Optimal sensor allocation for fault detection and isolation

• Published in: 2004 IEEE International Conference on Systems, Man and Cybernetics Vol. 2; pp. 1309 - 1314 vol.2
• Main Authors: Azam, M., Pattipati, K., Patterson-Hine, A.
• Format: Conference Proceeding
• Language: English
• Published: Ames Research Center IEEE 2004
• Subjects: Applied sciences; Computer science; control theory; systems; Condition monitoring; Constraint optimization; Control theory. Systems; Cost function; Exact sciences and technology; Fault detection; Information systems. Data bases; Memory organisation. Data processing; Modelling and identification; Operational research and scientific management; Operational research. Management science; Power system reliability; Pressure measurement; Reliability theory. Replacement problems; Sensor systems; Software; System testing; Systems Analysis And Operations Research; Temperature sensors; Vibration measurement; Quality assurance; Optimal strategy; Transducer position; Vibration; Optimal allocation; Complex system; Measurement sensor; Reliability; Fault diagnostic; Measurement error; Optimization; Defect detection
• ISBN: 0780385667; 9780780385665
• ISSN: 1062-922X
• DOI: 10.1109/ICSMC.2004.1399806

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.