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Open AccessArticle

Noise Reduction of Steel Cord Conveyor Belt Defect Electromagnetic Signal by Combined Use of Improved Wavelet and EMD

School of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
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This paper is an extended version of our paper published in the International Symposium on Computer, Consumer and Control, Xi’an, China, 4–6 July 2016.
Academic Editor: Hsiung-Cheng Lin
Algorithms 2016, 9(4), 62; https://doi.org/10.3390/a9040062
Received: 17 July 2016 / Revised: 3 September 2016 / Accepted: 13 September 2016 / Published: 26 September 2016
In order to reduce the noise of a defect electromagnetic signal of the steel cord conveyor belt used in coal mines, a new signal noise reduction method by combined use of the improved threshold wavelet and Empirical Mode Decomposition (EMD) is proposed. Firstly, the denoising method based on the improved threshold wavelet is applied to reduce the noise of a defect electromagnetic signal obtained by an electromagnetic testing system. Then, the EMD is used to decompose the denoised signal and then the effective Intrinsic Mode Function (IMF) is extracted by the dominant eigenvalue strategy. Finally, the signal reconstruction is carried out by utilizing the obtained IMF. In order to verify the proposed noise reduction method, the experiments are carried out in two cases including the defective joint and steel wire rope break. The experimental results show that the proposed method in this paper obtains the higher Signal to Noise Ratio (SNR) for the defect electromagnetic signal noise reduction of steel cord conveyor belts. View Full-Text
Keywords: steel cord conveyor belt; signal noise reduction; wavelet; Empirical Mode Decomposition (EMD) steel cord conveyor belt; signal noise reduction; wavelet; Empirical Mode Decomposition (EMD)
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MDPI and ACS Style

Ma, H.-W.; Fan, H.-W.; Mao, Q.-H.; Zhang, X.-H.; Xing, W. Noise Reduction of Steel Cord Conveyor Belt Defect Electromagnetic Signal by Combined Use of Improved Wavelet and EMD. Algorithms 2016, 9, 62.

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