SUN Yi-gang, WANG Lei, XUE Zhong-rui, et al. Hard fault detection of aero-engine sensor based on BP network[J]. 2013, 32(7): 120-122. DOI: 10.13873/j.1000-97872013.07.009.
基于BP网络的航空发动机传感器硬故障检测
摘要
研究了航空发动机传感器的故障类型。针对传感器硬故障本身的特点
使用神经网络训练并建立发动机传感器模型
依据建立的模型线计算出传感器正常运行时上下阈值
最后将计算出来的阈值嵌入到工控机中
进行航空发动机传感器在线实时硬故障检测的仿真模拟。整个算法软件采用C++语言编写
占用资源少、运行速度快、精度高、实时性强
根据仿真图形分析
该算法软件能够准确地监测航空发动机传感器的故障。
Abstract
Fault types of sensor of aero-engine is researched.Aiming at characteristic of hard fault
using neural network to train and establish model of aero-engine sensors
according to constructed lines of model
the maximum and minimum threshold value for sensors to work normally is calculated
and the calculated threshold values are embedded to IPC
in which the aero-engine sensors are online real-time simulated on hard fault detection.The algorithm software is written in C + +
which takes little resource but runs fast
high precision and good real-time performance
according to analysis on simulation graph
the program can accurately mornitor fault of aero-engine sensors.