Algorithm of Inclination Correction for Point Cloud in Dynamic Subsidence Monitoring

The stability of an instrument is a key factor in determining the quality of data acquired. During the process of dynamic deformation monitoring in mining areas, due to the impact of highly intensive underground mining practices, some non-uniform subsidence is likely to occur on the ground surface....

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Bibliographic Details
Published in2020 7th International Conference on Information Science and Control Engineering (ICISCE) pp. 195 - 199
Main Authors Wu, Junhe, Peng, Haiju, Sun, Guibin, Li, Zhi, Huo, Zhihong, Yan, Kewen, Ao, Jianfeng
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2020
Subjects
Data mining
Dynamic Deformation Monitoring
Error Correction
Heuristic algorithms
Inclination
Instruments
Interpolation
Point Cloud
Real-time systems
Stability analysis
Terrestrial Laser Scanner
Three-dimensional displays
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Summary:The stability of an instrument is a key factor in determining the quality of data acquired. During the process of dynamic deformation monitoring in mining areas, due to the impact of highly intensive underground mining practices, some non-uniform subsidence is likely to occur on the ground surface. Such subsidence will lead to relatively large inclination of the instrument within a short time, and consequently cause the automatic inclination compensator to exceed its limits during the scanning process. This is a particular problem encountered when the terrestrial laser scanner (TLS) is used for deformation monitoring in mining areas. This paper mainly analyzes the influence of inclination of the scanner upon precision of point cloud data based on the working principle of the scanner and puts forward an error correction method. First, the inclinations of an instrument at the beginning and at the end of a scanning process are recorded; second, the inclination of the instrument at every moment is determined basing on the relationship between the scanning time and the inclination of the instrument through interpolation, in this way the scanning point coordinates are being corrected. In the end, reasonability and effectiveness of the correction method are verified by means of experiment and comparison between the target control point and the feature planes within the scanning area before and after correction.
DOI:10.1109/ICISCE50968.2020.00050