Resonant Acoustic Sensor System for the Wireless Monitoring of Injection Moulding

F. Müller, P. O'Leary, G. Rath, C. Kukla, M. Harker, T. Lucyshyn, C. Holzer


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.


  1. Brandt, S. (1998). Data Analysis: Statistical and Computational Methods for Scientists and Engineers. Springer, Berlin, 3rd edition.
  2. Chen, Z. and Turng, L.-S. (2005). A review of current developments in process and quality control for injection molding. Advances in Polymer Technology, 24(3):165-182.
  3. Fano, R. (1951). Signal-to-noise Ratio in Correlation Detectors. Technical report (Massachusetts Institute of Technology. Research Laboratory of Electronics). Massachusetts Institute of Technology, Research Laboratory of Electronics.
  4. Frey, J. (2004). Method for automatically balancing the volumetric filling of cavities. US Patent 2004/0113303 A1.
  5. Gao, R., Fan, Z., and Kazmer, D. (2008). Injection molding process monitoring using a self-energized dualparameter sensor. CIRP Annals - Manufacturing Technology, 57(1):389-393.
  6. Giboz, J., Copponnex, T., and Mélé, P. (2007). Microinjection molding of thermoplastic polymers: a review. Journal of Micromechanics and Microengineering, 17(6):96-109.
  7. Golub, G. and Van Loan, C. (1996). Matrix Computations. The Johns Hopkins University Press, Baltimore, 3rd edition.
  8. Haase, S. (2002). Spectral and statistical methods for vibration analysis in steel rolling. PhD Thesis Montanuniversitaet Leoben.
  9. Johannaber, F. and Michaeli, W. (2004). Handbuch Spritzgiessen. Hanser, München, 2nd edition.
  10. Kamal, M. R., Patterson, W. I., Fara, D. A., and Haber, A. (1984). A study in injection molding dynamics. Polymer Engineering and Science, 24(9):686-691.
  11. Kazmer, D. O., Velusamy, S., Westerdale, S., Johnston, S., and Gao, R. X. (2010). A comparison of seven filling to packing switchover methods for injection molding. Polymer Engineering & Science, 50(10):2031-2043.
  12. Lindquist, C. S. (1988). Adaptive and Digital Signal Processing with Digital Filtering Applications. Steward & Sons.
  13. Müller, F., Rath, G., Lucyshyn, T., Kukla, C., Burgsteiner, M., and Holzer, C. (2012). Presentation of a novel sensor based on acoustic emission in injection molding. Journal of Applied Polymer Science. In Press.
  14. O'Leary, P. and Harker, M. (2011). Polynomial approximation: An alternative to windowing in fourier analysis. IEEE Proceedings of I2MTC 2011.
  15. Oppenheim, A. and Schafer, R. (1989). Discrete-Time Signal Processing. Prentice-Hall, Englewood Cliffs, NJ.
  16. Press, W. H., Teukolsky, S. A., Vetterling, W. T., and Flannery, B. P. (2002). Numerical Recipes in C++: The Art of Scientific Computing. Cambridge University Press.
  17. Zhang, L., Theurer, C. B., Gao, R. X., and Kazmer, D. O. (2005). Design of ultrasonic transmitters with defined frequency characteristics for wireless pressure sensing in injection molding. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control, 52(8):1360-1371.

Paper Citation

in Harvard Style

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 - Volume 1: SENSORNETS, ISBN 978-989-8565-45-7, pages 153-161. DOI: 10.5220/0004266301530161

in Bibtex Style

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 - Volume 1: SENSORNETS,},

in EndNote Style

JO - Proceedings of the 2nd International Conference on Sensor Networks - Volume 1: SENSORNETS,
TI - Resonant Acoustic Sensor System for the Wireless Monitoring of Injection Moulding
SN - 978-989-8565-45-7
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