The Application Of Improved Imperialist Competitive Algorithm In Structural Identification

Under the influence of multiple factors,such as harsh natural environment,overload operation and material fatigue aging,the engineering structures in service have serious hidden dangers.The traditional non-destructive testing and reliability assessment methods need to know the approximate posit ion of structural defects,and can not detect the internal structural defects,which can’t meet the practical requirements.In order to compensate for the above shortcomings,the researchers in this field have carried out a lot of research on structural health monitoring system.Structural identification(structural parameter identifica tion and damage identification)is the core content of structural health monitoring,and its identification methods are numerous,but so far there is no effective method for practical engineering.This paper has done much research on a swarm intelligence algorithm,Imperialist C ompetitive Algorithm(IC A).Aiming at the limitation of the algorithm,an improved algorithm is proposed,which is applied to the structural modal parameter identification and damage ide ntification.The main research contents and achievements are as follows:(1)The research status,main methods and application background about structural modal parameter identification and damage identification are reviewed systematically in this chapter.Then the research ideas and main research contents of applying IC A to structural identification are put forward.(2)The background of IC A,the basic principles and the calculation process are elaborated,and the main application areas of IC A are briefly described;(3)Aiming at the defects of premature convergence and local optimum in the practical application of IC A,the global optimization idea of PSO algorithm is introduced to improve the assimilation equation.By using the wavelet mutation to replace the random variation in the process of colonial revolut ion,an improved imperialist competit ive algorithm based on global optimization is developed.Through the test results of standard test function,compared with the ICA,GBIC A has been great improved in the ability of searching accuracy,searching ability and jumping out of the local optimal value.(4)In view of the fact that the identification of modal parameters under the known excitation is difficult to be carried out in practical application,this paper studies the modal parameter identification based on intelligent optimization algorithm under ambient excitation.By converting the parameter identification problem into the optimization problem,this method can identify the structural modal parameters simultaneously.Through numerical simulation and case analysis,it is found that GBIC A is obviously improved compared with IC A in the accuracy of modal parameter identification.O n the other hand,the identification results of GBIC A are more stable and the noise immunity performance is better than IC A under different noise environment.(5)Based on the defects of using generalized flexibility sensitivity in damage detection,the generalized flexibility matrix is used to construct the objective function.Combined with the optimization algorithm,the damage identification problem is transformed into an optimization problem.Through the numerical model damage identification analysis,on one hand,the two methods of IC A and GBIC A can quickly and accurately identify the damage location and damage degree of the structure,whether it is single damage or multiple damage.O n the other hand,compared with IC A,the accuracy of damage identification in GBIC A is obviously improved,and in the high noise environment,the stability of GBIC A is better than IC A,which shows that GBIC A has a stronger robustness.