基于神经网络和模糊逻辑的航空发动机状态监视

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Condition monitoring of aero-engine based on neural network and fuzzy logic

1.
College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
2.
China Aviation Powerplant Research Institute, Aviation Industry Corporation of China, Zhuzhou 412002, China

摘要: 设计了基于神经网络和模糊逻辑的航空发动机状态监视系统,它包含数据有效性检查和发动机健康评估.系统利用BP(back propagation)神经网络对发动机进行数据有效性检查,根据发动机的状态确定测量参数的有效边界以检测发动机的测量参数是否超限;利用模糊逻辑对发动机健康状况进行实时的评估,监控发动机因性能蜕化引起的异常.通过对某型涡扇发动机仿真,验证了基于神经网络和模糊逻辑的状态监视系统的有效性.
- 航空发动机 /
- 状态监视 /
- 神经网络 /
- 模糊逻辑
Abstract: The condition monitoring system based on neural network and fuzzy logic for an aero-engine was proposed,which covered data validity and health assessment.According to the validity inspection of dynamic data based on BP(back propagation) neural network,the measurement parameters exceeding normal boundary or otherwise was detected,and the boundary of instantaneous parameter could change along with aero-engine status.Fuzzy logic was used to estimate health parameters,and the abnormity caused by performance degradation was real-time monitored.Digital simulation carried out on a given turbofan engine highlights the validity of the condition monitoring system based on neural network and fuzzy logic.
- aero-engine /
- condition monitoring /
- neural network /
- fuzzy logic

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