Application of Interval Arithmetic to formulate a method in Fault Detection and Isolation (FDI)

dc.contributor.advisorSofrony Esmeral, Jorge Ivanspa
dc.contributor.advisorAvilés Velázquez, Jesús Davidspa
dc.contributor.authorCortés Cruz, Eduardospa
dc.date.accessioned2025-09-08T19:11:11Z
dc.date.available2025-09-08T19:11:11Z
dc.date.issued2025-06-06
dc.descriptionilustraciones, diagramasspa
dc.description.abstractThis doctoral thesis presents the use of interval observers in the field of Fault Detection and Isolation (FDI), with application to fluid transportation systems through horizontal pipelines. Employing interval arithmetic as the theoretical basis, the developed approach stands out for its reliability and precision, leveraging the fundamental principles of interval arithmetic to enhance efficiency in identifying system faults. The study delves into the formulation of a comprehensive method aiming to overcome conventional limitations by effectively addressing the inherent uncertainty in measurements and modeling errors encountered when using analytical models to describe fluid movement in a horizontal pipeline. System and signal uncertainty complicates the identification of faults, reducing accuracy. In this context, interval arithmetic provides an analytical framework for managing numerical variability and algebraic expressions that arise during the acquisition of the interval-type analytical model. An observer is designed using an interval model to provide enhanced fault detection and uncertainty rejection. The interval-type analytical models are then validated on a reals life example to obtain an FDI validation, enabling FDI analysis of faults. This analytical approach proves to be a key element in obtaining more structured and reliable results in fault detection under the presence of system uncertainty and signal perturbation. The practical relevance of this research is highlighted by the proposed method’s capability to achieve reliable leak detection. This achievement not only contributes to the advancement in academic research but also seeks to establish tangible and valuable applications in the industrial sector. The results if this research directly contribute to enhancing safety and resource management in critical infrastructures, marking a milestone in the convergence between theoretical research and the practical problem-solving in the fluid transportation sector. This approach promises to generate a positive impact on the integrity and operation of fluid transportation systems through pipelines.eng
dc.description.abstractEsta tesis doctoral introduce una propuesta novedosa en el ámbito de la detección y aislamiento de fallos FDI en sistemas de transporte de fluidos a través de tuberías horizontales, al emplear la aritmética por intervalos como referente analítico. El enfoque desarrollado destaca por su confiabilidad y precisión, haciendo uso de los principios fundamentales de la aritmética por intervalos para mejorar la eficiencia en la identificación de fugas en tuberías horizontales cuando un fluido circula a través de ellas. El estudio se adentra en la formulación de un método integral que busca superar las limitaciones convencionales al abordar de manera efectiva la incertidumbre inherente en las mediciones y los errores de modelado presentes al utilizar modelos analíticos para describir el movimiento de un fluido en una tubería horizontal. En este contexto, la aritmética por intervalos proporciona un marco analítico para gestionar las variabilidades numéricas y expresiones algebraicas surgidas durante la obtención del modelo analítico tipo intervalo y posteriormente diseñar sobre este modelo intervalo un estimador de estados analítico denominado observador intervalo, para tener una descripción total del fenómeno físico y posteriormente validar estos modelos analíticos tipo intervalo para obtener una validación FDI que va permitir realizar análisis FDI de fugas. Este enfoque analítico se revela como un elemento clave para obtener resultados más estructurados y confiables en la detección de fugas cuando un fluido circula por una tubería horizontal. La relevancia práctica de esta investigación resalta en la capacidad del método propuesto para lograr una detección confiable de fugas. Este logro no solo impulsa el avance en la investigación académica, sino que también busca establecer aplicaciones tangibles y valiosas en el ámbito industrial. La implementación de esta innovación contribuye directamente a mejorar la seguridad y la gestión de recursos en infraestructuras críticas, marcando un hito en la convergencia entre la investigación teórica y la solución de problemas prácticos en el sector del transporte de fluidos. Este enfoque integral promete generar un impacto positivo y duradero en la integridad y operación de sistemas de transporte de fluidos a través de tuberías a nivel global. (Texto tomado de la fuente).spa
dc.description.degreelevelDoctoradospa
dc.description.degreenameDoctor en Ingenieríaspa
dc.description.researchareaIngeniería de automatización, control y mecatrónicaspa
dc.format.extentxvi, 98 páginasspa
dc.format.mimetypeapplication/pdf
dc.identifier.instnameUniversidad Nacional de Colombiaspa
dc.identifier.reponameRepositorio Institucional Universidad Nacional de Colombiaspa
dc.identifier.repourlhttps://repositorio.unal.edu.co/spa
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/88646
dc.language.isoeng
dc.publisherUniversidad Nacional de Colombiaspa
dc.publisher.branchUniversidad Nacional de Colombia - Sede Bogotáspa
dc.publisher.facultyFacultad de Ingenieríaspa
dc.publisher.placeBogotá, Colombiaspa
dc.publisher.programBogotá - Ingeniería - Doctorado en Ingeniería - Ingeniería Mecánica y Mecatrónica
dc.relation.referencesAngeli, D. and Sontag, E. D. (2003). Monotone control systems. IEEE Transactions on automatic control, 48(10):1684–1698
dc.relation.referencesAvilés, J. D. and Moreno, J. A. (2014). Preserving order observers for nonlinear systems. International Journal of Robust and Nonlinear Control, 24(16):2153–2178.
dc.relation.referencesAvilés, J. D. and Moreno, J. A. (2018). Interval observer design for nonlinear systems: Stability radii approach. IEEE Access, 6:52801–52813.
dc.relation.referencesBesançon, G., Bornard, G., and Hammouri, H. (1996). Observer synthesis for a class of nonlinear control systems. European Journal of control, 2(3):176–192.
dc.relation.referencesBesançon, G., Guillén, M., Dulhoste, J.-F., Santos, R., and Scola, I. R. (2013). Pipeline partial blockage modeling and identification. IFAC Proceedings Volumes, 46(11):730–735
dc.relation.referencesBrogliato, B., Lozano, R., Maschke, B., Egeland, O., et al. (2007). Dissipative systems analysis and control. Theory and Applications, 2:2–5
dc.relation.referencesCacace, F., Germani, A., and Manes, C. (2015). A new approach to design interval observers for linear systems. IEEE Transactions on Automatic Control, 60(6):1665–1670.
dc.relation.referencesCarrillo, J. A. C. et al. (2012). Método de detección y ubicación de fugas, en ductos de gran longitud, mediante velocidad de propagación de onda de presión negativa, en ductos con mediciones de presión multipunto.
dc.relation.referencesChaudhry, M. H. (2014). Transient-Flow Equations, pages 35–64. Springer New York, New York, NY.
dc.relation.referencesChow, E. and Willsky, A. (1984). Analytical redundancy and the design of robust failure detection systems. IEEE Transactions on Automatic Control, 29(7):603–614.
dc.relation.referencesCruz, E. C., Esmeral, J. I. S., and Velásquez, J. D. A. (2023). Open-loop stability analysis of interval dynamic systems. In Workshop on Engineering Applications, pages 92–103. Springer.
dc.relation.referencesCugueró-Escofet, M. A., Puig, V., Quevedo, J., and Blesa, J. (2015). Optimal pressure sensor placement for leak localisation using a relaxed isolation index: Application to the barcelona water network. IFAC-PapersOnLine, 48(21):1108–1113
dc.relation.referencesDeif, A. S. (1990). Adv Matrix Theory Sci Eng. CRC Press.
dc.relation.referencesDelgado-Aguiñaga, J., Becerra-López, F., Torres, L., Besançon, G., Puig, V., and Magaña, M. J. (2020). Dynamic model for a water distribution network: Application to leak diagnosis and quality monitoring. IFAC-PapersOnLine, 53(2):16679–16684.
dc.relation.referencesDelgado-Aguiñaga, J., Besancon, G., Begovich, O., and Carvajal, J. (2016). Multi-leak diagnosis in pipelines based on extended kalman filter. Control Engineering Practice, 49:139–148.
dc.relation.referencesDelgado-Aguiñaga, J. A., Santos-Ruiz, I., Besançon, G., López-Estrada, F. R., and Puig, V. (2022). Ekf-based observers for multi-leak diagnosis in branched pipeline systems. Mechanical Systems and Signal Processing, 178:109198.
dc.relation.referencesDrogkoula, M., Kokkinos, K., and Samaras, N. (2023). A comprehensive survey of machine learning methodologies with emphasis in water resources management. Applied Sciences, 13(22):12147.
dc.relation.referencesEfimov, D., Raïssi, T., Chebotarev, S., and Zolghadri, A. (2013). Interval state observer for nonlinear time varying systems. Automatica, 49(1):200–205.
dc.relation.referencesFares, A., Tijani, I., Rui, Z., and Zayed, T. (2023). Leak detection in real water distribution networks based on acoustic emission and machine learning. Environmental Technology, 44(25):3850–3866.
dc.relation.referencesGao, Z., Cecati, C., and Ding, S. X. (2015). A survey of fault diagnosis and fault-tolerant techniques—part i: Fault diagnosis with model-based and signal-based approaches. IEEE transactions on industrial electronics, 62(6):3757–3767.
dc.relation.referencesGertler, J. (1997). Fault detection and isolation using parity relations. Control Engineering Practice, 5(5):653–661.
dc.relation.referencesGertler, J. (1998). Fault Detection and Diagnosis in Engineering Systems. Electrical Engineering & Electronics. CRC Press, 1 edition.
dc.relation.referencesHadroug, N., Hafaifa, A., Kouzou, A., and Chaibet, A. (2017). Dynamic model linearization of two shafts gas turbine via their input/output data around the equilibrium points. Energy, 120:488–497.
dc.relation.referencesIsermann, R. (2005a). Fault-diagnosis systems: an introduction from fault detection to fault tolerance. Springer Science & Business Media.
dc.relation.referencesIsermann, R. (2005b). Model-based fault-detection and diagnosis–status and applications. Annual Reviews in control, 29(1):71–85.
dc.relation.referencesJaulin, L. and Walter, E. (1993). Set inversion via interval analysis for nonlinear boundederror estimation. Automatica, 29(4):1053–1064.
dc.relation.referencesKarim, M. Z. A., Alrasheedy, A., and Gaafar, A. (2015). Compensated mass balance method for oil pipeline leakage detection using scada. Int. J. Comput. Sci. Secur.(IJCSS), 9:293–302.
dc.relation.referencesKhalil, H. K. (2002). Nonlinear systems. Prentice Hall, 3rd ed edition.
dc.relation.referencesKhan, A., Xie, W., Zhang, L., and Liu, L.-W. (2020). Design and applications of interval observers for uncertain dynamical systems. IET Circuits, Devices & Systems, 14(6):721– 740.
dc.relation.referencesKhan, A. Q. (2010). Observer-based fault detection in nonlinear systems. PhD thesis, Duisburg, Essen, Univ., Diss., 2010.
dc.relation.referencesLorenzo Farina, S. R. (2011). Positive Linear Systems -Theory and Applications. John Wiley & Sons.
dc.relation.referencesMeslem, N., Martinez, J., Ramdani, N., and Besançon, G. (2020). An interval observer for uncertain continuous-time linear systems. International Journal of Robust and Nonlinear Control, 30(5):1886–1902.
dc.relation.referencesMoore, R. E. (1987). Methods and applications of interval analysis. SIAM studies in applied mathematics 2. LAP LAMBERT Academic Publishing, 1 edition. Moore, R. E., Kearfott, R. B., and Cloud, M. J. (2009). Introduction to interval analysis. SIAM.
dc.relation.referencesNavarro-Díaz, A., Delgado-Aguiñaga, J.-A., Begovich, O., and Besançon, G. (2021). Two simultaneous leak diagnosis in pipelines based on input–output numerical differentiation. Sensors, 21(23):8035.
dc.relation.referencesRaïssi, T., Videau, G., and Zolghadri, A. (2010). Interval observer design for consistency checks of nonlinear continuous-time systems. Automatica, 46(3):518–527.
dc.relation.referencesRaïssi, T., Ramdani, N., and Candau, Y. (2005). Bounded error moving horizon state estimator for non-linear continuous-time systems: application to a bioprocess system. Journal of Process Control, 15(5):537–545.
dc.relation.referencesRoberson, J. A., Cassidy, J. J., and Chaudhry, M. H. (1998). Hydraulic engineering. Technical report.
dc.relation.referencesSamy, I. and Gu, D.-W. (2011). Fault Detection and Isolation (FDI), pages 5–17. Springer Berlin Heidelberg, Berlin, Heidelberg.
dc.relation.referencesSantos-Ruiz, I., Bermúdez, J. R., López-Estrada, F. R., Puig, V., Torres, L., and Delgado- Aguiñaga, J. (2018). Online leak diagnosis in pipelines using an ekf-based and steady-state mixed approach. Control Engineering Practice, 81:55–64.
dc.relation.referencesShary, S. (2018). A note on definitions of the rank for interval matrices. International Journal of Numerical Methods and Applications, 17(2):91–96.
dc.relation.referencesSin, S. T. (2006). Detección robusta de fallos utilizando análisis intervalar. PhD thesis, Universitat Politècnica de Catalunya (UPC).
dc.relation.referencesSontag, E. D. (2007). The iss philosophy as a unifying framework for stability-like behavior. In Nonlinear control in the year 2000 volume 2, pages 443–467. Springer.
dc.relation.referencesTorres, L., Verde, C., Carrera, R., and Cayetano, R. (2014). Algoritmos de diagnóstico para fallas en ductos. Tecnología y ciencias del agua, 5(4):57–78.
dc.relation.referencesVerde, C. (2001). Multi-leak detection and isolation in fluid pipelines. Control Engineering Practice, 9(6):673–682.
dc.relation.referencesVerde, C., Gentil, S., and Morales-Menéndez, R. (2013). Monitoreo y diagnóstico automético de fallas en sistemas dinámicos. Editorial Trillas.
dc.relation.referencesVerde, C. and Visairo, N. (2001). Bank of nonlinear observers for the detection of multiple leaks in a pipeline. In Proceedings of the 2001 IEEE International Conference on Control Applications (CCA’01)(Cat. No. 01CH37204), pages 714–719. IEEE.
dc.relation.referencesWang, X., Ghidaoui, M. S., and Lin, J. (2019). Identification of multiple leaks in pipeline iii: Experimental results. Mechanical Systems and Signal Processing, 130:395–408.
dc.relation.referencesWillems, J. C. (1972a). Dissipative dynamical systems part i: General theory. Archive for rational mechanics and analysis, 45(5):321–351.
dc.relation.referencesWillems, J. C. (1972b). Dissipative dynamical systems part ii: Linear systems with quadratic supply rates. Archive for rational mechanics and analysis, 45:352–393.
dc.relation.referencesYang, A. and Ma, S. (2021). Robust control for singular systems based on the uncertainty and disturbance estimator. IEEE Access, 9:109704–109717.
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.rights.licenseAtribución-CompartirIgual 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by-sa/4.0/
dc.subject.ddc620 - Ingeniería y operaciones afines::629 - Otras ramas de la ingenieríaspa
dc.subject.proposalInterval arithmeticeng
dc.subject.proposalInterval modelseng
dc.subject.proposalInterval observerseng
dc.subject.proposalFDI analysiseng
dc.subject.proposalFluid transporteng
dc.subject.proposalAritmética por Intervalosspa
dc.subject.proposalModelo intervalarspa
dc.subject.proposalObservador por intervalosspa
dc.subject.proposalAnálisis FDIspa
dc.subject.proposalTransporte de fluidosspa
dc.subject.unescoIngeniería de la industria y de los transportesspa
dc.subject.unescoManufacturing and transport engineeringeng
dc.subject.unescoAnálisis numéricospa
dc.subject.unescoNumerical analysiseng
dc.subject.wikidataTransporte por tuberíaspa
dc.subject.wikidatapipeline transporteng
dc.titleApplication of Interval Arithmetic to formulate a method in Fault Detection and Isolation (FDI)eng
dc.title.translatedAplicación de la Aritmética por Intervalos para formular un método en Detección y Aislamiento de Fallas (FDI)spa
dc.typeTrabajo de grado - Doctoradospa
dc.type.coarhttp://purl.org/coar/resource_type/c_db06
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.contentText
dc.type.driverinfo:eu-repo/semantics/doctoralThesis
dc.type.redcolhttp://purl.org/redcol/resource_type/TD
dc.type.versioninfo:eu-repo/semantics/acceptedVersion
dcterms.audience.professionaldevelopmentInvestigadoresspa
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2

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