A New Intelligent Model for Structural Reliability Identification Based on Optimal Machine Learning

It is very difficult to built reliability design model of structural parts working in a complex and uncertain environment because of their dynamic time-dependent characteristic, an intelligent method of reliability analysis based on compound algorithm is presented in this paper, support vector machine and finite element analysis combined with Monte Carlo numerical simulation is integrated to improve simulation computing precision. This method is applied to reliability analysis of catenary system, mathematic model of reliability calculation on catenary system based on compound algorithm is built, and reliability of location supporting seat and location pipe are calculated by the method, location supporting seat and location pipe are critical force-bearing parts of catenary system in the high-speed electrified railway, and fault rate is very high, their reliability analysis is important research subject in railway system. In this paper, analysis method of location installation based on support vector machine and finite element combined with monte carlo is used, and the influence of outside parameter on location installation is analyzed by the model.