magistrsko delo magistrskega študijskega programa II. stopnje Strojništvo
Boris Kuster (Author), Drago Bračun (Mentor), Damjan Klobčar (Co-mentor)

Abstract

Pri izdelavi 3D tiskanih kovinskih izdelkov s postopkom obločnega navarjanja z žico je težko doseči dobro dimenzijsko natančnost zaradi nestacionarnosti varilnega postopka, kar se odraža v valovitosti sten izdelkov in razliki med željeno in dejansko višino navarjenega sloja. Napaka se povečuje z večanjem števila navarjenih slojev. Z namenom povečanja dimenzijske natančnosti postopka smo razvili sistem za snemanje varjenja z visokohitrostno kamero ter algoritem za robustno in hitro zaznavo bazena taline iz dobljenih slik. Analizirali smo možnosti uporabe dobljenih podatkov o bazenu taline kot povratno zanko za krmiljenje varilnega aparata.

Keywords

magistrske naloge;aditivne tehnologije;obločno navarjanje z žico;zaznavanje taline;strojni vid;konvolucijske nevronske mreže;optimizacija postopka;

Data

Language: Slovenian
Year of publishing:
Typology: 2.09 - Master's Thesis
Organization: UL FS - Faculty of Mechanical Engineering
Publisher: [B. Kuster]
UDC: 004.946:681.518.52:621.9.04(043.2)
COBISS: 58915331 Link will open in a new window
Views: 400
Downloads: 88
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Other data

Secondary language: English
Secondary title: Melt pool detection at wire arc welding
Secondary abstract: Achieving good dimensional accuracy for 3D printed objects with the Gas metal arc welding process (Wire-arc additive manufacturing) is difficult because of the nonstationarity of the welding process, which results in object wall waviness and differences between the desired and actual layer height of the welded material. This error is cumulative and rises in proportion to the number of welded layers. To improve the dimensional accuracy of Wire-arc additively manufactured objects, we design a system to record welding using a high speed camera, and design an algorithm for robust and fast melt pool detection from the images. We analyze the possibilities of using this data as a feedback loop for controlling the welding machine parameters in real time
Secondary keywords: master thesis;additive manufacturing;gas metal arc welding;melt pool detection;computer vision;convolutional neural networks;process optimization;
Type (COBISS): Master's thesis/paper
Study programme: 0
Embargo end date (OpenAIRE): 1970-01-01
Thesis comment: Univ. Ljubljana, Fak. za strojništvo
Pages: XXII, 62 str.
ID: 12708615