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Wavelet packet decomposition to characterize injection molding tool damage
ID Kek, Tomaž (Author), ID Kusić, Dragan (Author), ID Grum, Janez (Author)

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Abstract
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.

Language:English
Keywords:acoustic emission, injection molding, cracks, feature vector, pattern recognition
Work type:Article
Typology:1.01 - Original Scientific Article
Organization:FS - Faculty of Mechanical Engineering
Publication status:Published
Publication version:Version of Record
Year:2016
Number of pages:13 str.
Numbering:Vol. 6, iss. 2, art. 45
PID:20.500.12556/RUL-130372 This link opens in a new window
UDC:620.179.17(045)
ISSN on article:2076-3417
DOI:10.3390/app6020045 This link opens in a new window
COBISS.SI-ID:14587419 This link opens in a new window
Publication date in RUL:14.09.2021
Views:2698
Downloads:417
Metadata:XML DC-XML DC-RDF
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KEK, Tomaž, KUSIĆ, Dragan and GRUM, Janez, 2016, Wavelet packet decomposition to characterize injection molding tool damage. Applied sciences [online]. 2016. Vol. 6, no. 2,  45. [Accessed 7 July 2025]. DOI 10.3390/app6020045. Retrieved from: https://repozitorij.uni-lj.si/IzpisGradiva.php?lang=eng&id=130372
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Record is a part of a journal

Title:Applied sciences
Shortened title:Appl. sci.
Publisher:MDPI
ISSN:2076-3417
COBISS.SI-ID:522979353 This link opens in a new window

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:04.02.2016

Secondary language

Language:Slovenian
Keywords:akustične emisije, injekcijsko brizganje, razpoke, vektorske funkcije, razpoznavanje vzorcev

Projects

Funder:EC - European Commission
Funding programme:European Social Fund

Funder:Other - Other funder or multiple funders
Funding programme:Slovenian Ministry for Higher Education, Science and Technology

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