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Proceedings Paper

Noise suppression during the electro-magnetic acoustic detection of wheels tread defects
Author(s): Xiaohong Zhou; Lixin Dai; Kai Yang; Li Wang
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Paper Abstract

Electro-magnetic acoustic detection technique has become a new development trend of nondestructive testing because of its high detection efficiency, accurate detection results, etc, so it now has been widely adopted in the railway department of our country. When the signal is detected using electro-magnetic acoustic detection technique, the influence of the poor condition of wheel surface, the existing electromagnetic interference and other factors will enable different levels of noise to exist in the detected signal, which will affect the signal quality, thereby reducing the detection accuracy. After introducing the structure and principle of electro-magnetic acoustic detection system, this paper has put forward two noise suppression algorithms for the noise problem of the detection signal, namely, phase difference algorithm and adaptive filtering algorithm. On the premise of reserving the necessary signal waveform of system, the algorithms can effectively suppress the noise of a detected signal, improve the quality of a data waveform, and obtain good detection results. The paper also compares two algorithms and points out that the better detection accuracy can be obtained if combining the two algorithms. This work has certain inspiration to raise the accuracy of electro-magnetic acoustic detection results.

Paper Details

Date Published: 28 December 2010
PDF: 8 pages
Proc. SPIE 7544, Sixth International Symposium on Precision Engineering Measurements and Instrumentation, 75441V (28 December 2010); doi: 10.1117/12.885203
Show Author Affiliations
Xiaohong Zhou, Southwest Jiaotong Univ. (China)
Lixin Dai, Southwest Jiaotong Univ. (China)
Kai Yang, Southwest Jiaotong Univ. (China)
Li Wang, Southwest Jiaotong Univ. (China)

Published in SPIE Proceedings Vol. 7544:
Sixth International Symposium on Precision Engineering Measurements and Instrumentation
Jiubin Tan; Xianfang Wen, Editor(s)

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