A Structural Damage Identification Method Based On Improved VMD And Time Domain Modal Statistical Moment

Due to the complexity and uncertainty and other factors of the structures,it is a huge challenge to carry out accurate and effective damage identification and extensive engineering applications.This thesis will try to research and solve the following two problems.Firstly,aiming at the hugeness and complexity of civil engineering structures,a damage identification method based on variational modal decomposition technology and time-domain modal statistical moments is proposed,which can identify structural damage through a small number of measuring points.Secondly,for the measurement of environmental noise,model parameter uncertainty and other issues,combined with variational modal decomposition technology and interval parameter sensitivity method,a method for interval damage parameter identification is proposed for the assessment of the probability of structural damage.The main research work of this thesis will start from the following aspects.1.In this thesis,the sensitivity-based model updating method is combined with a new L_1/2 regularization technology to identify structural damage.Compared with the traditional L₁regularization method,the L_1/2regularization method has better sparseness and faster iterative solution speed.In addition,since the L_1/2 problem is a non-convex problem,it is not easy to solve.This thesis introduces three solving algorithms for the L_1/2problem,and chooses an optimal solution algorithm.Finally,numerical examples such as simply supported beams and frames are used to prove the superiority of the L_1/2regularization method in identification accuracy and anti-noise ability under different working conditions.2.This thesis proposes a new index,time-domain modal statistical moments for damage identification.Firstly,the sequence method based on the MAC matrix is used to obtain the optimal measurement points of the structure,and then through the improved variational modal decomposition technique,the time-domain acceleration or displacement of the measurement points is obtained.The signal is decomposed to obtain the time-domain signal of each mode of the structure,and combined with the statistical moment theory to construct the time-domain modal statistical moment,and use it as a dynamic damage indicator,and finally we will achieve the completion of a large complex structure with fewer measuring points.The third chapter will further verify the effectiveness of the proposed damage identification method under the condition of few measuring points through numerical examples such as Tanjiang Bridge and cantilever beam experiment.3.The damage identification process is often affected by uncertain factors.Chapter 4will consider the distribution characteristics of uncertain parameters,and propose an uncertain structural damage identification method based on time-domain modal statistical moments and interval analysis theory.The basic process is to derive the sensitivity of the damage parameters with respect to the interval uncertain parameters firstly,and then combine the interval analysis theory to adopt a two-step interval model updating method to calculate the interval range of the damage parameters in the undamaged and damaged states respectively to realize the damage possibility assessment of the structure under the influence of uncertain parameters.Finally,through two numerical examples,plane truss and space truss structure,and compare the Monte Carlo method and the method based on probability statistics to further verify the effectiveness of the proposed method.