Practical Method of Predicting Slope Failure Based on Velocity Value (SLO Method) From Slope Stability Radar - Fery Andika Cahyo; Audi Farizka; Ahmad Amiruddin; Rachmat Hamid Musa (PERHAPI, 2018)
Predicting slope failure is one of the most sought after feature from Slope Stability Radar (SSR). An accurate slope failure prediction will potentially give an ample time to manage risk related with slope stability, wherein the evacuation ofequipment or personal would be executed on a timely manner. The renownedmethod to predict failure among geo-mechanical practitioner is utilizing inversevelocity method, in which collapse will be predicted to happen when the extension of inverse velocity line is intercepted at predefined value that is usually only fractal above zero. The tenet of this method is, if one has acquired the knowledge of inverse velocity value from previous collapses, the next collapse could be predicted based on it with the pretext that both share the same nature and geological feature. The same can be said for predicting collapse based on velocity value. Set of maximum velocity value from several previous collapses will be averaged to determine predefined assumption to predict the next collapse. This paper will demonstrate an alternative method to predict collapse that will use velocity value instead of inverse velocity. This method is called SLO method as proposed by Azania Mufundirwa.This paper will specifically exemplify the practical steps to produce the failureprediction from slope stability radar data, and discuss the characteristic of theprediction yield by this method. Velocity chart with velocity calculation period of60 minutes is first established from particular pixel deemed as the one that showing the most distinguished progressive deformation trend. The velocity data will then be an exported and reprocess as such that the time data will be converted into unit time stamp number. The designated time stamp will then be accumulated, in which the onset of failure, will be regarded as time 0 reference. Log linear chart will be generated in which X-axis will be occupied by velocity value, while Y-axis will depict Velocity x Accumulated time (SLO chart). Collapse can subsequently be predicted by intercepting the predefined assumption of velocity during collapse with the log linear curve from the SLO chart. Two methods, mathematical graphical, will be presented in this paper in order to give in depth understanding as to how one can predict collapse event with velocity value. Taking account on the study case from iron ore mining, SLO method yielded prediction of failuretime on 10:58 PM 31st January 2016, meanwhile the real failure occur on 11:32 PM 31st January 2016.