Title: Deep well construction of big data platform based on multi-source heterogeneous data fusion

Authors: Yu Zhang; Yange Wang; Hongwei Ding; Yongzhen Li; Yanping Bai

Addresses: School of Electrical and Information Engineering and Beijing Key Laboratory of Intelligent Processing for Building Big Data, Beijing University of Civil Engineering and Architecture, No. 1 Zhanlanguan Road, Xicheng District, Beijing, 100044, China; State Key Laboratory in China for GeoMechanics and Deep Underground Engineering (Beijing), China University of Mining and Technology, Baoyuan Building No. 16 Qinghua Road, Haidian District, Beijing, 100083, China ' School of Electrical and Information Engineering and Beijing Key Laboratory of Intelligent Processing for Building Big Data, Beijing University of Civil Engineering and Architecture, No. 1 zhanlanguan Road, Xicheng District, Beijing, 100044, China ' School of Electrical and Information Engineering and Beijing Key Laboratory of Intelligent Processing for Building Big Data, Beijing University of Civil Engineering and Architecture, No. 1 zhanlanguan Road, Xicheng District, Beijing, 100044, China ' School of Software, Beijing University of Technology, Beijing, 100124, China; Network Information Center, Beijing University of Civil Engineering and Architecture, Beijing, 100044, China ' College of Management, Capital Normal University, Beijing, 100048, China

Abstract: At present, energy saving and emission reduction had become a problem of great concern for mankind. At the same time, there were some problems in the mining industry, such as waste of resources, low efficiency and easy occurrence of industrial accidents. Therefore, this paper had designed a deep well construction big data platform. The high precision and bear great pressure sensors were added to the system to solve the difficult problem of collecting information in deep wells by ordinary sensors. The multi-source heterogeneous data fusion algorithm was added to the system to solve the problem that the format of the data acquisition was different. In conclusion, the completion of the platform could achieve data monitoring in the process of mines. It not only helps to enhance the safety of mine construction, but also provides data analytical tools for further theoretical research of mine construction.

Keywords: deep well; multi-source data fusion; big data.

DOI: 10.1504/IJIMS.2019.103856

International Journal of Internet Manufacturing and Services, 2019 Vol.6 No.4, pp.371 - 388

Received: 11 Dec 2017
Accepted: 13 Apr 2018

Published online: 28 Nov 2019 *

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