Mining area tailing classified filling system and filling method

Abstract

The mining area tailing grading filling system is composed of a tailing collecting device, a grading module, a filling slurry preparing module, a conveying module and a filling module and is designed according to the characteristics that tailings of lead-zinc-silver ore and copper-tin-silver-zinc ore contain heavy metal and are complex in particle size. A heavy metal adsorption layer is arranged at the bottom of a collection pool of the tailings collection device, and a sulfide adsorbent is adopted, so that heavy metal ions such as lead, zinc and copper in the tailings can be effectively adsorbed; a cyclone of the grading module is made of a corrosion-resistant material, erosion of chemical substances in the tailings is prevented, the tailings are accurately graded, and grading of filling materials is optimized; the tailings with different particle sizes are accurately separated according to the characteristics of the tailings of the lead-zinc-silver ore and the copper-tin-silver-zinc ore by using the cyclone and multi-layer vibrating screen combined grading equipment; equipment parameters are adjusted to accurately control the granularity of the tailings, so that reasonable grading raw materials are provided for preparation of filling slurry, and the compactness and the stability of a filling body are improved.

Description

Technical field:

[0001] The present invention relates to the technical field of tailings grading filling, and in particular to a mining area tailings grading filling system and a filling method. Background technology:

[0002] In the mining of lead-zinc-silver and copper-tin-silver-zinc mines, tailings treatment and goaf filling are important issues, and traditional tailings filling technology has many drawbacks. In the tailings grading process, most existing processes have difficulty in effectively grading tailings with complex particle size distribution and high heavy metal content. For example, a single cyclone grading method cannot accurately separate tailings of different particle sizes, resulting in unreasonable grading of subsequent filling materials and affecting the performance of the filling body. In terms of filling slurry preparation, existing technologies ignore the inhibitory effect of heavy metal ions in tailings on the hydration reaction of cementitious materials. Conventional proportions prevent cementitious materials from fully exerting their cementing effect, and the selection and use of additives lack specificity, making it difficult to improve the key properties of the slurry. There are also many problems with slurry transportation. The high specific gravity and high abrasiveness of tailings make ordinary conveying pipelines and pumping equipment prone to wear, increasing maintenance costs. It is difficult to accurately control the slurry flow rate, pressure and concentration when transporting over long distances and with large height differences. Problems such as pipeline blockage and slurry segregation are prone to occur, affecting the continuity and stability of the filling operation. In addition, the current filling process is not effective. The traditional filling method cannot fully utilize the characteristics of tailings of different particle sizes, resulting in poor density and integrity of the filling body, increasing the risk of surface collapse, and insufficient resource utilization of tailings, which wastes resources and poses a potential threat to the environment. Summary of the invention:

[0003] To this end, the present invention provides a mining tailings classification filling system and filling method to overcome the problems of the prior art.

[0004] The present invention is implemented by the following technical solutions:

[0005] A mining tailings classification filling system, comprising:

[0006] Tailings classification module, filling slurry preparation module, slurry delivery module, filling module and intelligent monitoring and control module;

[0007] The tailings classification module consists of a cyclone and a multi-layer vibrating screen, and is used to classify the whole tailings according to particle size. The tailings classification module classifies the whole tailings according to three classification limits: 500 mesh, 400 mesh, and 300 mesh. The classification scheme is determined based on material balance analysis, and the daily average filling volume Vr of the goaf, the daily slurry filling volume Qr, and the annual average filling slurry required Qa are calculated according to the following formula:

[0008] Q r =V r K1K2Q a =Q r T

[0009] Where Vk is the daily output of ore, Z is the adoption ratio, γ k is the weight of ore, K1 is the loss coefficient (value range is 0.95-1.05), K2 is the settlement ratio (value range is 1.1-1.3), and T is the filling working day;

[0010] Determine the optimal classification particle size by combining thickener torque analysis;

[0011] The filling slurry preparation module includes a mixer and an automated batching system, which is used to determine the slurry ratio based on experiments. The unconfined uniaxial compressive strength R = P / A is used to measure the filling body strength, where P is the maximum longitudinal load when the test block fails and A is the cross-sectional area perpendicular to the loading direction.

[0012] And through the water bleeding rate:

[0013]

[0014] Where B is the water bleeding rate, Vw is the total mass of water bleeding, W is the water consumption of slurry, G is the total mass of slurry + container, and Gw is the mass of slurry;

[0015] Shrinkage rate:

[0016]

[0017] δ is the slurry shrinkage rate, V1 is the reduced volume after the sinking is completed, and V2 is the total volume of the raw material slurry. Based on the simple volume ratio relationship, without considering the influence of the external environment on the sinking, the sinking rate is determined to determine the optimal slurry ratio;

[0018] The slurry transport module uses pipelines to transport slurry, and the pipeline transport resistance i is calculated by the Jinchuan formula. c , use the Durald formula to estimate the critical velocity V l , ensure that the actual flow rate is greater than V l ,

[0019] The filling module transports the slurry to the underground goaf for filling;

[0020] The intelligent monitoring and control module includes a pressure sensor, a flow sensor, a wear monitoring sensor and a PLC controller. The PLC controller is based on a PID algorithm and adjusts the pumping equipment speed and valve opening according to the real-time data of the pressure sensor, the flow sensor and the wear monitoring sensor.

[0021] Preferably, in the tailings classification module, the tailings particle size is allocated according to the force requirements of different areas of the goaf: fine-grained tailings with a particle size less than 500 mesh are used near the top plate, and coarse-grained tailings with a particle size greater than 300 mesh are used at the bottom; and the classification efficiency and dehydration effect are optimized through CFD simulation of the internal flow field of the thickener.

[0022] Preferably, the filling slurry preparation module introduces an artificial intelligence algorithm, and the artificial intelligence algorithm is a BP neural network model, and the training data comes from a historical proportion test data set.

[0023] Preferably, the slurry delivery module is equipped with a pipeline wear monitoring sensor, and the life is predicted in combination with the wear model; wear-resistant pipeline materials and anti-friction agents are used to reduce wear, and critical flow rate parameters are dynamically adjusted.

[0024] Preferably, the filling module adopts a layered interval filling process: the bottom is filled with coarse-grained slurry to form a base layer, and fine-grained slurry is filled after the intervals are set to a height; and the quality of the filling body is monitored in real time using geological radar and non-destructive testing technology.

[0025] A method for graded filling of tailings in a mining area comprises the following steps:

[0026] Step 1: Tailings classification: Classify the entire tailings according to the 500-mesh, 400-mesh, and 300-mesh classification limits, calculate Vr, Qr, and Qa, determine the optimal classification particle size based on thickener torque analysis, and lay a sulfide adsorption layer at the bottom of the tailings collection pool;

[0027] Step 2, slurry preparation: measure the unconfined compressive strength R = P / A, determine the optimal ratio by the water bleeding rate B and the shrinkage rate δ, and stir evenly;

[0028] Step 3: Slurry transportation: Use Jinchuan formula to calculate the pipe transportation resistance i c , Durald formula estimates the critical flow velocity V l , ensure that the actual flow rate is greater than V l ;

[0029] Step 4: Filling: transport the slurry to the goaf, and obtain the ash-sand ratio (adjustment range 1:6-1:8), slurry concentration (65%-75%) and flow rate (50-150m3) in real time through online detection equipment. 3 / h), when the lime-sand ratio deviates from the set value by ±5%, the automated batching system automatically adjusts the amount of cementitious material added; when the concentration is lower than 65%, the concentration equipment is started to increase the slurry consistency;

[0030] Step 5: Monitoring and control: Real-time monitoring of pressure, flow, and wear data, and automatic control of pumping equipment speed and valve opening through PID algorithm.

[0031] Preferably, in step 1, the tailings particle size is distributed according to different areas of the goaf, and the thickener flow field is optimized by CFD simulation.

[0032] Preferably, in step 2, an artificial intelligence model is used to predict the optimal ratio, and automated equipment accurately mixes ingredients.

[0033] Preferably, in step 3, pipeline wear is monitored and life is predicted, wear-resistant materials and friction-reducing agents are used, and critical flow rate parameters are dynamically adjusted.

[0034] Preferably, in step 4, a layered interval filling process is adopted, combined with geological radar and non-destructive testing technology to monitor the quality of the filling body.

[0035] Advantages of the present invention:

[0036] Accurate tailings classification and optimized filling material gradation: The present invention uses a cyclone and a multi-layer vibrating screen combined with a grading device to accurately separate tailings of different particle sizes according to the characteristics of lead-zinc-silver and copper-tin-silver-zinc ore tailings. The tailings particle size can be precisely controlled by adjusting equipment parameters, providing rationally graded raw materials for filling slurry preparation and improving the density and stability of the filling body.

[0037] Targeted slurry preparation improves filling strength: Considering the impact of heavy metal ions in tailings on the hydration reaction of cementitious materials, the present invention optimizes the filling slurry ratio through extensive experiments, increases the amount of cementitious materials, and selects additives, such as special water reducers and flocculants, to improve slurry fluidity and fine tailings agglomeration. The prepared filling slurry has an unconfined uniaxial compressive strength higher than that of traditional processes, meeting the support strength requirements of mine goafs;

[0038] Efficient and stable transportation, reducing equipment wear and maintenance costs: The transportation module uses suitable pipe materials such as ceramic-lined composite steel pipes and high-performance pumping equipment, and real-time monitoring and precise control of parameters such as slurry flow rate, reducing pipe wear and equipment failure rates, extending pipe service life, reducing maintenance costs, ensuring stable and continuous slurry transportation, and improving filling operation efficiency;

[0039] Improve resource utilization, achieving a win-win situation for both environmental and economic benefits: During the tailings collection and pretreatment stages, and the backfilling process, tailings are efficiently utilized, reducing pollution. For example, in a lead-zinc-silver mine, this invention reduced tailings discharge, recovered nonferrous metals, and lowered backfilling costs, increasing the mine's economic benefits and achieving both environmental and economic benefits. Description of the drawings:

[0040] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0041] Figure 1 This is a system structure diagram of the present invention;

[0042] Figure 2 This is a workflow diagram of the grading module of the present invention;

[0043] Figure 3 This is a schematic diagram of the slurry preparation and transportation principle of the present invention;

[0044] Figure 4 This is a schematic diagram of the layered filling method of the present invention;

[0045] Figure 5 This is the intelligent monitoring system architecture of an optional embodiment of the present invention. Specific implementation method:

[0046] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0047] like Figure 1-Figure 5 As shown, a mining tailings classification filling system includes:

[0048] The system consists of a tailings collection device, a grading module, a filling slurry preparation module, a conveying module, and a filling module. It is designed specifically for the heavy metal content and complex particle size characteristics of tailings from lead-zinc-silver and copper-tin-silver-zinc mines. The tailings collection device features a heavy metal adsorption layer at the bottom of the collection pool, using a sulfide adsorbent to effectively absorb heavy metal ions such as lead, zinc, and copper from the tailings. The cyclone in the grading module is constructed from corrosion-resistant materials to prevent erosion by chemicals in the tailings.

[0049] After settling in the collection pond, the tailings are conveyed to the grading module through the bottom sand discharge port. The magnetic separation equipment above the belt conveyor not only removes ferromagnetic materials but also uses eddy current separation equipment to separate non-ferrous metal particles that may be present in the tailings, thereby improving resource recovery.

[0050] When the cyclone is working, the density of the tailings of lead-zinc-silver ore, copper-tin-silver-zinc ore is relatively large (generally 2.7-4.5g / cm 3 ) characteristics, through the formula:

[0051] F c =mω 2 r

[0052] F c The centrifugal force is calculated by adjusting the feed pressure and cyclone parameters to achieve efficient separation of coarse tailings.

[0053] For example, for a density of 3.5 g / cm 3, Tailings particles with a particle size of 0.5mm rotate at an angular velocity of 100rad / s in the cyclone. At a distance of 0.1m from the center of rotation, the centrifugal force is:

[0054]

[0055] The vibrating screen uses the high-frequency vibration generated by the vibrating motor, according to the formula:

[0056]

[0057] f is the vibration frequency, and T is the vibration period. Adjusting the vibration frequency and amplitude allows for precise grading of tailings of varying particle sizes. For lead-zinc-silver, and copper-tin-silver-zinc tailings, the vibration frequency is generally set at 15-25Hz. Tests have shown that this frequency range can achieve a screening efficiency of over 90% for tailings below 500 mesh, while also preventing excessive wear on the screen and ensuring effective grading.

[0058] When determining the slurry ratio in the laboratory, for lead-zinc-silver ore and copper-tin-silver-zinc ore, the effect of heavy metals in tailings on the hydration reaction of the cementitious material was considered, and the amount of cementitious material was adjusted through a large number of tests. In the unconfined uniaxial compressive strength test, the specimen size was 50mm×50mm×50mm. When the failure load P=10000N, the compressive strength was:

[0059]

[0060] In the calculation of water bleeding rate, the water mass Vw = 20g, the water consumption W = 200g, the total mass of slurry + container G = 1000g (assuming the container mass is 200g), the slurry mass Gw = G-container mass = 800g, then the water bleeding rate is:

[0061]

[0062] When calculating the shrinkage rate, the raw material slurry volume V2 = 500cm 3 , after sedimentation, volume V1=450cm 3 , shrinkage rate:

[0063]

[0064] Using artificial intelligence algorithms to establish a mathematical model of slurry ratio and performance indicators, the chemical composition (such as lead content, zinc content, etc.) and particle size distribution data of lead-zinc-silver ore and copper-tin-silver-zinc ore tailings are input, and the neural network algorithm is used to continuously optimize the ratio to achieve precise control;

[0065] The artificial intelligence algorithm uses a BP neural network model. The input layer includes six parameters, including the Pb content (%), Zn content (%), and the proportion of -500 mesh particles (%) in the tailings. The output layer is the optimal addition amount of the cementitious material. The training data comes from 200 sets of lead-zinc-silver mine tailings ratio test data sets. The specific examples are as follows:

[0066] Input parameters: Pb content 1.8%, Zn content 2.3%, Cu content 0.9%, -500 mesh particles 72%, -300 mesh particles 88%, tailings density 3.4g / cm 3 ;

[0067] Output result: The amount of cementitious material added is 16.5% (as a percentage of the tailings mass);

[0068] The Jinchuan formula is used to calculate the pipeline transmission resistance. The Jinchuan formula is:

[0069]

[0070] Where λ is the friction coefficient, which is related to the roughness of the inner wall of the pipe, the Reynolds number, etc.

[0071] is the inner diameter of the pipeline, v is the slurry flow rate, g is the acceleration of gravity, ρ is the slurry density, H is the vertical height difference of the pipeline, τ0 is the yield stress of the slurry, L is the length of the pipeline, and Q is the slurry flow rate. For the transportation of lead-zinc-silver ore, copper-tin-silver-zinc ore filling slurry;

[0072] Assuming that the inner diameter of the pipeline d = 0.2m, the slurry flow rate v = 2m / s, the slurry density ρ = 1800kg / m3, the vertical height difference of the pipeline H = 50m, the friction resistance coefficient λ = 0.02, the yield stress τ0 = 10Pa, the pipeline length L = 1000m, and the slurry flow rate Q = 0.1m3 / s, the pipeline transportation resistance

[0073]

[0074] The critical velocity is estimated using the Durand formula, which is:

[0075]

[0076] Where C is a coefficient (usually 0.5-1.5, determined based on the slurry characteristics); Δρ is the density difference between the tailings particles and the slurry liquid phase; g is the acceleration due to gravity; d is the particle size; and ρ is the slurry density. For lead-zinc-silver and copper-tin-silver-zinc tailings, assuming particle size d = 0.3 mm, tailings particle density ρs = 3.2 g / cm3, slurry density ρ = 1.6 g / cm3, coefficient C = 1, and gravitational acceleration g = 9.8 m / s2, the critical velocity is:

[0077]

[0078] Sensors installed in the pipeline monitor parameters such as pressure and flow in real time, and the pressure and flow of the pumping equipment are adjusted according to the calculation results to ensure stable slurry transportation. At the same time, by adding special drag reducers (developed according to the characteristics of lead-zinc-silver ore and copper-tin-silver-zinc ore tailings), the pipeline transportation resistance is reduced. At the same time, based on the data of pipeline wear monitoring sensors, combined with the wear model to predict the pipeline life, the critical flow velocity parameter V is dynamically optimized. l The calculated value of , ensures that the actual flow rate is always higher than the adjusted critical flow rate.

[0079] Filling is done in layers and intervals, with coarse-grained slurry used in the bottom layer and fine-grained slurry used in the upper layer. Utilizing 3D laser scanning technology to monitor the shape and height of the filling in real time, the filling strategy is adjusted based on the monitoring data to ensure dense filling in the goaf and effectively control ground pressure.

[0080] In actual application:

[0081] Tailings classification principle: The cyclone uses centrifugal force to classify tailings. Particles of lead-zinc-silver, copper-tin-silver-zinc ores with different densities and particle sizes follow different motion paths under the action of centrifugal force, resulting in separation. The vibrating screen uses vibration to force tailings particles through the screen according to particle size, completing fine classification to meet different filling requirements.

[0082] Filling slurry preparation principle: Based on the characteristics of tailings from lead-zinc-silver and copper-tin-silver-zinc mines, tailings, cementitious materials, additives, and water are rationally mixed. The cementitious materials hydrate to bind the tailing particles, while the additives improve the slurry's properties. Water adjusts the concentration and fluidity, resulting in a filling slurry that meets both strength and construction requirements.

[0083] Slurry conveying principle: Pumping equipment provides pressure to overcome pipeline resistance. The Jinchuan and Durand formulas are used to calculate relevant parameters and optimize the conveying process. Monitoring and adjustments ensure stable slurry flow in the pipeline, preventing sedimentation and blockage.

[0084] Filling principle: Layered filling, coarse-grained slurry forms the bottom support, and fine-grained slurry fills the gaps, improving the density and integrity of the filling body, effectively supporting the surrounding rock, ensuring mining safety, and realizing the resource utilization of tailings.

[0085] The specific method of graded filling of tailings in mining areas is as follows:

[0086] Tailings Collection and Pretreatment: For tailings generated from lead-zinc-silver and copper-tin-silver-zinc mining, large collection ponds are constructed near the tailings discharge outlets. The bottom of the collection pond is paved with an inclined wear-resistant liner with a slope of 5°-8°, allowing the tailings to naturally flow to the discharge outlet at the center of the pond, reducing manual cleanup. Corrosion-resistant deflectors are installed on the pond walls to guide the tailings flow and prevent accumulation in corners. At the entrance to the collection pond, multi-layered screens are installed to intercept large debris such as rock fragments and branches, preventing them from entering the subsequent classification system and potentially clogging or damaging equipment. Heavy metal ion monitoring sensors installed in the collection ponds monitor the concentration of heavy metal ions, such as lead, zinc, and copper, in the tailings in real time. If the concentration exceeds a set range, a chemical addition system is automatically activated to precipitate the heavy metal ions by adding precipitants such as sodium sulfide, reducing the impact of heavy metals in the tailings on subsequent processing and the environment. The sulfide precipitate, which has absorbed the heavy metals, is then dehydrated by filtration to form a filter cake. Cement is then added to solidify the cake and securely landfilled in an impermeable tailings pond.

[0087] Tailings classification stage

[0088] Initial classification: Multiple cyclones of varying sizes are used for initial classification. Given the high density and wide particle size distribution of tailings from lead-zinc-silver and copper-tin-silver-zinc ores, large-diameter cyclones (e.g., 500mm-800mm) are selected to handle the coarse-particle fraction, while small-diameter cyclones (e.g., 150mm-300mm) handle the fine-particle fraction. Initial separation of tailings of varying particle sizes is achieved by adjusting the cyclone's feed pressure (generally controlled between 0.1-0.3MPa), feed flow rate (determined based on tailings production and classification requirements, e.g., 100-300 cubic meters per hour), and the diameters of the underflow and overflow outlets. For example, for lead-zinc-silver tailings with a density of 3.8g / cm3, when the feed pressure is 0.2MPa, the feed flow rate is 200 cubic meters / hour, the bottom flow port diameter of the large-diameter cyclone is 50mm, and the overflow port diameter is 100mm, the coarse-grained tailings with a particle size greater than 0.2mm can be effectively discharged from the bottom flow port, while the fine-grained tailings with a particle size less than 0.2mm and some water flow out from the overflow port.

[0089] Fine classification: The tailings overflowing from the cyclone enter a multi-layer vibrating screen for fine classification. The vibrating screening uses a multi-layer structure with screens of different mesh sizes, such as a 300-mesh screen on the upper layer, a 400-mesh screen in the middle layer, and a 500-mesh screen in the lower layer. By adjusting the frequency (15-25Hz) and amplitude (3-8mm) of the vibration motor, the tailings can be fully jumped and rolled on the screen surface. Tailings with a particle size of less than 300 mesh pass through the upper screen and enter the middle screen for further screening; tailings with a particle size of less than 400 mesh pass through the middle screen and enter the lower screen; finally, fine tailings with a particle size of less than 500 mesh pass through the lower screen, achieving precise classification. After classification, tailings of different particle sizes are transported to the corresponding storage silos via chutes or belt conveyors.

[0090] Filling slurry preparation stage

[0091] Determining the mix ratio: In the laboratory, extensive filling slurry mix ratio tests were conducted based on the geological conditions of the lead-zinc-silver and copper-tin-silver-zinc mine goafs, the surrounding rock stability requirements, and the tailings properties. Considering the potential inhibitory effect of heavy metal ions in the tailings on the hydration reaction of the cementitious material, the amount of cementitious material (such as cement) was appropriately increased. For example, for ordinary tailings filling, the lime-sand ratio may be 1:8-1:10; for lead-zinc-silver and copper-tin-silver-zinc mine tailings, the lime-sand ratio is adjusted to 1:6-1:8. At the same time, appropriate additives are added, such as polycarboxylate-based water reducers (0.5%-1.5%) to improve the fluidity of the slurry and flocculants (0.1%-0.3%) to enhance the agglomeration of fine tailings and improve sedimentation efficiency. The optimal mix ratio was determined by testing the unconfined uniaxial compressive strength, water bleeding rate, and sedimentation rate of slurries with different mix ratios.

[0092] Preparation Process: The tailings, cementitious materials, additives, and water are accurately measured in the set ratio using automated metering equipment (such as high-precision electronic scales and flow meters) and then fed sequentially into a twin-shaft forced mixer. The mixer stirs at a speed of 30-60 rpm for 3-5 minutes to thoroughly mix the various ingredients and form a filling slurry with good fluidity and stability. During the mixing process, temperature and pressure sensors installed in the mixer monitor the slurry temperature and mixing pressure in real time to ensure normal mixing. If the temperature is too high or the pressure is abnormal, an automatic alarm is issued and the mixing parameters are adjusted, such as reducing the mixing speed and increasing the cooling water flow.

[0093] Slurry conveying stage

[0094] Pipeline laying and selection: The pipeline route should be rationally planned based on the layout of the mine's underground tunnels and the location of the goaf. In the horizontal tunnel section, ceramic-lined composite steel pipes are preferred. They have good wear resistance and can effectively resist the erosion and wear of lead-zinc-silver ore and copper-tin-silver-zinc ore tailings. In the vertical shaft section, high-strength seamless steel pipes are used, and pipeline fixing brackets are installed to ensure the stability of the pipeline under gravity. The pipeline connection adopts a combination of welding and flange connection to ensure the sealing and strength of the connection. Removable wear-resistant bushings are installed on the elbows, tees and other easily worn parts of the pipeline to facilitate regular replacement.

[0095] Delivery parameter control: A piston concrete pump is used as the pumping equipment. According to the delivery distance, pipeline length and height difference, the pumping pressure (generally 1-5MPa) and pumping flow rate (determined according to the filling slurry production and the filling speed requirements of the goaf, such as 50-150 cubic meters per hour) are adjusted to ensure the stable flow of the slurry in the pipeline. The pressure sensor, flow sensor and density sensor installed on the pipeline are used to monitor the pressure, flow and density changes of the slurry in real time. When the pressure suddenly increases or the flow rate drops abnormally, it may be a signal of pipeline blockage. Stop pumping immediately and clear the pipeline through backwashing equipment or manual cleaning. At the same time, according to the change of slurry density, adjust the proportion of the filling slurry in time to ensure that the quality of the delivered slurry meets the requirements.

[0096] Pipeline maintenance and monitoring: During the transportation process, ultrasonic thickness gauges are regularly used to check pipeline wall thickness, particularly in areas prone to wear. Pipeline leak monitoring sensors are also installed to provide real-time monitoring for leaks. Once a leak is detected, emergency valves are immediately activated to prevent slurry leaks from causing environmental pollution and wasting resources. By combining pipeline wear models with actual operating data, pipeline service life is predicted, and the necessary materials and equipment for pipeline replacement are prepared in advance to ensure the continuity and stability of the transportation system.

[0097] Filling stage

[0098] Layered interval filling: In underground goafs, a layered interval filling process is used. First, the coarse-grained slurry is transported to the bottom of the goaf through the filling nozzle to form the bottom support structure. The thickness of each filling layer is determined according to the height of the goaf, geological conditions and the properties of the filling slurry, and is generally 1-3 meters. After the bottom layer of coarse-grained slurry is filled, wait 1-2 days for it to initially settle and solidify to form a stable foundation. Then, the upper layer of fine-grained slurry is filled. During the filling process, a three-dimensional laser scanner installed near the filling nozzle is used to monitor the shape and height changes of the filling body in real time to ensure uniform filling and avoid voids or insufficient filling.

[0099] Backfill quality monitoring and control: During the filling process, filler slurry samples are regularly collected from the filling pipe mouth, and on-site slump, density and other indicators are tested to ensure that the slurry performance meets the design requirements. At the same time, pressure sensors and displacement sensors are embedded in different locations in the goaf to monitor in real time the pressure of the filling body on the surrounding rock and the displacement changes of the surrounding rock. According to the monitoring data, the filling speed, slurry ratio and other parameters are adjusted in a timely manner to ensure that the filling body can effectively support the surrounding rock and prevent the surrounding rock from deforming too much and causing safety accidents. After the filling is completed, the strength and integrity of the filling body are tested by coring through drilling. If quality problems are found in the filling body, remedial measures are taken in a timely manner, such as secondary filling or reinforcement.

[0100] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A mining tailings classification filling system, characterized in that: include: Tailings classification module, filling slurry preparation module, slurry delivery module, filling module and intelligent monitoring and control module; The tailings classification module consists of a cyclone and a multi-layer vibrating screen, and is used to classify the whole tailings according to particle size. The tailings classification module classifies the whole tailings according to three classification limits: 500 mesh, 400 mesh, and 300 mesh. The classification scheme is determined based on material balance analysis, and the daily average filling volume Vr of the goaf, the daily slurry filling volume Qr, and the annual average filling slurry required Qa are calculated according to the following formula: Q r =V r K1K2 Q a =Q r T Where Vk is the daily output of ore, Z is the adoption ratio, γ k is the weight of ore, K1 is the loss coefficient (value range is 0.95-1.05), K2 is the settlement ratio (value range is 1.1-1.3), and T is the filling working day; Determine the optimal classification particle size by combining thickener torque analysis; The filling slurry preparation module includes a mixer and an automated batching system, which is used to determine the slurry ratio based on experiments. The unconfined uniaxial compressive strength R = P / A is used to measure the filling body strength, where P is the maximum longitudinal load when the test block fails and A is the cross-sectional area perpendicular to the loading direction. And through the water bleeding rate: Where B is the water bleeding rate, Vw is the total mass of water bleeding, W is the water consumption of slurry, G is the total mass of slurry + container, and Gw is the mass of slurry; Shrinkage rate: δ is the slurry shrinkage rate, V1 is the reduced volume after the sinking is completed, and V2 is the total volume of the raw material slurry. Based on the simple volume ratio relationship, without considering the influence of the external environment on the sinking, the sinking rate is determined to determine the optimal slurry ratio; The slurry transport module uses pipelines to transport slurry, and the pipeline transport resistance i is calculated by the Jinchuan formula. c , use the Durald formula to estimate the critical velocity V l , ensure that the actual flow rate is greater than V l , The filling module transports the slurry to the underground goaf for filling; The intelligent monitoring and control module includes a pressure sensor, a flow sensor, a wear monitoring sensor and a PLC controller. The PLC controller is based on a PID algorithm and adjusts the pumping equipment speed and valve opening according to the real-time data of the pressure sensor, the flow sensor and the wear monitoring sensor.

2. A mining tailings grading filling system according to claim 1, characterized in that: In the tailings grading module, tailings particle size is allocated based on the force requirements of different areas of the goaf: fine tailings with a particle size of less than 500 mesh are used near the roof, and coarse tailings with a particle size of greater than 300 mesh are used at the bottom. CFD simulation of the flow field inside the thickener is used to optimize grading efficiency and dewatering effects.

3. A mining tailings classification filling system according to claim 2, characterized in that: The filling slurry preparation module introduces an artificial intelligence algorithm, and the artificial intelligence algorithm is a BP neural network model, and the training data comes from a historical proportion test data set.

4. A mining tailings classification filling system according to claim 3, characterized in that: The slurry conveying module is equipped with a pipeline wear monitoring sensor, which is combined with a wear model to predict service life; wear-resistant pipeline materials and anti-friction agents are used to reduce wear, and critical flow rate parameters are dynamically adjusted.

5. The mining tailings classification filling system according to claim 4, characterized in that: The filling module adopts a layered interval filling process: the bottom is filled with coarse-grained slurry to form a base layer, and fine-grained slurry is filled after the intervals are set to a height; geological radar and non-destructive testing technology are used to monitor the quality of the filling body in real time.

6. A method for graded filling of tailings in mining areas, characterized in that: The following steps are involved: Step 1: Tailings classification: Classify the entire tailings according to the 500-mesh, 400-mesh, and 300-mesh classification limits, calculate Vr, Qr, and Qa, determine the optimal classification particle size based on thickener torque analysis, and lay a sulfide adsorption layer at the bottom of the tailings collection pool; Step 2, slurry preparation: measure the unconfined compressive strength R = P / A, determine the optimal ratio by the water bleeding rate B and the shrinkage rate δ, and stir evenly; Step 3: Slurry transportation: Use Jinchuan formula to calculate the pipe transportation resistance i c , Durald formula estimates the critical flow velocity V l , ensure that the actual flow rate is greater than V l ; Step 4: Filling: transport the slurry to the goaf, and obtain the ash-sand ratio (adjustment range 1:6-1:8), slurry concentration (65%-75%) and flow rate (50-150m3) in real time through online detection equipment. 3 / h), when the lime-sand ratio deviates from the set value by ±5%, the automated batching system automatically adjusts the amount of cementitious material added; when the concentration is lower than 65%, the concentration equipment is started to increase the slurry consistency; Step 5: Monitoring and control: Real-time monitoring of pressure, flow, and wear data, and automatic control of pumping equipment speed and valve opening through PID algorithm.

7. The tailings classification filling method according to claim 6, characterized in that: In step 1, the tailings particle size is distributed according to different areas of the goaf, and the thickener flow field is optimized through CFD simulation.

8. The tailings classification filling method according to claim 7, characterized in that: In step 2, an artificial intelligence model is used to predict the optimal ratio, and automated equipment accurately mixes ingredients.

9. The tailings classification filling method according to claim 8, characterized in that: In step 3, pipeline wear is monitored and life is predicted, wear-resistant materials and friction-reducing agents are used, and critical flow rate parameters are dynamically adjusted.

10. The tailings classification filling method according to claim 9, characterized in that: In step 4, a layered interval filling process is adopted, combined with geological radar and non-destructive testing technology to monitor the quality of the filling body.

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