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首页> 外文会议>International Conference on Computer Information Systems and Industrial Management Applications >Optimal design of induction motor for a spinning machine using population based metaheuristics
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Optimal design of induction motor for a spinning machine using population based metaheuristics

机译：基于群体的纺纱机的纺纱机型电动机的最佳设计

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This paper deals with the design optimization of a squirrel-cage three-phase induction motor, selected as the driving power of spinning machine in textile industry, using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). Efficiency, which decides the operating or running cost of the motor (industry), is considered as objective function. First, the algorithms are applied to design a general purpose motor with seven variables and nine performance related parameters with their nominal values as constraints. To make the machine feasible, practically acceptable to serve in textile industries and less operating cost, certain constraints are modified in accordance with the demands in spinning application. Comparison of the optimum designs with the industrial (existing) motor reveals that the motor designed for textile load diagram consumes less power input. Economical analysis is also given.
机译：本文涉及鼠笼式三相感应电动机的设计优化，采用遗传算法（GA）和粒子群优化（PSO）作为纺织工业纺纱机的驱动力。决定电机（行业）的操作或运行成本的效率被认为是客观函数。首先，应用算法以设计具有七个变量和九个性能相关参数的通用电机，其标称值作为约束。为了使机器可行，实际上可以在纺织工业中服务和较少的运营成本，根据纺纱应用的要求，改变某些约束。与工业（现有）电机的最佳设计比较显示，为纺织装载图设计的电机消耗更少的电源输入。还提供了经济分析。

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