摘要
通过对机油泵工作特性进行分析,建立机油泵工作特性曲面的数学模型。分别采用单种群基本遗传算法和自适应域多种群遗传算法求解了所建立的机油泵工作特性曲面模型的关键参数。通过计算和试验表明,自适应域多种群的遗传算法根据解的离散程度或集中程度动态调整参数域,使得求解空间收敛,搜索最优解的收敛速度较快,且所获得的解的质量更高,从而使机油泵工作特性曲面模型的预测精度更高。
A mathematical model of the characteristics surface of an oil pump was established by analyzing the operating characteristics of the oil pump. The key parameters of the characteristics sur- face model of the oil pump were solved using single population genetic algorithm and adaptive domain with multiple genetic algorithm respectively. Experimental results show that the adaptive domain with multiple genetic algorithm can adjust the parameter domain dynamically by the discrete or con- tinuous level of parameters, can make the solution space convergence, and the searching rate for the best solution be faster. And the quality of the solution is much better. Then the precision of the mod- el of the characteristics surface of the oil pump is better.
出处
《中国机械工程》
EI
CAS
CSCD
北大核心
2012年第13期1593-1597,1602,共6页
China Mechanical Engineering
基金
国家自然科学基金资助项目(50505030)
上海市教育委员会曙光计划资助项目(07SG51)
关键词
机油泵
性能曲面
遗传算法
自适应域
oil pump
characteristics surface
genetic algorithm
adaptive domain
