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A fault detection method for an automatic detection of spawning in oysters

hal.structure.identifierNon-Asymptotic estimation for online systems [NON-A]
dc.contributor.authorAHMED, Hafiz
hal.structure.identifierNon-Asymptotic estimation for online systems [NON-A]
dc.contributor.authorUSHIROBIRA, Rosane
hal.structure.identifierNon-Asymptotic estimation for online systems [NON-A]
dc.contributor.authorEFIMOV, Denis
hal.structure.identifierEnvironnements et Paléoenvironnements OCéaniques [EPOC]
dc.contributor.authorTRAN, Damien
hal.structure.identifierEnvironnements et Paléoenvironnements OCéaniques [EPOC]
dc.contributor.authorSOW, Mohamedou
hal.structure.identifierEnvironnements et Paléoenvironnements OCéaniques [EPOC]
dc.contributor.authorPAYTON, Laura
hal.structure.identifierEnvironnements et Paléoenvironnements OCéaniques [EPOC]
dc.contributor.authorMASSABUAU, Jean-Charles
dc.date.accessioned2024-05-15T12:29:33Z
dc.date.available2024-05-15T12:29:33Z
dc.date.issued2016-03-01
dc.identifier.issn1063-6536
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/199880
dc.description.abstractEnUsing measurements of valve activity (i.e. the distance between the two valves) in populations of bivalves under natural environmental condition (16 oysters in the Bay of Arcachon, France, in 2007, 2013 and 2014), an algorithm for an automatic detection of the spawning period of oysters is proposed in this paper. Spawning observations are important in aquaculture and biological studies, and until now, such a detection is done through visual analysis by an expert. The algorithm is based on the fault detection approach and it works through the estimation of velocity of valve movement activity, that can be obtained by calculating the time derivative of the valve distance. A summarized description of the methods used for the derivative estimation is provided, followed by the associated signal processing and decision making algorithm to determine spawning from the velocity signal. A protection from false spawning detection is also considered by analyzing the simultaneity in spawning. Through this study, it is shown that spawning in a population of oysters living in their natural habitat (i.e. in the sea) can be automatically detected without any human expertise saving time and resources. The fault detection method presented in the paper can also be used to detect complex oscillatory behavior which is of interest to control engineering community.
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers
dc.subject.enSpawning
dc.subject.enFiltering
dc.subject.enFault Detection
dc.title.enA fault detection method for an automatic detection of spawning in oysters
dc.typeArticle de revueen_US
dc.identifier.doi10.1109/TCST.2015.2472999
dc.subject.halSciences de l'ingénieur [physics]/Automatique / Robotique
bordeaux.journalIEEE Transactions on Control Systems Technologyen_US
bordeaux.page1140--1147
bordeaux.volume24
bordeaux.hal.laboratoriesEPOC : Environnements et Paléoenvironnements Océaniques et Continentaux - UMR 5805en_US
bordeaux.issue3
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
bordeaux.import.sourcehal
hal.identifierhal-01185118
hal.version1
hal.popularnon
hal.audienceInternationale
hal.exportfalse
workflow.import.sourcehal
dc.rights.ccPas de Licence CCen_US
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