Fault diagnosis method for HUD based on fuzzy BP neural network

Lei Huang, Jian Guo Nan, Yong Hua Sui, Lei Guo, Xue Feng Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

For the insufficiency of the Built-in-test-equipment (BITE) of HUD and the ground fault diagnosis equipment, this paper provides a novel fault diagnosis based on fuzzy BP neural network for a certain type HUD by researching the fault diagnosis theory and methods. The proposed method simplifies the structure of the fault diagnosis system, and has a farther effective distinguish from the source of fault diagnosed by Built-in-test-equipment, and isolates the fault from the LRU level to the SRU level. Finally. the fault diagnosis example is provided with the typical test item. Experiments show that the proposed method shows better performance in fault diagnosis for HUD.

Original languageEnglish
Title of host publicationProceedings - 2010 International Conference on Artificial Intelligence and Education, ICAIE 2010
Pages550-553
Number of pages4
DOIs
StatePublished - 2010
Event2010 3rd International Conference on Artificial Intelligence and Education, ICAIE 2010 - Hangzhou, China
Duration: 29 Oct 201030 Oct 2010

Publication series

NameProceedings - 2010 International Conference on Artificial Intelligence and Education, ICAIE 2010

Conference

Conference2010 3rd International Conference on Artificial Intelligence and Education, ICAIE 2010
Country/TerritoryChina
CityHangzhou
Period29/10/1030/10/10

Keywords

  • Fault diagnosis
  • Fuzzy neural network
  • HUD
  • Knowledge-base

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