期刊文献+

基于混合卡尔曼滤波器组的航空发动机双通道传感器故障检测 被引量:3

Aircraft Engine Sensor Fault Diagnostics Through Dual-Channel Sensor Measurements Based on a Bank of Hybrid Kalman Filters
下载PDF
导出
摘要 基于机载非线性模型与分段线性卡尔曼滤波器混合组成的混合卡尔曼滤波器组,结合双通道传感器的特点,建立了民用航空发动机传感器故障诊断系统;给出故障诊断原理及算法的同时,将该系统应用于民用涡扇发动机传感器常见典型故障进行了仿真;仿真结果表明,诊断系统可以在发动机发生健康蜕化后,通过只简单更新机载模型的蜕化因子,而保持线性卡尔曼滤波器的参数不变,便能准确地检测和隔离各类传感器故障而不发生误报;该更新过程可以在线自动完成,省时省力,易于工程实现。 Based on a bank of hybrid Kalman filters which are hybrids of a nonlinear on-board engine model(NOBEM) and piecewise linear Kalman filters,a civil aircraft engine sensor fault diagnostics system which utilizes dual-channel sensor measurements is developed.Principles and algorithms of sensor fault detection,isolation and accommodation are given.By this system applied to some typical civil turbofan engine sensor faults,simulation results show that the diagnostic effectiveness of the system is maintained to avoid false alarms as the health of the engine degrades over time through a simple process: by feeding the health degradation values into the NOBEM and not changing the parameters of the linear Kalman filters.The update process,which can be completed automatically online to save time and effort,is feasible in the real application environment.
出处 《计算机测量与控制》 CSCD 北大核心 2012年第1期21-24,共4页 Computer Measurement &Control
关键词 航空、航天推进系统 混合卡尔曼滤波器组 健康蜕化 传感器故障诊断 aerospace propulsion system a bank of hybrid Kalman filters health degradation sensor fault diagnostics
  • 相关文献

参考文献4

二级参考文献26

  • 1方昌德.发动机状态监视和故障诊断系统的发展[J].国际航空,2005(6):66-68. 被引量:4
  • 2袁春飞,姚华,杨刚.航空发动机机载实时自适应模型研究[J].航空学报,2006,27(4):561-564. 被引量:25
  • 3Litt J S,Simon D L,Garg S,et al. A survey of intelligent control and health management technologies for aircraft propulsion systems [R]. NASA/TM-2005-213622: ARL-TR-3413,2005.
  • 4Luppold R H, Roman J R, Gallops G W, et al. Estimating in-flight engine performance variations using kalman filter concepts[R]. AIAA-89-2584,1989.
  • 5Volponi A J, Depold H, Ganguli R, et al. The use of kal man filter and neural network methodologies in gas turbine performance diagnostics: a comparative study[J]. Journal of Engineering for Gas Turbines and Power,2003,125(4) : 917-924.
  • 6Borguet S, Dewallef P, Leonard O. A way to deal with model-plant mismatch for a reliable diagnosis in transient operation[J]. Journal of Engineering for Gas Turbines and Power, 2008,130(3) : 31601 (8 pages).
  • 7Sugiyama N. System identification of jet engines[J]. Jour nal of Engineering for Gas Turbines and Power, 2000,122 (1) :19-26.
  • 8Kobayashi T,Simon D L. Integration of on line and off line diagnostic algorithms for aircraft engine health management[J]. Journal of Engineering for Gas Turbines and Power,2007,129(4) : 986-993.
  • 9Tagashira T, Mizuno T, Koh M, et al. ATF test evaluation of model based control for a single spool turbojet engine [R]. ASME Paper GT2009-59854,2009.
  • 10Sugiyama N. Derivation of ABCD system matrices from nonlinear dynamic simulation of jet engines[R]. AIAA-92-23319,1992.

共引文献45

同被引文献21

  • 1姜彩虹,孙志岩,王曦.航空发动机预测健康管理系统设计的关键技术[J].航空动力学报,2009,24(11):2589-2594. 被引量:37
  • 2袁春飞,姚华,杨刚.航空发动机机载实时自适应模型研究[J].航空学报,2006,27(4):561-564. 被引量:25
  • 3王占学,刘增文,叶新农.某型涡扇发动机部件老化对性能影响的分析与计算[J].航空动力学报,2007,22(5):792-796. 被引量:19
  • 4Litt J S, Simon D L, Garg S, et al. A Survey of lntelli-gent Control and Health Management Technologies for Aircraft Propulsion Systems [ R ]. NASA/TM 2005- 213622.
  • 5Jaw L C. Recent Advancements in Aircraft Engine Health Management (EHM) Technologies and Recommendations for The Next Step[ R]. ASME 2005-GT-68625.
  • 6Kobayashi T. Aircraft Engine Sensor/Actuator/Compo- nent Fault Diagnosis Using a Bank of Kalman Filters[ R]. NASA/ CR 2003-212298.
  • 7Xue Wei, Guo Ying-qing. Aircraft Engine Sensor Fault Diagnostics Based on Estimation of Engine' s Health Deg- radation[J]. Chinese Journal of Aeronautics. 2009, 22 (1): 18-21.
  • 8Kobayashi T, Simon D L. Hybrid Kalman Filter Approachfor Aircraft Engine in-Flight Diagnostics: Sensor Fault Detection Case[ R]. NASA/TM 2006-214418.
  • 9Kobayashi T, Simon D L. Hybrid Kalman Filter: A New Approach for Aircraft Engine in-Flight Diagnostics [ R ]. NASA / TM 2006-214491.
  • 10Kobayashi T, Simon D L. Evaluation of an Enhanced Bank of Kalman Filters for in-Flight Aircraft Engine Sen- sor Fault Diagnostics[ R]. NASA/TM 2004-213203.

引证文献3

二级引证文献25

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部