Structure State Estimation And Damage Detection Based On Interval Analysis Considering Uncertainties

Structural damage identification is an important research direction in structural health monitoring.For example,the uncertainty of structural parameters,the uncertainty of external excitation,the uncertainty of environmental noise,etc.The existence of these uncertainties will lead to the deviation of structural damage identification results.At present,there are a lot of models and theories to deal with the uncertainty of the system.The mathematical models usually used are probability model,fuzzy model,convex model and interval model.When the uncertainty of the system model has the characteristics of poor information and little data,the interval analysis method is usually applicable,it only need to know the information of the upper and lower bounds of uncertain parameters can be achieved on the uncertainty of system damage.The(extended)Kalman filter is a closed loop recursive method,which can analyze the structural response state in real time.It only needs to observe the partial response,and is not sensitive to the model error,so it has been widely used in aerospace,mechanical,civil engineering and other fields.When the(Extended)Kalman filtering method and interval analysis method are combined,the interval(Extended)Kalman filtering method can be used to identify the structural response state in real time.It is necessary to discuss the problem of how to extend the(extended)Kalman filtering to t the(extended)Kalman filtering with unknown force.Basing on the above research background,the main work of this paper is as follows:(1)The traditional probabilistic damage identification method based on the response sensitivity is sensitive to noise.This paper introduces a method to improve the anti noise performance of damage identification method.The method is applied to the damage identification of the 10 story shear frame model and the truss structure model with 11 bars.The identification of damage probability and damage degree in noise environment is discussed.The results show that the method can effectively locate the damage location,identify the degree of damage,and has good noise immunity.(2)In this paper,a new the extended Kalman filter method is proposed to improve the condition that the traditional extended Kalman filter needs to know the external excitation.And the interval analysis method is combined with this method.Structural damage identification with structural parameter uncertainty is considered.The proposed method is applied to the 6 story shear frame and the 11 bar truss structure and good results are obtained.(3)In this paper,the restriction conditions of the external excitation information known by the interval Calman filtering method are improved.An interval Kalman filtering method based on unknown excitation is proposed,estimating the structural state and external excitation simultaneously.At the end of this chapter,the method is applied to the state estimation of the 6 story shear frame model and the truss model with 11 bars.Compared with Monte Carlo simulation method,the recognition results are good.(4)In this paper,we extend the extended interval Kalman filtering method with known external excitation information to extended interval Kalman filtering method with unknown external excitation information,estimating structural state,external excitation and structural parameters.The method is applied to the state estimation of 6 layer shear frame model.Compared with Monte Carlo simulation method,the recognition results are good.