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Title:Zaznavanje trkov na daljnovodih z optičnim interferometrom
Authors:Mikolič, Jan (Author)
Holobar, Aleš (Mentor) More about this mentor... New window
Đonlagić, Denis (Co-mentor)
Files:.pdf UN_Mikolic_Jan_2017.pdf (14,72 MB)
 
Language:Slovenian
Work type:Bachelor thesis/paper (mb11)
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V diplomski nalogi skušamo ugotoviti, v kolikšni meri je možno zaznavati in klasificirati trke na jeklenicah daljnovodov z optičnim interferometrom. Na začetku predstavimo osnovne pojme interferometrije in opišemo uporabljen optični interferometer. V jedru diplomske naloge natančneje opišemo eksperimentalni protokol in obdelavo signalov. Nadaljujemo z implementacijo algoritmov za segmentacijo in klasifikacijo zajetih signalov ter predstavimo dobljene rezultate. Segmentacijo izvedemo v domeni števila prehodov signala skozi ničlo, za klasifikacijo pa uporabimo večplastno nevronsko mrežo z algoritmom vzvratnega učenja. Rezultati študije nakazujejo, da sta implementirani segmentacija in klasifikacija uspešni v 77 % izvedenih trkov različnih predmetov.
Keywords:interferometrija, obdelava signalov, klasifikacija, detekcija trkov, računalniški algoritmi
Year of publishing:2017
Publisher:J. Mikolič
Source:[Maribor
UDC:004.421:528.872(043.2)
COBISS_ID:20869398 Link is opened in a new window
License:CC BY-NC-ND 4.0
This work is available under this license: Creative Commons Attribution Non-Commercial No Derivatives 4.0 International
Views:87
Downloads:5
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Categories:KTFMB - FERI
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Secondary language

Language:English
Title:Collision detection on transmission lines with optical interferometer
Abstract:We analyse feasibility of collision detection on transmission lines with optical interferometer. We first provide a brief introduction into interferometry, along with a description of the optical interferometer used for measurements in this study. Afterwards, we describe the conducted experimental protocol and signal processing methodology. The focus is on implementation of algorithms for signal segmentation and collision classification. We used zero-crossing algorithm to transform signals into segmentation domain. Classification of collisions is done with a multilayer neural network trained by the backpropagation algorithm. The results demonstrate an average success rate of 77% for segmentation and classification of collision with five different objects.
Keywords:interferometry, signal processing, classification, collision detection, computer algorithms


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