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

Through ZigBee technology, data information can be transmitted in the form of radio waves, the communication between multiple sensors can be coordinated, and data can be quickly transmitted to the computer for analysis and processing. The ZigBee technology is well-suited for transmitting data using radio waves as it is specifically designed for low-power, short-range wireless communication. It operates in the industrial, scientific, and medical (ISM) radio bands, such as 2.4 GHz, 900 MHz, or 868 MHz, depending on the region. It has the characteristics of high data transmission efficiency and low energy consumption. At present, the ZigBee technology is widely used in many fields such as smart home, remote monitoring, mining, and petrochemical industries (Hemmati et al., 2022; Freddi et al., 2022). The Zigbee technology offers high data transmission efficiency through its low data rate, low power consumption, short packet length, and direct device-to-device communication. It supports mesh networking and uses frequency hopping spread spectrum for reliable communication (Sung et al., 2017).

From the analysis and comparison of Table 1, we can see that each wireless SN technology has different characteristics and advantages in different application fields (Ammari et al., 2022; Popkov et al., 2022). The aim of this study was to design and study the monitoring system for the stope slope of RE mines. Most of the stopes of RE mines are mountainous areas far away from the city, and the engineering geological environment conditions are poor. Solution, the cost is very high. In response to these problems, the system must require low cost, low power consumption, and good scalability of transmission equipment. The ZigBee technology has unique advantages. Therefore, this study introduces the ZigBee network transmission technology into the system experiment research.

Monitoring components include mechanical, inductive (capacitive), and photoelectric components. To ensure the reliability of the monitoring system and conduct field tests on the stability of various monitoring components, the system adopts two sets of electromechanical and optical fiber solutions. Electromechanical solutions involve components such as antennas, switches, and connectors for signal transmission, while optical fiber solutions use optical fibers to transmit data as light signals in fiber optic communication systems. Electromechanical solutions include sensors detecting physical parameters and converting them into electrical signals, while optical fiber solutions use fiber optic sensors to measure parameters such as temperature or strain using light signals along the fiber. Surface, deep displacement, and osmotic pressure flow sensors are used, as well as fiber grating displacement gauges, strain gauges, and osmotic pressure gauges (Fathi et al., 2022; Concepcion et al., 2021). Fiber grating displacement gauges are used for accurate and distributed displacement measurements in structures, strain gauges measure mechanical deformation in materials, and osmotic pressure gauges measure osmotic pressure differences in solutions. Each gauge serves a distinct purpose and finds applications in different fields of engineering and scientific research (Figure 1).

Figure 1:

Data Acquisition Instruments: Traditional sensors use automatic data modulators, while fiber optic sensors use fiber grating demodulators. The fiber grating demodulator's advantages make it a valuable tool for a wide range of applications, including structural health monitoring, oil and gas exploration, environmental monitoring, aerospace, and telecommunications. The automatic data collection tool can collect data from all traditional sensors, and the collection time can be set (10 min to 30 days), which can automatically realize real-time data collection. Both sensor types measure a wide range of physical parameters and can offer real-time monitoring, accuracy, and reliability. The main difference is in the data modulation and demodulation method used in fiber optic sensors, enabling them to convert optical signals into digital data for enhanced capabilities like distributed sensing and multiplexing. The automatic data acquisition device realizes the unified power supply to the sensor and transmits, receives, and records the data measured by the sensor through it. It can choose DC power supply or solar power supply. Considering that most of the stope landslides occur during the continuous rainy period, it can be shared with the DC power supply of the video monitoring network of the mining area and is equipped with a battery for backup. The occurrence of stope landslides during continuous rainy periods can be attributed to factors like increased soil saturation, pore water pressure, reduced shear strength, erosion, and weathering. Groundwater seepage, dynamic loading, and rapid weather changes further contribute to slope instability. The collector has an internal storage function, which can ensure that the data can be continuously collected without loss even in the event of a communication failure. Single or multiple automatic data acquisition instruments can be networked as independent nodes to form a complete data acquisition system (Chernick et al., 2021; Ganepola et al., 2021).

The fiber grating demodulator is a multi-channel parallel acquisition of fiber grating wavelength information. It integrates data acquisition, analysis, and storage functions. Fiber grating demodulators effectively utilize fiber optic sensors in data acquisition instruments due to their high sensitivity, multiplexing capability, remote sensing ability, and intrinsic safety. These sensors offer high reliability, low intrusiveness, and non-invasive monitoring, making them suitable for various applications in industries such as aerospace, civil engineering, and oil and gas. It can be connected to sensors in series to achieve quasi-distributed monitoring. The demodulator can share the DC power supply with the video surveillance network and does not need to supply power to the optical fiber sensor connected in series on the instrument and also has the function of storing data locally. Optical fiber sensors are passive devices that do not need power supply as they rely on light reflection and modulation to measure physical quantities. Their interaction with light passing through the fiber allows them to detect changes in the environment. As passive sensors, they are suitable for remote locations, offer intrinsic safety, and are immune to electromagnetic interference, finding applications in structural monitoring, aerospace, and industrial process control. Storing data locally in a fiber grating demodulator refers to the ability of the demodulator to store measurement data within the device itself. This feature is valuable in scenarios where real-time data transmission or continuous connectivity is not feasible or necessary.

The ISL process is a mining method that uses strong electrolytes such as ammonium sulfate and magnesium sulfate to exchange and resolve RE ions adsorbed on the clay surface to recover RE resources (Binumol et al., 2020; Stevenson et al., 2022). The ISL process, also known as in situ recovery (ISR) or solution mining, offers ecological benefits compared to conventional mining. It minimizes surface disturbance, reduces greenhouse gas emissions, conserves water, and produces fewer tailings. ISL prevents acid mine drainage, lowers energy consumption, and enhances site restoration.

The reaction formula is as follows: (1) [CM]m.nRE3++3nA+→[CM]3nA++nRE3+ \left[ {CM} \right]m{.}n{RE^{3 + }} + 3n{A^ + } \to \left[ {CM} \right]3n{A^ + } + n{RE^{3 + }}

Among them, CM is a clay mineral. When using (NH₄)₂SO₄ as the leaching solution, the reaction equation is as follows: (2) 2(KC)3−RE3++3(NH4)1+S2O42−→2(KC)3−6(NH4)1++RE23+(SO4)32− 2{(KC)^{3 - }}R{E^{3 + }} + 3{(N{H_4})^{1 + }}{}_2^{}SO_4^{2 - } \to 2{(KC)^{3 - }}6{(N{H_4})^{1 + }} + RE_2^{3 + }(S{O_4})_3^{2 - }

Here, KC is kaolin. In the RE workshop, high-concentration ammonium sulfate and magnesium sulfate electrolytes are transported through pipelines to the high-level pool on the top of the stope. Electrolytes containing magnesium sulfate may be transferred via pipelines to the stope's high-level pool in mining or industrial processes for waste management, recycling, further processing, concentration, or safety reasons. The specific purpose depends on the process's requirements and considerations, such as safety, environmental concerns, and resource utilization. The mother liquor seeps to the foot of the mountain by gravity, passes through the liquid collecting ditch at the foot of the mountain, and then transports the collected mother liquor to the workshop through pipelines to achieve the purpose of recovering REs (Yuksekdag et al., 2022; Abbass et al., 2020).

ISL for uranium recovery and recycling/resource recovery in waste management: ISL minimizes surface disturbance and reuses leaching solutions, while waste management focuses on material separation, efficient processing, closed-loop systems, and eco-friendly practices to reduce environmental impact and conserve resources. ISL technical route: high-concentration strong electrolyte → stope high-level pool → liquid injection well network → liquid collection roadway or liquid collection ditch → recovery of RE mother liquor. The process flow is shown in Figure 2.

Figure 2:

Because the ISL process has the advantages of less environmental pollution and a high resource recovery rate, it has been widely used and has achieved good economic and ecological benefits. It has achieved good economic results in uranium extraction due to lower production costs, reduced capital investment, higher uranium recovery rates, and energy efficiency. It allows for shorter project development time, has a lower environmental impact, and enables simultaneous exploration and production. However, due to the short promotion time of the ISL process, the technology is not perfect. One significant drawback of the ISL process is its relatively short promotion time, indicating it has not been extensively developed and implemented compared to other mining and extraction methods. During the ISL and mining of RE, RE ions and fine soil particles migrate, and some of them are carried out of the surface, changing the microstructure of the soil. It is mainly manifested in two aspects: on the one hand, the porosity increases and the soil strength decreases; on the other hand, the soil porosity and permeability increase. Under the same hydraulic gradient, dynamic water pressure increases, which is more likely to damage the soil structure and decrease. Slope stability and landslides are prone to occur, which can be triggered by various factors, including heavy rainfall, earthquakes, construction activities, vegetation removal, geological conditions, and changes in groundwater levels. Human disturbances like deforestation and urbanization, as well as climate change, can also contribute to landslides. Because the ore soil is loose and the cracks are large in the process of leaching and mining resources, it is easy to cause the slope to become unstable and cause landslides. Therefore, the most important problem in the process of RE mining is how to ensure the slope of the mountain and stability and to prevent landslides.

The air-dried ore samples of ionic RE in the mining area were taken, and their initial moisture content was measured as w₀ = 1.39%. The test results of moisture content are shown in Table 1. The air-dried ore samples were prepared into test ore samples with the same void ratio and moisture content as the original ore. The relevant knowledge of soil mechanics shows that the calculation formula of the total mass m₀ of the ore sample is as follows: (3) m0=ds(1+w)1+e×ρw×A×h {m_0} = \frac{{{d_s}\left( {1 + w} \right)}}{{1 + e}} \times {\rho _w} \times A \times h where d_s is the relative density of soil particles, which is taken as 2.70 according to the properties of the ore sample; e is the void ratio, which is taken as 0.95 according to the on-site measurement; w is the moisture content of the original ore, which is taken as 18%; A is the sample area, A = 1 m × 0.5 m, ore sample height h = 1 m; and ρ_w is the density of water, which is taken as 1.0 × 103 kg/m³.

Substitute the relevant data into formula (2.4) to calculate: m₀ = 816.92 kg.

Assuming that the mass of the air-dried ore sample is X kg and the amount of water is Y kg, it can be obtained from Table 2: (4) X+Y=m0 X + Y = {m_0}

The mass of water contained in the X kg air-dried ore sample and the mass of the dry ore sample are as follows: (5) mw=w01+w0X {m_w} = \frac{{{w_0}}}{{1 + {w_0}}}X (6) ms=11+w0X {m_s} = \frac{1}{{1 + {w_0}}}X where m_w is the mass of water contained in the air-dried sample and m_s is the mass of the dry mineral sample.

It can be obtained from the moisture content formula: (7) mw+Yms×100%=w \frac{{{m_w} + Y}}{{{m_s}}} \times 100\% = w

It can be obtained from the aforementioned relations: X = 701.82 kg, Y = 115.099 kg.

After the micro-pore water pressure sensor is successfully re-calibrated, the accuracy of each sensor is tested. First, the micro-pore water pressure sensor is divided into 4 groups, and then 1, 2, and 4 groups of sensors are placed in the water with a water height of 13.9. cm, 22.3 cm, and 11.4 cm bottom of the barrel and the third group of sensors was placed in dry soil, and the water pressure was calculated according to the following formula: (8) pi=ρgh {p_i} = \rho gh

In the formula, ρ is the density of water, taking 1 g/cm³, and h is the height of water, in cm.

Calculate the actual water pressure p_i in each set of experiments, convert the stabilized voltage value measured by each micro-pore water pressure sensor into the water pressure value pai at the corresponding water height, i represents the i-th micro-pore water pressure sensor, then the obtained The accuracy θ of the first miniature pore water pressure sensor is given as follows: (9) θ=pi−paip0×100% \theta = \frac{{{p_i} - {p_{ai}}}}{{{p_0}}} \times 100\%

In the formula, p₀ is the full-scale water pressure value of the micro-pore water pressure sensor, which is 20 kPa.

The measurement accuracy of the micro-pore water pressure sensor calculated by the previous formula is compared with the factory accuracy ± 0.25%. If the absolute value of the calculated sensor accuracy is less than 0.25%, the measurement accuracy of the micro-pore water pressure meets the required accuracy requirements, otherwise, does not meet the accuracy requirements. The specific measurement results are shown in Table 3.

It can be seen from Figure 3 that the absolute value of the measurement error of the micro-pore water pressure is less than 0.25%, which meets the accuracy requirements. The third group of sensors placed in the dry soil passed the corresponding calculations, and the accuracy also met the requirements.

Figure 3:

In the experiment, a total of three groups A, B, and C are the ore soil with a depth of 3 m below the surface, the ore soil with a depth of 4 m below the surface, and the ore soil with a depth of 5 m below the surface. The entire leaching process involves a chemical replacement reaction between the magnesium sulfate solution and the RE (rare earth) ions. The strength law is explored. There are 2 samples in each group, one of which is leached with water, and the other is leached with magnesium sulfate. It was dried and re-shaped, and each soil column was treated according to the geotechnical test procedures. Geotechnical testing is a crucial process used to assess the physical and mechanical properties of soil and rock materials. The test procedures help engineers and geologists understand the behavior of these materials, which is essential for various engineering and construction projects. The detailed method is described in Chapter 2. The RE ion content detected in the leaching solution during the leaching process is provided in Tables 4 and 5.

The data in Tables 4 and 5 are plotted in the figures, and it can be clearly seen that the ion exchange reaction stage segment trend in the leaching reaction process.

It can be seen from Figure 4 that during the first leaching time period, almost no REs were precipitated for each sample, and the leaching solution did not completely penetrate the soil column. The solution began to undergo a replacement reaction with RE elements in the ore sample, and more RE elements could be detected in the leaching solution. After the 4th hour of the leaching process, it was found that a large amount of RE was precipitated, and the content of RE in the leaching solution increased significantly. The amount of RE precipitation peaked in the 4th hour. From the 5th to the 6th hour, it can be seen that the RE leaching rate slowed down. In the subsequent stages, the amount of RE precipitation gradually decreased. After the 7th hour, the RE in the leaching solution the content was greatly reduced, and by the 8th hour, almost no RE ions could be detected, and the reaction was deemed to have been completed. In the early stage of leaching, it can be seen that the B1 sample has the fastest leaching rate, and some REs are not leached in each sample.

Figure 4: