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
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;
Conference_Titel :
Control Conference (CCC), 2011 30th Chinese
Conference_Location :
Yantai
Print_ISBN :
978-1-4577-0677-6
Electronic_ISBN :
1934-1768