Abstract
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.
Highlights
In the modern coal mine, the belt conveyor [1] is one of the important transport machines
For the steel cord conveyor belt, the wavelet transform was used to denoise the electromagnetic signal with the steel wire rope break defect [8] and the corrected linear B-wavelet method was proposed to improve the Signal to Noise Ratio (SNR) [9]
Based on the above analysis, the new electromagnetic signal noise reduction method based on the improved threshold wavelet and Empirical Mode Decomposition (EMD) with the dominant eigenvalue is proposed in this paper the improved threshold wavelet and EMD with the dominant eigenvalue is proposed in this paper and used for the coal mine steel cord conveyor belt testing
Summary
In the modern coal mine, the belt conveyor [1] is one of the important transport machines. Under the complicated coal mine working conditions, the defect electromagnetic signal collected from steel cord conveyor belt usually contains a large amount of non-stationary noise which makes the signal feature extraction difficult. For the steel cord conveyor belt, the wavelet transform was used to denoise the electromagnetic signal with the steel wire rope break defect [8] and the corrected linear B-wavelet method was proposed to improve the Signal to Noise Ratio (SNR) [9]. Based on the above analysis, the new electromagnetic signal noise reduction method based on the improved threshold wavelet and EMD with the dominant eigenvalue is proposed in this paper the improved threshold wavelet and EMD with the dominant eigenvalue is proposed in this paper and used for the coal mine steel cord conveyor belt testing.
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