지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록· 키워드
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In the field of fault diagnosis, the deviations from normal operating conditions are monitored to identify the type of faults and find their root causes. One of the most representative methods is the statistical approaches, due to a large amount of advantages. However, ambiguous diagnosis results can be generated according to fault magnitudes, even if the same fault occurs. To tackle this issue, this work proposes principal component analysis (PCA) based method with qualitative information. The PCA model is constructed under normal operation data and the residuals from faulty conditions are calculated. The significant changes of these residuals are recorded to make the information for identifying the types of fault. This model can be employed easily and the tasks for building are smaller than these of other common approaches. The efficacy of the proposed model is illustrated in Tennessee Eastman process.
목차
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참고문헌 (6)
참고문헌 신청
C. J. Lee / 2012 / A Fault Magnitude Based Strategy for Effective Fault Classification / Chemical Engineering Research and Design 91(3):530~541
윤인섭 / 2004 / Support Vector Machine을 이용한 화학공정 모니터링에 관한 연구 / Korean Chemical Engineering Research(HWAHAK KONGHAK) 42(5):538~544
M. Kano / 2001 / A New Multivariate Statistical Process Monitoring Method using Principal Component Analysis / Computers and Chemical Engineering 25:1103~1113
L. H. Chiang / 2001 / Fault Detection and Diagnosis in Industrial Systems / Springer-verlag
J. J. Downs / 1993 / A Plant-Wide Industrial Process Control / Computers and Chemical Engineering 17(3):245~255
윤인섭 / 2004 / Support Vector Machine을 이용한 화학공정 모니터링에 관한 연구 / Korean Chemical Engineering Research(HWAHAK KONGHAK) 42(5):538~544
M. Kano / 2001 / A New Multivariate Statistical Process Monitoring Method using Principal Component Analysis / Computers and Chemical Engineering 25:1103~1113
L. H. Chiang / 2001 / Fault Detection and Diagnosis in Industrial Systems / Springer-verlag
J. J. Downs / 1993 / A Plant-Wide Industrial Process Control / Computers and Chemical Engineering 17(3):245~255
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