Signed directed graph based modeling and its validation from process knowledge and process data

Alonso, C. J., Llamas, C., Maestro, J. A. and Pulido, B. (2003). Diagnosis of dynamic systems: A knowledge model that allows tracking the system during the diagnosis process, in P. W. H. Chung, C. Hinde and M. Ali (Eds.), Developments in Applied Artificial Intelligence, Lecture Notes in Artificial Intelligence, Vol. 2718, Springer, Berlin, pp. 208-218.10.1007/3-540-45034-3_21Search in Google Scholar

Bauer, M., Cox, J. W., Caveness, M. H., Downs, J. J. and Thornhill, N. F. (2007). Finding the direction of disturbance propagation in a chemical process using transfer entropy, IEEE Transactions on Control Systems Technology 15(1): 12-21.10.1109/TCST.2006.883234Search in Google Scholar

Bauer, M. and Thornhill, N. F. (2008). A practical method for identifying the propagation path of plant-wide disturbances, Journal of Process Control 18(7-8): 707-719.10.1016/j.jprocont.2007.11.007Search in Google Scholar

Cheng, H., Tikkala, V.-M., Zakharov, A., Myller, T. and Jamsa-Jounela, S. L. (2011). Application of the enhanced dynamic causal digraph method on a three-layer board machine, IEEE Transactions on Control Systems Technology 19(3): 644-655.10.1109/TCST.2010.2051441Search in Google Scholar

Fagarasan, I., Ploix, S. and Gentil, S. (2004). Causal fault detection and isolation based on a set-membership approach, Automatica 40(12): 2099-2110.10.1016/S0005-1098(04)00196-7Search in Google Scholar

Fedai, M. and Drath, R. (2005). CAEX—A neutral data exchange format for engineering data, Automation Technology in Practice—ATP International 1(3): 43-51.Search in Google Scholar

Gigi, S. and Tangirala, A. K. (2010). Quantitative analysis of directional strengths in jointly stationary linear multivariate processes, Biological Cybernetics 103(2): 119-133.10.1007/s00422-010-0386-6Search in Google Scholar

Górny, B. (2001). Consistency-Based Reasoning in Model-Based Diagnosis, Ph.D. thesis, AGH University of Science and Technology, Cracow.Search in Google Scholar

Iri, M., Aoki, K., O'shima, E. and Matsuyama, H. (1979). An algorithm for diagnosis of system failures in the chemical process, Computers and Chemical Engineering 3(1-4): 489-493.10.1016/0098-1354(79)80079-4Search in Google Scholar

Jan, A., Jonas, B., Erik, F., Krysander, M. and Lars, N. (2007). Safety analysis of autonomous systems by extended fault tree analysis, International Journal of Adaptive Control and Signal Processing 21(2-3): 287-298.10.1002/acs.934Search in Google Scholar

Ligęza, A. (1996). A note on systematic conflict generation in CA-EN-type causal structures, LAAS Report No. 96317, Laboratory for Analysis and Architecture of Systems, Toulouse.Search in Google Scholar

Ligęza, A. and Kościelny, J. M. (2008). A new approach to multiple fault diagnosis: A combination of diagnostic matrices, graphs, algebraic and rule-based models. The case of two-layer models, International Journal of Applied Mathematics and Computer Science 18(4): 465-476, DOI: 10.2478/v10006-008-0041-8.10.2478/v10006-008-0041-8Search in Google Scholar

Korbicz, J. and Kościelny, J. M. (Eds.) (2010). Modeling, Diagnostics and Process Control: Implementation in the Dia-Ster System, Springer-Verlag, Berlin/Heidelberg.10.1007/978-3-642-16653-2Search in Google Scholar

Leyval, L., Gentil, S. and Feray-Beaumont, S. (1994). Model-based causal reasoning for process supervision, Automatica 30(8): 1295-1306.10.1016/0005-1098(94)90109-0Search in Google Scholar

Li, Q. and Racine, J. S. (2007). Nonparametric Econometrics: Theory and Practice, Princeton University Press, Princeton, NJ.Search in Google Scholar

Lungarella, M., Ishiguro, K., Kuniyoshi, Y. and Otsu, N. (2007). Methods for quantifying the causal structure of bivariate time series, International Journal of Bifurcation and Chaos 17(3): 903-921.10.1142/S0218127407017628Search in Google Scholar

Maurya, M. R., Rengaswamy, R. and Venkatasubramanian, V. (2003a). A systematic framework for the development and analysis of signed digraphs for chemical processes: 1. Algorithms and analysis, Industrial and Engineering Chemistry Research 42(20): 4789-4810.10.1021/ie020644aSearch in Google Scholar

Maurya, M. R., Rengaswamy, R. and Venkatasubramanian, V. (2003b). A systematic framework for the development and analysis of signed digraphs for chemical processes: 2. Control loops and flowsheet analysis, Industrial and Engineering Chemistry Research 42(20): 4811-4827.10.1021/ie0206453Search in Google Scholar

Maurya, M. R., Rengaswamy, R. and Venkatasubramanian, V. (2004). Application of signed digraphs-based analysis for fault diagnosis of chemical process flowsheets, Engineering Applications of Artificial Intelligence 17(5): 501-518.10.1016/j.engappai.2004.03.007Search in Google Scholar

Montmain, J. and Gentil, S. (2000). Dynamic causal model diagnostic reasoning for online technical process supervision, Automatica 36(8): 1137-1152.10.1016/S0005-1098(00)00024-8Search in Google Scholar

Mosterman, P. J. and Biswas, G. (1999). Diagnosis of continuous valued systems in transient operating regions, IEEE Transactions on Systems, Man, and Cybernetics: Part A 29(6): 554-565.10.1109/3468.798059Search in Google Scholar

Oyeleye, O. O. and Kramer, M. A. (1988). Qualitative simulation of chemical process systems: Steady-state analysis, AIChE Journal 34(9): 1441-1454.10.1002/aic.690340906Search in Google Scholar

Palmer, C. and Chung, P. W. H. (1999). Verifying signed directed graph models for process plants, Computers & Chemical Engineering 23(Suppl. 1): S394-S391.Search in Google Scholar

Palmer, C. and Chung, P. W. H. (2000). Creating signed directed graph models for process plants, Industrial and Engineering Chemistry Research 39(20): 2548-2558.10.1021/ie990637vSearch in Google Scholar

Pastor, J., Lafon, M., Trave-Massuyes, L., Demonet, J.-F., Doyon, B. and Celsis, P. (2000). Information processing in large-scale cerebral networks: The causal connectivity approach, Biological Cybernetics 82(1): 49-59.10.1007/PL0000796110650907Search in Google Scholar

Schreiber, T. (2000). Measuring information transfer, Physical Review Letters 85(2): 461-464.10.1103/PhysRevLett.85.46110991308Search in Google Scholar

Silverman, B. W. (1986). Density Estimation for Statistics and Data Analysis, Chapman and Hall, London/New York, NY.Search in Google Scholar

Staroswiecki, M. (2000). Quantitative and qualitative models for fault detection and isolation, Mechanical Systems and Signal Processing 14(3): 301-325.10.1006/mssp.2000.1293Search in Google Scholar

Tangirala, A. K., Shah, S. L. and Thornhill, N. F. (2005). PSC-MAP: A new tool for plant-wide oscillation detection, Journal of Process Control 15(8): 931-941.10.1016/j.jprocont.2005.01.005Search in Google Scholar

Thambirajah, J., Benabbas, L., Bauer, M. and Thornhill, N. F. (2009). Cause-and-effect analysis in chemical processes utilizing XML: Plant connectivity and quantitative process history, Computers and Chemical Engineering 33(2): 503-512.10.1016/j.compchemeng.2008.10.002Search in Google Scholar

Yang, F., Shah, S. L. and Xiao, D. (2010a). SDG (Signed Directed Graph) based process description and fault propagation analysis for a tailings pumping process, Proceedings of the 13th IFAC Symposium on Automation in Mining, Mineral and Metal Processing, Cape Town, South Africa, pp. 50-55.10.3182/20100802-3-ZA-2014.00011Search in Google Scholar

Yang, F., Xiao, D. and Shah, S. L. (2010b). Qualitative fault detection and hazard analysis based on signed directed graphs for large-scale complex systems, in W. Zhang (Ed.), Fault Detection, IN-TECH, Vukovar, pp. 15-50.10.5772/9077Search in Google Scholar

Yim, S. Y., Ananthakumar, H. G., Benabbas, L., Horch, A., Drath, R. and Thornhill, N. F. (2006). Using process topology in plant-wide control loop performance assessment, Computers and Chemical Engineering 31(2): 86-99.10.1016/j.compchemeng.2006.05.004Search in Google Scholar