Super-alarms with diagnosis proficiency used as an additional layer of protection applied to an oil transport system

In automated plants, particularly in the petrochemical, energy, and chemical industries, the combined management of all of the incidents that can produce a catastrophic accident is required. In order to do this, an alarm management methodology can be formulated as a discrete event sequence recogniti...

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Autores:
Vásquez, John W.
Perez-Zuñiga, Gustavo
Sotomayor-Moriano, Javier
Ospino C., Adalberto
Ospino C., Adalberto
Tipo de recurso:
Article of journal
Fecha de publicación:
2021
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/7920
Acceso en línea:
https://hdl.handle.net/11323/7920
https://doi.org/10.3390/e23020139
https://repositorio.cuc.edu.co/
Palabra clave:
Alarm management
Protection layers
Safe-process
Super-Alarm
Diagnosis
Rights
openAccess
License
CC0 1.0 Universal
id RCUC2_b14581381f273958d846630081439a67
oai_identifier_str oai:repositorio.cuc.edu.co:11323/7920
network_acronym_str RCUC2
network_name_str REDICUC - Repositorio CUC
repository_id_str
dc.title.spa.fl_str_mv Super-alarms with diagnosis proficiency used as an additional layer of protection applied to an oil transport system
title Super-alarms with diagnosis proficiency used as an additional layer of protection applied to an oil transport system
spellingShingle Super-alarms with diagnosis proficiency used as an additional layer of protection applied to an oil transport system
Alarm management
Protection layers
Safe-process
Super-Alarm
Diagnosis
title_short Super-alarms with diagnosis proficiency used as an additional layer of protection applied to an oil transport system
title_full Super-alarms with diagnosis proficiency used as an additional layer of protection applied to an oil transport system
title_fullStr Super-alarms with diagnosis proficiency used as an additional layer of protection applied to an oil transport system
title_full_unstemmed Super-alarms with diagnosis proficiency used as an additional layer of protection applied to an oil transport system
title_sort Super-alarms with diagnosis proficiency used as an additional layer of protection applied to an oil transport system
dc.creator.fl_str_mv Vásquez, John W.
Perez-Zuñiga, Gustavo
Sotomayor-Moriano, Javier
Ospino C., Adalberto
Ospino C., Adalberto
dc.contributor.author.spa.fl_str_mv Vásquez, John W.
Perez-Zuñiga, Gustavo
Sotomayor-Moriano, Javier
Ospino C., Adalberto
dc.contributor.author.none.fl_str_mv Ospino C., Adalberto
dc.subject.spa.fl_str_mv Alarm management
Protection layers
Safe-process
Super-Alarm
Diagnosis
topic Alarm management
Protection layers
Safe-process
Super-Alarm
Diagnosis
description In automated plants, particularly in the petrochemical, energy, and chemical industries, the combined management of all of the incidents that can produce a catastrophic accident is required. In order to do this, an alarm management methodology can be formulated as a discrete event sequence recognition problem, in which time patterns are used to identify the safe condition of the process, especially in the start-up and shutdown stages. In this paper, a new layer of protection (a Super-Alarm), based on the diagnostic stage to industrial processes is presented. The alarms and actions of the standard operating procedures are considered to be discrete events involved in sequences; the diagnostic stage corresponds to the recognition of the situation when these sequences occur. This provides operators with pertinent information about the normal or abnormal situations induced by the flow of the alarms. Chronicles Based Alarm Management (CBAM) is the methodology used in this document to build the chronicles that will permit us to generate the Super-Alarms; in addition, a case study of the petrochemical sector using CBAM is presented in order to build one chronicle that represents the scenario of an abnormal start-up of an oil transport system. Finally, the scenario’s validation for this case is performed, showing the way in which, a Super-Alarm is generated.
publishDate 2021
dc.date.accessioned.none.fl_str_mv 2021-02-24T17:24:16Z
dc.date.available.none.fl_str_mv 2021-02-24T17:24:16Z
dc.date.issued.none.fl_str_mv 2021
dc.type.spa.fl_str_mv Artículo de revista
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dc.identifier.doi.spa.fl_str_mv https://doi.org/10.3390/e23020139
dc.identifier.instname.spa.fl_str_mv Corporación Universidad de la Costa
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dc.relation.references.spa.fl_str_mv 1. Brennan, R. Toward Real-Time Distributed Intelligent Control: A Survey of Research Themes and Applications. IEEE Trans. Syst. Man Cybern. 2007, 37, 744–765. [CrossRef]
2. Zhang, J.; Khalgui, M.; Li, Z.; Frey, G.; Mosbahi, O.; Ben Salah, H. Reconfigurable Coordination of Distributed Discrete Event Control Systems. IEEE Trans. Control. Syst. Technol. 2014, 23, 323–330. [CrossRef]
3. Reifer, D.J. Software Failure Modes and Effects Analysis. IEEE Trans. Reliab. 1979, 28, 247–249. [CrossRef]
4. Morel, G.; Valckenaers, P.; Faure, J.-M.; Pereira, C.E.; Diedrich, C. Manufacturing Plant Control Challenges and Issues. Control. Eng. Pract. 2007, 15, 1321–1331. [CrossRef]
5. Rodrigo, V.; Chioua, M.; Hagglund, T.; Hollender, M. Causal Analysis for Alarm Flood Reduction. IFAC-PapersOnLine 2016, 49, 723–728. [CrossRef]
6. Bodsberg, L.; Hokstad, P. Alarm and Shutdown Frequencies in Offshore Production. IFAC Proc. Vol. 1988, 21, 19–25. [CrossRef]
7. Agudelo, C.; Morant Anglada, F.; Quiles Cucarella, E.; Garca Moreno, E. Secuencias De Alarmas Para detección Y diagnóstico de fallos. Rev. Colomb. Comput. 2011, 12, 31–44. (In Spanish) [CrossRef]
8. Izadi, I.; Shah, S.L.; Shook, D.S.; Chen, T. An Introduction to Alarm Analysis and Design. IFAC Proc. Vol. 2009, 42, 645–650. [CrossRef]
9. Gómez, C.F.A. Integracion de Tecnicas y Las Secuencias de Alarmas Para la Deteccion y el Diagnostico de Fallos; Universitat Politecnica de Valencia: Valencia, Spain, 2016. [CrossRef]
10. Vásquez Capacho, J.W. Chronicle Based Alarm Management. Available online: https://hal.laas.fr/Tel-02059631 (accessed on 1 October 2017).
11. Beebe, D.; Ferrer, S.; Logerot, D. The Connection of Peak Alarm Rates to Plant Incidents and What You Can Do to Minimize. Process. Saf. Prog. 2012, 32, 72–77. [CrossRef]
12. Zhu, J.; Shu, Y.; Zhao, J.; Yang, F. A Dynamic Alarm Management Strategy for Chemical Process Transitions. J. Loss Prev. Process. Ind. 2014, 30, 207–218. [CrossRef]
13. John, V.; Jorge, P.; Carlos, A.; Jose, J. Analysis of Alarm Management in Startups and Shutdowns for Oil Refining Processes. In Proceedings of the 2013 II International Congress of Engineering Mechatronics and Automation (CIIMA), Bogotá, Colombia, 23–25 October 2013; pp. 1–6. [CrossRef]
14. Willey, R.J. Layer of Protection Analysis. Procedia Eng. 2014, 84, 12–22. [CrossRef]
15. Hokstad, P.; Corneliussen, K. Loss of Safety Assessment and the IEC 61508 Standard. Reliab. Eng. Syst. Saf. 2004, 83, 111–120. [CrossRef]
16. Ko´scielny, J.; Barty´s, M. The Requirements for a New Layer in the Industrial Safety Systems. IFAC-PapersOnLine 2015, 48, 1333–1338. [CrossRef]
17. Sklet, S. Safety Barriers: Definition, Classification, and Performance. J. Loss Prev. Process. Ind. 2006, 19, 494–506. [CrossRef]
18. Dowell, A.M. Layer of Protection Analysis and Inherently Safer Processes. Process. Saf. Prog. 1999, 18, 214–220. [CrossRef]
19. Vásquez, J.; Zuñiga, C.G.P.; Moriano, J.S.; Maldonado, Y.A.M.; Ospino, A. New Concept of Safeprocess Based on a Fault Detection Methodology: Super Alarms. IFAC-PapersOnLine 2019, 52, 231–236. [CrossRef]
20. Vásquez Capacho, J.W.; Perez Zuñiga, C.G.; Muñoz Maldonado, Y.A.; Ospino Castro, A.J. An additional layer of protection through superalarms with diagnosis capability. CT&F Cienc. Tecnol. Futuro 2020, 10, 45–65. [CrossRef]
21. Bayoudh, M.; Travé-Massuyès, L.; Olive, X. Hybrid Systems Diagnosis by Coupling Continuous and Discrete Event Techniques. IFAC Proc. Vol. 2008, 41, 7265–7270. [CrossRef]
22. Gao, Z.; Cecati, C.; Ding, S.X. A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis with ModelBased and Signal-Based Approaches. IEEE Trans. Ind. Electron. 2015, 62, 3757–3767. [CrossRef]
23. Vásquez, J.; Travé-Massuyès, L.; Subias, A.; Jimenez, F.; Agudelo, C. Alarm Management Based on Diagnosis. IFAC-PapersOnLine 2016, 49, 126–131. [CrossRef]
24. Capacho, J.V.; Subias, A.; Travé-Massuyès, L.; Jimenez, F. Alarm Management via Temporal Pattern Learning. Eng. Appl. Artif. Intell. 2017, 65, 506–516. [CrossRef]
25. Vásquez, J.W.; Travé-Massuyès, L.; Subias, A.; Jiménez, F.; Agudelo, C. Chronicle Based Alarm Management in Startup and Shutdown stages. In Proceedings of the 26th International Workshop on Principles of Diagnosis, Paris, France, 31 August– 3 September 2015; pp. 277–280. Available online: https://hal.laas.fr/Hal-01847469 (accessed on 1 October 2017).
26. Cordier, M.-O.; Dousson, C. Alarm Driven Monitoring Based on Chronicles. IFAC Proc. Vol. 2000, 33, 291–296. [CrossRef]
27. Dousson, C. Suivi d’évolutions Et Reconnaissance De Chroniques. Ph.D. Thesis, Université de Toulouse, Toulouse, France, 1994. Available online: http://www.theses.fr/1994TOU30264 (accessed on 1 October 2017).
28. Pons, R.; Subias, A.; Travé-Massuyès, L. Iterative Hybrid Causal Model Based Diagnosis: Application to Automotive Embedded Functions. Eng. Appl. Artif. Intell. 2015, 37, 319–335. [CrossRef]
29. Vásquez, J.W.; Perez-Zuñiga, G.; Muñoz, Y.; Ospino, A. Simultaneous occurrences and false-positives analysis in discrete event dynamic systems. J. Comput. Sci. 2020, 44, 101162. [CrossRef]
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spelling Vásquez, John W.Perez-Zuñiga, GustavoSotomayor-Moriano, JavierOspino C., AdalbertoOspino C., Adalbertovirtual::914-12021-02-24T17:24:16Z2021-02-24T17:24:16Z20211099-4300https://hdl.handle.net/11323/7920https://doi.org/10.3390/e23020139Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/In automated plants, particularly in the petrochemical, energy, and chemical industries, the combined management of all of the incidents that can produce a catastrophic accident is required. In order to do this, an alarm management methodology can be formulated as a discrete event sequence recognition problem, in which time patterns are used to identify the safe condition of the process, especially in the start-up and shutdown stages. In this paper, a new layer of protection (a Super-Alarm), based on the diagnostic stage to industrial processes is presented. The alarms and actions of the standard operating procedures are considered to be discrete events involved in sequences; the diagnostic stage corresponds to the recognition of the situation when these sequences occur. This provides operators with pertinent information about the normal or abnormal situations induced by the flow of the alarms. Chronicles Based Alarm Management (CBAM) is the methodology used in this document to build the chronicles that will permit us to generate the Super-Alarms; in addition, a case study of the petrochemical sector using CBAM is presented in order to build one chronicle that represents the scenario of an abnormal start-up of an oil transport system. Finally, the scenario’s validation for this case is performed, showing the way in which, a Super-Alarm is generated.Vásquez, John W.Perez-Zuñiga, Gustavo-will be generated-orcid-0000-0001-5946-1395-600Sotomayor-Moriano, Javier-will be generated-orcid-0000-0003-0782-0530-600Ospino, Adalberto-will be generated-orcid-0000-0003-1466-0424-600application/pdfengCorporación Universidad de la CostaCC0 1.0 Universalhttp://creativecommons.org/publicdomain/zero/1.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Entropyhttps://www.mdpi.com/1099-4300/23/2/139Alarm managementProtection layersSafe-processSuper-AlarmDiagnosisSuper-alarms with diagnosis proficiency used as an additional layer of protection applied to an oil transport systemArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersion1. Brennan, R. Toward Real-Time Distributed Intelligent Control: A Survey of Research Themes and Applications. IEEE Trans. Syst. Man Cybern. 2007, 37, 744–765. [CrossRef]2. Zhang, J.; Khalgui, M.; Li, Z.; Frey, G.; Mosbahi, O.; Ben Salah, H. Reconfigurable Coordination of Distributed Discrete Event Control Systems. IEEE Trans. Control. Syst. Technol. 2014, 23, 323–330. [CrossRef]3. Reifer, D.J. Software Failure Modes and Effects Analysis. IEEE Trans. Reliab. 1979, 28, 247–249. [CrossRef]4. Morel, G.; Valckenaers, P.; Faure, J.-M.; Pereira, C.E.; Diedrich, C. Manufacturing Plant Control Challenges and Issues. Control. Eng. Pract. 2007, 15, 1321–1331. [CrossRef]5. Rodrigo, V.; Chioua, M.; Hagglund, T.; Hollender, M. Causal Analysis for Alarm Flood Reduction. IFAC-PapersOnLine 2016, 49, 723–728. [CrossRef]6. Bodsberg, L.; Hokstad, P. Alarm and Shutdown Frequencies in Offshore Production. IFAC Proc. Vol. 1988, 21, 19–25. [CrossRef]7. Agudelo, C.; Morant Anglada, F.; Quiles Cucarella, E.; Garca Moreno, E. Secuencias De Alarmas Para detección Y diagnóstico de fallos. Rev. Colomb. Comput. 2011, 12, 31–44. (In Spanish) [CrossRef]8. Izadi, I.; Shah, S.L.; Shook, D.S.; Chen, T. An Introduction to Alarm Analysis and Design. IFAC Proc. Vol. 2009, 42, 645–650. [CrossRef]9. Gómez, C.F.A. Integracion de Tecnicas y Las Secuencias de Alarmas Para la Deteccion y el Diagnostico de Fallos; Universitat Politecnica de Valencia: Valencia, Spain, 2016. [CrossRef]10. Vásquez Capacho, J.W. Chronicle Based Alarm Management. Available online: https://hal.laas.fr/Tel-02059631 (accessed on 1 October 2017).11. Beebe, D.; Ferrer, S.; Logerot, D. The Connection of Peak Alarm Rates to Plant Incidents and What You Can Do to Minimize. Process. Saf. Prog. 2012, 32, 72–77. [CrossRef]12. Zhu, J.; Shu, Y.; Zhao, J.; Yang, F. A Dynamic Alarm Management Strategy for Chemical Process Transitions. J. Loss Prev. Process. Ind. 2014, 30, 207–218. [CrossRef]13. John, V.; Jorge, P.; Carlos, A.; Jose, J. Analysis of Alarm Management in Startups and Shutdowns for Oil Refining Processes. In Proceedings of the 2013 II International Congress of Engineering Mechatronics and Automation (CIIMA), Bogotá, Colombia, 23–25 October 2013; pp. 1–6. [CrossRef]14. Willey, R.J. Layer of Protection Analysis. Procedia Eng. 2014, 84, 12–22. [CrossRef]15. Hokstad, P.; Corneliussen, K. Loss of Safety Assessment and the IEC 61508 Standard. Reliab. Eng. Syst. Saf. 2004, 83, 111–120. [CrossRef]16. Ko´scielny, J.; Barty´s, M. The Requirements for a New Layer in the Industrial Safety Systems. IFAC-PapersOnLine 2015, 48, 1333–1338. [CrossRef]17. Sklet, S. Safety Barriers: Definition, Classification, and Performance. J. Loss Prev. Process. Ind. 2006, 19, 494–506. [CrossRef]18. Dowell, A.M. Layer of Protection Analysis and Inherently Safer Processes. Process. Saf. Prog. 1999, 18, 214–220. [CrossRef]19. Vásquez, J.; Zuñiga, C.G.P.; Moriano, J.S.; Maldonado, Y.A.M.; Ospino, A. New Concept of Safeprocess Based on a Fault Detection Methodology: Super Alarms. IFAC-PapersOnLine 2019, 52, 231–236. [CrossRef]20. Vásquez Capacho, J.W.; Perez Zuñiga, C.G.; Muñoz Maldonado, Y.A.; Ospino Castro, A.J. An additional layer of protection through superalarms with diagnosis capability. CT&F Cienc. Tecnol. Futuro 2020, 10, 45–65. [CrossRef]21. Bayoudh, M.; Travé-Massuyès, L.; Olive, X. Hybrid Systems Diagnosis by Coupling Continuous and Discrete Event Techniques. IFAC Proc. Vol. 2008, 41, 7265–7270. [CrossRef]22. Gao, Z.; Cecati, C.; Ding, S.X. A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis with ModelBased and Signal-Based Approaches. IEEE Trans. Ind. Electron. 2015, 62, 3757–3767. [CrossRef]23. Vásquez, J.; Travé-Massuyès, L.; Subias, A.; Jimenez, F.; Agudelo, C. Alarm Management Based on Diagnosis. IFAC-PapersOnLine 2016, 49, 126–131. [CrossRef]24. Capacho, J.V.; Subias, A.; Travé-Massuyès, L.; Jimenez, F. Alarm Management via Temporal Pattern Learning. Eng. Appl. Artif. Intell. 2017, 65, 506–516. [CrossRef]25. Vásquez, J.W.; Travé-Massuyès, L.; Subias, A.; Jiménez, F.; Agudelo, C. Chronicle Based Alarm Management in Startup and Shutdown stages. In Proceedings of the 26th International Workshop on Principles of Diagnosis, Paris, France, 31 August– 3 September 2015; pp. 277–280. Available online: https://hal.laas.fr/Hal-01847469 (accessed on 1 October 2017).26. Cordier, M.-O.; Dousson, C. Alarm Driven Monitoring Based on Chronicles. IFAC Proc. Vol. 2000, 33, 291–296. [CrossRef]27. Dousson, C. Suivi d’évolutions Et Reconnaissance De Chroniques. Ph.D. Thesis, Université de Toulouse, Toulouse, France, 1994. Available online: http://www.theses.fr/1994TOU30264 (accessed on 1 October 2017).28. Pons, R.; Subias, A.; Travé-Massuyès, L. Iterative Hybrid Causal Model Based Diagnosis: Application to Automotive Embedded Functions. Eng. Appl. Artif. Intell. 2015, 37, 319–335. [CrossRef]29. Vásquez, J.W.; Perez-Zuñiga, G.; Muñoz, Y.; Ospino, A. Simultaneous occurrences and false-positives analysis in discrete event dynamic systems. J. Comput. Sci. 2020, 44, 101162. 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