Abstract

Application of wavelet transform theory on elastic wave signal detecting thickness of top coal

Author(s): Xiaolei Zhao

In the current coal mining business, the detecting signals are processed and analyzed in order to figure out the more difficult situation of top-coal thickness. This paper discusses the basic theory of top-coal thickness detection as well as its characteristics, and also discusses the principle of elastic wave detecting top-coal thickness. Wavelet transform is used to process the detected signal in order to calculate the top-coal thickness and carry out feasibility study and practical application. The Db4 wavelet base is selected to carry out wavelet decomposition on the collected signal, verifying the detection ability of wavelet base to signal singularity. And then by using the wavelet to detect signal for two dimensions analysis, the arrival time of the first arriving point of reflecting wave has been tested, thus the top-coal thickness is figured out. At last, nine signals in fully mechanized face have been chosen to verification, and then compare the calculation results with the actual mining situation. The results show that the top-coal thickness calculation result of using wavelet analysis is consistent with actual situation, having an ideal calculate effect. This research introduces the wavelet transform in the analysis of coal thickness detecting signal, and mainly uses the advantages of transform in the processing of modulus maximum. The relationship between wavelet coefficient modulus maximum obtained in the wavelet transform analysis of detected signal and the singularity of detected signal has been compared, and then the arrival time of the first arriving point of reflecting wave is estimated according to the relationship. Finally, the coal seam thickness is worked out by using the formula. It can be seen from the above research that the results are ideal.


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