Dimension-by-dimension Centroid Opposition-based TFPSO Algorithm And Its Application In Hydraulic Reliability Optimization

In the field of engineering,hydraulic system as an important transmission system has been applied in all aspects of production,especially in some complex large equipment.Therefore,its reliability is particularly important.High reliability can ensure the stable and normal operation of equipment,and avoid equipment failure as much as possible,and achieve a certain balance between high reliability and low cost.Compared with traditional methods,swarm intelligence optimization algorithm has obvious advantages in reliability research.Therefore,a dimension-by-dimension centroid opposition-based two-stage force particle swarm optimization algorithm is used to optimize the hydraulic system.First of all,referring to the problem that the standard particle swarm optimization is difficult to jump out of the local optimal solution in the later stage,the two-stage force rule is adopted.The particle renewal process is divided into two stages: the early stage and the late stage,and the gravitational and repulsive rules in different stages will change constantly.This dynamic change rule can more accurately imitate the instinct of biology,and is more helpful to search the optimal solution.On this basis,the test function is used to test the optimization ability,convergence speed and population diversity of the algorithm,so as to verify the feasibility and superiority of the improved algorithm.Then,in order to further improve the optimization performance of the algorithm,starting from the learning strategy,this paper adopts a dimension by dimension gravity center reverse learning strategy.Combining this strategy with the improved PSO,a dimension-by-dimension centroid opposition-based two-stage force particle swarm optimization algorithm is proposed.In the process of optimization iteration,the inverse calculation of the optimal particle's gravity center is carried out,which not only avoids the mutual interference between various dimensions,but also improves the diversity of the population,fully considers the information interaction between particles,and can more accurately simulate the behavior between organisms.The optimization ability and convergence speed of the algorithm are tested,and compared with the two-stage PSO,the superiority of the proposed algorithm is verified.Finally,in order to verify the feasibility of the proposed algorithm in actual production,this paper studies and analyzes the optimization of reliability distribution of hydraulic system and multi-state system.With T-S fault tree and general generating function as tools,each system is analyzed separately and a mathematical optimization model is established.The particle swarm optimization algorithm is applied to solve the problem by applying dimension-by-dimension centroid opposition-based two-stage force particle swarm optimization algorithm.The solution is compared with other algorithms,and the ability of the proposed algorithm to solve complex optimization problems is verified.