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Wavelet packet decomposition to characterize injection molding tool damage [Elektronski vir]Kek, Tomaž, 1974- ; Kusić, Dragan ; Grum, Janez, 1946-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.Source: Applied sciences [Elektronski vir]. - ISSN 2076-3417 (Vol. 6, iss. 2, Feb. 2016, f. 1-13)Type of material - e-articlePublish date - 2016Language - englishCOBISS.SI-ID - 14587419
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Database name | Field | Year |
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Links to authors' personal bibliographies | Links to information on researchers in the SICRIS system |
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Kek, Tomaž, 1974- | 23778 |
Kusić, Dragan | 32596 |
Grum, Janez, 1946- | 03551 |
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