Fault detection of an industrial heat-exchanger: A model-based approach

Strojniski Vestnik/Journal of Mechanical Engineering

Volumn 57, Issue 6, 2011, Pages 477-484

  Dragan, Dejan ^a  

^a UNIVERSITY OF MARIBOR   (Slovenia)

Author keywords

Condition monitoring; Fault detection; Identification; Industrial heat exchanger; Model based detection; Modelling

Indexed keywords

CONTINUOUS MODELS; DETECTION SYSTEM; IDENTIFICATION PROCEDURE; INDUSTRIAL HEAT EXCHANGER; LEAST SQUARES METHODS; LEVEL OF DETAIL; MODEL BASED APPROACH; MODEL DESCRIPTION; MODEL-BASED DETECTION; MODELLING; PRIOR KNOWLEDGE; PROCESS MODEL; STATE-VARIABLE FILTERS; TWO STAGE;

CONDITION MONITORING; HEAT EXCHANGERS; INDUSTRIAL HEATING; INDUSTRY; LEAST SQUARES APPROXIMATIONS;

FAULT DETECTION;

EID: 79959487429     PISSN: 00392480     EISSN: None     Source Type: Journal    
DOI: 10.5545/sv-jme.2010.128     Document Type: Article

References (15)

1. Bogaerts, P., Castillo, J., Hanus, R. (1997). Analytical solution of the non uniform heat exchange in a reactor cooling coil with constant fluid flow. Mathematics and Computers in Simulation, vol. 43, no. 2, p. 101-113. (Pubitemid 127451502)
2. Weyer, E., Hangos, K.M. (1997). Grey box fault detection in heat exchanger networks. Prepr. IFAC Symp. Safeprocess, vol. 1, p. 187-192.
3. Gertler, J. (1998). Fault detection and diagnosis in engineering systems. Marcel Dekker, New York.
4. Krishnan, R.A., Pappa, N. (2005). Real time fault diagnosis for a heat exchanger - a model based approach. INDICON, Annual IEEE, p. 78-82. (Pubitemid 46276053)
5. Klančar, G., Juričić, D., Karba, R. (2002). Robust fault detection based on compensation of the modelling error. International Journal of Systems Science, vol. 33, no. 2, p. 97-105. (Pubitemid 34593752)
6. Dragan, D., Juričić, D., Strmčnik, S. (2000). Modelling for condition monitoring application to a heat transfer process. Process control qual., vol. 11, p. 419-431.
7. Lalot, S., Mercère, G. (2008). Detection of fouling in a heat exchanger using a recursive subspace identification algorithm. Proceedings of the 19th International Symposium on Transport Phenomena Paper #37.
8. Jonsson, G.R., Lalot, S., Palsson, O.P., Desmet, B. (2007). Use of extended Kalman filtering in detecting fouling in heat exchangers. International Journal of Heat and Mass Transfer, vol. 50, no. 13-14, p. 2643-2655. (Pubitemid 46507462)
9. Ingimundardóttir, H., Lalot, S. (2009). Detection of fouling in a cross-flow heat exchanger using wavelets. Proceedings of International Conference on Heat Exchanger Fouling and Cleaning, p. 484-491.
10. Ramasamy, M., Shahid, A., Zabiri, H. (2008). Drift analysis on neural network model of heat exchanger fouling. Journal of Engineering Science and Technology, vol. 3, no. 1, p. 40-47.
11. Juan, C., Martínez, T., Morales-Menendez, R., Garza- Castañón, L.E. (2010). Fault diagnosis in a heat exchanger using process history based-methods, computer aided chemical engineering. 20th European Symposium on Computer Aided Process Engineering, Pierucci, S., Buzzi, G. (eds.), Elsevier B.V., vol. 28, p. 169-174.
12. Garnier, H., Wang, L. (2008). Identification of continuous-time models from sampled data. Springer-Verlag, London.
13. Ljung, L. (1999). System identification: theory for the user. 2nd ed., Prentice Hall, New York.
14. Rakar, A., Juričić, D., Balle, P. (1999). Transferable belief model in fault diagnosis. Engineering Applications of Artificial Intelligence, vol. 12, p. 555-567. (Pubitemid 32082364)
15. Rakar, A., Juričić, D. (2002). Diagnostic reasoning under conflicting data: the application of the transferable belief model. Journal of Process Control, vol. 12, p. 55-67. (Pubitemid 33110459)