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Title:Inteligentni nadzor obrabe rezalnega orodja s spremljanjem toka na glavnem vretenu : magistrsko delo
Authors:ID Turšič, Niko (Author)
ID Šafarič, Riko (Mentor) More about this mentor... New window
ID Klančnik, Simon (Mentor) More about this mentor... New window
Files:.pdf MAG_Tursic_Niko_2023.pdf (4,61 MB)
MD5: 074BBDB195586B0473E6144F70933609
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V magistrski nalogi je predstavljen sistem za nadzor rezalnega orodja, ki temelji na sledenju toka na glavnem vretenu z uporabo umetne nevronske mreže. Glavni namen aplikacije je razširiti vpogled, ki ga ima operater v stanje orodja med delovanjem stružnice CNC. Program za analizo lahko nemoteno deluje paralelno na procesnem računalniku in prejema podatke preko podatkovnega omrežja s krmilnika stružnice. V delu so predstavljeni proces zajemanja podatkov za učno bazo umetne nevronske mreže tipa Long-Short Term Memory, arhitektura in učenje nevronske mreže, ki je uporabljena v tej aplikaciji, ter validacija naučenega modela z umetno inteligenco na novih podatkih. Prav tako sta predstavljena tudi izdelava in delovanje programa, ki se lahko izvaja na procesnem računalniku za potrebe pomožne diagnostike orodja.
Keywords:tok na glavnem vretenu, nevronska mreža, nadzor obrabe orodja, LSTM, umetna inteligenca
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[N. Turšič]
Year of publishing:2023
Number of pages:1 spletni vir (1 datoteka PDF (VIII, 61 f.))
PID:20.500.12556/DKUM-84999 New window
UDC:621.941.025:004.8(043.2)
COBISS.SI-ID:172751619 New window
Publication date in DKUM:05.10.2023
Views:515
Downloads:65
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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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:15.08.2023

Secondary language

Language:English
Title:Intelligent tool condition monitoring system utilizing spindle current measurements
Abstract:The thesis presents a tool condition monitoring system, based on the tracking of current flowing through the main spindle with an artificial neural network. The main purpose of this application is to provide additional insight to the operator regarding tool wear during the operation of the CNC lathe. The TCM program can run independently on a process computer next to the lathe, receiving data via the ethernet network from the machines PLC. We present the measurement processes with which we have obtained the training data for the Long-Short Term Memory neural network, the design and training of said network and the validation of the artificial intelligence model on a new dataset. Along with the trained model we also provide a prototype software designed to use said model for the purposes of assistive tool condition monitoring.
Keywords:main spindle current, neural network, tool condition monitoring, long-short term memory, artificial intelligence


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