摘要
为探讨LNG工厂气动阀故障率与季节、温度的关系,帮助制定气动阀检修方案,运用GM(1,1)模型群进行简便图形预测。该方法既能反映气动阀故障率周期性波动特征,又不局限于常规时间序列数据建模要求的原始数据平稳性检验和数据分布假设性制约。研究得出:GM(1,1)模型能最少运用最近4组数据进行运算,有着“贫信息、小样本”的通用性优势,助LNG工厂进行零件库存和检修工作优化。
In order to explore the relationship between the failure rate of pneumatic valves in LNG plants and the season and temperature,and to help work out the maintenance plan for pneumatic valves,GM(1,1)model group was used to do simple graphical prediction.This method not only reflects the periodic fluctuation characteristics of pneumatic valve failure rate,but also is not limited to the stationary test of original data and data distribution assumptive restriction required by conventional time series data modeling.The findings show that GM(1,1)model can be used to calculate at least the latest four groups of data,and has the universality advantage of"poor information and small sample",which helps LNG plants to optimize parts inventory and maintenance.
作者
李杰
LI Jie(Jianghan Oil Production Plant,Sinopec Jianghan Oilfield Company,Huanggang,Hubei 438011,China)
出处
《江汉石油职工大学学报》
2022年第6期22-24,共3页
Journal of Jianghan Petroleum University of Staff and Workers
