Slope Deformation Map Generation via Multiscale Atmospheric Correction
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Solution Overview
Problem
Existing slope monitoring techniques, such as Slope Stability Radar and Slope Stability LiDAR, face challenges in accurately capturing both small, fast-moving and large, slow-moving deformations due to atmospheric conditions, often masking or suppressing critical wall movements, especially with snow, which current methods struggle to handle effectively.
Innovation Solution
A method involving multiscale processing for atmospheric correction, which includes spatial and temporal averaging of deformation data to derive a correction factor, applying masks to remove outliers, and combining datasets to produce improved deformation maps that suppress bulk atmospheric and instrument drift effects, thereby enhancing the accuracy of slope stability monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If bulk correction based on atmospheric correction region is applied, then atmospheric condition changes are corrected, but small fast moving deformations and large slow moving deformations cannot be captured simultaneously
Solution Approach 1:
The patent segments the deformation data into different scales: bulk atmospheric deformations (large-scale, slow-moving) and local slope deformations (small-scale, fast-moving). By applying different processing techniques to different scales - using spatial averaging for bulk correction and preserving high-frequency components for local deformations - the system simultaneously captures both types of movements without masking effects.
Solution Approach 2:
The patent applies different quality characteristics to different parts of the deformation data. Bulk atmospheric corrections are applied with smoothing and averaging characteristics, while local slope movements are preserved with high temporal and spatial resolution. This local differentiation allows the system to handle atmospheric noise without losing critical local deformation signals.
2Adaptability or versatility
If existing atmospheric correction techniques are used, then atmospheric effects are handled, but snow-caused atmospheric effects cannot be handled
Solution Approach 1:
The patent employs dynamic, adaptive processing that adjusts to different atmospheric conditions including snow. The system uses real-time analysis of deformation patterns to distinguish between snow-related atmospheric effects and actual slope movements, dynamically adjusting the correction application to maintain reliability in varying weather conditions.
3Reliability
If spatial averaging is applied to correct atmospheric effects, then bulk atmospheric drift is suppressed, but small fast moving deformations may be masked
Solution Approach 1:
The patent segments deformation data by spatial scale and temporal frequency. Spatial averaging is applied selectively to identify and correct bulk atmospheric trends, while the high-frequency, small-scale deformation signals are preserved through separate processing channels that do not undergo aggressive averaging, thus preventing masking of critical local movements.
Solution Approach 2:
The patent applies partial spatial averaging - enough to suppress atmospheric drift but not so much as to mask small deformations. By controlling the degree and scope of averaging (e.g., limiting spatial window sizes, using adaptive averaging weights), the system achieves just sufficient atmospheric correction while preserving local deformation signals.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach significantly improves the accuracy of deformation maps, reducing false alarms and allowing for earlier detection of impending slope failures by effectively handling both small and large deformations, including those caused by atmospheric conditions and instrument drift.
Implementation Method 1
The radar signal reflected from the slope is analysed for phase difference to provide movement data
Implementation Method 2
the Applicant has described a slope monitoring device based on Slope Stability LiDAR (SSL)... a laser-based device that is used in a similar manner to the SSR to monitor slope movement
Data Source
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AI summary
A slope stability monitoring apparatus which produces slope deformation maps that preserve measurements from fast moving small areas, slow moving small areas, slow moving large areas and fast moving large areas while minimising the effect of non-wall movement contamination, such as atmosphere and artefacts. Also a method of producing slope deformation maps by deriving a correction factor and applying the correction factor to correct for non-wall movement contamination.