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A method for fault detection and diagnostics in ventilation units using virtual sensors
dc.contributor.author | Giovanni Mattera, Claudio |
dc.contributor.author | Quevedo Casín, Joseba Jokin |
dc.contributor.author | Escobet Canal, Teresa |
dc.contributor.author | Reza Shaker, Hamir |
dc.contributor.author | Jradi, Muhyiddine |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria Minera, Industrial i TIC |
dc.date.accessioned | 2018-12-20T13:08:07Z |
dc.date.available | 2018-12-20T13:08:07Z |
dc.date.issued | 2018-11-14 |
dc.identifier.citation | Claudio Giovanni Mattera, Quevedo, J., Escobet, T., Hamid Reza Shaker, M. J. A method for fault detection and diagnostics in ventilation units using virtual sensors. "Sensors", 14 Novembre 2018, vol. 18, núm. 11, p. 3931-1-3931-21. |
dc.identifier.issn | 1424-8220 |
dc.identifier.uri | http://hdl.handle.net/2117/126083 |
dc.description.abstract | Buildings represent a significant portion of global energy consumption. Ventilation units are complex components, often customized for the specific building, responsible for a large part of energy consumption. Their faults impact buildings’ energy efficiency and occupancy comfort. In order to ensure their correct operation, proper fault detection and diagnostics methods must be applied. Hardware redundancy, an effective approach to detect faults, leads to increased costs and space requirements. We propose exploiting physical relations inside ventilation units to create virtual sensors from other sensors’ readings, introducing redundancy in the system. We use two different measures to detect when a virtual sensor deviates from the physical one: coefficient of determination for linear models, and acceptable range. We tested our method on a real building at the University of Southern Denmark, developing three virtual sensors: temperature, airflow, and fan speed. We employed linear regression models, statistical models, and non-linear regression models. All models detected an anomalous strong oscillation in the temperature sensors. Readings fell outside the acceptable range and the coefficient of determination dropped. Our method showed promising results by introducing redundancy in the system, which can benefit several applications, such as fault detection and diagnostics and fault-tolerant control. Future work will be necessary to discover thresholds and set up automatic fault detection and diagnostics. |
dc.language.iso | eng |
dc.publisher | Multidisciplinary Digital Publishing Institute (MDPI) |
dc.subject | Àrees temàtiques de la UPC::Edificació::Instal·lacions i acondicionament d'edificis::Domòtica |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Automàtica i control |
dc.subject.lcsh | Intelligent buildings |
dc.subject.lcsh | Detectors |
dc.subject.lcsh | Automatic control |
dc.subject.other | fault detection and diagnosis |
dc.subject.other | virtual sensors |
dc.subject.other | HVAC |
dc.subject.other | smart buildings |
dc.title | A method for fault detection and diagnostics in ventilation units using virtual sensors |
dc.type | Article |
dc.subject.lemac | Edificis intel·ligents |
dc.subject.lemac | Detectors |
dc.subject.lemac | Control automàtic |
dc.contributor.group | Universitat Politècnica de Catalunya. SAC - Sistemes Avançats de Control |
dc.identifier.doi | 10.3390/s18113931 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | https://www.mdpi.com/1424-8220/18/11/3931 |
dc.rights.access | Open Access |
local.identifier.drac | 23516450 |
dc.description.version | Postprint (published version) |
local.citation.author | Mattera, Claudio Giovanni; Quevedo, J.; Escobet, T.; Hamid Reza Shaker, Muhyiddine Jradi |
local.citation.publicationName | Sensors |
local.citation.volume | 18 |
local.citation.number | 11 |
local.citation.startingPage | 3931-1 |
local.citation.endingPage | 3931-21 |
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