition (SVD) to format thesquare root of covariance matrix, and bringing the noise vector to state vector to formaugmented state vector and to regenerate the sigma sample points. Numerical simulationshows IUKF is capable of detecting the time varying history of nonlinear hystereticstructural physical parameters, and improving the robustness, stability, accuracy andnoise-immunity.