TY - GEN
T1 - Fault detection and diagnosis using PDF for stochastic distribution systems
AU - Li, Tao
AU - Zheng, Weixing
AU - Yao, Xiuming
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
UR - http://handle.uws.edu.au:8081/1959.7/544933
M3 - Conference Paper
SN - 9789881725592
SP - 117
EP - 121
BT - Proceedings of the 30th Chinese Control Conference, July 22-24, 2011, Yantai, China
PB - IEEE
T2 - Chinese Control Conference
Y2 - 25 July 2012
ER -