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Operational Failure Detection Applied to Heat Exchange Systems Using State Observer Method

dc.contributor.authorRojas Suárez, Jhan Piero
dc.contributor.authorEspinel Blanco, Edwin
dc.contributor.authorFlorez, Eder
dc.date.accessioned2022-12-06T14:37:37Z
dc.date.available2022-12-06T14:37:37Z
dc.date.issued2021
dc.identifier.urihttps://repositorio.ufps.edu.co/handle/ufps/6649
dc.description.abstractThe role of computational modeling is becoming predominant in the exploration and evaluation of new technologies. Numerical simulations have solved the most complex phenomena immersed in thermal sciences by the implementation of sophisticated mathematical algorithms. This study incorporates a stationary thermodynamic model in order to evaluate the main operational parameters and the overall performance of heat exchange systems based on energy and exergy viewpoints while implementing unknown inputs. Moreover, the study introduces a UIO state observer technology in order to facilitate the early prediction of failure events in heat exchange systems using a detect, isolate and identify (FDI) methodology. Therefore, the proposed model has induced different fault conditions in order to examine the overall performance while integrating error state of signals criteria from the relative difference between the real and modeled estimates. The outcomes have demonstrated a good agreement for the estimated values of the mathematical algorithm considering the imminent presence of disturbance and interference that promotes modeling error. Finally, the results have outlined that the estimations of real operation conditions are not affected by the unknown inputs.eng
dc.format.extent10 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.language.isoengspa
dc.publisherInternational Review of Automatic Controlspa
dc.relation.ispartofInternational Review of Automatic Control. Vol.14 N°.1. (2021)
dc.rightsCopyright © 2021 Praise Worthy Prize - All rights reserved.eng
dc.sourcehttps://www.praiseworthyprize.org/jsm/index.php?journal=ireaco&page=article&op=view&path%5B%5D=24811spa
dc.titleOperational Failure Detection Applied to Heat Exchange Systems Using State Observer Methodeng
dc.typeArtículo de revistaspa
dcterms.referencesG. Valencia Ochoa, C. Isaza-Roldan, and J.D. Forero, Economic and Exergo-Advance Analysis of a Waste Heat Recovery System Based on Regenerative Organic Rankine Cycle under Organic Fluids with Low Global Warming Potential, Energies, vol 13, no. 6, p. 1317, 2020. https://doi.org/10.3390/en13061317spa
dcterms.referencesOrozco, T., Herrera, M., Duarte Forero, J., CFD Study of Heat Exchangers Applied in Brayton Cycles: a Case Study in Supercritical Condition Using Carbon Dioxide as Working Fluid, (2019) International Review on Modelling and Simulations (IREMOS), 12 (2), pp. 72-82. https://doi.org/10.15866/iremos.v12i2.17221spa
dcterms.referencesOrozco, W., Acuña, N., Duarte Forero, J., Characterization of Emissions in Low Displacement Diesel Engines Using Biodiesel and Energy Recovery System, (2019) International Review of Mechanical Engineering (IREME), 13 (7), pp. 420-426. https://doi.org/10.15866/ireme.v13i7.17389spa
dcterms.referencesDuarte Forero, J., Lopez Taborda, L., Bula Silvera, A., Characterization of the Performance of Centrifugal Pumps Powered by a Diesel Engine in Dredging Applications, (2019) International Review of Mechanical Engineering (IREME), 13 (1), pp. 11-20. https://doi.org/10.15866/ireme.v13i1.16690spa
dcterms.referencesY. Kong, W. Wang, Z. Zuo, L. Yang, X. Du, and Y. Yang, Combined air-cooled condenser layout with in line configured finned tube bundles to improve cooling performance, Applied Thermal Engineering, pp. 505–518, 2019. https://doi.org/10.1016/j.applthermaleng.2019.03.099spa
dcterms.referencesL. Zhao, W. Cui, Y. Zhan, Z. Wang, Y. Liang, and Y. Ge, Optimal structural design searching algorithm for cooling towers based on typical adverse wind load patterns, Thin-Walled Structures, vol. 151, p. 106740, 2020. https://doi.org/10.1016/j.tws.2020.106740spa
dcterms.referencesObregon, L., Valencia, G., Duarte Forero, J., Efficiency Optimization Study of a Centrifugal Pump for Industrial Dredging Applications Using CFD, (2019) International Review on Modelling and Simulations (IREMOS), 12 (4), pp. 245-252. https://doi.org/10.15866/iremos.v12i4.18009spa
dcterms.referencesJ. J. Tang, H. Wu, S. T. Ke, and Q. Fang, Numerical simulations of a large-scale cooling tower against the impact of commercial aircrafts, Thin-Walled Structures, vol. 144, p. 106367, 2019. https://doi.org/10.1016/j.tws.2019.106367spa
dcterms.referencesW. Ge, Y. Zhao, S. Song, W. Li, S. Gao, and T. Chen, Thermal characteristics of dry cooling tower reconstructed from obsolete natural draft wet cooling tower and the relevant thermal system coupling optimization, Applied Thermal Engineering, vol. 174, p. 115202, 2020. https://doi.org/10.1016/j.applthermaleng.2020.115202spa
dcterms.referencesD. Pandelidis, Numerical study and performance evaluation of the Maisotsenko cycle cooling tower, Energy Conversion and Management, vol. 210, p. 112735, 2020. https://doi.org/10.1016/j.enconman.2020.112735spa
dcterms.referencesDe la Hoz, J., Valencia, G., Duarte Forero, J., Reynolds Averaged Navier–Stokes Simulations of the Airflow in a Centrifugal Fan Using OpenFOAM, (2019) International Review on Modelling and Simulations (IREMOS), 12 (4), pp. 230-239. https://doi.org/10.15866/iremos.v12i4.17802spa
dcterms.referencesZ. Nourani, A. Naserbegi, S. Tayyebi, and M. Aghaie, Thermodynamic evaluation of hybrid cooling towers based on ambient temperature, Thermal Science and Engineering Progress, vol. 14, p. 100406, 2019. https://doi.org/10.1016/j.tsep.2019.100406spa
dcterms.referencesF. Consuegra, A. Bula, W. Guillín, J. Sánchez, and J. Duarte Forero, Instantaneous in-Cylinder Volume Considering Deformation and Clearance due to Lubricating Film in Reciprocating Internal Combustion Engines, Energies, vol. 12, no. 8, p. 1437, 2019. https://doi.org/10.3390/en12081437spa
dcterms.referencesL. Xia, H. Gurgenci, D. Liu, Z. Guan, L. Zhou, and P. Wang, CFD analysis of pre-cooling water spray system in natural draft dry cooling towers, Applied Thermal Engineering, vol. 105, pp. 1051–1060, 2016. https://doi.org/10.1016/j.applthermaleng.2016.03.096spa
dcterms.referencesA. A. Sedighi and M. Bazargan, A CFD analysis of the pollutant dispersion from cooling towers with various configurations in the lower region of atmospheric boundary layer, Science of The Total Environment, vol. 696, p. 133939, 2019. https://doi.org/10.1016/j.scitotenv.2019.133939spa
dcterms.referencesM. Cagnoli, A. de la Calle, J. Pye, L. Savoldi, and R. Zanino, A CFD-supported dynamic system-level model of a sodium-cooled billboard-type receiver for central tower CSP applications, Solar Energy, vol. 177, pp. 576–594, 2019. https://doi.org/10.1016/j.solener.2018.11.031spa
dcterms.referencesG. Valencia Ochoa, C. Acevedo Peñaloza, and J. Duarte Forero, Thermoeconomic Optimization with PSO Algorithm of Waste Heat Recovery Systems Based on Organic Rankine Cycle System for a Natural Gas Engine, Energies, vol. 12, no. 21, p. 4165, 2019. https://doi.org/10.3390/en12214165spa
dcterms.referencesJ. Duarte, J. Garcia, J. Jiménez, M. E. Sanjuan, A. Bula, and J. González, Auto-Ignition Control in Spark-Ignition Engines Using Internal Model Control Structure, Journal of Energy Resources Technology, vol. 139, no. 2, p. 022201, 2017. https://doi.org/10.1115/1.4034026spa
dcterms.referencesE. Hernández Martínez, M. C. P. Avitia Carlos, J. I. Cisneros Solís, and M. C. M. del C. Prieto Avalos, Thermodynamic simulation and mathematical model for single and double flash cycles of Cerro Prieto geothermal power plants, Geothermics, vol. 83, p. 101713, 2020. https://doi.org/10.1016/j.geothermics.2019.101713spa
dcterms.referencesP. Dong, A. S. Kaiser, Z. Guan, X. Li, H. Gurgenci, and K. Hooman, A novel method to predict the transient start-up time for natural draft dry cooling towers in dispatchable power plants, International Journal of Heat and Mass Transfer, vol. 145, p. 118794, 2019. https://doi.org/10.1016/j.ijheatmasstransfer.2019.118794spa
dcterms.referencesE. Terzi, A. Cataldo, P. Lorusso, and R. Scattolini, Modelling and predictive control of a recirculating cooling water system for an industrial plant, Journal of Process Control, vol. 68, pp. 205–217, 2018. https://doi.org/10.1016/j.jprocont.2018.04.009spa
dcterms.referencesM. Slootweg, K. J. Craig, and J. P. Meyer, A computational approach to simulate the optical and thermal performance of a novel complex geometry solar tower molten salt cavity receiver, Solar Energy, vol. 187, pp. 13–29, 2019. https://doi.org/10.1016/j.solener.2019.05.003spa
dcterms.referencesS. Razvarz, R. Jafari, C. Vargas-Jarillo, A. Gegov, and M. Forooshani, Leakage Detection in Pipeline Based on Second Order Extended Kalman Filter Observer, IFAC-PapersOnLine, vol. 52, no. 29, pp. 116–121, 2019. https://doi.org/10.1016/j.ifacol.2019.12.631spa
dcterms.referencesX. Zhao, A scientometric review of global BIM research: Analysis and visualization, Automation in Construction, vol. 80, pp. 37–47, 2017. https://doi.org/10.1016/j.autcon.2017.04.002spa
dcterms.referencesB. Truffer, J. Schippl, and T. Fleischer, Decentering technology in technology assessment: prospects for socio-technical transitions in electric mobility in Germany, Technological Forecasting and Social Change, vol. 122, pp. 34–48, 2017. https://doi.org/10.1016/j.techfore.2017.04.020spa
dcterms.referencesP. Tang, K. Peng, K. Zhang, Z. Chen, X. Yang, and L. Li, A Deep Belief Network-based Fault Detection Method for Nonlinear Processes, IFAC-PapersOnLine, vol. 51, no. 24, pp. 9–14, 2018. https://doi.org/10.1016/j.ifacol.2018.09.522spa
dcterms.referencesK. Zhang, B. Jiang, and J. Xia, UIO-Based Fault Diagnosis Design in Finite-Frequency Domain for Discrete-Time T-S Fuzzy Systems, IFAC-PapersOnLine, vol. 49, no. 19, pp. 301–306, 2016. https://doi.org/10.1016/j.ifacol.2016.10.558spa
dcterms.referencesN. K. Jain, S. Celo, and V. Kumar, Internationalization speed, resources and performance: Evidence from Indian software industry, Journal of Business Research, vol. 95, pp. 26–37, 2019. https://doi.org/10.1016/j.jbusres.2018.09.019spa
dcterms.referencesH. Haes Alhelou, M. E. Hamedani Golshan, and J. Askari-Marnani, Robust sensor fault detection and isolation scheme for interconnected smart power systems in presence of RER and EVs using unknown input observer, International Journal of Electrical Power & Energy Systems, vol. 99, pp. 682–694, 2018. https://doi.org/10.1016/j.ijepes.2018.02.013spa
dcterms.referencesM. Pourasghar, V. Puig, and C. Ocampo-Martinez, Characterisation of interval-observer fault detection and isolation properties using the set-invariance approach, Journal of the Franklin Institute, vol. 357, no. 3, pp. 1853–1886, 2020. https://doi.org/10.1016/j.jfranklin.2019.11.027spa
dcterms.referencesH. Haes Alhelou, M. E. H. Golshan, N. D. Hatziargyriou, and M. P. Moghaddam, A Novel Unknown Input Observer-based Measurement Fault Detection and Isolation scheme for Micro-Grid Systems, IEEE Transactions on Industrial Informatics, pp. 1–1, 2020. https://doi.org/10.1109/tii.2020.2970211spa
dcterms.referencesA. Amrane, A. Larabi, and A. Aitouche, Unknown Input Observer design for fault sensor estimation applied to Induction Machine, Mathematics and Computers in Simulation, vol. 163, no. 4, pp. 148–171, 2018. https://doi.org/10.1016/j.matcom.2018.09.018spa
dcterms.referencesH. Jeong, B. Park, S. Park, H. Min, and S. Lee, Fault Detection and Identification Method using Observer-based Residuals, Reliability Engineering and System Safety, vol. 184, no. 7, pp. 27–40, 2018. https://doi.org/10.1016/j.ress.2018.02.007spa
dc.contributor.corporatenameInternational Review of Automatic Controlspa
dc.identifier.doihttps://doi.org/10.15866/ireaco.v14i1.19191
dc.publisher.placeItaliaspa
dc.relation.citationeditionVol.14 N°.1. (2021)spa
dc.relation.citationendpage60spa
dc.relation.citationissue1(2021)spa
dc.relation.citationstartpage51spa
dc.relation.citationvolume14spa
dc.relation.citesRojas, J., Espinel, E., Florez, E., Operational Failure Detection Applied to Heat Exchange Systems Using State Observer Method, (2021) International Review of Automatic Control (IREACO), 14 (1), pp. 51-60.doi:https://doi.org/10.15866/ireaco.v14i1.19191
dc.relation.ispartofjournalInternational Review of Automatic Controlspa
dc.rights.accessrightsinfo:eu-repo/semantics/closedAccessspa
dc.subject.proposalCooling Towereng
dc.subject.proposalFault Detectioneng
dc.subject.proposalSystemseng
dc.subject.proposalThermodynamiceng
dc.subject.proposalUIO State Observereng
dc.type.coarhttp://purl.org/coar/resource_type/c_6501spa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/articlespa
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oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85spa
dc.type.versioninfo:eu-repo/semantics/publishedVersionspa


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