Title :
Bayesian fault diagnosis in large-scale measurement systems
Author :
Barford, Lee ; Kanevsky, Valery ; Kamas, Linda
Author_Institution :
Agilent Labs., Palo Alto, CA, USA
Abstract :
Because of both increasing complexity and increasing geographic distribution, faults in measurement systems are becoming more troublesome to diagnose in all life-cycle phases: manufacturing, deployment, and operation. This paper considers which features are necessary in an automatic diagnosis system for large-scale measurement systems. The paper describes MonteJade, a diagnosis system designed with these essential features in mind. Examples are given of MonteJade diagnosing faults and determining the next debugging actions to perform, in a measurement system constructed from more than one hundred components.
Keywords :
Bayes methods; diagnostic expert systems; electronic equipment testing; fault diagnosis; measurement systems; Bayesian fault diagnosis; MonteJade diagnosis system; analog system fault diagnosis; automatic diagnosis; debugging actions; diagnosis accuracy; diagnostic expert systems; digital system fault diagnosis; geographically distributed measurement systems; large-scale measurement systems; measurement system data handling; Automatic testing; Bayesian methods; Circuit faults; Debugging; Fault diagnosis; Instruments; Large-scale systems; Performance evaluation; Phase measurement; System testing;
Conference_Titel :
Instrumentation and Measurement Technology Conference, 2004. IMTC 04. Proceedings of the 21st IEEE
Print_ISBN :
0-7803-8248-X
DOI :
10.1109/IMTC.2004.1351288
