센서 고장 검출 기법의 수질 계측 시스템에의 적용

Application of Sensor Fault Detection Method to Water Measurement System

  • 이영삼 (군산대학교 전자정보공학부) ;
  • 한윤종 (군산대학교 전자정보공학부) ;
  • 김성호 (군산대학교 전자정보공학부)
  • Lee, Young-Sam (School of Electronics and Information Eng., Kunsan National University) ;
  • Han, Yun-Jong (School of Electronics and Information Eng., Kunsan National University) ;
  • Kim, Sung-Ho (School of Electronics and Information Eng., Kunsan National University)
  • 발행 : 2003.07.21

초록

NLPCA(Nonlinear Principal Component Analysis is a novel technique for multivariate data analysis, similar to the well-known method of principal component analysis. NLPCA can be implemented by a feedforward neural network called AANN (AutoAssociative Neural Network) which performs the identity mapping. In this work, a sensor fault detection system based on NLPCA and Maximum Likelihood Estimation scheme is presented. To verify its applicability, simulation study on the data supplied from Saemangeum measurement stations is executed.

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