基于边界值的多元混沌发动机性能预测算法

史永胜; 彭朋; 宋云雪

基于边界值的多元混沌发动机性能预测算法

1.
中国民航大学航空工程学院,天津 300300
2.
深圳航空有限责任公司维修工程部,广东深圳 518128

基金项目: 国家自然科学基金委员会与中国民用航空总局联合资助(60879017,61179048); 天津市支撑计划项目(重点)(11ZCKFGX04100); 航空科学基金(20110267001)

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出版历程
- 收稿日期: 2011-01-25
- 修回日期: 2011-06-29
- 刊出日期: 2012-01-28

Multivariable chaotic arithmetic for aero-engine performance forecasting based on boundary values

1.
College of Aeronautical Engineering, Civil Aviation University of China, Tianjin 300300, China
2.
Maintenance and Engineering Department, Shenzhen Airlines, Shenzhen Guangdong 518128, China

摘要

摘要: 首先提取航空发动机排气温度数据序列的边界值,并且证明了边界值序列具有混沌特征.其次提出了一种基于多元相空间重构的发动机状态混沌预测算法,实现对排气温度的预测.通过检验排气温度预测值是否超过所规定的红线,从而进行发动机的健康状态排查.作为验证实例,使用一组某机型发动机实际飞行数据对该预测算法进行了验证,结果表明:该组合算法降低了预测模型的时间复杂度,并大大提高了疑似异常点的预测精度.该方法可以为这种机型发动机故障预测提供决策依据.
- 航空发动机 /
- 边界提取 /
- 排气温度 /
- 多变量相空间重构 /
- 预测
Abstract: Firstly,the boundary values of exhaust gas temperature(t_eg) was extracted from the original exhaust gas temperature data series.Further analysis on the boundary values data series indicated that there existed a chaos feature in it.Then,chaotic forecasting arithmetic based on multivariable phase space reconstruction was established to forecast the data series.Finally,by comparing the series with the red line,the condition of aero-engine was defined.The proposed arithmetic was verified through some type of aircraft aero-engine t_eg data series obtained from actual flight.The result shows that the proposed arithmetic can reduce the time complexity and has a better forecast accuracy in the prediction of outliers.It can be used as a supporting model in the decision making of this aero-engine fault forecast.
- aero-engine /
- boundary values extraction /
- exhaust gas temperature /
- multivariable phase space reconstruction /
- forecasting

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参考文献(13)

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