Improvement Of Artificial Searching Swarm Algorithm And Its Application To The Optimization Of Electrical Appliances

The artificial searching swarm algorithm is a bionic intelligence algorithm which is designed based on the searching rules of the soldiers when performing search tasks.The artificial searching swarm algorithm has the advantages of simple principle,few parameters,easy to implement,and has good development potential.However,the artificial searching swarm algorithm has some problems that it is easy to fall into the local optimal value and the convergence rate is slow.Besides,the artificial searching swarm algorithm proposed in recent years has not been applied in many fields.This paper analyzed and improved the artificial searching swarm algorithm,then uses the improved artificial searching swarm algorithm to optimize the electrical appliances.Main work as followings:Firstly,the optimization concept,traditional optimization algorithm and bionic intelligent optimization algorithm are introduced in this paper,and some different traditional optimization algorithms and bionic intelligent optimization algorithms are analyzed theoretically.Secondly,this paper introduces the principles and analyzes the advantages and disadvantages of the artificial searching swarm algorithm.On the basis of Levy flight theory,this paper puts forward the Levy flight artificial searching swarm algorithm(LASSA).In order to verify the effectiveness of LASSA,12 standard test functions are selected for testing.The LASSA and ASSA are compared in different dimensions and iteration times.It is proved that the improved algorithm converge speed and calculation precision are better than before.In addition,the Levy flight artificial searching swarm algorithm,Artificial Bee Colony Algorithm and differential evolution algorithm are compared to prove that the Levy flight artificial searching swarm algorithm has a good performance.Thirdly,a parametric finite element model of under-voltage tripping device is established and the attraction between static and dynamic core is calculated by using ANSYS software.The improved artificial searching swarm algorithm combines with the ANSYS software is used to optimize the under-voltage tripping device.The optimization results show that volume of under-voltage tripping device is reduced based on meeting the attraction between static and dynamic core,saving production cost and achieving the optimization purpose.Finally,ANSYS Workbench is used to analyze the whole stress of the gear set of electric operating mechanism for an external circuit breaker of electric power meter.By using the stress calculation formula,the author calculates the maximum stress of the gear surface and root.Based on comparison of the simulation results and calculation results,the correctness of the stress analysis is determined.Then,mathematical models and constraints are established.The author used improved artificial searching swarm algorithm to optimize the gear set.The optimized results show that the optimized gear stress is reduced and the purpose of optimization is achieved.