Low-cost environment-friendly flocculation thickening optimization method for filling graded fine tailings

Abstract

The invention discloses a low-cost environment-friendly flocculation thickening optimization method for filling graded fine tailings, and belongs to the technical field of energy conservation, environment protection and green mining. The method comprises the following implementation steps: taking the concentration of a flocculating agent solution, the concentration of fine tailing slurry and the unit consumption of a flocculating agent as influence factors, and carrying out a fine tailing flocculating settling orthogonal test to obtain a tailing settling rate and an underflow limit concentration; performing polynomial fitting on orthogonal test data to obtain a relation function between the fine tailing flocculation capacity, the underflow limit concentration, the supernatant turbidity, the flocculation cost and the return water utilization rate and the influence factors, and taking the condition that the underflow limit concentration meets the requirements of preparing high-concentration slurry and the condition that the supernatant turbidity meets the requirements of selecting plant return water utilization as constraint conditions; and establishing a fine tailing flocculation thickening parameter multi-objective optimization model for flocculation parameter optimization. By means of the method, flocculation optimization parameters with the lowest grading fine tailing flocculation cost and the highest return water utilization rate can be obtained, and technical support is provided for improving the economic benefits and environmental protection benefits of fine tailing filling mining.

Description

Technical Field

[0001] The invention relates to the field of comprehensive utilization of bulk tailings solid waste and green mining technology for energy conservation and emission reduction, and in particular to a low-cost and environmentally friendly flocculation sedimentation and thickening optimization method for using fine tailings for filling mining. Background Art

[0002] my country's iron ore grade is low, production capacity is high, and tailings discharge is large, accounting for about 40% of the total tailings discharge of the entire mine. At present, my country's iron tailings reserves are about 5 billion tons, and are increasing at a rate of 500 million tons per year. Usually, tailings are discharged into tailings ponds, which not only occupy a large amount of land, but also pose major safety hazards. As the capacity of existing tailings ponds decreases year by year and tends to be full, new tailings ponds face site selection and huge investment problems. Using tailings for filling mining is one of the best ways to solve tailings discharge. Tailings filling mining can control the ground pressure of the mine, prevent and control geological disasters, reduce the loss and depletion of ore, and improve the scale and high-value utilization of bulk solid waste resources. Therefore, tailings filling mining has been widely used in precious metal mines such as non-ferrous gold, and in the past 10 years, iron ore tailings cementation filling mining has also developed rapidly.

[0003] Iron ore has low metal value, large emissions, high filling mining costs and poor economic benefits. With the development of mineral processing equipment and technological progress, the tailings from mineral processing have become finer and finer. In recent years, in order to solve the problem of excess tailings discharge from mineral processing, cyclone classification technology has been used to use coarse tailings for construction fine sand, and fine tailings filling mining has become the only way to create a waste-free green and environmentally friendly mine. Therefore, the cost of fine tailings concentration and environmental protection have become key issues in filling mining.

[0004] Fine tailings flocculation, sedimentation and thickening technology is one of the core links of backfill mining. Fine tailings slurry concentration, flocculant unit consumption and flocculant solution concentration are important factors affecting the tailings flocculation effect and cost. In actual on-site applications, there are large differences in the particle size distribution and chemical composition of tailings from different types of mines, and there are great differences in the flocculation and sedimentation effects of tailings with different particle size gradations. In particular, fine tailings have many ultrafine particles and a slow sedimentation rate, which brings technical and economic problems to the use of fine tailings to prepare high-concentration backfill slurry. A large number of studies have been carried out on tailings flocculation and thickening technology at home and abroad, and the research can be roughly divided into the following three types.

[0005] 1. Traditional tailings flocculation and sedimentation method

[0006] For actual mine filling tailings, the tailings flocculation test follows the following three steps (Shi Xiuzhi et al. 2010, Tang Zian et al. 2015, Zhang Meidao et al. 2020, Wei Fuhai et al. 2021, Meng Aoshu et al. 2024):

[0007] (1) Flocculant selection test. N flocculants on the current market were selected through experience and prepared into a flocculant solution with a mass concentration of 0.1%; then, the mortar concentration and flocculant unit consumption were fixed, and tailings flocculation and sedimentation tests of N flocculants were carried out; finally, the flocculant was selected according to the tailings flocculation and sedimentation rate.

[0008] (2) Flocculation tailings slurry concentration test. The flocculant was determined through the above test to carry out the flocculation tailings slurry concentration test. First, a flocculant solvent with a mass concentration of 0.1% was prepared, and then the flocculant unit consumption was determined, and flocculation sedimentation tests of M mortar concentrations were carried out; finally, the tailings slurry concentration was determined according to the tailings sedimentation rate.

[0009] (3) Flocculant unit consumption sedimentation test. According to the selected flocculant preparation solution and the determined tailings slurry concentration, different flocculant unit consumption tests are carried out; the flocculant unit consumption is determined according to the sedimentation rate.

[0010] 2. Optimization method of tailings flocculation and sedimentation

[0011] The traditional flocculation sedimentation method has the following problems: it does not consider the concentration of the flocculant solution; it does not consider the interaction between the mortar concentration and the unit consumption of flocculants on the flocculation effect of tailings; and it does not optimize the flocculation parameters. In response to the above problems, further research on the interaction of the tailings flocculation sedimentation process and the experimental method for optimizing the flocculation parameters was carried out (Zhang Qinli et al. 2013, Wang Xinmin et al. 2014, Wang Xinmin et al. 2016, Wen Zhenjiang et al. 2020, Zheng Bokun. 2022, Shi Yuzhou et al. 2023).

[0012] The main characteristics of the tailings flocculation and sedimentation optimization method are: after selecting the flocculant, firstly, the flocculant solution concentration, tailings slurry concentration and flocculant unit consumption are taken as influencing factors, and the tailings sedimentation rate and underflow concentration are taken as evaluation indicators, and an orthogonal test or an interactive test of the response surface method for tailings sedimentation and flocculation effect is carried out; then, the tailings flocculation parameters are comprehensively decided based on the tailings sedimentation rate, combined with the underflow concentration or the overflow water clarity.

[0013] 3. Combined filling of mine tailings flocculation method

[0014] The tailings flocculation and sedimentation optimization method considers the interaction of flocculant solution concentration and influencing factors on the tailings flocculation effect, but there are problems: the tailings sedimentation rate is still used as an indicator to evaluate the flocculation effect, and the underflow concentration and overflow water clarity are used as reference indicators. The flocculation and sedimentation parameters are not optimized in combination with the actual mine production capacity, thickening equipment, and the amount of filling tailings; although the relationship function between the sedimentation rate and the underflow concentration and the thickening factor is established, it has not been applied to the optimization of tailings flocculation parameters.

[0015] In recent years, research on flocculation sedimentation test methods combined with actual filling mines has emerged (Gao Zhiyong et al. 2017, Shi Caixing et al. 2021, Wu Pengjie et al. 2022, Li Yongming et al. 2024).

[0016] The tailings flocculation and thickening method is combined with the production capacity of the filling mine, the thickening equipment and the demand for filling tailings production capacity. The main features are: the tailings settling rate is to meet the continuous sand discharge requirements of the mine sand bin; the tailings flocculation capacity analysis is carried out in combination with the mine flocculation and thickening equipment (sand bin area). The solid flux is used as the flocculation evaluation parameter, and the settling rate and tailings production capacity are evaluated together. This tailings flocculation test method combined with the actual mine filling system has test results and optimization parameters that are closer to the actual mine than the early tests, and can provide technical support for mine tailings flocculation filling.

[0017] The invention patent CN114212911B discloses a "tailings separation method", the main feature of which is that the fine tailings slurry is thickened twice, and the underflow coarse tailings slurry and overflow ultra-fine slurry are pressed into filter cakes for filling mining. Although this provides a way to thicken fine tailings, the tailings thickening process is complicated and the filter pressing cost is high, thereby reducing the economic and environmental benefits of fine tailings filling mining.

[0018] The invention patent CN115615885B discloses "an intelligent analysis method for tailings flocculation and sedimentation". During the flocculation and thickening process of fine tailings, an intelligent auxiliary analysis system for the sedimentation interface is provided, thereby improving the automatic recognition capability of the fine tailings flocculation and sedimentation interface.

[0019] The invention CN115639108A ​​discloses a method for testing the flocculation network formation time of fine tailings cemented filling slurry. The main feature of the method is that a dynamic rheometer is used to perform a fixed-frequency strain amplitude test and a shear test on the fine tailings cemented filling slurry to determine the flocculation network formation time of the fine tailings cemented filling slurry, which helps to deeply understand the fine tailings flocculation and sedimentation process and the fluidity of the fine tailings cemented filling slurry, and provides a more accurate testing technology for optimizing the fine tailings mortar ratio.

[0020] The cost of fine tailings flocculation and thickening and the utilization of backwater are the core technologies of fine tailings filling. At present, the tailings flocculation and thickening technology has comprehensively considered the interaction and optimization design of flocculant solution, flocculant dosage and slurry concentration, but the evaluation indicators and parameters of tailings flocculation are still limited to sedimentation rate or underflow concentration. Therefore, the optimization of tailings flocculation and sedimentation parameters all consider the flocculation cost, which involves the economic benefits of filling mining. Therefore, the economic and environmental benefits of tailings flocculation filling mining are the most important factors affecting whether tailings filling mining can be promoted and applied. Due to the different particle size distribution and chemical composition of tailings in different types of mines, and the different thickening equipment and production capacity of mines, the main problems in the current research on tailings flocculation and filling test methods are as follows:

[0021] (1) The problem of optimizing the target of tailings flocculation and density. At present, all tailings flocculation and sedimentation test methods use tailings sedimentation rate or solid flux as the optimization target. It is true that sedimentation rate and solid flux characterize the production capacity of tailings flocculation and density. But it is not the case that the faster the tailings settle and the higher the production capacity, the better. Therefore, the production capacity of tailings for filling mines only needs to meet the demand for tailings for filling. During the tailings flocculation process, when the tailings in the sand bin flocculate too quickly, the amount of flocculated tailings in the sand bin is greater than the amount of tailings for filling, resulting in the accumulation and compaction of tailings in the sand bin, which makes it difficult to release the tailings. It can be seen that the faster the tailings flocculation and the higher the production capacity, not only the flocculation cost increases, but it is also not conducive to tailings slurrying. Therefore, it is obviously unreasonable to use sedimentation rate or solid flux as the optimization target. Under the premise of meeting the tailings consumption for mine filling, the tailings flocculation cost is the lowest and the return water utilization rate is the highest, which can improve the economic and environmental benefits of filling mining. Therefore, the tailings flocculation cost and return water utilization rate should be the optimization goals of tailings flocculation.

[0022] (2) The problem of tailings flocculation and density constraints. At present, most studies take the range of variation of flocculation factor parameters as constraints (Li Yongming et al. 2024). In fact, flocculation tailings filling mining is based on the pursuit of maximizing economic and environmental benefits. First, the flocculated tailings can meet the tailings filling amount of the mine (involving the sand bin area and sedimentation rate). Secondly, the bottom flow limit concentration should meet the high-concentration filling requirements of the mine, and the clarity of the supernatant can meet the tailings return water utilization standards. Therefore, the tailings flocculation capacity, bottom flow concentration and supernatant turbidity should be the constraints for tailings flocculation optimization. All current tailings flocculation experimental studies have not taken into account the above three constraints.

[0023] (3) The problem of combining tailings flocculation and thickening with filling mines. The tailings flocculation test needs to be combined with the actual mine thickening equipment, production capacity and tailings characteristics, so that the experimental research results obtained can be actually applied in the mine. However, most of the tailings flocculation tests are not closely combined with the actual mines, and the flocculation parameters obtained cannot be applied in the actual mines. Summary of the invention

[0024] In view of the problems of slow settling speed of fine tailings, turbid supernatant, low tailings production capacity and high flocculation cost, the present invention discloses a low-cost environmentally friendly flocculation and thickening optimization method for filling graded fine tailings. By establishing a fine tailings flocculation optimization model for parameter optimization, the graded fine tailings flocculation optimization parameters with the lowest flocculation cost and the highest return water utilization rate are obtained. The specific steps are as follows:

[0025] In response to the problems existing in the current tailings flocculation and sedimentation tests, the technical features disclosed in the patent of this invention are: combining the characteristics of graded fine tailings in actual filling mines, as well as the thickening equipment and mineral processing technology of mines, taking the fine tailings flocculation cost and return water utilization rate as optimization targets, taking the amount of mine filling tailings, the demand for preparing high-concentration slurry and the return water utilization quality requirements as constraints, selecting three factors: flocculant solvent concentration, fine tailings concentration and flocculant unit consumption, carrying out orthogonal experiments, establishing a multi-objective optimization model for fine tailings flocculation and thickening and flocculation parameter optimization, and providing a flocculation parameter optimization method for the application of graded fine tailings in filling mining. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 is a tailings particle size distribution curve of an embodiment of the present invention;

[0027] Figure 2 1 and 2 are the regression curves of the flocculation and sedimentation of the fine tailings slurry according to the implementation cases of the present invention. FIG. (a) is the L1 to L3 test scheme, FIG. (b) is the L4 to L6 test scheme, and FIG. (c) is the L7 to L9 test scheme. DETAILED DESCRIPTION

[0028] In order to more clearly illustrate the key technologies and implementation steps involved in the low-cost environmentally friendly flocculation and thickening optimization method for filling and grading fine tailings disclosed in the present invention, the following will be described in detail with reference to the accompanying drawings and specific implementation cases. The implementation plan specifically includes the following 6 steps:

[0029] Step 1: Investigation and analysis of backfill mining in an iron ore mine

[0030] (1) The production scale of a certain iron ore filling mining is 2.6 million tons / year. The staged subsequent filling mining method is adopted. The dry tailings required for the mine filling mining is 76.05m 3 / h. Filling system capacity 100m 3 / h, using a vertical sand bin with a diameter of 11m to flocculate tailings to prepare high-concentration slurry, the bottom flow slurry mass concentration is required to be 68%. Sand bin flocculation sedimentation area A = 94.99m 2 The sand discharge design is Q = 80m 3 / h, when the settling velocity of fine tailings v≥0.842m / h, the purpose of dynamic settling of tailings in sand bin and continuous sand filling can be achieved.

[0031] (2) The mine uses a hydrocyclone to implement graded fine tailings filling mining, and the graded fine tailings are determined to be -140 mesh in size. The results of the analysis using a laser particle size analyzer are: the tailings particle size range is 0.28 to 181.6 μm, the content of -75 μm (-200 mesh) fine particles in the tailings is 88.1%, and the content of -38 μm (-400 mesh) ultrafine particles is 53.15%. The tailings particle size distribution curve is shown in Figure 1 , the particle size distribution characteristic values ​​are shown in Table 1.

[0032] (3) For the six flocculants in Table 2, a fine tailings flocculant selection test was carried out and 1 was selected # Noel flocculant was used as the flocculant for the fine tailings slurry flocculation and sedimentation test of the mine, and the price of the flocculant was 8 yuan / kg.

[0033] Table 1 Characteristic values ​​of particle size distribution of fine tailings of an iron ore - 140 mesh

[0034]

[0035] Table 2 Types and prices of polyacrylamide flocculants

[0036]

[0037] Step 2: Orthogonal design of fine tailing slurry flocculation and sedimentation test

[0038] (1) According to the Noel flocculant determined in step 1, the mass concentration of the flocculant solution x1, the mass concentration of the fine tailings mortar x2 and the unit consumption of flocculant per ton of dry sand x3 are selected as the factors affecting the flocculation and sedimentation of the fine tailings mortar;

[0039] (2) With the help of engineering experience, the range of parameters of factors affecting flocculation and sedimentation was determined, and an orthogonal experimental scheme for fine tailings flocculation and sedimentation was designed (see Tables 3 and 4).

[0040] Table 3 Factors and levels of orthogonal test for flocculation and sedimentation of fine tailings slurry in an iron ore

[0041]

[0042] Table 4 Orthogonal test scheme for flocculation and sedimentation of fine tailings slurry in an iron ore

[0043]

[0044] Step 3: Tailings flocculation sedimentation test and sedimentation rate calculation

[0045] (1) According to steps 1 and 2, an orthogonal test of tailings flocculation and sedimentation was carried out to obtain the experimental data of tailings sedimentation time and sedimentation height as well as the bottom flow limit concentration C wf and supernatant turbidity C wy (See Tables 5 and 6);

[0046] (2) Based on Tables 5 and 6, polynomial regression analysis was used to fit the tailings settling time and settling height data to obtain the settling regression function (see Table 7) and regression curve (see Figure 2 );

[0047] (3) The derivative of the fine tailings flocculation sedimentation regression function is obtained, and the function value at the initial time (t = 0) is calculated, thereby obtaining the flocculation tailings sedimentation rate (see Table 7).

[0048] Table 5 Results of flocculation and sedimentation test of fine tailings slurry of an iron ore

[0049]

[0050]

[0051] Table 6 Results of flocculation and sedimentation test of fine tailings slurry of an iron ore

[0052]

[0053]

[0054] Table 7 Regression function and sedimentation rate of fine tailing slurry flocculation

[0055]

[0056] Step 4: Cost analysis of fine tailings flocculation and sedimentation and derivation of return water utilization rate

[0057] (1) According to step 2, based on the unit consumption and cost of Nol flocculant in the orthogonal test scheme of fine tailings flocculation and sedimentation in Table 4, the fine tailings flocculation and sedimentation cost of each test scheme is calculated (see Table 8);

[0058] Table 8 Flocculation effect and flocculation cost of Noel flocculant flocculation fine tailings slurry sedimentation test

[0059]

[0060] (2) According to steps 1 to 3, the tailings flocculation return water utilization rate W is derived L The calculation formula is:

[0061] Order: The amount of fine tailings sand entering the sand bin is m j, m 3 , the mass concentration of the tailings entering is C wj (x2), %;

[0062] From this we can get: the amount of dry tailings entering the sand bin: m jg =m j C wj , m 3 (1)

[0063] Amount of water entering the sand bin: m js = m j (1-C wj ), m 3 (2)

[0064] Order: Sand bin bottom discharge volume m f , m 3 , the sand concentration is C wf (underflow concentration), %;

[0065] From this we can get: The amount of dry tailings released from the sand bin: m fg =m f C wf , m 3 (3)

[0066] Sand bin water discharge volume: m fs =m f (1-C wf ), m 3 (4)

[0067] The overflow water volume m at the top of the sand bin is obtained y :

[0068] m y =m js -m fs =m j (1-C wj )- m f (1-C wf ) (5)

[0069] According to equations (2) and (5), the tailings return water utilization rate W L :

[0070] W L =m y / m js =[m j (1-C wj )-m f (1-C wf )] / [m j (1-C wj )]

[0071] =[(m j -m f )-(m j C wj -m f C wf )] / (m j -m j C wj ) (6)

[0072] Where: W L —— utilization rate of tailings slurry return water, %;

[0073] m j ——The amount of tailings slurry entering the sand bin, m j =vA, A is the cross-sectional area of ​​the sand bin (94.99m 2 );

[0074] C wj ——The concentration of tailings slurry entering the sand bin is the influencing factor x2 value;

[0075] m f ——The amount of mortar released from the bottom of the sand bin and the amount of tailings filled in the mine is Q=76.05m 3 / h, then

[0076] m f =Q / C wf =76.05 / C wf ; C wf is the mass concentration of tailings discharged from the bottom of the sand bin, %.

[0077] (3) According to formula (6), the tailings return water utilization rate of each test scheme is calculated (see Table 8).

[0078] Step 5: Regression analysis of fine tailings flocculation and sedimentation data

[0079] According to step 4, the polynomial regression analysis method is used for fitting, thereby obtaining the regression function between the tailings settling rate, bottom flow limit concentration and supernatant turbidity and the influencing factors as follows:

[0080] (1) Sedimentation rate regression function

[0081] v = f1(x1, x2, x3) (1)

[0082] v1=56.193-462.27x1+1.093x2+5.113x3+12.96x1x2-10.366x1x3-0.218x2x3

[0083] (2) Underflow concentration regression function

[0084] C wf=f2(x1, x2, x3) (2)

[0085] C wf =25.467+90.667x1+0.873x2+2.4x3+2.4x1x2-8.057x1x3-0.079x2x3

[0086] (3) Supernatant turbidity regression function

[0087] C wy =f3(x1, x2, x3) (3)

[0088] C wy =25.016+769.43x1-5.112x2-5.899x3-5.314x1x2-17.314x1x3+0.432x2x3

[0089] (4) Tailings flocculation cost regression function

[0090] C T =f4(x1, x2, x3) (4)

[0091] C T =-0.229+1.429x1+0.021x2+0.781x3-0.114x1x2+0.686x1x3

[0092] (5) Regression function of mortar backwater utilization rate

[0093] W L =f5(x1, x2, x3) (5)

[0094] W L =-0.219+1.129x1+0.021x2+0.78x3-0.14x1x2+0.66x1x3

[0095] Where: x1——mass concentration of flocculant solution, %;

[0096] x2——mass concentration of tailings slurry, %;

[0097] x3——flocculant dosage, g / t.

[0098] Step 6: Establish and solve the optimization model of fine tailings flocculation and sedimentation

[0099] Taking tailings flocculation cost and return water utilization rate as optimization targets, and tailings settling rate, bottom flow limit concentration, and supernatant turbidity as constraints, a multi-objective optimization model for tailings flocculation density parameters was established.

[0100] (1) Optimization goal

[0101] Min[C T -W L ]=Min{f4(x1,x2,x3)-f5(x1,x2,x3)} (1)

[0102] (2) Constraints

[0103]

[0104] (3) Using MATLAB software, the tailings flocculation and density optimization model constructed by equations (1) and (2) was solved, and the optimization parameters for flocculation and density of graded fine tailings in a certain iron ore filling were obtained as follows: flocculant mass concentration x1 = 0.2%; tailings slurry mass concentration x2 = 20%; flocculant unit consumption x3 = 10 g / t. The cost of graded fine tailings slurry flocculation is 9.20 yuan / t dry sand.

[0105] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A low-cost, environmentally friendly flocculation and thickening optimization method for filling and grading fine tailings, characterized by: Here are the steps: 1). First, take samples of the backfill graded fine tailings for particle size distribution analysis, then select the appropriate flocculant and clarify the cost of the selected flocculant; 2). According to step 1), select the mass concentration of flocculant solution, the mass concentration of fine tailings slurry and the unit consumption of flocculant as influencing factors, determine the parameter range of the influencing factors with the help of experience, and design an orthogonal test scheme for fine tailings flocculation and sedimentation; 3). According to steps 1) and 2), an orthogonal test of flocculation and sedimentation of graded fine tailings slurry is carried out to obtain the experimental data of sedimentation time and sedimentation height, bottom flow limit concentration and supernatant turbidity; polynomial regression analysis is used to fit the flocculation and sedimentation test data to obtain the tailings sedimentation regression function; the regression function is derived, and the derivative function value at the initial time (t = 0) is calculated, thereby obtaining the fine tailings flocculation and sedimentation rate; 4). According to steps 1) and 2), based on the flocculation sedimentation cost and the unit consumption of flocculant in the orthogonal test scheme, calculate the tailings flocculation cost of each orthogonal test scheme; 5) According to steps 1), 2), and 3), derive the tailings flocculation sedimentation return water utilization rate W L The calculation formula is: W L =m y / m js =[(m j -m f )-(m j C wj -m f C wf )] / (m j -m j C wj ); Among them, W L is the tailings slurry return water rate, %; m y is the upper overflow water volume, m 3 ;m js is the water content of feed mortar, m 3 ;m j is the amount of mortar entering the sand bin, m j =vA, A is the sedimentation area of ​​the sand bin, v is the sedimentation rate of the tailings; C wj is the mass concentration of mortar entering the sand bin; m f is the amount of mortar released from the bottom of the sand bin, m 3 ;m fg =Q,m fg is the amount of dry tailings released from the sand bin, t; Q is the demand for tailings in the mine filling mining, m 3 / h; C wf is the concentration of tailings slurry discharged from the bottom of the sand bin, %; 6). Polynomial regression analysis was used to fit the relationship functions between the tailings slurry settling rate, bottom flow limit concentration, supernatant turbidity, flocculation cost, return water rate and influencing factors: settling rate regression function v = f1 (x1, x2, x3), bottom flow limit concentration regression function C wf =f2(x1, x2, x3), supernatant turbidity regression function C wy =f3(x1, x2, x3), tailings flocculation cost regression function C T =f4(x1, x2, x3), mortar backwater utilization rate regression function W L =f5(x1, x2, x3); where x1 represents the mass concentration of flocculant solution, %; x2 represents the mass concentration of mortar, %; x3 represents the amount of flocculant, g / t; 7). Taking the mortar flocculation cost and return water utilization rate as the optimization targets, and taking the mortar settling rate (to meet the requirements of continuous sand discharge in the sand bin), the bottom flow limit concentration (to meet the requirements of preparing high-concentration slurry) and the supernatant turbidity (to meet the quality requirements of return water utilization) as the constraints, the mortar flocculation optimization model is established as follows: Optimization goal: Min[C T -W L ]=Min{f4(x1,x2,x3)-f5(x1,x2,x3)} Constraints: v=f1(x1, x2, x3)≥0.842m / h (requirements for tailings usage in mine filling); C wf =f2(x1, x2, x3)≥68% (required for preparing high-concentration filling slurry); C wy =f3(x1, x2, x3)≤300ppm (quality requirement for utilization of concentrator return water); 0.1%≤x1≤0.2%, 10%≤x2≤20%, 10g / t≤x3≤20g / t. Among them, C T is the flocculation cost, W L is the mortar backwater utilization rate, v is the mortar sedimentation rate; C wf is the mortar underflow limit concentration, C wy is the turbidity of the supernatant; f1 is the mortar flocculation sedimentation function, f2 is the flocculation mortar bottom flow limit concentration function, f3 is the supernatant turbidity function, f4 is the tailings flocculation density cost function, and f5 is the mortar backwater utilization function; x1, x2, and x3 are the mass concentration of flocculant solvent, the mass concentration of mortar, and the unit consumption of flocculant in flocculation mortar, respectively. 8) The optimization model was solved using MATLAB mathematical software to obtain the optimal parameters for the flocculation, sedimentation and density of fine tailings.

2. The low-cost and environmentally friendly flocculation and thickening optimization method for classified fine tailings according to claim 1 is characterized in that: Before step 1), it also includes: Based on the analysis of the mine filling mining production scale, filling mining method and sand bin thickening equipment, the mine filling tailings dosage and underflow limit concentration are determined to meet the slurry settling rate for continuous filling operations.

3. The low-cost environmentally friendly flocculation optimization method for filling and grading fine tailings according to claim 1 is characterized in that: The particle size distribution analysis of the classified fine tailings in step 1) is as follows: the tailings particle size range is 0.28-181.6 μm, the content of -75 μm fine sand in the tailings is 88.1%, and the content of -38 μm ultrafine sand is 53.15%.

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