Geometric modeling
Computer-Aided Design and Manufacture
Computer-Aided Design and Manufacture
CAD/Cam: Computer-Aided Design and Manufacturing
CAD/Cam: Computer-Aided Design and Manufacturing
Parameter Selection in Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
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Optimal problem is often met in engineering practice. The method to solve complex optimal problem is always studied by people. Springs are important mechanical members which are often used in machines to exert force, to provide flexibility, and to store or absorb energy. Helical spring is the most popular type of springs. The method of helical spring optimization is a typical one which can be used to solving other mechanical optimal design problem. Particle Swarm Optimization algorithm is a good method in solving optimal problem. MATLAB is a high-performance language for technical computing and is an easy tool for us to simulate the optimization. In this paper, we mainly introduce the optimization of helical spring based on particle swarm algorithms and simulation in MATLAB. Directed by the theory of Particle Swarm Optimization algorithm, with the minimum weight of helical spring as objective function, with d, D2 and n as design variables, with shear stress, maximum axial deflection, critical frequency, bucking, fatigue strength, coils not touch, space and dimension as constraint conditions, the complex helical spring optimal design mathematics model with three design variables and fourteen inequality constraints conditions is established. When the model is simulated in MATLAB the minimal optimal value of variables and the minimal weight of helical spring can be obtained. Simulating Result shows that Particle Swarm Optimization is practical in solving complicated optimal design problems and effectively on avoiding constraint of solution. The fundamental idea, the method of establishing mathematic model, the simulation process in MATLAB of helical spring can be used for reference to other similar mechanical optimal design.