Earticle

초록

영어

Aiming at the becoming, uncertainty and space distributing of input multi-fault characteristic information in train intelligent control system fault diagnosis, a system structure for fault diagnosis of multi-information fusion in train intelligent control system is presented. The method of fault diagnosis of multi-information fusion in train intelligent control system based on fuzzy neural network and D-S evidential theory is discussed. Result of example indicates that this method can effectively improve the probability and reduce the uncertainty of diagnosis.

목차

Abstract
 1. Introduction
 2. Fuzzy Neutral Network, Evidential Theory & Multi-information Fusion
  2.1 Fuzzy Neutral Network and Multi-information Fusion
  2.2 Evidential Theory and Multi-information Fusion
  2.3 D-S Rule of Combination
 3. Hierarchical Structure and Model of Fusion System
  3.1 Hierarchical Structure of Multi-information Fusion of Fault Diagnosis in Train Intelligent Control System
  3.2 Fusion Model of Fuzzy Neutral Network
 4. Multi-information Fusion Fault Diagnosis Model in Train Intelligent Control System Based on Fuzzy Neutral Network and Evidential Theory
  4.1 Recognition Frame U
  4.2 Selection of Sensor
  4.3 Fuzzy Neutral Network Fusion
  4.4 Fusion Process
 5. Cases of Fault Diagnosis
 6. Conclusion
 Acknowledgements
 References

키워드

저자

• Li Ruoqiong [ School of Automation & Electrical Engineering, Lanzhou JiaoTong University, Lanzhou, Gansu ]
• Li Xin [ School of Automation & Electrical Engineering, Lanzhou JiaoTong University, Lanzhou, Gansu ]
• Zhang Youpeng [ School of Automation & Electrical Engineering, Lanzhou JiaoTong University, Lanzhou, Gansu ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605