dc.contributor.advisor | Δημογιαννόπουλος, Δημήτριος | |
dc.contributor.author | Μπέζος, Ευάγγελος | |
dc.date.accessioned | 2023-10-03T12:35:03Z | |
dc.date.available | 2023-10-03T12:35:03Z | |
dc.date.issued | 2023-09-11 | |
dc.identifier.uri | https://polynoe.lib.uniwa.gr/xmlui/handle/11400/5197 | |
dc.identifier.uri | http://dx.doi.org/10.26265/polynoe-5035 | |
dc.description.abstract | The exploitation of wind energy potential for the production of electrical energy from renewable sources has been in a continuous uptrend since the beginning of the 21st century. The demand for larger, more efficient and safer wind turbines has stimulated research on a multitude of fields, ranging from composite materials to automation control systems. A challenging aspect in the operation of all energy production systems is the uninterrupted and optimal power generation, which can be realized through the implementation of different condition monitoring methods. Likewise, condition monitoring in wind turbines enables operators to obtain real-time operation data, keeping track of the system’s health and intervening with preventive maintenance when deemed necessary. Emphasis is given on both structural and functional condition of wind turbines, implementing methods that require the least downtime for fault diagnosis and classification. In this master’s thesis a bibliographic review and categorization of modern (State-of-the-Art) model-based methodologies for performance and condition monitoring will be carried out. | el |
dc.format.extent | 126 | el |
dc.language.iso | en | el |
dc.publisher | Πανεπιστήμιο Δυτικής Αττικής | el |
dc.rights | Αναφορά Δημιουργού - Μη Εμπορική Χρήση - Παρόμοια Διανομή 4.0 Διεθνές | * |
dc.rights | Αναφορά Δημιουργού 4.0 Διεθνές | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.subject | Wind turbines | el |
dc.subject | Condition monitoring | el |
dc.subject | Fault prognosis | el |
dc.subject | Fault diagnosis | el |
dc.subject | Model-based condition monitoring | el |
dc.subject | Predictive maintenance | el |
dc.subject | State observers | el |
dc.subject | Neural networks | el |
dc.subject | Parameter estimation | el |
dc.subject | Kalman filter | el |
dc.subject | Parity equations | el |
dc.subject | Residual generation | el |
dc.subject | Modelling | el |
dc.subject | Ανεμογεννήτριες | el |
dc.title | Model-based methodologies for wind turbine performance and condition monitoring: a review | el |
dc.title.alternative | Μεθοδολογίες βασισμένες σε μοντέλο για την παρακολούθηση της απόδοσης και κατάστασης ανεμογεννητριών | el |
dc.type | Μεταπτυχιακή διπλωματική εργασία | el |
dc.contributor.committee | Κάντζος, Δημήτριος | |
dc.contributor.committee | Ganetsos, Theodore | |
dc.contributor.faculty | Σχολή Μηχανικών | el |
dc.contributor.department | Τμήμα Μηχανικών Βιομηχανικής Σχεδίασης και Παραγωγής | el |
dc.contributor.master | Αυτοματισμός Παραγωγής και Υπηρεσιών | el |