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.
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ASME 2015 Dynamic Systems and Control Conference
October 28–30, 2015
Columbus, Ohio, USA
Conference Sponsors:
- Dynamic Systems and Control Division
ISBN:
978-0-7918-5725-0
PROCEEDINGS PAPER
Full-Order Distributed Fault Diagnosis for Large-Scale Nonlinear Stochastic Systems Available to Purchase
Elaheh Noursadeghi,
Elaheh Noursadeghi
University of Massachusetts Lowell, Lowell, MA
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Ioannis Raptis
Ioannis Raptis
University of Massachusetts Lowell, Lowell, MA
Search for other works by this author on:
Elaheh Noursadeghi
University of Massachusetts Lowell, Lowell, MA
Ioannis Raptis
University of Massachusetts Lowell, Lowell, MA
Paper No:
DSCC2015-9927, V002T19A004; 10 pages
Published Online:
January 12, 2016
Citation
Noursadeghi, E, & Raptis, I. "Full-Order Distributed Fault Diagnosis for Large-Scale Nonlinear Stochastic Systems." Proceedings of the ASME 2015 Dynamic Systems and Control Conference. Volume 2: 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. Columbus, Ohio, USA. October 28–30, 2015. V002T19A004. ASME. https://doi.org/10.1115/DSCC2015-9927
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