Prepoznavanje i klasifikacija ostećenja na lopaticama vjetro-elektrane

undergraduate thesis

• Title (english): Recognition and classification of damages on a wind-farm blade
• Author: Dorian Dončević
• Mentor: Stjepan Bogdan (mentor)
• Committee member: Stjepan Bogdan (predsjednik povjerenstva)
• Committee member: Antonella Barišić (član povjerenstva)
• Committee member: Robert Milijaš (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2021-07-15, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

U okviru ovog rada implementiran je model dubokog učenja YOLOv3-tiny za prepoznavanje i klasifikaciju oštećenja na lopaticama vjetroelektrane. Prikupljene fotografije korištene su za treniranje i testiranje modela te su na kraju prikazani rezultati kao i pregled mogućih poboljšanja.

Abstract (english)

In this paper, a deep learning model yolov3-tiny for recognition and classification of damage on wind turbine blades was implemented. The collected photographs were used to train and test the model and finally the results were presented as well as an overview of possible improvements.

• Keywords: python; umjetna inteligencija; strojno učenje; duboko učenje; neuronske mreže; vjetroelektrane; oštećenje; YOLO; YOLOv3-tiny
• Keywords (english): python; artificial inteligence; machine learning; deep learning; neural networks; windturbine; damage; YOLO; YOLOv3-tiny
• Language: croatian
• URN:NBN: urn:nbn:hr:168:043574
• Study programme: Title: Computing; Study programme type: university; Study level: undergraduate; Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2023-01-14 20:19:00