Open AccessIntelligent maintenance model for condition assessment of circuit breakers using fuzzy set theory and evidential reasoning
Author(s) -
Lin PoChun,
Gu JyhCherng,
Yang MingTa
Publication year - 2014
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2013.0124
Subject(s) - analytic hierarchy process , evidential reasoning approach , circuit breaker , fuzzy logic , reliability engineering , data mining , fuzzy set , set (abstract data type) , condition monitoring , computer science , fault (geology) , process (computing) , condition based maintenance , field (mathematics) , artificial intelligence , machine learning , engineering , operations research , decision support system , mathematics , pure mathematics , business decision mapping , electrical engineering , seismology , geology , programming language , operating system
This paper proposes a circuit breaker (CB) condition assessment model which combines the fuzzy set theory, the analytical hierarchy process (AHP) and evidential reasoning (ER). Four assessment factors, that is, (i) electrical characteristics, (ii) mechanical characteristics, (iii) insulation characteristics and (iv) miscellaneous factors, are selected as the condition parameters. A hierarchical assessment index system is constructed based on preventive tests data, intelligent electronic device monitoring data, maintenance data and operating environment. The inputted condition parameters indices are processed by the membership functions of a fuzzy distribution to obtain relative impairment grades which represent the relative grade of the CB condition towards the fault. The weights of the CB condition factors and indices are generated by the AHP based on experts’ interviews and feedbacks, and the final assessment is determined by ER according to the decision factors combined. An intelligent maintenance model is built with field examples to demonstrate the effectiveness of the proposed model in assessing the CB operation conditions.