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Nonlinear Ultrasonics for In-line Quality Monitoring of Polymer Processing Methods / NONLINEAR ULTRASONICS FOR POLYMER QUALITY MONITORING

Ultrasonic testing is a nondestructive structural characterization technique with limited
examples of application for polymeric products due to the high signal attenuation
in this class of materials. Recent developments in this thesis on ultrasonics have
focused on a guided waves test method and used nonlinear analysis of harmonic
frequencies to characterize polyethylene, a semi-crystalline polymer. This sensor
technology was demonstrated in the detection of initial plastic deformation and to
monitor solvent swelling. Frequency regions of low signal attenuation and a nonlinear
ultrasonic parameter using amplitude ratio of harmonic peaks were used to classify
different crystalline morphologies, controlled by thermal treatment. With an established
connection between the ultrasonic spectrum signal and the internal structure of
polyethylene, a quality monitoring tool was developed and applied to a batch rotational
molding process. Multiple traditional quality measurements were correlated with the
ultrasonic signal using multivariate statistical analysis. Finally, an in-line statistical
approach for quality classification and an on-line process monitoring using dynamic
process modeling were validated. The results presented in this study demonstrate the
relevancy of incorporation of the ultrasonic sensor technology to promote advanced
manufacturing practices for the polymer manufacturing industry. / Thesis / Doctor of Philosophy (PhD) / We have been using ultrasonic devices to investigate different things from medical
diagnosis of prenatal development to nondestructive exploration of small rocks brought
from the Moon. This study takes the ultrasonic testing to the challenge of characterizing
plastics. Using information from the propagation of these inaudible sound waves, we
can explore the entire structure and observe structural changes that can lead to defects
or failures. With the help of computer-based data processing, we investigate these
complex signals creating tools for more efficient manufacturing and safer products like
water and fuel storage tanks.

Identiferoai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/24005
Date January 2019
CreatorsGomes, Felipe Pedro
ContributorsThompson, Michael, Chemical Engineering
Source SetsMcMaster University
LanguageEnglish
Detected LanguageEnglish
TypeThesis

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