基于数据挖掘的飞机系统故障关联规则研究

Research on Aircraft System Fault Association Rules Based on Data Mining

为在日常运行中降低飞机系统故障率,提高飞机运行的可靠度,运用Apriori算法挖掘飞机系统故障间的关联规则。首先从2010-2019年间有记录的空客A320和波音B737系列飞机故障案例中提取有效数据,建立原始数据库;然后使用Apriori算法建立飞机系统故障关联规则挖掘模型,确定最小支持度和置信度;最后,使用MATLAB编程,遍历数据库,挖掘出各故障间的强关联规则。实证计算结果显示,飞机系统不同故障间存在隐形联系和不同强度的关联规则。

In order to reduce the failure rate of aircraft system and improve the reliability of aircraft operation,Apriori algorithm is used to mine the association rules among aircraft system faults.Firstly,the effective data are extracted from the fault cases of Airbus A320 and Boeing B737 series aircraft which have been recorded from 2010 to 2019,and the original database is established.Then,the mining model of aircraft system fault association rules is established by using Apriori algorithm to determine the minimum support and confidence.Finally,MATLAB programming is used to traverse the database to mine strong association rules among faults.The empirical results show that there are invisible connections and association rules with different strength among different faults of aircraft system.