【摘要】 以发动机气门弹簧为例,考虑设计参数的离散性,建立了以部件可靠度为目标函数的数学模型,确定了设计变量、目标函数及约束条件,使用遗传算法通过选择、交叉和变异等操作使种群逐代进化,同时以全局并行搜索来优化群体,利用遗传算法进行优化运算并得到了全局最优解。设计结果表明:使用遗传算法可以有效地解决非线性和离散性的优化设计问题,能够得到全局最优解,既可保证优化结果,又提高了优化效率;该优化方法合理有效,能够解决非线性约束条件下的优化问题,是对现代机械可靠性优化方法的丰富,可广泛应用于机械零部件的优化设计。更多还原

【Abstract】 To use engine valve spring as an example,considering discreteness of design parameters,it sets up the mathematic model with component reliability as the objective functional,establishing the design variables,objective function,and constraints.The utilization of genetic algorithm which through selection,intersection and variation makes the population evolve by generation,and in the mean time to global parallel search to optimize the group.By using the genetic algorithm to optimize operation and get the global optimal solution.Design results shows that by using genetic algorithm the nonlinear and discrete problem of optimization design can effectively be solved,which not only can get the global optimal solution,but also can ensure the optimization results,and also improve the optimization efficiency.The optimization method is reasonable and effective,which can solve nonlinear constraints optimization problem,and also it enriches the modern mechanical reliability optimization method,which can be widely used in mechanical parts of the optimization design.更多还原