摘要
性能参数监控是航空发动机监控的重要手段之一,而对性能参数进行预测可以提前掌握航空发动机在未来时刻的性能状况,从而预防和排除故障。本文首先介绍了改进的加权一阶局域混沌预测算法,然后对航空发动机性能参数(转差率S)进行了混沌识别,最后采用改进的加权一阶局域预测算法对航空发动机性能参数进行了混沌预测。实验结果表明,改进的加权一阶局域预测算法具有很好的学习能力和较高的预测精度,适用于航空发动机性能参数监控。
Performance parameter monitoring is a key means of aeroengine monitoring, and performance parameter forecasting can be used to obtain the future performance condition of aeroengine, thus preventing and eliminating faults. This article firstly introduces the improved local weighted linear chaotic forecast model briefly, then the aeroengine character parameter （i.e. rotor speed ratio S） is recognized as chaotic, at last the aeroengine character parameter is forecasted by using the improved local weighted linear forecast model. Experimental results show that the improved local weighted linear forecast model has good learning capability and high forecasting accuracy, which is suitable to aeroengine character parameters monitoring.
作者
邸亚洲
高峰
王小飞
曲建岭
DI Ya-zhou GAO Feng WANG Xiao-fei QU Jian-ling(Naval Aeronautical Engineering Institute Qingdao Branch, Qingdao 266041, China)
出处
《电子设计工程》
2017年第3期141-144,共4页
Electronic Design Engineering
基金
国家自然科学基金(51505491)
关键词
性能参数
发动机监控
混沌识别
混沌预测
performance parameter
aeroengine monitoring
chaotic recognition
forecasting
chaotic forecasting
