Indirektni nadzor istrošenosti alata i tvrdoće obratka kod bušenja kamena

Klaić, Miho (2018) Indirektni nadzor istrošenosti alata i tvrdoće obratka kod bušenja kamena. = Indirect tool wear and workpiece hardness monitoring in stone drilling. Doctoral thesis , Sveučilište u Zagrebu, Fakultet strojarstva i brodogradnje, UNSPECIFIED. Mentor: Udiljak, Toma.

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Klaic_Miho_2018_phd.pdf - Published Version Jezik dokumenta:Croatian

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Abstract (Croatian)

Kamen je po svojoj strukturi krhak, nehomogen i anizotropan materijal, čija mehanička svojstva u zoni obrade mogu značajno varirati. Promjenjiva mehanička svojstva, poglavito tvrdoća, imaju veliki značaj kod izbora parametara obrade. Neodgovarajući parametri obrade mogu negativno djelovati na dinamiku trošenja alata, te izazvati lom alata ili obrađivanog materijala uslijed povećanih sila rezanja. Imajući u vidu nemogućnost mjerenja istrošenosti reznog alata tijekom postupka obrade, u predloženom istraživanju analizirat će se mogućnost indirektnog nadzora procesa bušenja u smislu procjene stupnja istrošenosti svrdla i vrste (tvrdoće) obrađivanog kamena. Modeliranje navedenih parametara procesa provest će se primjenom algoritama računalne inteligencije u uvjetima bušenja triju vrsta kamena različitih tvrdoća i stupnjeva heterogenosti, primjenom svrdla s četiri različita stupnja istrošenosti, a na temelju značajki izdvojenih iz eksperimentalno snimljenih signala procesa bušenja.

Abstract

Stone is a brittle, non-homogeneous and anisotropic material whose physical-mechanical properties usually substantially vary in the cutting zone. Variable material properties, especially hardness, have important influence in cutting parameters selection. Improper values of cutting parameters can have negative influence on tool wear dynamic, and can potentially result in tool or workpiece breakage due to occurrence of the higher cutting forces. Since direct tool wear measurement is not possible during the cutting process, application of indirect monitoring techniques for tool wear and material type (hardness) classification in stone drilling will be analyzed in this study. Classification models of these two parameters will be based on artificial intelligence algorithms. They will be analyzed based on the features extracted from several types of process signals acquired during stone drilling experiment. Three types of stone samples of different hardness and heterogeneity will be analyzed, with the use of drills with the four different wear levels.

Item Type: Thesis (Doctoral thesis)
Uncontrolled Keywords: Bušenje kamena, neuronske mreže, klasifikacija stupnja istrošenosti svrdla, klasifikacija tvrdoće kamena, višesenzorski nadzor
Keywords (Croatian): stone drilling, neural networks, classification of drill wear, stone hardness estimation, multisensor fusion-based drill condition monitoring
Subjects: TECHNICAL SCIENCE > Mechanical Engineering
Divisions: 1200 Department of Technology > 1230 Chair of Machine Tools
Date Deposited: 29 Aug 2018 09:33
Last Modified: 06 Apr 2020 22:42
URI: http://repozitorij.fsb.hr/id/eprint/8687

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