基于Monte Carlo法与GA算法的复杂系统可靠度求解

Reliability calculating method of complex systems based on Monte Carlo method and genetic algorithm

复杂系统可靠性问题是可靠性工程中丞待解决的问题。提出了基于可靠性框图的复杂系统蒙特.卡罗仿真方法,给出了各种基本可靠性模型系统与其组成单元的失效时间关系,解决了含有旁联模型的复杂系统仿真问题。以可靠性仿真数据为寿命样本,待估计参数的置信区间为编码空间,以经验分布与所求分布误差倒数为适应度函数,建立了基于遗传算法的寿命分布参数点估计模型,求得了复杂系统可靠度函数。最后以两个实例表明该方法比传统方法具有更高的精度。

The complex system reliability is a problem to be solved in reliability engineering. The reliability simulation of Monte Carlo method for a large complex system is proposed based on the reliability block diagram. The relationships of the failure time of various reliability model systems and their component units are given, the reliability simulation problem of complex systems including bypass model is solved. Choosing reliability simulation data as a sample, the parameter confidence interval as coding space and the reciprocal of errors between empirical distribution function and acquired distribution function as a fitness function, the point estimation model of age distribution is established based on the genetic algorithm, and the reliability function of complex systems is acquired. Finally, two cases are given to indicate that this method is more accurate than the traditional method.