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Sistem za avtomatski optični pregled tiskanih vezij
ID Zadravec, Aljaž (Author), ID Trost, Andrej (Mentor) More about this mentor... This link opens in a new window

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Abstract
Sisteme za avtomatski optični pregled tiskanih vezij se v industriji uporablja med proizvodnim procesom. Njihov glavni namen je iskanje nepravilnosti na tiskanih vezjih. Prispevajo k izboljšanju kakovosti, zanesljivosti in učinkovitosti proizvodnje tiskanih vezij. V magistrskem delu je raziskana možnost poenostavitve in pocenitve takšnih sistemov, saj so običajno precej dragi. Sistem za avtomatski optični pregled tiskanih vezij v magistrski nalogi je bil razvit na platformi Raspberry Pi 4. Z namenom, da bi bile slike vedno zajete v enakem okolju, je bila narejena osvetlitvena enota. Zajeto sliko tiskanega vezja zasukamo z afinimi transformacijami tako, da so robovi tiskanega vezja vzporedni z robovi slike. Zasukana slika je obrezana, da na njej ostane le tiskano vezje brez ozadja. Aplikacija je razdeljena na dva dela. Prvi se izvede, ko vezje vsebuje markerje (angl. fiducial markers), drugi pa, ko jih ne vsebuje. V primeru, da vezje ne vsebuje markerjev, lahko takoj določimo izhodiščno točko koordinatnega sistema in poiščemo robove na sliki; če pa vezje vsebuje markerje, jih najprej poiščemo z metodo primerjanja vzorca markerja po sliki in iz njihove lokacije določimo koordinatno izhodišče. Po postopku iskanja robov z algoritmom s podtočkovno natančnostjo te robove filtriramo s ciljem, da ugotovimo kateri komponenti pripadajo. Na koncu iz filtriranih robov določimo, ali je komponenta pravilno pritrjena na tiskano vezje ali ne. Sistem je zmožen zaznati napake pri uporih, tuljavah in kondenzatorjih. Napake, ki jih je tak sistem zmožen zaznati, so komponenta, ki je preveč izmaknjena iz središča, manjkajoča komponenta in obrnjena komponenta.

Language:Slovenian
Keywords:detektorji robov, računalniški vid, OpenCV, AOI, Raspberry Pi
Work type:Master's thesis/paper
Organization:FE - Faculty of Electrical Engineering
Year:2023
PID:20.500.12556/RUL-149959 This link opens in a new window
COBISS.SI-ID:165367555 This link opens in a new window
Publication date in RUL:12.09.2023
Views:693
Downloads:39
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Secondary language

Language:English
Title:System for automatic optical inspection of printed circuit boards
Abstract:
Automatic optical inspection (AOI) systems for printed circuit boards are used within the industry during the manufacturing process. The primary purpose of such systems is to detect irregularities on printed circuit boards. They contribute to improving the quality, reliability, and efficiency of printed circuit board production. In this master's thesis, the possibility of simplifying and reducing the cost of such a system is explored, as these types of systems can be quite expensive. Automatic optical inspection (AOI) systems for printed circuit boards in our master’s thesis was developed on the Raspberry Pi 4 platform. In order to capture images in a consistent environment, an illumination unit was created. The captured image of the printed circuit board is rotated using affine transformations so that the edges of the circuit board are parallel to the edges of the image. The rotated image is then cropped, leaving only the printed circuit board without background in the image. The application is divided into two parts. The first one emerges when the circuit contains fiducial markers and the second one when it does not. If the circuit doesn't have markers, the origin point of the coordinate system is determined immediately, and the edges on the image are detected. However, if the circuit contains markers, they are first located using a template matching method, and their positions establish the coordinate origin. After locating the edges through a subpixel accuracy algorithm, these edges are filtered to determine which components they belong to. In the final phase, based on the filtered edges, it is determined whether a component is correctly attached to the printed circuit board or not. The system is capable of detecting errors in resistors, coils, and capacitors. Errors that such a system can detect include components that are too displaced from the center, missing components, and inverted components.

Keywords:edge detectors, computer vision, OpenCV, AOI, Raspberry Pi

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