汽车工程学报2025，Vol.15Issue(3)：385-394,10.DOI:10.3969/j.issn.2095-1469.2025.03.11
基于新型B&R-SSA算法的混合威布尔参数估计优化方法
An Optimized Parameter Estimation Method for the Mixed Weibull Distribution Based on a Novel B&R-SSA Algorithm
摘要
Abstract
The mixed Weibull distribution is widely used for modeling failure distributions and predicting durability.In practical engineering development,accurate parameter estimation for the model is critically important.Therefore,improving the estimation accuracy of the mixed Weibull distribution has become an urgent and challenging issue in the field.Based on the original mixed Weibull distribution,this paper proposes an optimized parameter estimation approach using a novel B&R-SSA algorithm.Firstly,this method establishes an iterative optimization model to estimate the location,scale,and shape parameters based on the method of successive approximation.To address the low efficiency and tendency of the original Salp Swarm Algorithm(SSA)to become trapped in local optima,a novel B&R-SSA algorithm is proposed by introducing a"betrayal"behavior mechanism and an adaptive inertia weight strategy.This improved algorithm is then applied to solve the iterative model.Finally,Monte Carlo simulations and engineering case studies are conducted.Both the simulation and experimental results demonstrate that the proposed method achieves good accuracy and computational efficiency in estimating the parameters of the mixed Weibull distribution.关键词
可靠性/混合威布尔分布/樽海鞘算法/参数估计/蒙特卡洛模拟Key words
reliability/mixed weibull distribution/salp swarm algorithm/parameter estimation/Monte Carlo simulation分类
数理科学引用本文复制引用
赵闵清,姜维,黄子龙,熊德明,龚春辉,程小强..基于新型B&R-SSA算法的混合威布尔参数估计优化方法[J].汽车工程学报,2025,15(3):385-394,10.基金项目
国家自然科学基金项目(12262022) （12262022）
陕西省科技重大专项(2019zdzx01-02-02) （2019zdzx01-02-02）
