A new rockburst experiment data compression storage algorithm based on big data technology

Yu Zhang, Yan Ge Wang, Yan Ping Bai*, Yong Zhen Li, Zhao Yong Lv, Hong Wei Ding

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

6 引用 (Scopus)

摘要

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.

源语言英语
页(从-至)561-572
页数12
期刊Intelligent Automation and Soft Computing
25
3
DOI
出版状态已出版 - 9月 2019
已对外发布

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