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Nadgradnja naprave za natezni preizkus z optičnim spremljanjem raztezka
ID Skok, Aljaž (Author), ID Lebar, Andrej (Mentor) More about this mentor... This link opens in a new window, ID Valentinčič, Joško (Comentor)

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Abstract
V magistrskem delu smo izvedli menjavo RPi kamere s HQ kamero ter objektiva, na Raspberry Pi 4 SBC (ang. single board computer). S tem smo povečali ločljivost meritve raztezka in izvedli kalibracijo kamere. Kalibracijo kamere smo izvedli po Zhangovem postopku in se s tem znebili distorzije, ki se pojavi na robovih zajetih slik. Distorzija je posledica lomov žarkov skozi objektiv. Primerjali smo tudi med dvema različnima algoritmoma za zaznavo oznak na epruvetah in izbrali najboljšega za našo aplikacijo. Izdelali smo tudi prototip prijemala ter ga natisnili s 3D tiskalnikom. Na koncu smo izvedli še 25 nateznih testov natisnjenih epruvet iz PETG materiala in jih nato primerjali s testi, ki smo jih izvedli na preizkuševališču MultiTest 2.5-dV. Preračunali smo tudi standardni odklon meritev raztezka in natezne napetosti. Ugotovili smo, da se maksimalna natezna napetost zadovoljivo sklada z referenčno vrednostjo in vrednostjo katero jo zagotavlja proizvajalec filamenta.

Language:Slovenian
Keywords:strojni vid kalibracija kamere prijemala Raspberry Pi OpenCV natezni preizkus
Work type:Master's thesis/paper
Organization:FS - Faculty of Mechanical Engineering
Year:2024
PID:20.500.12556/RUL-161662 This link opens in a new window
Publication date in RUL:13.09.2024
Views:138
Downloads:85
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Secondary language

Language:English
Title:Upgrade of the tensile test device with optical strain monitoring
Abstract:
In the master thesis, we have replaced the RPi camera with an HQ camera and lens, on a Raspberry Pi 4 single board computer. This increased the resolution of the elongation measurement and calibration of the camera. The camera calibration was performed according to Zhang's procedure, thus getting rid of the distortion that appears at the edges of the captured images. The distortion is caused by the refraction of the rays through the lens. We also compared two different algorithms for detecting markings on test tubes and chose the best one for our application. We also made a prototype of the gripper and printed it with a 3D printer. Finally, we performed 25 tests on the printed PETG test tubes and then compared them with the tests we performed on the MultiTest 2.5-dV testbed. The standard deviation of the elongation and tensile stress measurements was also calculated. The maximum tensile stress was found to be in satisfactory agreement with the reference value and the value provided by the filament manufacturer.

Keywords:machine vision camera calibration grippers Raspberry Pi OpenCV tensile test

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