Advances and new directions in plant-wide disturbance detection and diagnosis

Control Engineering Practice

Volumn 15, Issue 10 SPEC. ISS., 2007, Pages 1196-1206

  Thornhill, Nina F ^a   Horch, Alexander ^b  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

^b ABB CORPORATE RESEARCH   (Germany)

Author keywords

Fault detection; Oscillation; Plant wide; Process monitoring; Signal analysis; Whole plant

Indexed keywords

CHEMICAL PLANTS; CLOSED LOOP CONTROL SYSTEMS; CONTROL EQUIPMENT; FAILURE ANALYSIS; NONLINEAR CONTROL SYSTEMS; PROCESS MONITORING; SIGNAL ANALYSIS;

NON-LINEAR LIMIT CYCLES; PLANT-WIDE DISTURBANCE DETECTION;

CONTROL SYSTEM ANALYSIS;

CHEMICAL PLANTS; CLOSED LOOP CONTROL SYSTEMS; CONTROL EQUIPMENT; CONTROL SYSTEM ANALYSIS; FAILURE ANALYSIS; NONLINEAR CONTROL SYSTEMS; PROCESS MONITORING; SIGNAL ANALYSIS;

EID: 34547141675     PISSN: 09670661     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.conengprac.2006.10.011     Document Type: Article

References (86)

1. Bauer, M. (2005). Data-driven methods for process analysis. Ph.D. thesis, University of London.
2. Bauer, M., Cox, J. W., Caveness, M. H., Downs, J. J., & 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), corrected proof available on-line.
3. Bauer, M., Thornhill, N. F., & Meaburn, A. (2004). Specifying the directionality of fault propagation paths using transfer entropy. DYCOPS 7 conference, Boston, July 5-7, 2004.
4. Chatfield C., and Collins A.J. Introduction to multivariate analysis (1980), Chapman & Hall, London, UK
5. Chiang L.H., and Braatz R.D. Process monitoring using causal map and multivariate statistics: Fault detection and identification. Chemometrics and Intelligent Laboratory Systems 65 (2003) 159-178
6. Choudhury, M. A. A. S. (2004). Detection and diagnosis of control loop nonlinearities using higher order statistics. Ph.D. thesis, University of Alberta.
7. Choudhury, M. A. A. S., Kariwala, V., Shah, S. L., Douke, H., Takada, H., & Thornhill, N. F. (2005). A simple test to confirm control valve stiction. IFAC world congress, Praha, July 4-8, 2005.
8. Choudhury M.A.A.S., Shah S.L., and Thornhill N.F. Diagnosis of poor control loop performance using higher order statistics. Automatica 40 (2004) 1719-1728
9. Choudhury M.A.A.S., Thornhill N.F., and Shah S.L. Modelling of valve stiction. Control Engineering Practice 13 (2005) 641-658
10. Desborough L., and Miller R. Increasing customer value of industrial control performance monitoring-Honeywell's experience. AIChE Symposium Series No. 326 98 (2002) 153-186
11. Dewit C.C., Olsson H., Åström K.J., and Lischinsky P. A new model for control of systems with friction. IEEE Transactions on Automatic Control 40 (1995) 419-425
12. Emara-Shabaik, H. E., Bomberger, J., & Seborg, D. E. (1996). Cumulant/bispectrum model structure identification applied to a pH neutralization process. IEE Control '96 conference, Exeter, UK, 1996.
13. Fedai M., and Drath R. CAEX-A neutral data exchange format for engineering data. ATP International Automation Technology 01/2005 3 (2005) 43-51
14. Forsman, K., & Stattin, A. (1999). A new criterion for detecting oscillations in control loops. European control conference, Karlsruhe, Germany.
15. Geary S., Disney S.M., and Towill D.R. On bullwhip in supply chains-Historical review, present practice and expected future impact. International Journal of Production Economics 101 (2006) 2-18
16. Gerry, J., & Ruel, M. (2001). How to measure and combat valve stiction on line. In Proceedings of the ISA, Houston, TX.
17. Golder, A., & Wilson, D. H. (2004). Electric power transmission. US Patent 2004/0186671 A1.
18. Graebe S.F., Goodwin G.C., and Elsley G. Control design and implementation in continuous steel casting. IEEE Control Systems Magazine 15 4 (1995) 64-71
19. Hägglund T. A control-loop performance monitor. Control Engineering Practice 3 (1995) 1543-1551
20. Hägglund T. A friction compensator for pneumatic control valves. Journal of Process Control 12 (2002) 897-904
21. Hägglund T. Industrial implementation of on-line performance monitoring tools. Control Engineering Practice 13 (2005) 1383-1390
22. Horch A. A simple method for detection of stiction in control valves. Control Engineering Practice 7 (1999) 1221-1231
23. Horch, A. (2002). Patents WO0239201 and US2004/0078168.
24. Horch A. Cause analysis for facility-wide breakdowns. BWK 57 6 (2005) 55-58 (in German)
25. Horch A. Benchmarking control loops with oscillations and stiction. In: Ordys A., Uduehi D., and Johnson M.A. (Eds). Process control performance assessment (2007), Springer, London, UK
26. Horch A., Isaksson A.J., and Forsman K. Diagnosis and characterization of oscillations in process control loops. Pulp & Paper-Canada 103 3 (2002) 19-23
27. Jelali M. An overview of control performance assessment technology and industrial applications. Control Engineering Practice 14 (2006) 441-466
28. Jiang, H., Choudhury, M. A. A. S., Shah, S. L., Cox, J., & Paulonis, M. (2006). Detection and diagnosis of plant-wide oscillations via the method of spectral envelope. In Proceedings of the IFAC-ADCHEM 2006, Gramado, Brazil, April 3-5.
29. Kano, M., Maruta, H., Kugemoto, H., & Shimizu, K. (2004). Practical model and detection algorithm for valve stiction. DYCOPS 7, Boston, USA, July 5-7.
30. Kantz H., and Schreiber T. Nonlinear time series analysis (1997), Cambridge University Press, Cambridge
31. Karnopp D. Computer simulation of stick-slip friction in mechanical dynamical systems. Journal of Dynamic Systems, Measurement, and Control 107 (1985) 100-103
32. Kayihan A., and Doyle III F.J. Friction compensation for a process control valve. Control Engineering Practice 8 (2000) 799-812
33. Lapide, L. (2000). What about measuring supply chain performance? On-line, retrieved 9 October 2006. 〈http://lapide.ASCET.com〉.
34. Lee D.D., and Seung H.S. Learning the parts of objects by non-negative matrix factorization. Nature 401 (1999) 788-791
35. Lee G.B., Song S.O., and Yoon E.S. Multiple-fault diagnosis based on system decomposition and dynamic PLS. Industrial and Engineering Chemistry Research 42 (2003) 6145-6154
36. Luyben W.L., Tyreus B.D., and Luyben M.L. Plant-wide process control (1999), McGraw-Hill, New York
37. Matsuo T., Sasaoka H., and Yamashita Y. Detection and diagnosis of oscillations in process plants. Lecture Notes in Computer Science 2773 (2003) 1258-1264
38. Matsuo, T., Tadakuma, I., & Thornhill, N. F. (2004). Diagnosis of a unit-wide disturbance caused by saturation in a manipulated variable. IEEE Advanced Process Control Applications for Industry Workshop, Vancouver, April 26-28.
39. Maurya M.R., Rengaswamy R., and Venkatasubramanian V. Application of signed digraphs-based analysis for fault diagnosis of chemical process flowsheets. Engineering Applications of Artificial Intelligence 17 (2004) 501-518
40. McMillan G.K. Improve control valve response. Chemical Engineering Progress 91 6 (1995) 76-84
41. Miao, T., & Seborg, D. E. (1999). Automatic detection of excessively oscillatory feedback control loops. IEEE conference on control applications, Hawaii (pp. 359-364).
42. Odgaard, P., & Trangbaek, K. (2006). Comparison of methods for oscillation detection-Case study on a coal-fired power plant. In Proceedings of the IFAC symposium on power plants and power systems control, June 25-28, Kananaskis, Canada.
43. Olsson, H. (1996). Control systems with friction. Ph.D. thesis, Lund Institute of Technology, Sweden.
44. Olsson H., and Astrom K.J. Friction generated limit cycles. IEEE Transactions on Control Systems Technology 9 (2001) 629-636
45. Owen, J. G., Read, D., Blekkenhorst, H., & Roche, A. A. (1996). A mill prototype for automatic monitoring of control loop performance. In Proceedings of the control systems'96, Halifax, Nova Scotia (pp. 171-178).
46. Paulonis M.A., and Cox J.W. A practical approach for large-scale controller performance assessment, diagnosis, and improvement. Journal of Process Control 13 (2003) 155-168
47. Petersen, J. (2000). Causal reasoning based on MFM. In Proceedings of the cognitive systems engineering in process control (CSEPC 2000), Taejon, Korea (pp. 36-43).
48. Piipponen, J. (1996). Controlling processes with nonideal valves: Tuning of loops and selection of valves. In Proceedings of the control systems '96, Halifax, Nova Scotia, Canada (pp. 179-186).
49. Qin S.J. Control performance monitoring-A review and assessment. Computers and Chemical Engineering 23 (1998) 173-186
50. Rengaswamy R., Hägglund T., and Venkatasubramanian V. A qualitative shape analysis formalism for monitoring control loop performance. Engineering Applications of Artificial Intelligence 14 (2001) 23-33
51. Rossi M., and Scali C. A comparison of techniques for automatic detection of stiction: simulation and application to industrial data. Journal of Process Control 15 (2005) 505-514
52. Rossi, M., Tangirala, A. K., Shah, S. L., & Scali, C. (2006). A data-base measure for interactions in multivariate systems. In Proceedings of the IFAC-ADCHEM 2006, Gramado, Brazil, April 3-5.
53. Ruel M., and Gerry J. Quebec quandary solved by Fourier transform. Intech (August) (1998) 53-55
54. Salsbury, T. I., & Singhal, A. (2005). A new approach for ARMA pole estimation using higher-order crossings. In Proceedings of the ACC 2005, Portland, USA.
55. Schreiber T. Measuring information transfer. Physical Review Letters 85 (2000) 461-464
56. Shah N. Process industry supply chains: Advances and challenges. Computers & Chemical Engineering 29 (2005) 1225-1235
57. Singhal A., and Salsbury T.I. A simple method for detecting valve stiction in oscillating control loops. Journal of Process Control 15 (2005) 371-382
58. Srinivasan, R., Maurya, M. R., & Rengaswamy, R. (2006). Root cause analysis of oscillating control loops. In Proceedings of the IFAC-ADCHEM 2006, Gramado, Brazil, April 3-5.
59. Srinivasan R., and Rengaswamy R. Stiction compensation in process control loops: A framework for integrating stiction measure and compensation. Industrial and Engineering Chemistry Research 44 (2005) 9164-9174
60. Srinivasan R., Rengaswamy R., and Miller R. Control loop performance assessment. 1. A qualitative approach for stiction diagnosis. Industrial & Engineering Chemistry Research 44 (2005) 6708-6718
61. Srinivasan R., Rengaswamy R., Narasimhan S., and Miller R. Control loop performance assessment. 2. Hammerstein model approach for stiction diagnosis. Industrial & Engineering Chemistry Research 44 (2005) 6719-6728
62. Stenman A., Gustafsson F., and Forsman K. A segmentation-based method for detection of stiction in control valves. International Journal of Adaptive Control and Signal Processing 17 (2003) 625-634
63. Tangirala, A. K., Kanodia, J., & Shah, S. L. (2007). Non-negative matrix factorization for detection of plant-wide oscillations. Industrial & Engineering Chemistry Research, accepted for publication.
64. Tangirala A.K., Shah S.L., and Thornhill N.F. PSCMAP: A new measure for plant-wide oscillation detection. Journal of Process Control 15 (2005) 931-941
65. Theron J.P., and Aldrich C. Identification of nonlinearities in dynamic process systems. Journal of the South African Institute of Mining and Metallurgy 104 (2004) 191-200
66. Thornhill N.F. Finding the source of nonlinearity in a process with plant-wide oscillation. IEEE Transactions on Control System Technology 13 (2005) 434-443
67. Thornhill N.F., Cox J.W., and Paulonis M. Diagnosis of plant-wide oscillation through data-driven analysis and process understanding. Control Engineering Practice 11 (2003) 1481-1490
68. Thornhill N.F., and Hägglund T. Detection and diagnosis of oscillation in control loops. Control Engineering Practice 5 (1997) 1343-1354
69. Thornhill N.F., Huang B., and Zhang H. Detection of multiple oscillations in control loops. Journal of Process Control 13 (2003) 91-100
70. Thornhill, N. F., & Melbø, H. (2006). Detection of plant-wide disturbances using a spectral classification tree. In Proceedings of the IFAC-ADCHEM 2006, Gramado, Brazil, April 3-5.
71. Thornhill N.F., and Naim M.M. An exploratory study on the use of spectral principal component analysis in supply networks to identify rogue seasonality. European Journal of Operational Research 172 (2006) 146-162
72. Thornhill N.F., Shah S.L., Huang B., and Vishnubhotla A. Spectral principal component analysis of dynamic process data. Control Engineering Practice 10 (2002) 833-846
73. Venkatasubramanian V., Rengaswamy R., and Kavuri S.N. A review of process fault detection and diagnosis Part II: Qualitative model and search strategies. Computers and Chemical Engineering 27 (2003) 313-326
74. Weidl G., Madsen A.L., and Israelson S. Applications of object-oriented Bayesian networks for condition monitoring, root cause analysis and decision support on operation of complex continuous processes. Computers and Chemical Engineering 29 (2005) 1996-2009
75. Xia C., and Howell J. Loop status monitoring and fault localisation. Journal of Process Control 13 (2003) 679-691
76. Xia C., and Howell J. Isolating multiple sources of plant-wide oscillations via spectral independent component analysis. Control Engineering Practice 13 (2005) 1027-1035
77. Xia C., Howell J., and Thornhill N.F. Detecting and isolating multiple plant-wide oscillations via spectral independent component analysis. Automatica 41 (2005) 2067-2075
78. Xia, C., Zheng, J., & Howell, J. (2007). Isolation of whole-plant multiple oscillations via non-negative spectral decomposition. Chinese Journal of Chemical Engineering, accepted for publication.
79. Yamashita Y. Qualitative analysis for detection of stiction in control valves. Lecture Notes in Computer Science 3214 Part II (2004) 391-397
80. Yamashita Y. An automatic method for detection of valve stiction in process control loops. Control Engineering Practice 14 (2006) 503-510
81. Yamashita, Y. (2006b). Diagnosis of oscillations in process control loops. In Proceedings of the ESCAPE-16 and PSE'2006, Garmisch-Partenkirchen, Germany, July 10-14.
82. Yim S.Y., Ananthakumar H.G., Benabbas L., Horch A., Drath R., and Thornhill N.F. Using process topology in plant-wide control loop performance assessment. Computers & Chemical Engineering 31 (2006) 86-99
83. Zang, X., & Howell, J. (2003). Discrimination between bad turning and non-linearity induced oscillations through bispectral analysis. In Proceedings of the SICE annual conference, Fukui, Japan.
84. Zang, X., & Howell, J. (2004). Correlation dimension and Lyapunov exponents based isolation of plant-wide oscillations. DYCOPS 7, Boston, July 5-7.
85. Zang X., and Howell J. Isolating the root cause of propagated oscillations in process plants. International Journal of Adaptive Control Signal Processing 19 (2005) 247-265
86. Zang X., and Howell J. Isolating the source of whole-plant oscillations through bi-amplitude ratio analysis. Control Engineering Practice 15 (2007) 69-76