Monitoring unstable slopes in an open pit lignite mine using ARIMA

Abstract

Slope stability is a widely studied area because of the significant consequences of slope failure. There are various factors affecting slope stability in open pit mines, and predicting the time of failure can be difficult due to the complex nature of the rock mass. Regression methods are often used in this prediction process, but they are limited in that they use a strict mathematical model. Therefore, possible future changes within the structure of a slope can be underestimated because once a mathematical model has been established to predict slope failure, it is then used indefinitely. For this reason, an autoregressive integrated moving average (ARIMA) model is used in this study as a time series analysis (TSA) method for the prediction of slope failure. Data obtained from the movements of tension cracks from six out of ten established stations in Ilgin open pit lignite mine of Turkish Coal Enterprises, West Lignite Enterprises (TKI-GLI) were used to predict future values. The prediction results from the ARIMA method were also compared with results from regression methods and were shown to be more successful.