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Model of Gross Error Elimination for Monitoring Data Collected by A Surveying Robot

Yachun Mao, Yong‐Sheng Chen, Shuhong Wang, Roaj Betouber

Year
2014
Citations
2
Access
Open access

Abstract

The 3D monitoring system based on a surveying robot and the Geomos software is widely used in the slope monitoring of open pits. The effect of various factors, such as refraction and blasting vibration, is crucial to the monitoring process. The probability of monitoring data to contain gross error is significantly higher than 0.3%. Thus, using the Pata criterion as the elimination criterion of the gross error is unreasonable. In this study, the data on multi-period monitoring were used as the source, and the accuracy requirements of the Code for Engineering Survey (2007) were set as the goal of the slope monitoring of open pits. The actual probability of the monitoring data to contain gross error was calculated through mathematical statistics. An elimination model of gross error was developed based on probability theory. The practicality of the proposed model was tested vis--vis the practical data on the slope monitoring of open pits.

Keywords

SoftwareProcess (computing)Computer scienceOpen sourceError detection and correctionData setData miningStatisticsEngineeringReliability engineering

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