A Method for Quality Inspection of Motors by Detecting Abnormal Sound
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A Method for Quality Inspection of Motors by Detecting Abnormal Sound

Authors: Tadatsugu Kitamoto

Abstract:

Recently, a quality of motors is inspected by human ears. In this paper, I propose two systems using a method of speech recognition for automation of the inspection. The first system is based on a method of linear processing which uses K-means and Nearest Neighbor method, and the second is based on a method of non-linear processing which uses neural networks. I used motor sounds in these systems, and I successfully recognize 86.67% of motor sounds in the linear processing system and 97.78% in the non-linear processing system.

Keywords: Acoustical diagnosis, Neural networks, K-means, Short-time Fourier transformation

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1328364

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References:


[1] H. Sugimoto and K. Fukuda, "Abnormal noise detector for gear units", J. Acoust. Soc. Am., vol.82, pp.1856, 1987.
[2] Z.Zhang and H.Kawabata, "Study of Detection Method of Abnormal Sound Using Cellular Neural Network", Trans. J. Soc. of Mechanical Engineers. C, vol. 69, no. 668, pp. 3207-3214, 2003.
[3] Munehiro Namba "On the quality inspection of motors by detecting abnormal noise".
[4] S. Miyamoto, introduction to cluster analysis (Book style). Tokyo, CA: Morikita, 1999, pp. 13-24.
[5] G. F. Page, J. B. Gomm and D. Williams, Application of neural networks to modeling and control (Book style). London, CA: CHAPMAN & HALL, 1993, pp.9-23.
[6] Simon Haykin, Neural networks (Book style). New Jersey, CA: Prentice Hall, 1999, pp. 159-173.