DocumentCode :
550558
Title :
Fault detection and diagnosis using PDF for stochastic distribution systems
Author :
Li Tao ; Zheng Weixing ; Yao Xiuming
Author_Institution :
Dept. of Inf. & Commun., Nanjing Univ. of Inf. Sci. & Technol., Nanjing, China
fYear :
2011
fDate :
22-24 July 2011
Firstpage :
117
Lastpage :
121
Abstract :
With the rapid advances in sensor technology, image manipulation and data processing, the feedback measurement information is the stochastic distribution of the system output rather than its value. In this paper, based on the output probability density functions (PDFs) and neural networks, a new fault detection and diagnosis strategy is studied by designing an adaptive observer. The designed observer can not only detect the fault, but also realize the fault diagnosis. Computer simulations are given to demonstrate the efficiency of the proposed approach.
Keywords :
adaptive systems; control system synthesis; fault diagnosis; feedback; neural nets; observers; statistical distributions; stochastic systems; PDF; adaptive observer design; computer simulation; data processing; fault detection; fault diagnosis; feedback measurement information; image manipulation; neural networks; output probability density function; sensor technology; stochastic distribution system; Circuit faults; Fault detection; Neural networks; Observers; Spline; Stochastic processes; Stochastic systems; Fault detection; PDF; fault diagnosis; observer design;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2011 30th Chinese
Conference_Location :
Yantai
ISSN :
1934-1768
Print_ISBN :
978-1-4577-0677-6
Electronic_ISBN :
1934-1768
Type :
conf
Filename :
6000897
Link To Document :
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