岩土力学 ›› 2022, Vol. 43 ›› Issue (S1): 443-451.doi: 10.16285/j.rsm.2021.0168

• 岩土工程研究 • 上一篇    下一篇

基于统计理论与试验的地铁工程监测数据分析

王熠琛,郑宏,李立云,卢鑫月   

  1. 北京工业大学 城市与工程安全减灾教育部重点实验室,北京 100124
  • 收稿日期:2021-01-28 修回日期:2022-02-21 出版日期:2022-06-30 发布日期:2022-07-15
  • 作者简介:王熠琛,男,1989年生,博士后,助理研究员,主要从事城市地下工程智能化风险管控领域的研究。
  • 基金资助:
    国家自然科学基金重点项目(No.51538001);北京市博士后工作经费资助项目(No.2021zz-104)。

Analysis of monitoring data in metro construction based on statistical theory and test

WANG Yi-chen, ZHENG Hong, LI Li-yun, LU Xin-yue   

  1. Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education, Beijing University of Technology, Beijing 100124, China
  • Received:2021-01-28 Revised:2022-02-21 Online:2022-06-30 Published:2022-07-15
  • Supported by:
    This work was supported by the Key Program of National Natural Science Foundation of China(51538001) and the Beijing Postdoctoral Research Foundation (2021zz-104).

摘要: 地铁施工监测数据的不确定性分析对工程决策管理有重要意义,统计推断是使用最广的分析理论。为更加科学地应用该理论,必须明确3个基本问题:(1)统计分析时以什么原则选取监测数据才有科学的统计意义?(2)具有统计意义的监测数据在大多数情况下有怎样的统计特征?(3)实际工程中如何检验监测数据的统计意义与特征? 深入结合统计理论与统计试验法,围绕这3个问题展开研究。得到如下结论:(1)获取监测数据的测点必须有相似的工况与受力状态,才可使其满足随机样本的要求,才可能具有科学的统计意义;(2)根据中心极限定理,绝大多数情况下具有统计意义的监测数据应服从正态分布,实际分析中的正态性假定有理论依据;(3)实际分析中应利用游程检验法验证数据的统计意义,利用概率纸与卡方检验法验证数据的正态性,从而基于理论与试验两方面确保对统计推断理论的严格应用。

关键词: U231, X830.2

Abstract: The uncertainty analysis of the monitoring data in metro construction is significant for the decision-making and management of engineering. Statistical inference theory is employed frequently to analyze uncertainty. Three key issues must be ascertained in order to employ the theory scientifically. (1) What is the principle of monitoring data collection to ensure the statistical scientificity of monitoring data? (2) What are normally the statistical properties of monitoring data with statistical scientificity in practical cases? (3) How to test the statistical scientificity and properties of monitoring data in practical construction? The study on these issues is implemented by employing statistical theory and statistical test methods. Some conclusions achieved are that: (1) All the monitoring points selected to collect data must have similar engineering conditions to ensure that the data collected can comply with the demands of a random sample and statistical scientificity. (2) The monitoring data with statistical scientificity should follow Gaussian distributions because of the central limit theorem, therefore the normality assumption of practical analysis has a rationale. (3) The practical analysis should verify the statistical scientificity by employing run tests, and verify the normality of the monitoring data by probability plots and χ2 tests. These can ensure the scientificity and reliability of statistical inference by combining statistical theory and tests.

Key words: statistical scientificity, normality assumption, run test, probability plot, χ2 test

中图分类号: 

  • U231
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