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2020, vol. 48, br. 3, str. 611-619
Tehnika dubokog učenja bazirana na akustičnoj emisiji za predviđanje jačine adhezije kod laserski tretiranih CFRP kompozita
aAalim Muhammed Salegh College of Engineering, Department of Mechanical Engineering, Chennai, Tamilnadu, India
bNational Institute of Technology - Tiruchirappalli, Department of Production Engineering, Tamilnadu, India
cSA Engineering College, Department of Mechanical Engineering, Chennai, Tamilnadu, India

e-adresadurai@nitt.edu
Ključne reči: acoustic emission; NDT; neural network; prediction; failure characterization
Sažetak
Visok stepen nehomogenosti materijala i problemi nastali obradom CFRP kompozita onemogućavaju primenu analitičkih modela za precizno predviđanje zaostale čvrstoće veze dobijene adhezijom spoja. U novije vreme koriste se tehnike veštačke inteligencije kao alternativni metod za predviđanje rezultata ove složene pojave. Rad prikazuje pokušaj predviđanja jačine spoja kod površine tretirane laserom i adhezijom dobijene veze kod uzoraka CFRP kompozita korišćenjem veštačke inteligencije na osnovu parametara akustične emisije dobijenih ispitivanjem na smicanje. Izvršena je predobrada površine 12 uzoraka laserom 3W Nd:YAG pri različitim parametrima obrade. Veštačka inteligencija je trenirana odabranim podacima dobijenim akustičnom emisijom na osnovu mehanizma otkaza i opterećenja otkaza (5 - 100%). Predviđene vrednosti su upoređene sa vrednostima dobijenim eksperimentom i izvršena je analiza rezultata u cilju utvrđivanja mogućnosti primene veštačke inteligencije sa akustičnom emisijom.
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O članku

jezik rada: engleski
vrsta rada: neklasifikovan
DOI: 10.5937/fme2003611S
objavljen u SCIndeksu: 24.06.2020.
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