DocumentCode
3169101
Title
Fault diagnosis method for HUD based on fuzzy BP neural network
Author
Huang Lei ; Jian-guo, Nan ; Yong-hua, Sui ; Guo Lei ; Xue-feng, Wang
Author_Institution
Dept. of Autom., Northwest Polytech. Univ., Xi´´an, China
fYear
2010
fDate
29-30 Oct. 2010
Firstpage
550
Lastpage
553
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.
Keywords
backpropagation; built-in self test; fault diagnosis; fuzzy neural nets; head-up displays; HUD; built in test equipment; fault diagnosis method; fuzzy BP neural network; head up display; Anodes; Fuzzy Neural Network; HUD; Knowledge-base; fault diagnosis;
fLanguage
English
Publisher
ieee
Conference_Titel
Artificial Intelligence and Education (ICAIE), 2010 International Conference on
Conference_Location
Hangzhou
Print_ISBN
978-1-4244-6935-2
Type
conf
DOI
10.1109/ICAIE.2010.5641101
Filename
5641101
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