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http://dx.doi.org/10.5139/JKSAS.2004.32.3.051

A Study on Intelligent Performance Diagnostics of a Gas Turbine Engine Using Neural Networks  

Kong, Chang-Duk (조선대학교 항공 조선 공학부)
Kho, Seong-Hee (조선대학교 항공우주공학과 대학원)
Ki, Ja-Young (조선대학교 항공 조선 공학부)
Publication Information
Journal of the Korean Society for Aeronautical & Space Sciences / v.32, no.3, 2004 , pp. 51-57 More about this Journal
Abstract
An intelligent performance diagnostic computer program of a gas turbine using the NN(Neural Network) was developed. Recently on-condition performance monitoring of major gas path components using the GPA(Gas Path Analysis) method has been performed in analyzing of engine faults. However because the types and severities of engine faults are various and complex, it is not easy that all fault conditions of the engine would be monitored only by the GPA approach Therefore in order to solve this problem, application of using the NNs for learning and diagnosis would be required. Among then, a BPN (Back Propagation Neural Network) with one hidden layer, which can use an updating learning rate, was proposed for diagnostics of PT6A-62 turboprop engine in this work.
Keywords
Intelligent Performance Diagnostic; Gas Path Analysis; Neural Network;
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