An Equipment Fault Sound Location System Design

Dong Xie; Min Wang; Jian Qu Zhu; Feng Wang

doi:10.4028/www.scientific.net/AMM.462-463.298

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 462-463An Equipment Fault Sound Location System Design

An Equipment Fault Sound Location System Design

Abstract:

The location of the sound source is an important technique for equipment failures diagnostic application. This paper design a specific fault sound location system for capturing the specific sound source and determine its orientation. The two functions of sound recognition and location system are combined. The frequency domain characteristics based on similarity calculation method is used to identify the sound signal. The source localization algorithm based on the time delay estimation is used to calculate the time difference of arrival sound signal. By method of combining hardware circuit preprocessing and software design, the orientation of positioning of sound source is determined by the known sound pickup arrays spatial position. The sound location system uses two piece of MCU to achieve its function with simplification efficient algorithm and high accuracy.

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Periodical:

Applied Mechanics and Materials (Volumes 462-463)

Pages:

298-301

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.462-463.298

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Online since:

November 2013

Authors:

Dong Xie, Min Wang, Jian Qu Zhu, Feng Wang

Keywords:

Sound Localization, Sound Recognition, Time Difference of Arrival

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References

[1] D.W. Hagstrum, K.W. Vick, P.W. Flinn, Automated acoustical monitoring of Tribolium castaneum populations in stored wheat. J. Econ. Entomol. 84(1991)1604-1608.

DOI: 10.1093/jee/84.5.1604

Google Scholar

[2] R.W. Mankin, J. S. Sun, D. Shuman, et al. Shielding against noise interfering with quantitation of insect infestations by acoustic detection systems in grain elevators. Appl. Acoust. 50(1997)309-323.

DOI: 10.1016/s0003-682x(96)00038-2

Google Scholar

[3] K. M. Coggins, J. Principe, Detection and classfication of inset sounds in a grain silo using a neual network. IEEE Int. Conf. Networks Conf. Proc., IEEE Piscataway N.J. (USA), 3(1998)1760-1765.

Google Scholar

[4] M.H. SUN, Y.T. YU. Simulation of car horn localization system. Technical Acoustics. 28( 2009) 640- 644. (In Chinese).

Google Scholar

[5] M. S. BRANDSTEIN, H.F. SILVERMAN, A practical methodology for speech source localization with microphone arrays. Computer Speech & Language. 11(1997)91- 126.

DOI: 10.1006/csla.1996.0024

Google Scholar

[6] Y. HAN, C.N. WU, L.F. LI, Research and development of sound localization system based on time difference of arrival[J]. Computer Engineering and Design. 31(2010)2462- 2465. (In Chinese).

Google Scholar