小样本情形集中供热系统元件失效率估计方法研究

Research on estimation methods for component failure rates in district heating systems under small sample scenarios

对国内3个典型城市集中供热系统失效事件进行了调查统计,并对元件失效率进行了估计。针对直接估计模型存在的限制,引入了Bayes(贝叶斯)理论,融合历史信息,提出了一般Bayes模型和分层Bayes模型。比较了3种模型的精度,管道、阀门和补偿器3类元件的分层Bayes模型精度分别为0.31、0.32、0.29,在3种模型中精度最高;最终通过改变样本量,得出3种模型精度随样本量增加均呈现上升趋势,且相互差距逐渐缩小,验证了Bayes模型在小样本情形的适用性。

This paper investigates and statistically analyses the failure events of the district heating systems in three typical cities in China,and estimates the failure rates of components.In view of the limitations of the direct estimation model,the Bayes theory is introduced,and integrating historical information,the general Bayes model and hierarchical Bayes model are proposed.The accuracies of these three models are compared.The accuracies of the hierarchical Bayes model for the three types of components,namely pipes,valves,and compensators,are 0.31,0.32,and 0.29 respectively,which are the highest among the three models.By changing the sample size,it is concluded that the accuracies of the three models all show an upward trend with the increase of the sample size,and the mutual gap is gradually narrowed,verifying the applicability of the Bayes model in the case of small samples.