Research of Parallel Process Method of Ground Penetrating Radar (GPR) Data Based on Hadoop

Authors

Yincheng Liang, School of Mechanical Electronic&Information Engineering, China University of Mining&Technology, Beijing 100083, China;
Yuan Yuan, School of Mechanical Electronic&Information Engineering, China University of Mining&Technology, Beijing 100083, China;
Yang Feng, School of Mechanical Electronic&Information Engineering, China University of Mining&Technology, Beijing 100083, China;

Abstract

Abstract: The change of research way brought by big data and cloud computing has an impact on the research of GPR data processing. Filtering and analysis research for large scale GPR data was conducted by cloud computing platforms. Data preprocessing to GPR data was realized through flow computing framework Storm so as to solve the mismatch of GPR data format and input data format of Hadoop and realize parallel convolution and gain process based on Hadoop. The filtering result and performance index was analyzed. Experimental results show that the proposed method is accurate and effective on GPR data process, and it has significantly improved operating speed and parallel speed-up in comparison with previous method.

Recommended Citation

Liang, Yincheng; Yuan, Yuan; and Feng, Yang (2020) "Research of Parallel Process Method of Ground Penetrating Radar (GPR) Data Based on Hadoop," Journal of System Simulation: Vol. 29: Iss. 1, Article 17.
DOI: 10.16182/j.issn1004731x.joss.201701017
Available at: https://dc-china-simulation.researchcommons.org/journal/vol29/iss1/17

First Page

120

Revised Date

2015-07-10

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201701017

Last Page

128

CLC

TP391

Recommended Citation

Liang Yincheng, Yuan Yuan, Yang Feng . Research of Parallel Process Method of Ground Penetrating Radar (GPR) Data Based on Hadoop[J]. Journal of System Simulation, 2017, 29(1): 120-128.

DOI

10.16182/j.issn1004731x.joss.201701017