| In order to realize the basic function of the bridge structure health monitoring system,it is necessary to use a sensor system,that is,to select an appropriate degree of freedom through an algorithm,and then to arrange the sensor above these selected degrees of freedom,and then obtain a variety of structures of dynamic response information.According to theoretical research,the more the number of master degrees of freedom is selected,the more sensors are used,the more structural dynamic information is acquired,and the more accurate structural features are described,the more accurate dynamic response data can be obtained.However,in the actual application process,many large and complex bridge structures have very high degree of freedom in measurement,and it is unrealistic to obtain the frequency response information in the full degree of freedom of the bridge structure.It is impossible to use the sensors in the structure that monitoring obtains response information in all degrees of freedom;taking into account the cost of the power test and the cost of the entire structural health monitoring system,the total number of sensors is limited,making the number of measurement points and degrees of freedom selected in the test much smaller the total number of degrees of freedom of the structure.Therefore,it is of great theoretical and practical significance to study how to reasonably select the main degrees of freedom to be measured to ensure the quality of structural monitoring.In this paper,under the support of the National Natural Science Foundation of China(NO:51778506)Youth Fund Project,a study was carried out to optimize the selection method of main degrees of freedom for the purpose of structural health monitoring for large-scale and complex bridge structures in order to solve the health monitoring of large-scale and complex bridge structures.The operational safety assessment problem provides a new approach,and a damage identification method based on model polycondensation is developed.Information entropy is used to quantitatively characterize the uncertainty of the identification results of the structural modeling parameters to be identified.Based on the Bayesian statistical system identification method,minimizing the uncertainty of structural modeling parameter identification results is the optimization criterion,maximizing the posterior probability density function of structural modeling parameters,given the number of master degrees of freedom.The binary-coded genetic algorithm is used to solve the optimization problem of the master degrees of freedom,and an optimization method for the sensor layout problem is obtained,namely,a targeted improvement on the basis of the traditional binary coded genetic algorithm,and the master degree of freedom is ensured during the evolution of the population.In the selection problem,there will be no repeat of the main freedom degree selection position and the number of main freedom degrees selected;at the same time,the accuracy of the results obtained by the genetic algorithm is verified by the exhaustive method.The free commercial mathematics programming software MATLAB is used to program,realize the three-dimensional finite element modeling and dynamic response of the bridge structure(ie,a simple simple beam model,a space truss bridge model,and a complex spatial 3D concrete arch bridge model),the improvement of the genetic algorithm,and the optimization of the master degree of freedom is the optimal placement of sensors;among them,commercial finite element software ANSYS The correctness of the numerical model built by MATLAB software was verified.Through the numerical simulation study of three typical bridge structure models,the correctness and effectiveness of the proposed method are verified.The results show that under the condition of a given number of sensors,this method can quickly and accurately identify the combination of degrees of freedom of large-scale and complex bridge structure optimization.Under this optimal combination,the maximum amount of information collected by the structure can be obtained and the bridge can be obtained.The structural modelling parameter identification results have the least uncertainty. |
