Dynamic risk assessment and fault detection using a multivariate technique

Process Safety Progress

Volumn 32, Issue 4, 2013, Pages 365-375

  Zadakbar, O ^a   Imtiaz, S ^a   Khan, F ^a  

^a MEMORIAL UNIVERSITY OF NEWFOUNDLAND   (Canada)

Author keywords

Dynamic risk assessment; Kalman filter; Multivariate fault diagnosis; Risk assessment of process system

Indexed keywords

ASSESSMENT OF PROCESS; ASSESSMENT PROCEDURE; DYNAMIC RISK ASSESSMENTS; FAULT DETECTION ALGORITHM; FAULT DETECTION AND DIAGNOSIS; MULTIVARIATE TECHNIQUES; PROCESS VARIABLES; RESIDUAL GENERATION;

KALMAN FILTERS; RISK ASSESSMENT; SAFETY ENGINEERING;

FAULT DETECTION;

EID: 84888390212     PISSN: 10668527     EISSN: 15475913     Source Type: Journal    
DOI: 10.1002/prs.11609     Document Type: Article

References (17)

1. S. Dash and V. Venkatasubramanian, Challenges in the industrial applications of fault diagnostic systems, Comput Chem Eng 24 (2000), 785-791.
2. S. Park and D.M. Himmelblau, Fault detection and diagnosis via parameter estimation in lumped dynamic systems, Ind Eng Chem Process Des Dev 22 (1983), 482-487.
3. Y. Chetouani, N. Mouhab, J. Cosmao, and L. Estel, Dynamic model-based technique for detecting faults in a chemical reactor, Process Saf Prog 22 (2003), 183-190.
4. R. lsermann, Fault detection methods for the supervision of technical processes. Process Automat 1 (1981), 36-44.
5. R. lsermann, Process fault detection based on modeling and estimation methods a survey, Automatica 20 (1984), 387-404.
6. F. Khan, H. Bao, T. Iqbal, and Y. Chang, Risk-based fault diagnosis and safety management for process systems, Process Saf Prog 30 (2011), 6-17.
7. M. Misra, H. Yue, S. Qin, and C. Ling, Multivariate process monitoring and fault diagnosis by multi-scale PCA, Comput Chem Eng 26 (2002), 1281-1293.
8. O. Zadakbar, S. Imtiaz, F. Khan, Dynamic risk assessment and fault detection using principal component analysis, Ind Eng Chem Res 52 (2013), 809-816.
9. R. Isermann, Model-based fault-detection and diagnosis-status and applications, Ann Rev Control 29 (2005), 71-85.
10. V. Venkatasubramanian, R. Rengaswamy, S.N. Kavuri, and K. Yin, A review of process fault detection and diagnosis, Part III: Process history based methods, Comput Chem Eng 27 (2003), 327-346.
11. A. Hsoumi, R. El Harabi, S. Ali, and M. Abdelkrim, Diagnosis of A Continuous Stirred Tank Reactor Using Kalman Filter, International Conference On Computational Intelligence, Modelling And Simulation, Brno, Czech Republic, 2009.
12. W. Lia, S.L. Shaha, and D. Xiaob, Kalman filters in non-uniformly sampled multirate systems: For FDI and beyond, Automatica 44 (2008), 199-208.
13. Center for Chemical Process Safety (CCPS), Guidelines For Chemical Process Quantitative Risk Analysis, 2nd Ed., Center For Chemical Process Safety Of The American Institute Of Chemical Engineers, Wiley Publication, New York, 2000.
14. Sodium Thiosulfate; Material Safety Data Sheet No. S5230; Mallenckrodt Baker: Phillipsburg, NJ, September 16, 2009. Available at: http://www.jtbaker.com/msds/englishhtml/s5230.htm, accessed on April 2011.
15. S. Skogestad, Dynamics and control of distillation columns-A tutorial introduction, Trans IChemE (UK), 75A (1997), 539-562.
16. S. Skogestad and M. Morari, Understanding the dynamic behavior of distillation columns, Ind Eng Chem Res 27 (1988), 1848-1862.
17. H.A. Elnemr and M.M. Elewa, Expert Failure Detection Technique for Distillation Column, Proceedings of the 22nd International Conference on Industrial Electronics, Control, and Instrumentation, Taipei, Taiwan, 1996.