Composite Advanced Detection for Coal Seam Thickness in Coal Roadway
Wang Bo1, 2, Zhang Xiayang1, 2, Liu Shengdong1, 2, *, Lu Tuo1, 2, Chen Mulan1
Identifiers and Pagination:Year: 2015
First Page: 153
Last Page: 157
Publisher Id: TOPEJ-8-153
Article History:Received Date: 15/12/2014
Revision Received Date: 4/1/2015
Acceptance Date: 25/2/2015
Electronic publication date: 31/3/2015
Collection year: 2015
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
The thickness change of coal seam can be resulted from several reasons, like primary sedimentary environment and later tectonic deformation. The thickness change ahead of driving face may have an impact on the efficiency and safety of the mining progress, thus the advanced prediction of seam thickness is important. However, it is hard to predict the seam thickness with a single advanced detection method. This paper combines three methods, e.g., MSP, MRP, and MTEM to perform a joint detection, and makes data fusion through wavelet analysis, which makes use of the elastic wave field and geo-electrical field characteristics. A field test indicates that the prediction of seam thickness by means of integrated advanced detection is approximately accurate with an error less than 5%.