Fault Isolation by Comparison of Event Lists Using a Weighted Distance

Author

Bouchair, Nabil ; Gayet, Philippe ; Charbonnier, Sylvie

Author_Institution

Eng. Dept., CERN, Geneva, Switzerland

fYear

2013

fDate

13-16 Oct. 2013

Firstpage

595

Lastpage

600

Abstract

A decision support system for operators monitoring complex systems is proposed. It consists in a fault isolation method based on pattern matching using binary information, in this case event lists. A training set composed of faults is used to create fault templates. Event lists generated by unknown faults are classified by comparing them with the fault templates using an original weighted distance. Each event is weighted using two independent criteria, one evaluating the frequency of appearance of the event in a given fault and the other evaluating the frequency of appearance of the same event in the other faults. The method was validated using data obtained from a realistic simulator of CERN Large Hadron Collider process and showed good performance.

Keywords

decision support systems; fault diagnosis; pattern classification; pattern matching; CERN Large Hadron Collider process; binary information; complex system monitoring; decision support system; event list classification; event lists; fault isolation; fault templates; pattern matching; weighted distance; Accuracy; Gases; Mathematical model; Monitoring; Sensors; Training; Vectors; binary data; decision support system; diagnostic; distance;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on

Conference_Location

Manchester

Type

conf

DOI

10.1109/SMC.2013.107

Filename

6721860