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Defect Diagnostics of Gas Turbine Engine Using Support Vector Machine and Artificial Neural Network  

Park Jun-Cheol (인하대학교 항공공학과)
Roh Tae-Seong (인하대학교 항공공학과)
Choi Dong-Whan (인하대학교 항공공학과)
Lee Chang-Ho (한국항공우주연구원 스마트무인기기술개발사업단)
Publication Information
Journal of the Korean Society of Propulsion Engineers / v.10, no.2, 2006 , pp. 102-109 More about this Journal
Abstract
In this Paper, Support Vector Machine(SVM) and Artificial Neural Network(ANN) are used for developing the defect diagnostic algorithm of the aircraft turbo-shaft engine. The system that uses the ANN falls in a local minima when it learns many nonlinear data, and its classification accuracy ratio becomes low. To make up for this risk, the Separate Learning Algorithm(SLA) of ANN has been proposed by using SVM. This is the method that ANN learns selectively after discriminating the defect position by SVM, then more improved performance estimation can be obtained than using ANN only. The proposed SLA can make the higher classification accuracy by decreasing the nonlinearity of the massive data during the training procedure.
Keywords
Support Vector Machine; Artificial Neural Network; Separate Learning Algorithm;
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1 김기성, 황진수, "Support Vector Machine을 이용한 분류분석", 인하대학교 통계학과 대학원 석사 논문, 2003
2 Stanislaw Osowski, Krzysztof Siwek, Tomasz Markiewicz, "MLP and SVM Networks - a Comparative Study", Proceedings of the 6th Nordic Signal Processing Symposium - NORSIG 2004
3 어상준, "Support Vector Machine을 이용한 문서 정보 기반의 단백질 기능 분류", 석사학위논문, 서울대학교 컴퓨터공학과, 2004
4 강문식, 이상용, "데이터 마이닝을 위한 경쟁학습모델과 BP 알고리즘을 결합한 하이브리드형 신경망", 한국정보기술응용학회, 제9권 2호, 2002, pp.1-16
5 K. Schittkowski, "QL: A Fortran Code for Convex Quadratic Programming - User's Guide, Version 2.1", University of Bayreuth , 2004
6 Christopher J.C. Burges, "A Tutorial on Support Vector Machines for Pattern Recognition", Kluwer Academic Publishers, Boston, pp.1-433
7 오장민, "신경망 기반의 자연 언어 문서 검색", 석사학위논문, 서울대학교 컴퓨터공학과, 1999