TY - GEN
T1 - Fault diagnosis of avionics system based on artificial neural network
AU - Xu, Qingshan
AU - Chen, Jie
AU - Wu, Boying
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/12
Y1 - 2020/12
N2 - Prognostics and health management can be used for monitoring and life prediction of integrated modular avionics systems. As one of the methods of prognostics and health management, the BP neural network has good self-learning, self-adaptation and generalization capabilities, but it is easy to fall into a local minimum during the operation. Therefore, this paper chooses to use genetic algorithm to optimize the initial weights and thresholds of the BP neural network training, which can greatly improve the accuracy of the BP neural network for fault diagnosis; at the same time, choose to use unsupervised learning self-organizing feature map for fault diagnosis. The simulation results show that the fault diagnosis accuracy rate of the BP neural network optimized by the genetic algorithm is greatly improved, and self-organizing feature map can reach a higher fault sample classification accuracy rate after 200 training.
AB - Prognostics and health management can be used for monitoring and life prediction of integrated modular avionics systems. As one of the methods of prognostics and health management, the BP neural network has good self-learning, self-adaptation and generalization capabilities, but it is easy to fall into a local minimum during the operation. Therefore, this paper chooses to use genetic algorithm to optimize the initial weights and thresholds of the BP neural network training, which can greatly improve the accuracy of the BP neural network for fault diagnosis; at the same time, choose to use unsupervised learning self-organizing feature map for fault diagnosis. The simulation results show that the fault diagnosis accuracy rate of the BP neural network optimized by the genetic algorithm is greatly improved, and self-organizing feature map can reach a higher fault sample classification accuracy rate after 200 training.
KW - BP neural network
KW - Genetic algorithm (GA)
KW - Integrated modular avionics systems (IMA)
KW - Prognostics and health management (PHM)
KW - Self-organizing feature map (SOM)
UR - http://www.scopus.com/inward/record.url?scp=85106877553&partnerID=8YFLogxK
U2 - 10.1109/ICMCCE51767.2020.00228
DO - 10.1109/ICMCCE51767.2020.00228
M3 - 会议稿件
AN - SCOPUS:85106877553
T3 - Proceedings - 2020 5th International Conference on Mechanical, Control and Computer Engineering, ICMCCE 2020
SP - 1040
EP - 1045
BT - Proceedings - 2020 5th International Conference on Mechanical, Control and Computer Engineering, ICMCCE 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th International Conference on Mechanical, Control and Computer Engineering, ICMCCE 2020
Y2 - 25 December 2020 through 27 December 2020
ER -