Abstract:
Automatic fault diagnostic schemes rely on various types of sensors (e.g., temperature, pressure, vibration, etc.) to measure the system parameters. Efficacy of a diagnos...Show MoreMetadata
Abstract:
Automatic fault diagnostic schemes rely on various types of sensors (e.g., temperature, pressure, vibration, etc.) to measure the system parameters. Efficacy of a diagnostic scheme is largely dependent on the amount and quality of information available from these sensors. The reliability of sensors, as well as the weight, volume, power, and cost constraints, often makes it impractical to monitor a large number of system parameters. An optimized sensor allocation that maximizes the fault diagnosability, subject to specified weight, volume, power, and cost constraints is required. Use of optimal sensor allocation strategies during the design phase can ensure better diagnostics at a reduced cost for a system incorporating a high degree of built-in testing. In this paper, we propose an approach that employs multiple fault diagnosis (MFD) and optimization techniques for optimal sensor placement for fault detection and isolation (FDI) in complex systems.
Published in: 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583)
Date of Conference: 10-13 October 2004
Date Added to IEEE Xplore: 07 March 2005
Print ISBN:0-7803-8566-7
Print ISSN: 1062-922X