Bayes小样本统计理论在舰艇导航装备维修中的应用  

Application of Bayes small sample statistical theory in naval vessel navigation equipment service

作　　者：邹艳忠[1] 孙铭明[1] 王婷婷[2] 

机构地区：[1]92956部队 [2]海军南海舰队海洋水文气象中心

出　　处：《中国修船》2010年第5期37-40,共4页China Shiprepair

摘　　要：舰艇导航装备属于高精度、高可靠性、高成本的精密设备。为了解决大型导航设备在小样本条件下的维修性评估问题,研究了Bayes小样本统计理论在导航装备维修中的应用。根据导航装备维修时间的小样本数据,进行了数据的K-S检验,建立了导航装备的维修时间分布模型,运用Bootstrap方法对确立的模型进行参数辨识,确定了导航装备的平均修复时间、中位修复时间、最大修复时间等参数,结果表明Bootstrap方法的有效性和准确性。The naval vessel navigation equipment belongs to those with high accuracy, reliable and high cost. In order to solve the appraisable problem about maintenance of the large-scale navigation equipment under the small sample condition, application of the Bayes small sample statistical theory is studied in this article. According to the small sample data of the navigation equipment maintenance time, the time distribution model for the navigation equipment maintenance has been established, the K-S examination about the data and parameter identification are carried on by using the Bootstrap method, determining some parameters about the mean time, position time and the biggest time to repair for the navigation equipment. Finally the Bootstrap method proves valid and accurate.

关 键 词：导航装备 BAYES 小样本 BOOTSTRAP方法 维修性 

分 类 号：U673[交通运输工程—船舶及航道工程]