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Fault detection and isolation in wind turbines using PCA and statistical hypothesis testing
dc.contributor | Pozo Montero, Francesc |
dc.contributor | Rodellar Benedé, José |
dc.contributor.author | Ollé Navarro, Ricard |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Matemàtica Aplicada III |
dc.date.accessioned | 2017-07-06T11:01:49Z |
dc.date.available | 2017-07-06T11:01:49Z |
dc.date.issued | 2016-06-08 |
dc.identifier.uri | http://hdl.handle.net/2117/106200 |
dc.description.abstract | This project aims to demonstrate the effectiveness of two fault detection strategies from a wind turbine’s structure, based on obtaining a baseline pattern through the principal component analysis (PCA) on the healthy state of the device’s structure. The data obtained from the structure which we want to check its integrity is projected to the pattern so that we can establish two different hypothesis tests –univariate and multivariate statistical inference- to define whether the structure is damaged or not. It also aims to use these strategies to detect what type of fault affects the wind turbine. To verify the correct operation of the fault detection plans, we will analyse data from structures affected by different types of faults that have been generated from a simulator (FAST software). Thus, we can tell if we are able to distinguish data from a healthy wind turbine or from a faulty one. |
dc.language.iso | eng |
dc.publisher | Universitat Politècnica de Catalunya |
dc.subject | Àrees temàtiques de la UPC::Enginyeria mecànica |
dc.subject.lcsh | Wind power |
dc.title | Fault detection and isolation in wind turbines using PCA and statistical hypothesis testing |
dc.type | Bachelor thesis |
dc.subject.lemac | Aerogeneradors |
dc.rights.access | Open Access |
dc.audience.educationlevel | Grau |
dc.audience.mediator | Escola d'Enginyeria de Barcelona Est |
dc.audience.degree | GRAU EN ENGINYERIA MECÀNICA (Pla 2009) |