3S: A Novel Data Quality Control Algorithm Based on RTK

Hydraulic engineering dams are affected by surrounding environmental and natural factors, leading to deformations of the dam body. These deformations are usually minor. When GNSS RTK technology is used for deformation monitoring of dams, the presence of numerous outliers and noise in the monitoring data significantly affects data quality. To solve this problem, this paper proposes the 3S algorithm, which improves the quality of deformation monitoring data. Firstly, it employs a 3σ criterion method to eliminate outliers from the data. Subsequently, the Savitzky-Golay filtering method is used to filter out the noise within the data, resulting in higher quality deformation monitoring data. Experiments show that the 3S algorithm outperforms wavelet and Kalman filtering in terms of filtering effects, making it the best option for improving the accuracy of deformation monitoring. The use of the 3S algorithm significantly enhances the precision of deformation monitoring.

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Publication Details

Published
2024-08-19
DOI
https://doi.org/10.1109/icspcc62635.2024.10770442
Citations
2
Primary Topic
Data Quality and Management
Type
article
Field-Weighted Citation Impact
0.98
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article

3S: A Novel Data Quality Control Algorithm Based on RTK

Xiaoang Li, Yanyan Zhao, Hongwei Zhao, Z. S. Ji
2 citations
Data Quality and Management
0.98
article

3S: A Novel Data Quality Control Algorithm Based on RTK

Xiaoang Li, Yanyan Zhao, Hongwei Zhao, Z. S. Ji
article en
2 citations

Abstract

Hydraulic engineering dams are affected by surrounding environmental and natural factors, leading to deformations of the dam body. These deformations are usually minor. When GNSS RTK technology is used for deformation monitoring of dams, the presence of numerous outliers and noise in the monitoring data significantly affects data quality. To solve this problem, this paper proposes the 3S algorithm, which improves the quality of deformation monitoring data. Firstly, it employs a 3σ criterion method to eliminate outliers from the data. Subsequently, the Savitzky-Golay filtering method is used to filter out the noise within the data, resulting in higher quality deformation monitoring data. Experiments show that the 3S algorithm outperforms wavelet and Kalman filtering in terms of filtering effects, making it the best option for improving the accuracy of deformation monitoring. The use of the 3S algorithm significantly enhances the precision of deformation monitoring.

Northwestern Polytechnical University (CN)
Openalex Percentile: Top 19%
Data Quality and Management
0.98
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