Detection of Damaged Tool in Injection Molding Processwith Acoustic Emission
Publication: Publication Date: 1 May 2016Testing Method:
The measurement of acoustic emission (AE) signals during
injection molding of polypropylene with new and damaged
mold is presented. The damaged injection mold was fitted with
a steel insert with cracks induced by laser surface heat treatment.
Two resonant piezoelectric AE sensors were attached to
the mold via AE waveguides. To improve the mold integrity
prediction with smaller defects, AE signal frequency characteristics
and a measure of AE signal amplitude probability distribution
are implemented. A 5-dimensional feature vector with
real-valued explanatory variables is proposed, providing the
defining points in an appropriate multidimensional space to
characterize the state of injection molding tool. Feature vectors
are classified with neural network pattern recognition. The
results confirm that presented AE technique offers characterizing
the integrity of molds also with resonant sensors.
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