基于案例推理和粗糙集的商用飞机故障诊断研究

Research on Fault Diagnosis of Commercial Aircraft Based on Case Base Reasoning and Rough SetYan Zhenqian1, Cao Lei2,3,4, Chen Jin1

摘要:

本文将采用基于案例推理和粗糙集的方法进行国产商用飞机故障诊断的研究。其中,用MongoDB存储飞机故障案例库,通过构建中文航空词本进行同义词替换减少案例描述的中文表述差异,使用粗糙集表示故障案例,粗糙集确定属性权重结合海明距离实现案例检索,并通过实例验证该方法的可行性和有效性,最后是案例库学习提高基于案例推理系统的可靠性。

Abstract:

This paper will use case-based reasoning and rough set methods to conduct commercial aircraft fault diagnosis research. MongoDB is used to store the aircraft fault case, and the constructed Chinese aviation wordbook is used to replace synonyms to reduce the difference in the Chinese expression of the case description. The rough set is used to represent the case, attribute weights by rough set and hamming distance are used to case retrieval, and verify the feasibility and effectiveness of the method by the instance case. Finally, case library learning improves the reliability of case-based reasoning system.