DocumentCode :
2120457
Title :
Analysis of Fault Diagnosis Based on One Advanced Discernibility Function Reduction Algorithm
Author :
Zhang, Guang-yi ; Su, Yan-qin ; Gao, Shan
Author_Institution :
Naval Aeronaut. & Astronaut. Univ., Yantai, China
fYear :
2010
fDate :
24-26 Dec. 2010
Firstpage :
358
Lastpage :
361
Abstract :
Rough sets theory can eliminate the redundant and imprecise information effectively and correctly in fault diagnosis, which improve the real time and has much advantage of transforming afterwards and regular equipment logistics support to real-time logistics support. So the research on equipment fault diagnosis based on rough sets theory has much signification. The paper applies one advanced reduction algorithm based on discernibility function to some aero radio equipment´s fault diagnosis according to the deficiency of familiar attribution reduction algorithm based on discernibility function. The results show the algorithm can not only diagnose effectively and correctly but save much time.
Keywords :
avionics; fault diagnosis; radio equipment; rough set theory; advanced discernibility function reduction algorithm; aero radio equipment fault diagnosis; attribution reduction algorithm; equipment logistics support; imprecise information elimination; real-time logistics support; redundant information elimination; rough set theory; Fault diagnosis; Frequency synthesizers; Logistics; Real time systems; Receivers; Rough sets; Synchronization; attributive reduction algoithm; discernibility function; fault diagnosis; real-time;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Engineering (ISISE), 2010 International Symposium on
Conference_Location :
Shanghai
ISSN :
2160-1283
Print_ISBN :
978-1-61284-428-2
Type :
conf
DOI :
10.1109/ISISE.2010.86
Filename :
5945122
Link To Document :
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