Based On Artificial Immune Particle Swarm Algorithm Of Hoist Spindle Device Design Optimization

The mine hoist mining equipment. The rapid development in the nationaleconomic construction, the demand for energy is also increasing, increasing theyield and performance requirements of the mine hoist. We need to learn thestate-of-the-art design and manufacturing methods and theories applied to theoptimization of the design of the mine hoist, to improve the practicality andeconomy of the mine hoist.This paper discusses the immune algorithm standard particle algorithms,the basic idea and algorithm processes of immune particle swarm algorithmfound three intelligent algorithms have some deficiencies, the immunealgorithms generally require some a priori knowledge of the formation ofmemory, a lot of The circumstances do not have such conditions, the lack ofstandard PSO diversity, slow convergence, this article discusses the two immuneparticle swarm algorithm, these two algorithms both the advantages of immunealgorithm and particle swarm optimization, but there is still room forimprovement in diversity and convergence rate of the algorithm to improve theplace. On this basis, the paper proposes a novel improved immune particleswarm algorithm, the combination of immune algorithm and particle swarmalgorithm, added immune eliminated and particles flying speed controlmechanism, the formation of a new immune particle swarm optimization(AI-PSO) and function to verify the effectiveness of the algorithm. Immuneparticle swarm algorithm using standard particle swarm algorithm, the twoimmune particle swarm optimization, improved the same function, immuneparticle swarm optimization simulation proved that the improved algorithm hasbetter global convergence ability and faster convergence rate.This article spindle device with improved immune particle swarmoptimization (AI-PSO) of2JK-3/30hoists to reduce weight as the goal tooptimize the design. Force spindle device in the optimization process, themechanical model, to complete the establishment of the constraints. The spindledevice optimized25.87%lighter than before, reduce the cost of manufacturing. In order to verify the immune particle swarm algorithms improved the accuracyand effectiveness of the the spindle device optimized results, use the elevatorshaft optimized device data, through the establishment of a three-dimensionalmapping software Pro/E and finite element software ANSYS spindle deviceoverall, a separate reel, separate spindle three finite element model analysiscalculated to obtain the maximum equivalent stress and equivalent strain of themine hoist spindle device security checking, and the results prove that the threemodels to meet the security checking conditions, indicating that the AI-PSOalgorithm for the optimization of the spindle device the results arereliable.Keywords: hoist; spindle device; immune particle swarm optimization;optimal design; finite element analysis.