改进的粒子群优化算法对断路器储能弹簧的优化设计

Optimal design of energy storage spring in circuit breaker based on improved particle swarm optimization algorithm

针对断路器储能弹簧传统经验试算的设计方法易导致弹簧结构参数不合理、断路器的体积大及分断性能差的问题,应用一种结合鲶鱼效应改进的云粒子群优化算法对断路器的储能弹簧参数进行优化设计。首先,根据储能弹簧的工作原理,推导储能弹簧的数学优化设计模型以及弹簧参数设计的约束条件;然后,根据优化模型对算法进行改进,在传统粒子群优化算法的基础上,引入鲶鱼效应策略产生多样候选解,避免算法陷入局部最优值,并结合云模型适时调整寻优速度权重因子,以加快算法的收敛和提高全局搜索能力;最后,采用改进算法对断路器的储能弹簧优化模型进行仿真及相应的弹簧参数计算。实验结果表明,可以应用改进的粒子群优化算法对断路器储能弹簧进行优化设计,设计结果更加小型化、分断性能更优。

In the traditional way to design the energy storage spring of the circuit breaker the method of experience trial calculation is mainly adopted, which may easily lead to unreasonable parameters of the spring structure, large volume of circuit breaker and poor breaking performance. Therefore, An improved cloud particle swarm optimization algorithm combined with catfish effect was applied to optimize the parameters of energy storage spring of circuit breaker. Firstly, according to the working principle of energy storage springs, the mathematical optimization design model of the energy storage springs and the constraints of the spring parameter design were deduced. Then, improving the algorithm based on the optimization model, on the basis of the traditional particle swarm optimization algorithm, catfish effect strategy was introduced to produce various candidate solutions, avoiding the algorithm falling into local optimal value and the optimization speed weighting factor was adjusted combined with the cloud model to speed up the convergence of the algorithm and improve the ability of global search solutions. Finally, the improved algorithm was used to simulate the optimization model of the energy storage spring of circuit breakers and calculate the corresponding spring parameters. The results show that the improved particle swarm optimization algorithm can achieve miniaturization and better breaking performance of circuit breakers.