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Authors: F. Müller ; P. O'Leary ; G. Rath ; C. Kukla ; M. Harker ; T. Lucyshyn and C. Holzer

Affiliation: Montanuniversitaet Leoben, Austria

Keyword(s): Pattern Recognition, Gibbs Error, Discrete Fourier Spectrum, Orthogonal Complement, Covariance Propagation, Discrete Fourier Transform.

Related Ontology Subjects/Areas/Topics: Applications and Uses ; Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Data Manipulation ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Industrial and Structural Monitoring ; Methodologies and Methods ; Multimedia/Audio Signal Processing ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: The production of high quality plastic parts requires in-mould sensors to monitor the injection moulding process. A novel wireless sensor concept is presented where structure borne sound is used to transmit information from the inside of an injection mould to the outside surface, eliminating the need for cabling within the mould. The sound is acquired and analyzed using new algebraic basis function techniques to enable the detection of temporal occurrence of frequency patterns in the presence of large levels of noise. The temporal occurrence of the resonators represents the passing melt front. The reduction of spectral leakage is computed by an alternative method using low degree Gram polynomials. The computation of the pattern matching algorithm yields both the correlation coefficients and their covariances which are used to determine the certainty of the measurement. The paper presents the used mathematical background as well as real measurements performed on an injection moulding machine. A test mould was equipped with two different resonant structures. Besides calculating the correlation coefficients the 3s confidence interval of the coefficients is computed. With the novel algebraic approach a reliable separation of the two temporal points of occurrence of the resonant structures was computed. (More)

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Paper citation in several formats:
Müller, F.; O'Leary, P.; Rath, G.; Kukla, C.; Harker, M.; Lucyshyn, T. and Holzer, C. (2013). Resonant Acoustic Sensor System for the Wireless Monitoring of Injection Moulding. In Proceedings of the 2nd International Conference on Sensor Networks - SENSORNETS, ISBN 978-989-8565-45-7; ISSN 2184-4380, pages 153-161. DOI: 10.5220/0004266301530161

@conference{sensornets13,
author={F. Müller. and P. O'Leary. and G. Rath. and C. Kukla. and M. Harker. and T. Lucyshyn. and C. Holzer.},
title={Resonant Acoustic Sensor System for the Wireless Monitoring of Injection Moulding},
booktitle={Proceedings of the 2nd International Conference on Sensor Networks - SENSORNETS,},
year={2013},
pages={153-161},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004266301530161},
isbn={978-989-8565-45-7},
issn={2184-4380},
}

TY - CONF

JO - Proceedings of the 2nd International Conference on Sensor Networks - SENSORNETS,
TI - Resonant Acoustic Sensor System for the Wireless Monitoring of Injection Moulding
SN - 978-989-8565-45-7
IS - 2184-4380
AU - Müller, F.
AU - O'Leary, P.
AU - Rath, G.
AU - Kukla, C.
AU - Harker, M.
AU - Lucyshyn, T.
AU - Holzer, C.
PY - 2013
SP - 153
EP - 161
DO - 10.5220/0004266301530161

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