Stability of Sensor Network based on Non-linear Data Analysis for in situ Leaching of Ionic Rare Earth Ore Bodies under Similar Simulation Experiments

Abstract

Abstract Ionic rare earth (RE) mines use the in situ leaching (ISL) method to operate, but after investigation, it is found that the geological damage caused by RE mines is still serious in recent years. The structure is damaged, which affects the stability of the mine slope and even causes geological disasters such as landslides and collapses to a certain extent, which has a huge impact on the lives of local people. Therefore, it is very important to analyze the slope stability of RE mines. In this study, indoor similarity simulation experiments were conducted using the sensor network (SN) of non-linear data analysis, and its stability of the ISL of ionic RE ore bodies was studied. In addition, an indoor column leaching simulation experiment was carried out to observe the internal fine and microstructure of the ore sample during the whole leaching process using nuclear magnetic resonance (NMR) under the conditions of magnesium sulfate solution and water leaching, respectively. The evolution mechanism of the pore structure was analyzed during the leaching process. The experiments showed that during the whole leaching process, the ore body reaches saturation in the early stages, resulting in a sharp increase in the porosity of the ore sample within the first 1 h due to seepage. Subsequently, the porosity of each sample increases, indicating that the seepage of the leaching solution inside the sample has reached a relatively stable state.