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
오류제보하기
In order to guarantee the process safety and prevent accidents, the deviations from normal operating conditions should be monitored and their root causes have to be identified as soon as possible. The statistical theories-based method among various fault diagnosis methods has been gaining popularity, due to simplicity and quickness. However, according to fault magnitudes, the scalar value generated by statistical methods can be changed and this point can lead to produce wrong information. To solve this difficulty, this work employs PCA (Principal Component Analysis) based method with qualitative information. In the case study of our previous study, the number of assumed faults is much smaller than that of process variables. In the case study of this study, the number of predefined faults is 19, while that of process variables is 6. It means that a fault diagnosis becomes more difficult and it is really hard to isolate a single fault with a small number of variables. The PCA model is constructed under normal operation data in order to get a loading vector and the data set of assumed faulty conditions is applied with PCA model. The significant changes on PC (Principal Components) axes are monitored with CUSUM (Cumulative Sum Control Chart) and recorded to make the information, which can be used to identify the types of fault.
목차
등록된 정보가 없습니다.
참고문헌 (18)
참고문헌 신청
C. J. Lee / 2015 / Optimal Multi-floor Plant Layout Based on the Mathematical Programming and Particle Swarm Optimization / Industrial Health 53(6):491~497
C. J. Lee / 2012 / A Fault Magnitude Based Strategy for Effective Fault Classification / Chemical Engineering Research and Design 91(3):530~541
Tarun Chopra / 2011 / Classification of Faults in DAMADICS Benchmark Process Control System using Self Organizing Maps / International Journal of Soft Computing and Engineering 1(3)
Sa da Costa, J. / 2003 / Modelling and Simulation of an Industrial Actuator Valve for Fault Diagnosis Benchmark / Proceedings of the Fourth International Symposium on Mathematical Modelling :1212~1221
M Bartys / 2006 / Introduction to the DAMADICS Actuator FDI Benchmark Study / Control Engineering Practice 14(6):577~596
C. J. Lee / 2012 / A Fault Magnitude Based Strategy for Effective Fault Classification / Chemical Engineering Research and Design 91(3):530~541
Tarun Chopra / 2011 / Classification of Faults in DAMADICS Benchmark Process Control System using Self Organizing Maps / International Journal of Soft Computing and Engineering 1(3)
Sa da Costa, J. / 2003 / Modelling and Simulation of an Industrial Actuator Valve for Fault Diagnosis Benchmark / Proceedings of the Fourth International Symposium on Mathematical Modelling :1212~1221
M Bartys / 2006 / Introduction to the DAMADICS Actuator FDI Benchmark Study / Control Engineering Practice 14(6):577~596
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