Abstract:

Abstract: The parameter optimization of vibration isolation system for refrigerator compressor is closely related to the effects of vibration isolation. A method of natural frequency discrete distribution to optimize vibration isolation was proposed to improve the shortcomings of easily falling into local optimum solution and iterative divergence for traditional optimization design with taking 6-DOF energy decoupling of the vibration isolation system as the objectives, and taking the stiffness of 4 rubber supports as the design variables. The chaos particle swarm algorithm based on penalty function constraints was developed to optimize isolation parameters for the first time. The results showed that optimized distribution of its natural frequencies is more reasonable, and the optimized decoupling ratios in main directions are improved significantly. Furthermore, it was shown that compared to the sequential quadratic programming and genetic algorithm, the particle swarm algorithm overcomes its weakness of converging to local optimal solution, and it is higher than genetic algorithm in terms of energy decoupling ratios. At last, it was verified with dynamics simulation that the proposed optimization method applied to vibration isolation design have both rationality and effectiveness.

摘要：

冰箱压缩机隔振系统的参数寻优问题关系到隔振成败，传统参数优化设计存在容易陷入局部最优和迭代发散问题。针对该问题建立压缩机4 点隔振的动力学模型，提出以隔振系统的6 自由度能量最大程度解耦为优化目、以4 点支撑的各向刚度为设计参数的系统频率离散分配优化方法，首次采用基于罚函数约束的混沌粒子群算法进行隔振参数寻优求解。结果表明，优化后隔振系统固有频率分配更加合理，主要方向解耦率得到显著提高。混沌粒子群算法克服传统序列二次规划法容易陷入局部最优的缺点，所得系统隔振效果优良，相对于遗传算法优化结果解耦程度更高。动力学仿真分析验证所提优化方法的合理性和有效性。

关键词: 振动与波, 隔振系统, 能量解耦, 优化设计, 混沌粒子群算法