摘要
提出了一种基于神经网络的发动机性能实时检测与故障诊断系统。其诊断的特点是利用各种传感器实时采集数据 ,结合人工神经网络 ,从不同的角度、不同层次进行诊断推理 ,并以神经网络来完成自学习功能 ,大大提高了诊断的效率。研究提出了实时诊断系统的各种抗干扰措施 ,通过实验验证 ,该系统具有较高的准确性 。
In accordance with the historical data and the real time data collected from the different sensors, a system of performance inspecting and fault diagnosis for engines in real time was built up based on the theory of neural network. The features of this system are: (1) It combines the real time data collecting with ANN to diagnose the fault. (2) It can diagnose faults from different aspects and different layers by several different ways. (3) The function of self learning is realized by ANN module. Using this system, users can analyze and diagnose the faults quickly and easily. The hardware structure, the software function and the principles of working and practicability of this system were introduced. The functions, methods and actualized principles of the system were expounded emphatically. It was proved by the experiments that the system had merits both high accuracy and economical practicability.
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2001年第4期80-83,共4页
Transactions of the Chinese Society for Agricultural Machinery
基金
浙江省科技基金重点资助项目 (项目编号 :96 110 10 48)
关键词
神经网络
发动机
故障诊断
实时检测
Neural networks, Engine, Fault diagnosis, Measurement
