| 王灿灿1，孔祥兴2，梁宁宁2，童志伟3.航空发动机增强型机载自适应模型气路故障诊断方法[J].航空发动机,2021,47(S1):108-114 |
| 航空发动机增强型机载自适应模型气路故障诊断方法 |
| Research on Gas Path Fault Diagnosis of Aeroengine Enhanced Self Tuning on-board Real-time Model |
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| DOI： |
| 中文关键词: 气路故障诊断 增强型自适应模型 性能基线模型 健康管理 航空发动机 |
| 英文关键词:gas path fault diagnosis enhanced self tuning on-board real-time model performance baseline model health manage⁃
ment aeroengine |
| 基金项目:国防重点工程项目资助 |
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| 中文摘要: |
| 针对航空发动机在工程应用中气路健康状态的评估问题，提出一种基于增强型机载自适应模型的气路故障诊断方法。
该方法在机载模型中加入神经网络补偿算法，在线修正机载模型的输出误差，提高了卡尔曼滤波器估计精度，以此为基础建立了
发动机增强型自适应模型和性能基线模型。增强型自适应模型可实时评估健康参数状态，并指导性能基线模型跟踪发动机正常
性能降级趋势，确保剪裁精准的故障信息用于检测和诊断。基于发动机性能仿真模型模拟故障特征数据库，采用RBF神经网络训
练样本，完成了故障模式判定和故障隔离。通过构建某型涡轴发动机气路故障诊断平台进行仿真验证，结果表明：该方法能够有
效监视发动机在全包线、全寿命周期的气路健康状况，在实际工作流程中具备可行性。 |
| 英文摘要: |
| A gas path fault diagnosis approach based on enhanced self tuning on-board real-time model was proposed for aeroengine
gas path health assessment in engineering application. In this method，neural network compensation algorithm was introduced into onboard
model for declining output errors and improving Kalman filter’s accuracy，as well as establishing enhanced self tuning model and
performance baseline model. The enhanced self tuning model evaluated health parameters in real time，which provided normal perfor?
mance degradation trend for performance baseline model to ensure the accurate information was used in detection and diagnosis. Fault fea?
ture database was established based on the engine performance simulation model，and the RBF neural network was used to train samples to
achieve fault mode deter-mination and fault isolation.The simulation results of a turbo-shaft engine gas path fault diagnosis plat-form show
that it can monitor gas path health status effectively in full flight envelope and life cycle，and it is feasible in practical engineering process. |
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