摘要
飞机发动机故障往往表现出一种故障表征出多种特征信号,同一特征信号还可能反映了不同的故障的特点,而传统的基于灰色理论的飞机发动机故障预测由于只考虑表征发动机故障的一个特征参数或单独考虑几个特征参数,使得预测的准确性不能满足实际工程需要。针对某型发动机故障,借鉴灰色预测建模和信息融合的思想,提出了基于多故障特征参数的发动机故障预测模型,使得多个相关特征参数时间序列不仅可以为各自的预测提供相关信息,也可为其他序列预测提供必要的信息,增加了预测的准确性。仿真验证结果表明,该预测模型具有较高的预测准确性,是一个有效的预测模型。
The aero-engine faults often characterize as a variety of feature signal, and the same characteristic signal may also reflect the different faults. But the traditional aero-engine fault prediction methods based on grey theory have not sufficient accuracy to fulfill the engineering requirement because only one characteristic parameter is considered or several characteristic parameters are considered in isolation. This paper analyzes a certain aero-engine faults, and a multi-parameter prediction model is proposed based on the idea of grey forecast model and information fusion. Using this model, the relevant parameters of time-series can be not only to provide for their own forecast information but also to provide the necessary information for the others, so the accuracy of the forecast is improved. Finally, a good forecast effect is given through an aero-engine fault prediction example, the obtained results show that the model is availability.
出处
《计算机工程与应用》
CSCD
2012年第13期240-243,共4页
Computer Engineering and Applications
基金
陕西省自然科学基础研究计划(No.2010JQ8005)
航天支撑技术基金项目
航空科学基金项目(No.2010ZD53039)
关键词
发动机故障
多参数
灰色预测
预测模型
aero-engine fault
multi-parameter
grey prediction
prediction model
