基于改进CS的混合威布尔分布最优化参数估计

发布时间：2018-02-24 15:12

本文关键词： 可靠性分析参数估计最小二乘法布谷鸟搜索算法算法改进　出处：《现代制造工程》2017年04期 　论文类型：期刊论文

【摘要】：混合威布尔分布常用于拟合多失效模式的设备寿命数据,但由于该分布的形式复杂且参数众多,其参数估计较为困难。针对该问题,在对布谷鸟搜索(Cuckoo Search,CS)算法的步长比例和寄主鸟发现概率改进的基础上,提出基于改进CS的混合威布尔分布最优化参数估计方法。该方法以最小化残差平方和为目标,建立参数估计优化模型,并通过改进的CS算法进行参数寻优。案例以飞机挡风玻璃寿命数据为对象,采用CS算法以及3种改进的CS算法分别对两重两参数威布尔分布进行2 000次参数估计,对比分析各算法的寻优结果表明:融合步长比例改进和寄主鸟发现概率改进的CS算法的参数估计精度较高,估计结果较可靠。
[Abstract]:The mixed Weibull distribution is often used to fit the equipment life data of multiple failure modes, but it is difficult to estimate its parameters because of its complex form and numerous parameters. Based on the improvement of step size ratio and host bird discovery probability of Cuckoo SearchCass algorithm, a hybrid Weibull distribution optimization parameter estimation method based on improved CS is proposed. The objective of this method is to minimize the sum of squared residuals. The parameter estimation optimization model is established, and the parameters are optimized by the improved CS algorithm. The case is based on the aircraft windshield life data. The double two-parameter Weibull distribution is estimated by using CS algorithm and three improved CS algorithms for 2,000 times respectively. The comparison and analysis of the optimization results show that the improved CS algorithm with improved step size ratio and host bird discovery probability has higher estimation accuracy and reliable estimation results.
【作者单位】：军械工程学院;
【分类号】：O212.1;TP18

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