东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2011, Vol. 32 ›› Issue (7): 1020-1023.DOI: -

• 论著 • 上一篇    下一篇

剔除变形监测粗差数据的新方法——数据跳跃法

毛亚纯;王恩德;修春华;   

  1. 东北大学资源与土木工程学院;
  • 收稿日期:2013-06-19 修回日期:2013-06-19 发布日期:2013-04-04
  • 通讯作者: -
  • 作者简介:-
  • 基金资助:
    国家高技术研究发展计划项目(2007AA06Z108)

Data jump method: A new approach to eliminating the deformation monitoring data with gross errors

Mao, Ya-Chun (1); Wang, En-De (1); Xiu, Chun-Hua (1)   

  1. (1) School of Resources and Civil Engineering, Northeastern University, Shenyang 110819, China
  • Received:2013-06-19 Revised:2013-06-19 Published:2013-04-04
  • Contact: Mao, Y.-C.
  • About author:-
  • Supported by:
    -

RichHTML

1

PDF (PC)

937

摘要： 当观测值中有多个粗差时拉依达法则一次只能剔除一个粗差,并且多个粗差之间互差不满足一定条件时拉依达法则失效.针对此问题在拉依达法则基础上提出了一种剔除变形监测粗差数据的新方法数据跳跃法.数据跳跃法克服了拉依达法则的部分局限性,可将含有粗差的变形监测值批量剔除,为一次剔除多个粗差提供了解决方法.采用该方法对实际监测数据进行了处理,取得了较好的效果.数据跳跃法为利用程序进行粗差判定与剔除提供了理论依据和算法.

关键词: 变形监测, 粗差剔除, 数据跳跃法, 拉依达法则, 粗差互差

Abstract: When there are several gross errors in the observations, the Pau Ta's criterion can only eliminate one at a time. If the mutual deviations among the gross errors do not satisfy certain conditions, the Pau Ta's criterion will be invalid. To solve this problem, a new approach named as data jump method based on the Pau Ta's criterion was proposed. It overcomes the limitation of the Pau Ta's criterion. The deformation monitoring data with gross errors can be eliminated in batches. The method is used to process some actual monitoring data, and a good result is obtained, which provides a theoretical basis and algorithm for the gross error determination and elimination using computer program.

中图分类号: