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Research on the Application of Dynamic Process Correlation Based on Radar Data in Mine Slope Sliding Early Warning
Yuejuan Chen1,2, Yang Liu1,2, Yaolong Qi1,2
1College of Information Engineering, Inner Mongolia University of Technology, Hohhot 010080, China.
Sensors (Basel, Switzerland)
|August 10, 2024
Summary
This study introduces a novel method for predicting open-pit coal mine slope sliding by analyzing phase noise and deformation data. The technique accurately forecasts landslide events, enhancing slope monitoring and early warning systems.
Area of Science:
- Geotechnical Engineering
- Remote Sensing
- Mining Safety
Background:
- Open-pit coal mine slope safety is increasingly complex due to expanding operations.
- Slope failures pose significant risks to life and property in mining areas.
Purpose of the Study:
- To develop a method for predicting slope sliding time in open-pit coal mines.
- To analyze the relationship between phase noise and deformation for early warning.
Main Methods:
- Utilized differential InSAR (D-InSAR) to obtain micro-deformations from radar monitoring data.
- Extracted phase noise from radar echo data and calculated deformation volume.
- Developed a prediction model based on the tangent angle of deformation volume to phase noise standard deviation.
Main Results:
- Identified maximum deformation rates of 10.1 mm/h and 6.65 mm/h in case study areas.
- Calculated maximum deformation volumes of 2,619,521.74 mm³ and 2,503,794.206 mm³.
- Predicted landslide times earlier than actual occurrences, validating the method's effectiveness.
Conclusions:
- The proposed phase noise and deformation analysis method effectively predicts slope sliding events.
- The technique enhances the accuracy and reliability of slope monitoring and early warning systems.
- Improved efficiency in slope monitoring and early warning for mining operations.
Keywords:
deformable bodydeformation time predictiondynamic course correlationmicrovariation monitoring radarphase noise standard deviationMore Related Videos
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