Abstract
This work presents a diagnosis algorithm that combines structural causal graphical model and nonlinear dynamic Principal Component Analysis (PCA) for nonlinear systems with coupled energies incorporate the chemical kinetics of an equilibrated reaction, heat and mass transport phenomena. Therein, a coupled Bond Graph (BG) model, as an integrated decision tool, is used for modeling purpose. A Signed Directed Graph (SDG) is then deduced. A fault detection step is later carried out by generating initial responses through causal paths between exogenous and measured variables. After that, the localization of the actual fault is performed based on a nonlinear PCA (NLPCA) and back/forward propagations on the SDG. Simulation results on a pilot reactor show that the physic-chemical defects such as matter leakage, thermal insulation, or appearance of secondary reaction or temperature runaway when a very exothermic reaction occurs, can be detected and isolated.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Chiang, L.H., Braatz, R.D., Russell, E.L.: Fault Detection and Diagnosis in Industrial Systems. Springer, London (2001)
Colbert, D.: Toxic Relief: Restore Health and Energy Through Fasting and Detoxification. Charisma Media, Lake Mary (2011)
Dauphin-Tanguy, G.: Les Bond Graphs. Hermès Science, Paris (2000)
El Harabi, R., Ould-Bouamama, B., Gayed, M.K.B., Abdelkrim, M.N.: Pseudo bond graph for fault detection and isolation of an industrial chemical reactor part I: bond graph modeling. In: Proceedings of the 2010 Spring Simulation Multiconference, p. 220. Society for Computer Simulation International (2010)
Gilles, E.D.: Network theory for chemical processes. Chem. Eng. Technol. 21(2), 121–132 (1998)
Heny, C., Simanca, D., Delgado, M.: Pseudo-bond graph model and simulation of a continuous stirred tank reactor. J. Franklin Inst. 337(1), 21–42 (2000)
Iri, M., Aoki, K., O’Shima, E., Matsuyama, H.: An algorithm for diagnosis of system failures in the chemical process. Comput. Chem. Eng. 3(1), 489–493 (1979)
Jackson, J.E., Mudholkar, G.S.: Control procedures for residuals associated with principal component analysis. Technometrics 21(3), 341–349 (1979)
Kramer, M.A.: Nonlinear principal component analysis using autoassociative neural networks. AIChE J. 37(2), 233–243 (1991)
Ku, W., Storer, R.H., Georgakis, C.: Disturbance detection and isolation by dynamic principal component analysis. Chemometr. Intell. Lab. Syst. 30(1), 179–196 (1995)
MacGregor, J., Kourti, T., Nomikos, P.: Analysis, monitoring and fault diagnosis of industrial processes using multivariate statistical projection methods. In: Proceedings of 13th IFAC World Congress, San Francisco, USA (1996)
Maurya, M., Rengaswamy, R., Venkatasubramanian, V.: A signed directed graph-based systematic framework for steady-state malfunction diagnosis inside control loops. Chem. Eng. Sci. 61(6), 1790–1810 (2006)
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. Ind. Eng. Chem. Res. 42(20), 4789–4810 (2003)
Maurya, M.R., Rengaswamy, R., Venkatasubramanian, V.: A signed directed graph and qualitative trend analysis-based framework for incipient fault diagnosis. Chem. Eng. Res. Des. 85(10), 1407–1422 (2007)
Miller, P., Swanson, R.E., Heckler, C.E.: Contribution plots: a missing link in multivariate quality control. Appl. Math. Comput. Sci. 8, 775–792 (1998)
Mosterman, P.J., Biswas, G.: Diagnosis of continuous valued systems in transient operating regions. IEEE Trans. Syst. Man Cybern. Part A Syst. Hum. 29(6), 554–565 (1999)
Ould Bouamama, B.: Modélisation et supervision des systèmes en Génie des procédés–approche Bond Graphs. PhD thesis, Laboratoire d’Automatique et Informatique Industrielle de Lille USTL, France (2002)
Ould Bouamama, B.: Applications de la méthode bond graph à la modélisation des systèmes énergétiques. Article publié dans les techniques d’ingénieurs (2005)
Ould-Bouamama, B., El Harabi, R., Abdelkrim, M.N., Ben Gayed, M.: Bond graphs for the diagnosis of chemical processes. Comput. Chem. Eng. 36, 301–324 (2012)
Oyeleye, O., Kramer, M.: Qualitative simulation of chemical process systems: steady-state analysis. AIChE J. 34(9), 1441–1454 (1988)
Raich, A., Cinar, A.: Statistical process monitoring and disturbance diagnosis in multivariable continuous processes. AIChE J. 42(4), 995–1009 (1996)
Samantaray, A., Ghoshal, S.: Bicausal bond graphs for supervision: From fault detection and isolation to fault accommodation. J. Franklin Inst. 345(1), 1–28 (2008)
Samantaray, A.K., Bouamama, B.O.: Model-Based Process Supervision. Springer, London (2008)
Samantaray, A.K., Medjaher, K., Ould Bouamama, B., Staroswiecki, M., Dauphin-Tanguy, G.: Diagnostic bond graphs for online fault detection and isolation. Simul. Model. Pract. Theory 14(3), 237–262 (2006)
Smaili, R., El Harabi, R., Abdelkrim, M.N.: Fdi based on causal graphical approaches for nonlinear processes. In: 10th International Multi-conference on Systems, Signals and Devices (SSD), 2013, pp. 1–6. IEEE (2013a)
Smaili, R., Harabi, R.E., Abdelkrim, M.N.: Model-based process diagnosis: bond graph and signed directed graph tools. In: International Conference on Control, Decision and Information Technologies (CoDIT), 2013, pp. 782–787. IEEE (2013b)
Stoessel, F.: Thermal Safety of Chemical Processes: Risk Assessment and Process Design. Wiley, Weinheim (2008)
Thoma, J., Bouamama, B.O.: Modelling and Simulation in Thermal and Chemical Engineering: A Bond Graph Approach. Springer, Berlin (2000)
Vedam, H., Venkatasubramanian, V.: PCA-SDG based process monitoring and fault diagnosis. Control Eng. Pract. 7(7), 903–917 (1999)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this chapter
Cite this chapter
El Harabi, R., Smaili, R., Abdelkrim, M.N. (2015). Fault Diagnosis Algorithms by Combining Structural Graphs and PCA Approaches for Chemical Processes. In: Azar, A., Vaidyanathan, S. (eds) Chaos Modeling and Control Systems Design. Studies in Computational Intelligence, vol 581. Springer, Cham. https://doi.org/10.1007/978-3-319-13132-0_15
Download citation
DOI: https://doi.org/10.1007/978-3-319-13132-0_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13131-3
Online ISBN: 978-3-319-13132-0
eBook Packages: EngineeringEngineering (R0)