Wavelet packet decomposition to characterize injection molding tool damage

Kek, Tomaž (avtor), Kusić, Dragan (avtor), Grum, Janez (avtor)

This paper presents measurements of acoustic emission (AE) signals during the injection molding of polypropylene with new and damaged mold. The damaged injection mold has cracks induced by laser surface heat treatment. Standard test specimens were injection molded, commonly used for examining the shrinkage behavior of various thermoplastic materials. The measured AE burst signals during injection molding cycle are presented. For injection molding tool integrity prediction, different AE burst signals descriptors are defined. To lower computational complexity and increase performance, the feature selection method was implemented to define a feature subset in an appropriate multidimensional space to characterize the integrity of the injection molding tool and the injection molding process steps. The feature subset was used for neural network pattern recognition of AE signals during the full time of the injection molding cycle. The results confirm that acoustic emission measurement during injection molding of polymer materials is a promising technique for characterizing the integrity of molds with respect to damage, even with resonant sensors.

• Jezik: Angleški jezik
• Ključne besede: acoustic emission, injection molding, cracks, feature vector, pattern recognition
• Vrsta gradiva: Članek v reviji
• Tipologija: 1.01 - Izvirni znanstveni članek
• Organizacija: FS - Fakulteta za strojništvo
• Status publikacije: Objavljeno
• Različica publikacije: Objavljena publikacija
• Leto izida: 2016
• Št. strani: 13 str.
• Številčenje: Vol. 6, iss. 2, art. 45
• PID: 20.500.12556/RUL-130372
• UDK: 620.179.17(045)
• ISSN pri članku: 2076-3417
• DOI: 10.3390/app6020045
• COBISS.SI-ID: 14587419
• Datum objave v RUL: 14.09.2021

Gradivo je del revije

• Naslov: Applied sciences
• Skrajšan naslov: Appl. sci.
• Založnik: MDPI
• ISSN: 2076-3417
• COBISS.SI-ID: 522979353

Licence

• Licenca: CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
• Povezava: http://creativecommons.org/licenses/by/4.0/deed.sl
• Opis: To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.
• Začetek licenciranja: 04.02.2016

Sekundarni jezik

• Jezik: Slovenski jezik
• Ključne besede: akustične emisije, injekcijsko brizganje, razpoke, vektorske funkcije, razpoznavanje vzorcev

Projekti

• Financer: EC - European Commission
• Program financ.: European Social Fund

• Financer: Drugi - Drug financer ali več financerjev
• Program financ.: Slovenian Ministry for Higher Education, Science and Technology