Deep well construction of big data platform based on multi-source heterogeneous data fusion Online publication date: Mon, 02-Dec-2019
by Yu Zhang; Yange Wang; Hongwei Ding; Yongzhen Li; Yanping Bai
International Journal of Internet Manufacturing and Services (IJIMS), Vol. 6, No. 4, 2019
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.
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