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Predictive model of overburden deformation: based on machine learning and distributed optical fiber sensing technology

Wenyuan Liu (School of Resources and Geosciences, China University of Mining and Technology, Xuzhou, China)
Chunde Piao (School of Resources and Geosciences, China University of Mining and Technology, Xuzhou, China)
Yazhou Zhou (College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, China)
Chaoqi Zhao (School of Resources and Geosciences, China University of Mining and Technology, Xuzhou, China)

Engineering Computations

ISSN: 0264-4401

Article publication date: 12 October 2020

Issue publication date: 30 June 2021

296

Abstract

Purpose

The purpose of this paper is to establish a strain prediction model of mining overburden deformation, to predict the strain in the subsequent mining stage. In this way, the mining area can be divided into zones with different degrees of risk, and the prevention measures can be taken for the areas predicted to have large deformation.

Design/methodology/approach

A similar-material model was built by geological and mining conditions of Zhangzhuang Coal Mine. The evolution characteristics of overburden strain were studied by using the distributed optical fiber sensing (DOFS) technology and the predictive model about overburden deformation was established by applying machine learning. The modeling method of the predictive model based on the similar-material model test was summarized. Finally, this method was applied to engineering.

Findings

The strain value predicted by the proposed model was compared with the actual measured value and the accuracy is as high as 97%, which proves that it is feasible to combine DOFS technology with machine learning and introduce it into overburden deformation prediction. When this method was applied to engineering, it also showed good performance.

Originality/value

This paper helps to promote the application of machine learning in the geosciences and mining engineering. It provides a new way to solve similar problems.

Keywords

Acknowledgements

The work is funded by the Fundamental Research Funds for the Central Universities (2017XKQY057) and A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (2018).

Citation

Liu, W., Piao, C., Zhou, Y. and Zhao, C. (2021), "Predictive model of overburden deformation: based on machine learning and distributed optical fiber sensing technology", Engineering Computations, Vol. 38 No. 5, pp. 2207-2227. https://doi.org/10.1108/EC-05-2020-0281

Publisher

:

Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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