Open Cut

Estimation of True Deformation Vector from Slope Radar Monitoring

Open Cut » Geology

Published: April 20Project Number: C27046

Get ReportAuthor: Marc Elmouttie, Peter Dean, Matt Van De Werken | CSIRO

Slope deformation radar monitors are now widely used in open cut coal mining for monitoring highwall and low wall deformations. Their introduction has facilitated better management of risk associated with slope failure during mining and therefore protection of personnel and equipment. A well recognised problem is that radar monitors only measure deformation directed towards the detector - line of sight bias. This bias can lead to misinterpretation of deformation size, rate and failure mechanism, and therefore miscalculation of failure volume, which can significantly impact safety and productivity.  Current methods to compensate for the bias make potentially inaccurate assumptions about the deformation vector relative to the wall/slope orientation. Using multiple slope monitors to observe the same region of highwall or low wall can address this problem but this is rarely done due to the expense associated with deploying multiple monitors for the one zone.

This project has investigated the feasibility of a low cost solution based on CSIRO research on a patent-pending method. By integrating a computer vision system with an existing slope monitor, high precision tracking of features in the field of view can be performed. Combined with assumptions on the deformation characteristics, the true deformation vector can be estimated. This project field tested and quantified the performance of a prototype system. It assessed the implementation options (usage of cameras currently installed with radar monitors versus retrofitting of higher performing cameras).

Experiments at Site A demonstrated the efficacy of the approach for monitoring both oblique and transversely oriented failures in a low wall dump. Even using post-processed and compressed imagery, the computer vision algorithms and sensor fusion technique clearly demonstrated 3D vector estimation which was consistent with the surface type failure being observed. Site B focussed on the use of the technique using raw, high resolution imagery to obliquely monitor a deeper seated multi-bench failure, in a hard-rock environment. The method clearly detected deformation perpendicular to the radar with deformations significantly greater than those measured along the line-of-sight. The derived 3D deformation vectors were consistent with both an understanding of the failure mechanism as well as previous measurements undertaken using a dual-radar system.

Through fusion of vision and radar data, it has been also demonstrated that at least millimetre precision at a range of around 500m can be achieved but it is expected much greater ranges can be supported with suitably chosen optics. This then supports estimation of 3D deformation vectors with equivalent angular precisions.

An integrated solution has been designed as part of this project, including a high-level requirements analysis. Consultation on this project with GroundProbe and IDS GeoRadar has ensured that the proposed solution is implementable on at least a significant fraction of existing radar systems. Finally, the STPA (System-Theoretic Process Analysis) process has been applied to help identify and mitigate potentially undesirable system states that may arise through this fused sensor approach.


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