Threshold assessment of low displacement rates through slow movement analysis

Authors: Calderon, J; Barnes, R

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DOI https://doi.org/10.36487/ACG_repo/2535_54

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Calderon, J & Barnes, R 2025, 'Threshold assessment of low displacement rates through slow movement analysis', in JJ Potter & J Wesseloo (eds), SSIM 2025: Fourth International Slope Stability in Mining Conference, Australian Centre for Geomechanics, Perth, https://doi.org/10.36487/ACG_repo/2535_54

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Abstract:
Detecting low-velocity slope movement in open pit mines is vital for early hazard identification and operational risk mitigation. This study explores the use of slow movement analysis (SMA) applied to displacement, velocity, amplitude, and acceleration data from ground-based radar (IDS ArcSAR radars) systems. For a given monitoring area, and across selected time between scans (T) values, statistical and frequency-based features – including those derived from Fast Fourier Transforms – were extracted to characterise slope behaviour. A hierarchical clustering approach was used to group movement patterns, which were then categorised by geotechnical experts into failure, pre-failure, and stable classes. The analysis included not only failure-related movement but also data from areas showing no signs of instability, allowing for a comprehensive understanding of both indicative and non-indicative movement patterns. This approach aims to identify consistent feature signatures across failure and non-failure cases and to support the development of interpretive rules that help geotechnical engineers assess whether SMA data predicts failure. The results lay the groundwork for integrating such rule-based insights into predictive monitoring workflows, enhancing safety and decision-making in mine slope management.

Keywords: slow movement analysis, open pit mining, geotechnical monitoring, ground-based radar, hierarchical clustering, failure detection, feature engineering, Fast Fourier Transforms

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