Off-line temporal signal comparison using singular points augmented time warping

Industrial and Engineering Chemistry Research

Volumn 44, Issue 13, 2005, Pages 4697-4716

  Srinivasan, Rajagopalan ^a   Qian, M S ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

DATA-BASED KNOWLEDGE ACQUISITION; DYNAMIC TIME WARPING (DTW); INSTRUMENTATION; SIGNAL COMPARISON;

COMPUTATIONAL COMPLEXITY; COMPUTER SIMULATION; DATA ACQUISITION; DATA STORAGE EQUIPMENT; DECISION SUPPORT SYSTEMS; KNOWLEDGE ACQUISITION; MONITORING;

MANUFACTURING DATA PROCESSING;

INSTRUMENTATION;

EID: 22544457628     PISSN: 08885885     EISSN: None     Source Type: Journal    
DOI: 10.1021/ie049528t     Document Type: Article

References (28)

1. Webb, A. R. Statistical Pattern Recognition; Wiley: West Sussex, U.K., 2002.
2. Chiang, L. H.; Russell, E. L.; Braatz, R. D. Fault Detection and Diagnosis in Industrial Systems; Springer: London, New York, 2001.
3. Sankoff, D.; Kruskal, J. B. Time Warps, String Edits, and Macromolecules: The Theory and Practice of Sequence Comparison; Addison-Wesley: Reading, MA, 1983.
4. Kassidas, A. Ph.D. Thesis, McMaster University, Hamilton, Ontario, Canada, 1997.
5. Kassidas, A.; MacGregor, J. F.; Taylor, P. A. Synchronization of batch trajectories using dynamic time warping. AIChE J. 1998, 44 (4), 864-875.
6. Kassidas, A.; Taylor, P. A.; MacGregor, J. F. Off-line diagnosis of deterministic faults in continuous dynamic multivariable processes using speech recognition methods. J. Process Control 1998, 8 (5-6), 381-393.
7. Nomikos, P.; MacGregor, J. F. Monitoring batch processes using multiway principle component analysis. AIChE J. 1994, 40 (8), 1361-1375.
8. Li, Y.; Wen, C. L.; Xie, Z.; Xu, X. H. Synchronization of batch trajectory based on multi-scale dynamic time warping. In Proceedings of the Second International Conference on Machine Learning and Cybernetics (ICMLC 2003); 2004; Vol. 4, pp 2403-2408.
9. Colomer, J.; Melendez, J.; Gamero, F. I. Pattern recognition based on episodes and DTW. Application to diagnosis of a level control system, presented at the Sixteenth International Workshop on Qualitative Reasoning, Catalunya, Spain, 2002.
10. Krzanowski, W. J. Between-group comparison of principle components, J. Am. Stat. Assoc. 1979, 74 (367), 703-707.
11. Raich, A.; Cinar, A. Diagnosis of process disturbances by statistical distance and angle measures. Comput. Chem. Eng. 1997, 21 (6), 661-673.
12. Singhal, A.; Seborg, D. E. Pattern matching in historical batch data using PCA. IEEE Control Syst. Mag. 2002, 22 (5), 53-63.
13. Srinivasan, R.; Wang, C.; Ho, W. K.; Lim, K. W. Dynamic PCA based methodology for clustering process states in agile chemical plants. Ind. Eng. Chem. Res. 2004, 43 (9), 2123-2139.
14. Jain, A. K.; Duin, R. P. W.; Mao, J. C. Statistical pattern recognition: A review. IEEE Trans. Pattern Anal. Machine Intell. 2000, 22 (1), 4-37.
15. Bakshi, B. R.; Stephanopoulos, G. Intelligent Systems in Process Engineering-Paradigms from Design to Operations; Academic Press: San Diego, CA, 1996.
16. Mallet, S.; Hwang, W. L. Singularity detection and processing with wavelets. IEEE Trans. Inf. Theory 1992, 38 (2), 617-643.
17. Qian, M. S. Ph.D. Thesis, National University of Singapore, Singapore, 2005.
18. Williams, K. Dynamic Programming Sequential Decision-Making; Longman: London, 1970.
19. Honeywell, Guide to the Fluidized Catalytic Cracking Unit Standard Model, 2000.
20. Sundarraman, A.; Srinivasan, R. Monitoring transitions in chemical plants using enhanced trend analysis. Comput. Chem. Eng. 2003, 27 (10), 1455-1472.
21. Srinivasan, R.; Viswanathan, P.; Vedam, H.; Nochur, A. A Framework for Managing Transitions in Chemical Plants. Comput. Chem. Eng. 2005, 29 (2), 305-322.
22. Singhal, A. Tennessee Eastman simulation model, http://www.chemengr.ucsb. edu/~ceweb/computing/TE/tesimulation.htm, 2003.
23. Mcavoy, T. J.; Ye, N. Base control for the Tennessee Eastman problem. Comput. Chem. Eng. 1994, 18 (5), 383-413.
24. Kotz, S.; Johnsan, N. L. Encyclopedia of Statistical Sciences; Wiley: New York, 1988; Vol. 9, pp 135-136.
25. Muthuswamy, K.; Srinivasan, R. Phase-based supervisory control for fermentation process development. J. Process Control 2003, 13 (5), 367-382.
26. Nielsen, N. V.; Carstensen, J. M.; Smedsgarrd, J. Aligning of single and multiple wavelength Chromatographic profile for chemometric data analysis using correlation optimized warping. J. Chromatogr. A 1998, 805, 17-35.
27. Pravdova, V.; Walczak, B.; Massart, D. L. A comparison of two algorithms for warping of analytical signals. Anal. Chim. Acta 2002, 456, 77-92.
28. Rengaswamy, R.; Venkatasubramanian, V. A syntactic pattern recognition approach for process monitoring and fault diagnosis. Eng. Appl. Artif. Intell. 1995, 8 (1), 35-51.