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Pregled bibliografske jedinice broj: 759878

Artificial Neural Network Model for Tool Condition Monitoring in Stone Drilling


Brezak, Danko; Staroveški, Tomislav; Stiperski, Ivan; Klaić, Miho; Majetić, Dubravko
Artificial Neural Network Model for Tool Condition Monitoring in Stone Drilling // Applied Mechanics and Materials, 772 (2015), 268-273 doi:10.4028/www.scientific.net/AMM.772.268 (međunarodna recenzija, članak, znanstveni)


Naslov
Artificial Neural Network Model for Tool Condition Monitoring in Stone Drilling

Autori
Brezak, Danko ; Staroveški, Tomislav ; Stiperski, Ivan ; Klaić, Miho ; Majetić, Dubravko

Izvornik
Applied Mechanics and Materials (1660-9336) 772 (2015); 268-273

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Stone drilling; tool wear classification; neural networks

Sažetak
This paper explores the possibility of tool wear classification in stone drilling. Wear model is based on Radial Basis Function Neural Network which links tool wear features extracted from motor drive current signals and acoustic emission signals with two wear levels – sharp and worn drill. Signals were measured during stone drilling under different cutting conditions, and then filtered before tool wear features extraction. Features were obtained from time and frequency domain. They have been analyzed individually and in combinations. The results indicate tool wear monitoring capacity of the proposed model in stone drilling, and its potential for simple and cost-effective integration with CNC machine tools.

Izvorni jezik
Engleski

Znanstvena područja
Strojarstvo



POVEZANOST RADA


Projekt / tema
120-1201948-1938 - Napredni obradni sustavi i procesi (Toma Udiljak, )
120-1201948-1945 - Inteligentno vođenje obradnih sustava (Dubravko Majetić, )

Ustanove
Fakultet strojarstva i brodogradnje, Zagreb

Citiraj ovu publikaciju

Brezak, Danko; Staroveški, Tomislav; Stiperski, Ivan; Klaić, Miho; Majetić, Dubravko
Artificial Neural Network Model for Tool Condition Monitoring in Stone Drilling // Applied Mechanics and Materials, 772 (2015), 268-273 doi:10.4028/www.scientific.net/AMM.772.268 (međunarodna recenzija, članak, znanstveni)
Brezak, D., Staroveški, T., Stiperski, I., Klaić, M. & Majetić, D. (2015) Artificial Neural Network Model for Tool Condition Monitoring in Stone Drilling. Applied Mechanics and Materials, 772, 268-273 doi:10.4028/www.scientific.net/AMM.772.268.
@article{article, year = {2015}, pages = {268-273}, DOI = {10.4028/www.scientific.net/AMM.772.268}, keywords = {Stone drilling, tool wear classification, neural networks}, journal = {Applied Mechanics and Materials}, doi = {10.4028/www.scientific.net/AMM.772.268}, volume = {772}, issn = {1660-9336}, title = {Artificial Neural Network Model for Tool Condition Monitoring in Stone Drilling}, keyword = {Stone drilling, tool wear classification, neural networks} }

Časopis indeksira:


  • Scopus


Uključenost u ostale bibliografske baze podataka:


  • Compendex (EI Village)
  • INSPEC
  • SCOPUS, Cambridge Scientific Abstracts (CSA)


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