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Abstract:

This work proposes an automatic method of qualitative simulation for industrial processes to predict the steady-state measurement patterns arising from different faults. Due to their characteristics, qualitative simulations tend to generate multiple spurious solutions. The proposed method limits the number of such spurious solutions by automatically generating new qualitative equations from the generic quantitative model (i.e. without the need of knowing the value of its parameters) and using simple qualitative known relations or other readily available information. An algorithm to obtain such solutions from the set of qualitative equations is also presented. © 2014 Elsevier Ltd.

Registro:

Documento: Artículo
Título:Automatic qualitative trend simulation method for diagnosing faults in industrial processes
Autor:Maestri, M.; Ziella, D.; Cassanello, M.; Horowitz, G.
Filiación:LARSI, Departamento de Industrias, FCEyN, Universidad de Buenos Aires, Int. Güiraldes 2620, C1428BGA Buenos Aires, Argentina
Departamento de Física, FCEyN, Universidad de Buenos Aires, Argentina
Y-TEC, Baradero S/N, 1925 Ensenada, Argentina
Palabras clave:Confluences; Fault diagnosis; Qualitative simulation; Chemical engineering; Failure analysis; Confluences; Industrial processs; Qualitative equations; Qualitative simulation; Quantitative modeling; Spurious solutions; Steady-state measurements; Trend simulation; Computer applications
Año:2014
Volumen:64
Página de inicio:55
Página de fin:62
DOI: http://dx.doi.org/10.1016/j.compchemeng.2014.01.007
Título revista:Computers and Chemical Engineering
Título revista abreviado:Comput. Chem. Eng.
ISSN:00981354
CODEN:CCEND
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00981354_v64_n_p55_Maestri

Referencias:

  • Alfíe, E., Gouzden, T., Maestri, M., Martínez, J., Sosa, S., Ziella, D., Monitoreo inteligente de procesos (2010) Cursos y Seminarios de Matemática - Serie B - TAMI 2010, pp. 43-54. , G. Acosta, J. Etcheverry, F. Reitich, R. Spies, C. Tarzia, D. Turner, A. Will (Eds.)
  • Bloch, H., (2006) Compressors And Modern Process Applications, , John Wiley & Sons, United State of America
  • Chang, C.T., Chen, C.Y., Fault diagnosis with automata generated languages (2011) Computers and Chemical Engineering, 35, pp. 329-341
  • Clancy, D., Kuipers, B., Time in qualitative simulation (2005) Foundations of artificial intelligence, 1, pp. 655-664. , Elsevier, The Netherlands, ISSN 1574-6526
  • Jong, H., Qualitative simulation and related approaches for the analysis of dynamic systems (2004) The Knowledge Engineering Review, 19, pp. 93-132
  • Gao, D., Wu, C., Zhang, B., Ma, X., Signed direct graph and qualitative trend analysis based fault diagnosis in chemical industry (2010) Chinese Journal of Chemical Engineering, 18, pp. 265-276
  • Liu, J., Wang, S., Application of information fusion based on fuzzy neural network to rotating machinery fault diagnosis (2009) Intelligent Information Technology Application Workshops, IITAW 2009, pp. 344-347
  • Maurya, M.R., Rengaswamy, R., Venkatasubramanian, V., A systematic framework for the development and analysis of signed digraphs for chemical processes. 1. Algorithms and analysis (2003) Industrial and Engineering Chemistry Research, 42, pp. 4789-4810
  • Maurya, M.R., Rengaswamy, R., Venkatasubramanian, V., A systematic framework for the development and analysis of signed digraphs for chemical processes. 2. Control loops and flowsheet analysis (2003) Industrial and Engineering Chemistry Research, 42, pp. 4811-4827
  • Maurya, M.R., Rengaswamy, R., Venkatasubramanian, V., Application of signed digraphs-based analysis for fault diagnosis of chemical process flowsheets (2004) Engineering Applications of Artificial Intelligence, 17, pp. 501-518
  • Maurya, M.R., Rengaswamy, R., Venkatasubramanian, V., Fault diagnosis using dynamic trend analysis: A review and recent developments (2007) Engineering Applications of Artificial Intelligence, 20, pp. 133-146
  • Oyeleye, O.O., Kramer, M.A., Qualitative simulation of chemical process systems: Steady state analysis (1988) American Institute of Chemical Engineers Journal, 34 (9), pp. 1441-1454
  • Venkatasubramanian, V., Rengaswamy, R., Kavuri, S.N., A review of process fault detection and diagnosis. Part I: Quantitative model-based methods (2003) Computers and Chemical Engineering, 27, pp. 293-311
  • Venkatasubramanian, V., Rengaswamy, R., Kavuri, S.N., A review of process fault detection and diagnosis. Part II: Qualitative models and search strategies (2003) Computers and Chemical Engineering, 27, pp. 313-326
  • Zhang, W., Wu, C., Wang, C., Qualitative algebra and graph theory methods for dynamic trend analysis of continuous system (2011) Chinese Journal of Chemical Engineering, 19, pp. 308-315

Citas:

---------- APA ----------
Maestri, M., Ziella, D., Cassanello, M. & Horowitz, G. (2014) . Automatic qualitative trend simulation method for diagnosing faults in industrial processes. Computers and Chemical Engineering, 64, 55-62.
http://dx.doi.org/10.1016/j.compchemeng.2014.01.007
---------- CHICAGO ----------
Maestri, M., Ziella, D., Cassanello, M., Horowitz, G. "Automatic qualitative trend simulation method for diagnosing faults in industrial processes" . Computers and Chemical Engineering 64 (2014) : 55-62.
http://dx.doi.org/10.1016/j.compchemeng.2014.01.007
---------- MLA ----------
Maestri, M., Ziella, D., Cassanello, M., Horowitz, G. "Automatic qualitative trend simulation method for diagnosing faults in industrial processes" . Computers and Chemical Engineering, vol. 64, 2014, pp. 55-62.
http://dx.doi.org/10.1016/j.compchemeng.2014.01.007
---------- VANCOUVER ----------
Maestri, M., Ziella, D., Cassanello, M., Horowitz, G. Automatic qualitative trend simulation method for diagnosing faults in industrial processes. Comput. Chem. Eng. 2014;64:55-62.
http://dx.doi.org/10.1016/j.compchemeng.2014.01.007