TY - GEN
T1 - Full-order distributed fault diagnosis for large-scale nonlinear stochastic systems
AU - Noursadeghi, Elaheh
AU - Raptis, Ioannis
N1 - Publisher Copyright:
© Copyright 2015 by ASME.
PY - 2015
Y1 - 2015
N2 - This paper deals with the problem of designing a distributed fault detection and isolation algorithm for nonlinear large-scale systems that are subjected to multiple fault modes. To solve this problem, a network of detection nodes is deployed to monitor the monolithic system. Each node consists of an estimator with partial observation of the system's state. The local estimator executes a distributed variation of the particle filtering algorithm; that process the local sensor measurements and the fault progression model of the system. In addition, each node communicates with its neighbors by sharing pre-processed information. The communication topology is defined using graph theoretic tools. The information fusion between the neighboring nodes is performed by a distributed average consensus algorithm to ensure the agreement on the value of the local estimates. The simulation results demonstrate the efficiency of the proposed approach.
AB - This paper deals with the problem of designing a distributed fault detection and isolation algorithm for nonlinear large-scale systems that are subjected to multiple fault modes. To solve this problem, a network of detection nodes is deployed to monitor the monolithic system. Each node consists of an estimator with partial observation of the system's state. The local estimator executes a distributed variation of the particle filtering algorithm; that process the local sensor measurements and the fault progression model of the system. In addition, each node communicates with its neighbors by sharing pre-processed information. The communication topology is defined using graph theoretic tools. The information fusion between the neighboring nodes is performed by a distributed average consensus algorithm to ensure the agreement on the value of the local estimates. The simulation results demonstrate the efficiency of the proposed approach.
UR - https://www.scopus.com/pages/publications/84973345053
U2 - 10.1115/DSCC2015-9927
DO - 10.1115/DSCC2015-9927
M3 - Conference contribution
T3 - ASME 2015 Dynamic Systems and Control Conference, DSCC 2015
BT - Diagnostics and Detection; Drilling; Dynamics and Control of Wind Energy Systems; Energy Harvesting; Estimation and Identification; Flexible and Smart Structure Control; Fuels Cells/Energy Storage; Human Robot Interaction; HVAC Building Energy Management; Industrial Applications; Intelligent Transportation Systems; Manufacturing; Mechatronics; Modelling and Validation; Motion and Vibration Control Applications
PB - American Society of Mechanical Engineers
T2 - ASME 2015 Dynamic Systems and Control Conference, DSCC 2015
Y2 - 28 October 2015 through 30 October 2015
ER -