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Study on Fault Diagnostics of a Turboprop Engine Using Fuzzy Logic and BBNN  

Kong, Chang-Duk (조선대학교 항공우주공학과)
Lim, Se-Myung (조선대학교 항공우주공학과)
Kim, Keon-Woo (조선대학교 항공우주공학과)
Publication Information
Journal of the Korean Society of Propulsion Engineers / v.15, no.2, 2011 , pp. 1-7 More about this Journal
Abstract
The UAV(Unmanned Aerial Vehicle) which is remotely operating with long endurance in high altitude must have a very reliable propulsion system. The precise fault diagnostic system of the turboprop engine as a propulsion system of this type UAV can promote reliability and availability. This work proposes a diagnostic method which can identify the faulted components from engine measuring parameter changes using Fuzzy Logic and quantify its faults from the identified fault pattern using Neural Network Algorithms. It is found by evaluation examples that the proposed diagnostic method can detect well not only single type faults but also multiple type faults.
Keywords
Turboprop Engine; Feed Forward Back Propagation; Fuzzy Logic; Neural Network Algorithm;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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