摘要
为实现不完全维修条件下的安全关键设备可靠性评估,针对传统可靠性评估模型未考虑多个故障样本间存在的数据差异问题,以及模型参数求解复杂的问题,提出了一种混合KijimaⅠ虚拟役龄模型。首先通过累积故障强度函数对时间图描述系统的故障趋势,根据AIC、BIC信息准则选取合适的可靠性评估模型,利用非线性约束规划法转换得到不完全维修下的分布参数估计值。随后针对不同故障原因造成的多类别样本故障数据,考虑故障数据间的差异性,建立了混合KijimaⅠ模型。将该模型应用到某LNG接收站卸船系统中,实例分析表明,该模型在实际可靠性评估中比常用的混合样本分布模型更加有效,有助于实现差异化维修和设备高可用性之间的平衡。
To realize the reliability evaluation of safety-critical equipment under incomplete maintenance conditions,the traditional reliability evaluation model does not consider the data difference between multiple fault samples and the complex problem of solving model parameters.This paper proposes a hybrid KijimaⅠVirtual service age model.Firstly,the cumulative failure intensity function is used to describe the failure trend of the system on the time diagram.The appropriate reliability evaluation model is selected based on the AIC and BIC information criteria,and the non-linear constraint programming method is used to transform the estimated value of the distributed parameter under imperfect repair.Then,for the multi-category sample failure data caused by different reasons,the hybrid KijimaⅠmodel is established by considering the difference between failure data.The case analysis of the ship unloading system of an LNG receiving station shows that this model is more effective than the commonly used mixed sample distribution model in actual reliability evaluation.At the same time this helps to achieve a balance between differentiated maintenance and high equipment availability.
作者
屈持
王海清
姜巍巍
孙浩
张景康
QU Chi;WANG Haiqing;JIANG Weiwei;SUN Hao;ZHANG Jingkang(Department of Safety Science and Engineering,School of Mechanical and Electrical Engineering,China University of Petroleum(East China),Qingdao 266580,Shandong,China;Sinopec Research Institute of Safety Engineering,Qingdao 266071,Shandong,China;CNOOC Safety&Technology Service Co.Ltd.,Tianjin 300450,China)
出处
《化工学报》
EI
CAS
CSCD
北大核心
2021年第4期2328-2336,共9页
CIESC Journal
基金
国家重点研发计划项目(2019YFB2006305)
山东省自然科学基金项目(ZR2017MEE008)。
