Diagnosis of multiple and unknown faults using the causal map and multivariate statistics

Journal of Process Control

Volumn 28, Issue , 2015, Pages 27-39

  Chiang, Leo H ^a,b   Jiang, Benben ^c,d   Zhu, Xiaoxiang ^c   Huang, Dexian ^d   Braatz, Richard D ^a,c  

^a UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^b DOW CHEMICAL COMPANY   (United States)

^c Massachusetts Institute of Technology   (United States)

^d TSINGHUA UNIVERSITY   (China)

Author keywords

Causal map; Chemometrics; Fault diagnosis; Feature extraction; Feature representation; Multiple faults Unknown faults; Multivariate statistics; Process monitoring

Indexed keywords

EXTRACTION; FAILURE ANALYSIS; FEATURE EXTRACTION; MULTIVARIANT ANALYSIS; PROCESS MONITORING;

CHEMOMETRICS; COMPLEMENTARY FEATURES; DIAGNOSTIC PERFORMANCE; FAULT DIAGNOSIS METHOD; FEATURE REPRESENTATION; MULTIPLE FAULTS; MULTIVARIATE STATISTICS; TENNESSEE EASTMAN PROCESS;

FAULT DETECTION;

EID: 84924733661     PISSN: 09591524     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jprocont.2015.02.004     Document Type: Article

References (17)

1. R. Brunelli, and T. Poggio Face recognition: features versus templates IEEE Trans. Pattern Anal. Mach. Intell. 15 1993 1042 1052
2. H. Jiang, R. Patwardhan, and S.L. Shah Root case diagnosis of plant-wide oscillations using the concept of the adjacency matrix J. Process Control 19 2009 1347 1354
3. L.H. Chiang, E.L. Russell, and R.D. Braatz Fault Detection and Diagnosis in Industrial Systems 2001 Springer Verlag London, UK
4. S. Yoon, and J.F. MacGregor Statistical and causal model-based approaches to fault detection and isolation AIChE J. 46 2000 1813 1824
5. R. Isermann Supervision, fault-detection and fault-diagnosis methods: an introduction Control Eng. Pract. 5 1997 639 652
6. A.C. Raich, and A. Cinar Multivariate statistical methods for monitoring continuous processes: assessment of discriminatory power disturbance models and diagnosis of multiple disturbances Chemom. Intell. Lab. Syst. 30 1995 37 48
7. A.C. Raich, and A. Cinar Statistical process monitoring and disturbance diagnosis in multivariable continuous processes AIChE J. 42 1996 995 1009
8. L.H. Chiang, E.L. Russell, and R.D. Braatz Fault diagnosis in chemical processes using Fisher discriminant analysis, discriminant partial least squares, and principal component analysis Chemom. Intell. Lab. Syst. 50 2000 243 252
9. G. Lee, S.-O. Song, and E.S. Yoon Multiple-fault diagnosis based on system decomposition and dynamic PLS Ind. Eng. Chem. Res. 42 2003 6145 6154
10. N.F. Thornhill, and A. Horch Advances and new directions in plant-wide disturbance detection and diagnosis Control Eng. Pract. 15 2007 1196 1206
11. M. Bauer, J.W. Cox, M.H. Caveness, J.J. Downs, and N.F. Thornhill Finding the direction of disturbance propagation in a chemical process using transfer entropy IEEE Trans. Control Syst. Technol. 15 2007 12 21
12. N.F. Thornhill, J.W. Cox, and M.A. Paulonis Diagnosis of plant-wide oscillation through data-driven analysis and process understanding Control Eng. Pract. 11 2003 1481 1490
13. J. Thambirajah, L. Benabbas, M. Bauer, and N.F. Thornhill Cause-and-effect analysis in chemical processes utilizing XML, plant connectivity and quantitative process history Comput. Chem. Eng. 33 2009 503 512
14. R.M. Cruz, G.D. Cavalcanti, I.R. Tsang, and R. Sabourin Feature representation selection based on Classifier Projection Space and Oracle analysis Expert Syst. Appl. 40 2013 3813 3827
15. L.H. Chiang Fault Detection and Diagnosis for Large-scale Systems (Ph.D. Thesis) 2001 University of Illinois Urbana, IL
16. L.H. Chiang, and R.D. Braatz Process monitoring using causal map and multivariate statistics: fault detection and identification Chemom. Intell. Lab. Syst. 65 2003 159 178
17. J.J. Downs, and E.F. Vogel A plant-wide industrial process control problem Comput. Chem. Eng. 17 1993 245 255