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A New Rockburst Experiment Data Compression Storage Algorithm Based on Big Data Technology

Yu Zhang1,2, Yan-Ge Wang1, Yan-Ping Bai3, Yong-Zhen Li1,4, Zhao-Yong Lv5, Hong-Wei Ding6

1 School of Electrical and Information Engineering & Beijing Key Laboratory of Intelligent Processing for Building Big Data, Beijing University of Civil Engineering and Architecture, China;
2 State Key Laboratory in China for GeoMechanics and Deep Underground Engineering (Beijing), China University of Mining & Technology, China;
3 College of Management, Capital Normal University, China;
4 School of Software, Beijing University of Technology, China;
5 Computing Center, Beijing University of Civil Engineering and Architecture, China;
6 China IPPR International Engineering CO., LTO, China

* Corresponding Author: Yan-Ping Bai, email

Intelligent Automation & Soft Computing 2019, 25(3), 561-572. https://doi.org/10.31209/2019.100000111

Abstract

Rockburst phenomenon is a kind of phenomenon that the rock is out and ejected because the mineral was dug out, and the original force balance was destroyed in the process of mineral exploitation. From 2007, GeoLab (abbreviation of State Key Laboratory in China for GeoMechanics and Deep Underground Engineering) had made a series of important achievements in rockburst. Up to now, GeoLab’s rockburst experiment data is reached 800T, and these data may occupy about 2PB hard disk space after analyzed. At this ratio, GeoLab need to buy a new hard disk to save all these data every 46 hours rockburst experiment. Since there is not enough hard disk space to save all these data, GeoLab had to slow down the speed of do rockburst experiment and only analyzed about 4 percent of the data. We call this phenomenon a dilemma for data storage. This hindered the research process of rockburst phenomenon. We proposed a structure to obtain data from a cloud platform based on big data technology. And basing on this we analyzed the distribution characteristics of rockburst experiment data, data frequency and data frequency domain. And a new rockburst experiment data compression storage algorithm (NDCS) based on big data technology and cloud platform was proposed. Then we compared NDCS with WinRAR and BDSS by occupied disk space, compress ratio and consuming time. Theoretical analysis and experiments show that NDCS has the best performance of all three algorithms. NDCS is the most suitable data compression storage algorithm for rockburst, and it has successfully solved the data storage dilemma in rockburst experiment.

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Cite This Article

APA Style
Zhang, Y., Wang, Y., Bai, Y., Li, Y., Lv, Z. et al. (2019). A new rockburst experiment data compression storage algorithm based on big data technology. Intelligent Automation & Soft Computing, 25(3), 561-572. https://doi.org/10.31209/2019.100000111
Vancouver Style
Zhang Y, Wang Y, Bai Y, Li Y, Lv Z, Ding H. A new rockburst experiment data compression storage algorithm based on big data technology. Intell Automat Soft Comput . 2019;25(3):561-572 https://doi.org/10.31209/2019.100000111
IEEE Style
Y. Zhang, Y. Wang, Y. Bai, Y. Li, Z. Lv, and H. Ding "A New Rockburst Experiment Data Compression Storage Algorithm Based on Big Data Technology," Intell. Automat. Soft Comput. , vol. 25, no. 3, pp. 561-572. 2019. https://doi.org/10.31209/2019.100000111



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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