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Title:Detekcija napak med 3D tiskom z uporabo strojnega vida : magistrsko delo
Authors:ID Tovornik, Nejc (Author)
ID Klančnik, Simon (Mentor) More about this mentor... New window
ID Šafarič, Riko (Mentor) More about this mentor... New window
Files:.pdf MAG_Tovornik_Nejc_2022.pdf (6,37 MB)
MD5: FBC9DF941AF1E51CB36324B783924806
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FS - Faculty of Mechanical Engineering
Abstract:V magistrski nalogi smo zasnovali cenovno ugodno rešitev za zajem slike in odkrivanje napak pri 3D tisku več enakih izdelkov. Najprej smo na kratko pregledali osnove 3D tiska in strojnega vida. Za zajem slike smo izbrali cenovno dostopen komercialni 1D linijski slikovni senzor, ki ne povzroča popačenja leče. Na podlagi meritev smo preučili delovanje tovrstnega senzorja, izdelali tiskano vezje in krmilni program za DSP mikrokrmilnik. Ustvarili smo vtičnik za rezalnik Ultimaker Cura, ki v sloje tiskanega izdelka doda G-kodo za izvajanje skeniranja, ter izdelali program za detekcijo napak. Program temelji na metodi primerjanja zajetih slik prvega uspešnega tiska s slikami nadaljnjih. Potrdili smo, da program uspešno zazna večino napak in ustrezno prekine proces 3D tiskanja.
Keywords:Strojni vid, CIS senzor, 3D-tisk, STM32, Python, G-koda, Duet3D, OpenCV, Altium, C++, Ultimaker Cura
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[N. Tovornik]
Year of publishing:2022
Number of pages:1 spletni vir (1 datoteka PDF (XII, 73 f.))
PID:20.500.12556/DKUM-82750 New window
UDC:004.932:[004.9:621.7.04](043.2)
COBISS.SI-ID:151466243 New window
Publication date in DKUM:22.09.2022
Views:690
Downloads:102
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FS
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:31.08.2022

Secondary language

Language:English
Title:Error detection during 3D printing using machine vision
Abstract:In our master's thesis, we designed an affordable solution for image capture and error detection during the 3D printing of several identical prints. First, we briefly reviewed the basics of 3D printing and machine vision. We chose an affordable commercial 1D line image sensor for image capture that does not cause lens distortion. Based on the measurements taken from sensor operation, we made a printed circuit board and a control program for a DSP microcontroller. We created an Ultimaker Cura slicer plug-in that adds G code lines for the image capturing process and a program for error detection. The program is based on the method of comparing captured images of the first successful print with images of subsequent ones. We have confirmed that the program successfully detects most errors and appropriately terminates the 3D printing process.
Keywords:Machine vision, CIS sensor, 3D printing, STM32, Python, G-code, Duet3D, OpenCV, Altium, C++, Ultimaker Cura


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