摘要
准确估计飞机整体驱动发电机(Integrated drive generator,IDG)的可靠性分布参数,对掌握该部件的故障变化规律和制定维修策略起到关键性作用。针对飞机IDG故障数据为小样本的特点,以威布尔分布为例,采用最小二乘支持向量回归机(LSSVR)、支持向量回归机(SVR)和最小二乘法(LSR)对飞机IDG进行可靠性参数估计。结合实例与蒙特卡罗仿真,对比分析3种参数估计方法的精度、运行时间以及样本量变化时的稳定性。结果表明,在小样本情况下,LSSVR的参数估计精度最高,LSR的运行时间最短;随着样本量的减小,3种参数估计方法的精度均有所减小,但LSSVR的稳定性最好。
Accurately estimating the reliability parameters of the aircraft integral drive generator(IDG)plays a key role in mastering the failure variation law of the component and formulating maintenance strategies.Aiming at the characteristics of aircraft IDG failure data as small samples,taking Weibull distribution as an example,least squares support vector regression(LSSVR),support vector regression(SVR)and least square regression(LSR)are respectively used to estimate the reliability parameters of aircraft IDG.The accuracy,running time and stability of the three parameter estimation methods are compared and analyzed.The results show that in the case of small samples,LSSVR has the highest parameter estimation accuracy and LSR has the shortest running time;as the sample size decreases,the accuracy of the three parameter estimation methods decreases,but LSSVR has the best stability.
作者
孔祥芬
刘敬赟
王杰
唐淑珍
KONG Xiangfen;LIU Jingyun;WANG Jie;TANG Shuzhen(Aeronautical Engineering Institute,Civil Aviation University of China,Tianjin 300300,China)
出处
《机械科学与技术》
CSCD
北大核心
2022年第6期977-984,共8页
Mechanical Science and Technology for Aerospace Engineering
基金
航空科学基金项目(20170267002)
民航机场群智慧运营重点实验室开放基金项目(KLAGIO20180302)。
