Real-time Identification Of Time-varying Structures And Integration With Vibration Control Based On Extended Kalman Filter With Unknown Inputs

Structural identification and damage detection are significant subject in Structural health monitoring(SHM)technology.In the past few decades,different experts and scholars have come up with different theories and methods of Structural identification and damage detection based on structural vibration response.While,many of these identification methodologies are mostly aimed at the time-invariant system.However,structural health monitoring systems must be able to detect structural damage on-line and provide online warning of damage at heavy loads,such as high-intensity earthquakes.In the second chapter,an on-line identification method of time-varying systems based on improved adaptive Kalman filter was proposed,in which,the adaptive factors are used to reflect the change of the structural parameters,and the time-varying parameters of the structure can be identified on-line based on only partial structure response data.Firstly,the classical extended Kalman filter algorithm is used to identify the invariant structural parameters until the parameters are convergent and stable.Then,the error covariance of the 'correction term,in Kalman filter is used to establish the nonlinear matrix equation of the adaptive factor matrix.By transforming the matrix equation into an optimization problem with nonlinear constraints,the adaptive factor matrix can be worked out,before which,the occurrence of damage was determined in order to identify the system on-line.And finally,the effectiveness of the proposed method is verified by two numerical examples of shear frame and plane frame.Considering that the external inputs are frequently difficult to be accurately measured in reality.In the third chapter,the adaptive Kalman filter is generalized to the unknown inputs case.By taking into account the two cases of acceleration observation and non-observation of the DOF where the external excitation inputs,the on-line identification method of time-varying systems based on improved adaptive Kalman filter was proposed with unknown input was proposed.Firstly,the time-invariant structural parameters are identified until the parameters are convergent and stable.Then the equation of the adaptive factor matrix was established and worked out by transforming the equation into an optimization problem with nonlinear constraints.And the occurrence of damage was determined in order to identify the system on-line.Finally,the feasibility of the proposed method is verified by two plane shear frames subjected to unknown earthquake excitation and white noise excitation.Due to the global system parameter identification always involve too much structural degrees of freedom and unknown structural parameters,moreover,in the solution progress of the adaptive factors which are related to the time-varying parameters,too many unknown elements will bring the computational pressure.So that the 'substructure' was applied,some of the elements in the global structure are separated and the unknown internal forces in the original structure are applied to the degrees of freedom of the boundary to make it an independent structure.And then the parameter identification method is used to identify the time-varying system with unknown inputs.Finally,the accuracy of the method is verified by using bilateral overhanging Euler beam.At last,considering the structural damage detection and vibration control system are using the same sensor system,so it is necessary to study the integration method of structural parameter identification and vibration control for the building structure which need the two systems both.In the fifth chapter,the time-varying system identification method and the semi-active control are integrated to identify the time-varying structure parameters in real time with unknown input.Finally,the correctness of the proposed method is verified by using the plane shear frames with unknown seismic excitation and white noise excitation.