数据挖掘在航空发动机状态判别中的应用

摘要

In order to tap the information and knowledge hidden behind the flight data, we use data mining technology to judge and research the health statua of aero-engine. Making use of nine parameters and typical fault data related with engine health, the models of neural network and decision tree were established respectively, and the optimum model of classification and prediction was determined by comparing the results.%为了挖掘隐藏在飞参数据背后的信息知识,应用数据挖掘技术对航空发动机健康状态进行判别研究.利用飞参数据中与发动机健康状态相关的九个参数和典型的故障数据,分别建立了神经网络和决策树模型,通过结果的比较,确定了最佳分类预测模型.