关键词: 快速存取记录器数据, 粗糙集, 离散化, 属性约简, 规则提取

Abstract: Researches on characteristics of QAR data and rough set theory, combined with knowledge of information decision tables are used in the paper to inspect the QAR outliers in the data mining to support aircraft fault detection and exclusion. It utilizes the application of rough set theory characteristics to discretize the QAR data, establishes decision tables for discretized data, performs attribute reduction and rule extraction for the decision tables. According to the particularities of the QAR data, improved algorithms are given for both of discretization of the QAR data and decision table attribute reduction in this article. Finally, the paper compares the results of project trials with the data given by experts, it proves that improved algorithms are feasible and efficient, improving the efficiency of the aircraft troubleshooting, having very important practical significance.

Key words: Quick Access Recorders（QAR） data, rough set, discretization, attribute reduction, rule extraction