Indirektni nadzor istrošenosti svrdla kod bušenja kompozitnih materijala

master's thesis

• Title (english): Indirect tool wear condition monitoring in drilling of composite materials
• Author: Mate Zoričić
• Mentor: Danko Brezak (mentor)
• Granter: University of Zagreb; Faculty of Mechanical Engineering and Naval Architecture; Zagreb
• Defense date and country: 2015-12-03, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Mechanical Engineering

Abstract

U ovom radu obrađeni su i analizirani signali sila i signali struja pogonskih motora alatnog stroja snimljeni tijekom bušenja polimernog kompozita ojačanog staklenim vlaknima. U programskom jeziku MATLAB izrađena je programska podrška za umjetnu neuronsku mrežu s radijalnim baznim funkcijama. Pomoću značajki izdvojenih iz signala sila i struja pokušalo se utvrditi može li se umjetnom neuronskom mrežom uspješno procijeniti stupanj istrošenosti svrdla.

Abstract (english)

This thesis analysed cutting force signals and current signals in the drives of a machine tool recorded during the drilling of a glass fiber reinforced polymer. A programme support for the artificial neural network with radial basis functions was created in the MATLAB programming language. Using the features extracted from the force signals and current signals, an attempt was made to ascertain whether an artificial neural network can successfully estimate the degree of tool wear.

• Keywords: umjetna neuronska mreža; nadzor istrošenosti alata
• Keywords (english): radial basis function; tool wear monitoring
• Language: croatian
• URN:NBN: urn:nbn:hr:235:662807
• Study programme: Title: Mechanical Engineering; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra inženjer/inženjerka strojarstva (magistar/magistra inženjer/inženjerka strojarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2019-05-22 15:20:41