基于改进人工鱼群算法的车辆可靠性估计技术  

Vehicle Reliability Estimation Technique Based on Improved Artificial Fish Swarm Algorithm

作　　者：孙文政[1] SUN Wenzheng(Nanjing Iveco Automobile Company Limited,Nanjing 210028,China)

机构地区：[1]南京依维柯汽车有限公司,江苏南京210028

出　　处：《汽车实用技术》2024年第22期78-82,共5页Automobile Applied Technology

摘　　要：在零部件研发过程中,对零部件进行可靠性估计至关重要,而威布尔分布被广泛用于模拟失效分布,因此对威布尔分布的参数估计对零部件可靠性预测和分析非常关键。对此,文章提出了一种用于车辆零部件可靠性评估的基于改进人工鱼群算法的新型威布尔分布估计方法,首先从理论上构建了威布尔分布的最大似然估计模型,并对相关模型进行详细的介绍;然后基于人工鱼群算法求解效率低和质量不高的缺陷,通过引入Levy飞行策略和感知距离自适应调节策略对原始人工鱼群算法其进行改进;最后,运用改进人工鱼群算法进行蒙特卡洛模拟仿真试验,进而对威布尔分布参数拟合效果进行比较和分析。结果表明,对于威布尔分布的参数估计,文章所提出的改进人工鱼群算法比其他元启发式算法给出了更准确的参数估计,能够为汽车零部件开发与可靠性评估提供科学有效的指导。In the process of component development,reliable estimation of component reliability is crucial.The Weibull distribution is widely used to simulate failure distributions,making parameter estimation of the Weibull distribution essential for component reliability prediction and analysis.To address this,this paper proposes a novel Weibull distribution estimation method based on an improved artificial fish swarm algorithm for vehicle component reliability assessment.Firstly,the paper theoretically constructs a maximum likelihood estimation model for the Weibull distribution and provides a detailed introduction to the relevant model.Subsequently,in light of the low efficiency and suboptimal quality inherent in the original artificial fish swarm algorithm,improve-ments are made by introducing Levy flight strategy and adaptive adjustment of perceptual distance.Lastly,the improved artificial fish swarm algorithm is employed for Monte Carlo simulation experiments to compare and analyze the fitting effects of Weibull distribution parameters.The results indicate that for Weibull distribution parameter estimation,the proposed improved artificial fish swarm algorithm more accurate parameter estimations compared to other metaheuristic algorithms,thereby providing scientifically effective guidance for automotive component development and reliability assessment.

关 键 词：威布尔分布 可靠性 参数估计 人工鱼群算法 耐久寿命 

分 类 号：U463.81[机械工程—车辆工程]