| 大数据时代的岩土工程监测——转折与机遇 |
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| 引用本文： | 王 浩,覃卫民,焦玉勇,何 政.大数据时代的岩土工程监测——转折与机遇[J].岩土力学,2014,35(9):2634-2641. |
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| 作者姓名： | 王 浩 覃卫民 焦玉勇 何 政 |
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| 作者单位： | 1.中国科学院武汉岩土力学研究所 岩土力学与工程国家重点实验室，武汉 430071；2.武汉大学 计算机学院，武汉 430071 |
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| 摘 要： | 随着电子信息技术、科学研究与工程实践的快速发展，不断产生种类繁多、数量巨大的数据，大数据现象已经出现，在科学数据分析、电子商务和银行业等领域得到了越来越多的重视和应用，大数据即将深刻地影响着人类的生活、工作及思维。传统的数据存储方法、关系数据库、数据处理和数据分析方法逐渐不能满足大数据业务的需要。简要介绍了大数据的定义、特征、所涉及的方法和技术、带来的变革及简单的应用实例，回顾了岩土工程监测学科的历史、现状及面临的问题，指出大数据的概念与岩土工程监测具有天然的契合性，今后大规模、全方位、多维度及多场的岩土工程监测将得以实现。在大数据时代，以关联分析、成因分析及决策支持为核心的深入分析能力将成为监测工作的核心，现场监测将被提升到与试验、理论与数值模拟相同甚至是更为重要的地位。因此，岩土工程监测工作者应该重视大数据的研究，加强应用其他行业的大数据研究成果，抓住大数据对岩土工程监测带来的机遇，为未来岩土工程监测的跨越式发展奠定基础。
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| 关 键 词： | 大数据 岩土工程 监测 数据分析 传感器 |
| 收稿时间： | 2013-10-10 |
Transitions and opportunities of geotechnical engineering monitoring in coming big data era |
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| WANG Hao,QIN Wei-min,JIAO Yu-yong,HE Zheng.Transitions and opportunities of geotechnical engineering monitoring in coming big data era[J].Rock and Soil Mechanics,2014,35(9):2634-2641. |
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| Authors: | WANG Hao QIN Wei-min JIAO Yu-yong HE Zheng |
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| Institution: | 1. State Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan 430071, China; 2. School of Computer, Wuhan University, Wuhan 430071, China |
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| Abstract: | With the rapid development of electronic information technology, scientific research and engineering practice, a wide range and a large quantity of data have been produced continuously. The big data phenomenon has emerged. It is attracting more and more attention and application in scientific data analysis, electronic commerce and banking industry, and taking a profound impact on human life, work and thinking. Traditional data storage methods, relational databases, data processing and data analysis methods can’t meet the current needs on big data gradually. The paper introduces the definitions, characteristics, methods involved, changes brought about and simple application examples of big data. A review on history, state of art and problems of geotechnical engineering monitoring is presented. The concepts of big data naturally agree well with the geotechnical engineering monitoring. Large-scale, comprehensive, multidirectional and multifield geotechnical monitoring will become a reality in the future. The in-depth analysis capabilities such as correlation analysis, cause analysis and decision support will become the core works for the monitoring projects in the era of big data. Furthermore, the site monitoring will be promoted to the same or even more important role as the experiment, theoretical analysis and numerical simulation. Thus, the geotechnical engineering workers should pay highly attention to big data research, enhancing the use of research results of big data from other disciplines. With the opportunities brought about by big data, a rapid development of geotechnical engineering monitoring will arise in the future. |
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| Keywords: | big data geotechnical engineering monitoring data analysis transducer |
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