In order to solve the problem of insufficient text data mining in the risk analysis process of aircraft maintenance,an improved Apriori association rule mining method based on binary logic AND operation was proposed.By using the unsafe event reports of aircraft maintenance collected from aircraft maintenance enterprises from 2012 to 2021,the risk elements with coupling and correlation in the civil aviation maintenance field were successfully mined,and the association rules between risk elements were analyzed.The results show that the running time of the improved algorithm is reduced from 0.153 s to 0.034 s.The main factors identified in the mining of maintenance risks include incomplete aircraft inspections and personnel forget-ting/negligence,which are consistent with the actual engineering situation.The research results can provide decision support for maintenance safety management.
维普
万方数据