Oxidized concentrate yield control method based on different flotation raw ore acid consumption conditions

Abstract

The application discloses a kind of based on the yield control method of different flotation crude ore acid consumption under oxidized concentrate, by establishing the quantitative correlation model between flotation oxidized concentrate and flotation crude ore acid consumption, and the quantitative correlation model between oxidized concentrate yield and copper, cobalt comprehensive recovery rate, build the economic benefit evaluation model of combined selection and smelting economic benefit with ton ore economic benefit as objective function, and sulfuric acid market price, metal market price and other external dynamic factors are included in yield optimization decision system, realize the dynamic optimization control of flotation yield, can solve the technical problems that yield control strategy is difficult to dynamically adjust according to the change of crude ore nature and market fluctuation in prior art, cannot guarantee the whole process economic benefit optimal, reaches the purpose that selection and smelting system overall economic benefit maximization.

Description

Technical Field

[0001] This invention relates to the field of mineral processing technology, and specifically to a method for controlling the yield of oxidized concentrate under different acid consumption conditions of raw flotation ore. Background Technology

[0002] When developing and utilizing copper-cobalt oxide ores, the high calcium and magnesium impurities result in a huge consumption of sulfuric acid during direct acid leaching, significantly reducing economic benefits. This has long been a technical problem plaguing the beneficiation and smelting industry (Ba Hongfei, Hu Zhiqiang, Shi Yucheng, et al. Joint beneficiation and smelting test study of a high calcium and magnesium copper-cobalt oxide ore in the Democratic Republic of Congo [J]. China Mining, 2024, 33(z2):405-412). To address this problem, a joint beneficiation and smelting process is now commonly used to treat high acid-consuming copper-cobalt oxide ores. This involves first removing some acid-consuming gangue through flotation, and then feeding the oxide concentrate into the acid leaching system, thereby reducing acid consumption and improving efficiency (Wang Fuyuan, Yu Xun, Wang Ligang, et al. Joint beneficiation and smelting test study of a copper-cobalt oxide ore in the Democratic Republic of Congo [J]. Modern Mining, 2024, 40(7):154-157,162).

[0003] Currently, a large number of production practices have been carried out for the combined beneficiation and smelting process for high acid consumption copper-cobalt ore. Liu Jiapeng et al. (Liu Jiapeng, Xu Jingyuan, Feng Xingliang, et al. Combined beneficiation and smelting test study of a high calcium magnesium copper-cobalt ore in the Democratic Republic of Congo [J]. Nonferrous Metals (Mineral Processing), 2023(3):101-109) adopted a process of five consecutive oxidation ore roughing and no further fine beneficiation of the rough concentrate in a high calcium magnesium copper-cobalt ore in the Democratic Republic of Congo, and obtained a concentrate with a yield of 26.27%, copper grade of 6.45%, and copper recovery rate of 90.61%. Some scholars have gradually optimized the combined beneficiation and smelting process parameters, namely by adjusting the grinding fineness, the amount of frother and collector (Ou Wenjun, Xu Wei, Tian Yan, et al. Study on the adsorption behavior of a calcium-magnesium phosphate rock in Guizhou and its solid-liquid interface by WF-01 reverse flotation [J]. Nonferrous Metals (Mineral Processing), 2025(07):35-41.), and the pH value of the pulp to optimize the flotation index. There are also models based on operating data and foam images, which predict the flotation index by identifying the foam phenomenon and realize the control of the mineral flotation process (Wang Kang, Xu Hang, Li Xiaoli, et al. Research progress on data-driven flotation process modeling, control and optimization [J]. Journal of Beijing University of Technology, 2023, 49(4): 485-506).

[0004] However, most existing integrated beneficiation and metallurgical technologies focus on the technical indicators of the flotation process itself (such as concentrate grade and recovery rate), and rarely consider adjustment strategies from the perspective of the overall economic value of the beneficiation and metallurgical system. This results in the following technical shortcomings: (1) There is a lack of a quantitative correlation model between the properties of oxide concentrate and the properties of raw ore. Without establishing a quantitative functional relationship, it is impossible to provide accurate data support for yield control.

[0005] (2) Lack of a yield control system based on economic benefits. At present, process strategies are mostly adjusted based on flotation indicators (grade, recovery rate), without incorporating sulfuric acid and metal value factors into the yield control decision-making system, making it difficult to ensure the optimal overall economic benefits of the beneficiation system.

[0006] (3) The production strategy lacks a dynamic adjustment mechanism. The existing flotation yield control is mostly based on fixed parameter settings, which cannot be dynamically adjusted according to changes in the properties of the raw ore, fluctuations in external market prices, and other conditions.

[0007] Therefore, it is urgent to establish a quantitative correlation model between flotation yield and the overall economic benefits of the beneficiation and metallurgical system to guide the control logic of the combined beneficiation and metallurgical process, solve the problems in the existing technology that make it difficult to dynamically adjust the yield control strategy according to changes in the properties of the raw ore and market fluctuations, and to ensure the economic benefits of the whole process, so as to provide technical support for the regulation of the combined beneficiation and metallurgical process indicators. Summary of the Invention

[0008] To address the shortcomings of existing technologies, this invention aims to provide a method for controlling the yield of oxidized concentrate under different acid consumption conditions of raw flotation ore.

[0009] To achieve the above objectives, the present invention adopts the following technical solution: A method for controlling the yield of oxidized concentrate under different acid consumption conditions of raw flotation ore includes the following steps: S1. Based on the properties of the raw ore, the relationship between acid consumption of flotation oxidation concentrate and acid consumption of raw ore is regressed: Based on the properties of the feed ore and the actual production performance of flotation, the acid consumption data of the raw ore and the acid consumption data of the oxide concentrate obtained after flotation of the raw ore are statistically analyzed. The least squares method is used to conduct regression analysis to establish a quantitative correlation model between the acid consumption of the oxide concentrate obtained after flotation and the acid consumption of the raw ore, so as to realize the rapid prediction of the acid consumption of the oxide concentrate from the known acid consumption of the raw ore. Step S2: Relationship between flotation oxide concentrate yield and copper and cobalt recovery rates: Based on flotation production data, we analyzed the copper and cobalt recovery rates of oxide concentrate under different oxide concentrate yields. Then, we used the least squares method to conduct regression analysis and established a quantitative correlation model between oxide concentrate yield and copper and cobalt recovery rates of oxide concentrate, thus clarifying the copper and cobalt metal recovery levels of flotation operations under different oxide concentrate yields. Step S3: Establish an economic benefit evaluation model: Cathode copper production = Annual ore processing volume * Raw ore copper grade * Oxide concentrate copper recovery rate * (Leaching rate * Washing efficiency * Extraction and electrowinning recovery rate); Cobalt metal production = annual ore processing volume * raw ore cobalt grade * oxide concentrate cobalt recovery rate * (leaching rate * washing efficiency * cobalt system recovery rate); Cash cost of cathode copper production = mining cost + grinding cost + flotation cost + leaching cost + copper smelting cost + management expenses + manufacturing expenses + sales expenses; Cash cost of cobalt metal production = mining cost + grinding cost + flotation cost + leaching cost + cobalt system cost + management expenses + manufacturing expenses + sales expenses; Cathode copper profit = Cathode copper output * (Cathode copper price - discount) - Cathode copper production cash cost; Cobalt metal profit = Cobalt metal production * (Cobalt metal price * Cobalt pricing factor in cobalt hydroxide) - Cobalt production cash cost; Step S4: Determine the target oxide concentrate yield based on optimal economic benefits: Sulfuric acid cost is included in leaching cost. Combining the current market price of sulfuric acid and the acid consumption of the raw ore to be floated, the economic benefit evaluation model constructed in step S3 is used to solve the problem one by one according to the constraints. With the goal of maximizing the benefit per ton of flotation, the optimal oxide concentrate yield is obtained by changing the oxide concentrate yield under the condition of maximizing the benefit per ton of flotation. Step S5: Calculation and analysis of optimal yield under different sulfuric acid unit prices and raw ore acid consumption conditions: Based on multiple sets of calculation results, a corresponding mapping relationship between different sulfuric acid unit prices, raw ore acid consumption and optimal oxide concentrate yield is established. This facilitates on-site production personnel to quickly determine the optimal oxide concentrate yield control value under current production conditions based on real-time sulfuric acid market prices and raw ore property parameters, thereby achieving dynamic benefit optimization of the beneficiation and smelting combined production process.

[0010] Furthermore, the specific process of step S1 includes: S1.1 Collection of production data: During a continuous six-month production cycle, for copper-cobalt oxide ore processed by the beneficiation and smelting combined system, the acid consumption data per ton of raw copper-cobalt oxide ore and the corresponding acid consumption data per ton of oxide concentrate obtained after flotation are collected daily, and finally, valid data pairs of the set quantity are obtained. S1.2. The regression analysis uses the least squares method, with the acid consumption n of the raw ore as the independent variable and the acid consumption m of the oxide concentrate obtained after flotation as the dependent variable. The resulting univariate linear regression model is as follows: ; Where m is the acid consumption per ton of oxide concentrate obtained after flotation, in kg / t ore; n is the acid consumption of the raw ore, in kg / t ore. k 1 represents the slope. k 2 represents the intercept; The above univariate linear regression model is a quantitative correlation model between the acid consumption of the oxide concentrate obtained after flotation and the acid consumption of the raw ore.

[0011] Furthermore, in step S1.1, the daily data collection process is as follows: the daily production time is divided into two shifts. Every 4 hours in each shift, the acid consumption data per ton of raw copper-cobalt oxide ore and the corresponding acid consumption data per ton of oxide concentrate obtained after flotation are collected and tested. Then, the data collected in each shift are weighted and averaged to obtain the average acid consumption data per ton of raw copper-cobalt oxide ore and the corresponding average acid consumption data per ton of oxide concentrate obtained after flotation for that shift. Then, the average acid consumption data per ton of raw copper-cobalt oxide ore and the corresponding average acid consumption data per ton of oxide concentrate obtained after flotation for each shift are weighted and averaged according to the amount of ore in each shift, and finally, the acid consumption data per ton of raw copper-cobalt oxide ore and the corresponding acid consumption data per ton of oxide concentrate obtained after flotation for that day are obtained.

[0012] Furthermore, the specific process of step S2 is as follows: S2.1 Obtain daily production data of the combined beneficiation and metallurgical system for six months, including the raw ore feed grade, sulfide concentrate grade, and sulfide tailings grade data of the flotation sulfidation section; and the raw oxidation section feed grade, oxidation section tailings grade, and oxidation concentrate grade data of the flotation oxidation section. S2.2. Based on the production data collected in step S2.1, the oxide concentrate yield is calculated using the following formula. c Copper recovery rate of oxide concentrate e Cu Cobalt recovery rate from oxide concentrate e Co : Sulfide concentrate yield = (copper grade of raw ore entering the beneficiation process - copper grade of tailings from the sulfide section) / (copper grade of sulfide concentrate - copper grade of tailings from the sulfide section); Oxide concentrate yield c = (Copper grade of the original oxidation section - Copper grade of the oxidation section tailings) / (Copper grade of the oxidation concentrate - Copper grade of the oxidation section tailings) * (1 - Copper yield of the sulfide concentrate); Copper recovery rate of oxide concentrate e Cu = c *Copper grade of oxide concentrate / Copper grade of the original oxide section; Cobalt recovery rate in oxide concentrate e Co = c *Cobalt grade in oxide concentrate / Cobalt grade in the original oxide section; S2.3 Using the data obtained in step S2.2, perform regression analysis using the least squares method, with the oxide concentrate yield as the metric. cAs independent variables, and respectively using the copper recovery rate of oxide concentrate... e Cu Cobalt recovery rate from oxide concentrate e Co Nonlinear regression was performed on the dependent variable to obtain quantitative correlation models between oxide concentrate yield and copper recovery rate, and between oxide concentrate yield and cobalt recovery rate: ; ; in, k 3. k 5 represents the slope. k 4. k 6 represents the intercept. e Cu The copper recovery rate of oxide concentrate is %; e Co The cobalt recovery rate of oxide concentrate is %; c The yield of oxide concentrate is %.

[0013] Furthermore, in step S2.1, the daily production data collection process is as follows: the daily production time is divided into two shifts, and production data is collected and analyzed every 4 hours in each shift; in step S2.2, the oxide concentrate yield is calculated based on the production data collected for each shift. c Copper recovery rate of oxide concentrate e Cu 、 Cobalt recovery rate in oxide concentrate e Co The average oxide concentrate yield for each shift was obtained through weighted calculation. c Average copper recovery rate of oxide concentrate e Cu and average cobalt recovery rate of oxide concentrate e Co Finally, the average oxide concentrate yield for each shift was calculated based on the amount of ore produced in each shift. c Average copper recovery rate of oxide concentrate e Cu 、 Average cobalt recovery rate in oxide concentrate e Co A weighted average is then performed to obtain the oxide concentrate yield for that day. c Copper recovery rate of oxide concentrate e Cu Cobalt recovery rate from oxide concentrate e Co .

[0014] Furthermore, in step S4, the constraints for the planning solution include: the enrichment ratio of copper and cobalt in the oxide concentrate is ≤4, and the copper grade in the oxide concentrate is between 10% and 50%.

[0015] Furthermore, in step S5, in establishing the corresponding mapping relationship between different sulfuric acid unit prices, raw ore acid consumption and optimal oxidized concentrate yield, the different sulfuric acid unit prices include at least $285 / t, $570 / t, $716 / t, and $840 / t; the different raw ore acid consumption includes at least 150 kg / t ore, 200 kg / t ore, 250 kg / t ore, 300 kg / t ore, 350 kg / t ore, 400 kg / t ore, 500 kg / t ore, 600 kg / t ore, 700 kg / t ore and 800 kg / t ore.

[0016] The beneficial effects of this invention are as follows: This invention establishes a quantitative correlation model between the acid consumption of flotation oxide concentrate and raw flotation ore, as well as a quantitative correlation model between the yield of oxide concentrate and the comprehensive recovery rate of copper and cobalt. It constructs a combined beneficiation and metallurgical economic benefit evaluation model with the economic benefit per ton of ore as the objective function. Furthermore, it incorporates external dynamic factors such as sulfuric acid market prices and metal market prices into the yield optimization decision-making system, achieving dynamic optimization control of flotation yield. This solves the technical problems in existing technologies where it is difficult to dynamically adjust yield control strategies based on changes in raw ore properties and market fluctuations, and where optimal economic benefits throughout the entire process cannot be guaranteed. Ultimately, it achieves the goal of maximizing the overall economic benefits of the beneficiation and metallurgical system. Specifically: (1) Significantly improve the overall economic benefits of the beneficiation system. This invention establishes a quantitative relationship between the yield of oxidized concentrate and raw ore and acid consumption, and plans and solves the dynamic optimization control of flotation yield with the goal of maximizing economic benefits.

[0017] (2) Establish a scientific basis for quantitative decision-making on raw ore acid consumption and flotation yield. This invention proposes for the first time to establish a quantitative relationship between acid consumption of flotation oxide concentrate and acid consumption of raw ore, as well as a quantitative relationship between oxide concentrate yield and copper and cobalt recovery rates. This can provide accurate data support for yield control and overcome the subjectivity and uncertainty of traditional experience-based parameter adjustment.

[0018] (3) Strong dynamic adaptability. By establishing a complete mapping relationship between different sulfuric acid prices, raw ore acid consumption and optimal yield, this invention can adjust the yield control strategy in real time according to changes in ore properties and market price fluctuations, and is applicable to the combined beneficiation and smelting production scenarios of various copper-cobalt oxide ores.

[0019] (4) Simple to operate and highly industrialized. This invention is based on actual production data modeling, without the need for additional equipment investment. On-site production personnel can quickly determine the optimal yield control target by simply looking up the table according to the real-time parameters, which has good prospects for industrial promotion and application. Attached Figure Description

[0020] Figure 1 This is a schematic diagram showing the relationship between the acid consumption of the oxide concentrate and the acid consumption of the raw ore obtained in the embodiments of the present invention; Figure 2 This is a schematic diagram illustrating the relationship between oxide concentrate yield and copper recovery rate obtained in the embodiments of the present invention; Figure 3 This is a schematic diagram illustrating the relationship between oxide concentrate yield and cobalt recovery rate obtained in the embodiments of the present invention; Figure 4 This is a graph showing the variation of acid consumption of raw ore and yield of optimal oxidized concentrate from flotation under different sulfuric acid unit prices in embodiments of the present invention. Detailed Implementation

[0021] The present invention will be further described below with reference to the accompanying drawings. It should be noted that this embodiment is based on the present technical solution and provides detailed implementation methods and specific operation processes, but the protection scope of the present invention is not limited to this embodiment.

[0022] This embodiment provides a method for controlling the yield of oxidized concentrate under different acid consumption conditions of raw flotation ore. Taking a copper-cobalt oxide ore beneficiation system as an example, the flotation ore processing capacity is 1.25 million tons / year, the raw flotation ore has a Cu grade of about 2.10%, a Co grade of about 0.30%, and an oxidation rate of about 90%.

[0023] The method includes the following steps: S1. Based on the properties of the raw ore, the relationship between acid consumption of flotation oxidation concentrate and acid consumption of raw ore is regressed: Based on the properties of the selected raw ore and the actual performance of flotation, the acid consumption data of the raw ore and the acid consumption data of the oxide concentrate obtained after flotation are statistically analyzed. By conducting regression analysis using the least squares method, a quantitative correlation model between the acid consumption of the oxide concentrate obtained after flotation and the acid consumption of the raw ore is established, so as to realize the rapid prediction of the acid consumption of the oxide concentrate from the known acid consumption of the raw ore.

[0024] The specific process of step S1.1 is as follows: S1.1 Production Data Collection: The daily production time is divided into two shifts (day shift 8:00-17:00, night shift 18:00-7:00). Every 4 hours in each shift, acid consumption data per ton of raw copper-cobalt oxide ore and the corresponding acid consumption data per ton of oxide concentrate obtained after flotation are collected and tested. Then, the data collected in each shift are weighted and averaged to obtain the average acid consumption data per ton of raw copper-cobalt oxide ore and the corresponding average acid consumption data per ton of oxide concentrate obtained after flotation for that shift. Then, the average acid consumption data per ton of raw copper-cobalt oxide ore and the corresponding average acid consumption data per ton of oxide concentrate obtained after flotation for each shift are weighted and averaged according to the amount of ore in each shift, and finally, the acid consumption data per ton of raw copper-cobalt oxide ore and the corresponding acid consumption data per ton of oxide concentrate obtained after flotation for the day are obtained. Ultimately, a large number of valid data pairs were obtained, covering the range of raw ore with acid consumption of 70–350 kg / t and oxidized concentrate with acid consumption of 110–400 kg / t, encompassing the main types of ore encountered in the mine's production practice.

[0025] S1.2 The acid consumption of raw copper-cobalt oxide ore is mainly affected by the content of acid-consuming gangue minerals in the ore. During flotation, valuable minerals are separated from acid-consuming gangue minerals through reagent action. Therefore, there is a positive correlation between the residual acid-consuming gangue mineral content in the oxide concentrate obtained after flotation and the total content of acid-consuming gangue minerals in the raw ore. In production, the properties of the ore fed into the flotation process are relatively stable within a specific time period, and the content of acid-consuming gangue minerals has an approximately linear relationship with the acid consumption of the raw ore. Therefore, a univariate linear regression model can be established between the acid consumption of the oxide concentrate obtained after flotation and the acid consumption of the raw ore, such as... Figure 1 As shown, this is a quantitative correlation model between the acid consumption of the oxide concentrate obtained after flotation and the acid consumption of the raw ore.

[0026] The regression analysis used the least squares method, with the acid consumption n of the raw ore as the independent variable and the acid consumption m of the oxide concentrate obtained after flotation as the dependent variable. The resulting univariate linear regression model is as follows: ; Where m is the acid consumption of the oxide concentrate obtained after flotation, in kg / t ore; n is the acid consumption of the raw ore, in kg / t ore; 0.5962 is the slope, and 97.4710 is the intercept.

[0027] The correlation coefficient R was obtained by fitting. 2 A value >0.85 indicates that the above univariate linear regression model has a good fit.

[0028] It should be noted that the above univariate linear regression model basically reflects the fundamental laws in the combined beneficiation and metallurgical production: the higher the acid consumption of the raw ore, the higher the content of acid-consuming gangue in the ore, and the corresponding increase in the absolute amount of acid-consuming gangue entering the oxide concentrate after flotation, leading to an increase in the acid consumption of the oxide concentrate. The model slope of 0.5962 indicates that about 59.62% of the acid-consuming substances in the raw ore are discarded through flotation, which is basically consistent with the actual waste rate in the flotation operation of copper-cobalt oxide ore; the intercept of 97.4710 reflects that even when the acid consumption of the raw ore approaches zero, there is still a background acid consumption of about 97.47 kg / t of ore in the oxide concentrate, which corresponds to the stoichiometric acid consumption required for the leaching of copper-cobalt oxide minerals in the oxide concentrate, and has clear physical significance.

[0029] Step S2: Relationship between flotation oxide concentrate yield and copper and cobalt recovery rates: Based on flotation production data, the copper and cobalt recovery rates of oxide concentrates under different oxide concentrate yields were analyzed. Then, the least squares method was used to conduct regression analysis to establish a quantitative correlation model between oxide concentrate yield and copper and cobalt recovery rates of oxide concentrates, thus clarifying the copper and cobalt metal recovery levels of flotation operations under different oxide concentrate yields.

[0030] The specific process of step S2 is as follows: S2.1 Obtain daily production data of the combined beneficiation and metallurgical system for six months, including the raw ore feed grade, sulfide concentrate grade, and sulfide tailings grade data of the flotation sulfidation section; the raw oxidation section feed grade, oxidation section tailings grade, and oxidation concentrate grade data of the flotation oxidation section; and collect and analyze production data every 4 hours in each shift. S2.2 Calculate the oxide concentrate yield based on the production data collected for each shift. c Copper recovery rate of oxide concentrate e Cu Cobalt recovery rate from oxide concentrate e Co The average oxide concentrate yield for each shift was obtained through weighted calculation. c Average copper recovery rate of oxide concentrate e Cu 、 Average cobalt recovery rate in oxide concentrate e Co Finally, the average oxide concentrate yield for each shift was calculated based on the amount of ore produced in each shift. c Average copper recovery rate of oxide concentrate e Cu 、 Average cobalt recovery rate in oxide concentrate e Co A weighted average is then performed to obtain the oxide concentrate yield for that day. cCopper recovery rate of oxide concentrate e Cu 、 Cobalt recovery rate in oxide concentrate e Co Yields range from 10% to 60%, and copper recovery rates range from 50% to 90%.

[0031] The yield of oxide concentrate is calculated using the following formula. c Copper recovery rate of oxide concentrate e Cu Cobalt recovery rate from oxide concentrate e Co : The yield of sulfide concentrate is calculated as follows: (Copper grade in raw ore - Copper grade in tailings of sulfide section) / (Copper grade in sulfide concentrate - Copper grade in tailings of sulfide section). It should be noted that since the processed ore is primarily copper-grade with secondary cobalt grade (which is significantly lower than copper grade), copper grade analysis data is used as the benchmark for yield calculation to minimize systematic errors.

[0032] Oxide concentrate yield c = (Copper grade of the original oxidation section - Copper grade of the oxidation section tailings) / (Copper grade of the oxidation concentrate - Copper grade of the oxidation section tailings) * (1 - Copper yield of the sulfide concentrate); Copper recovery rate of oxide concentrate e Cu = c *Copper grade of oxide concentrate / Copper grade of the original oxide section; Cobalt recovery rate in oxide concentrate e Co = c *Cobalt grade in oxide concentrate / Cobalt grade in the original oxide section; S2.3. During flotation, the relationship between concentrate yield and metal recovery rate is not a simple linear one, but follows the basic principle of "diminishing marginal recovery": when the yield is low, flotation prioritizes the recovery of the most floatable minerals, resulting in a higher metal recovery rate per unit yield; as the yield increases, flotation gradually recovers less floatable ores and some intergrowth minerals, leading to a gradual decrease in the increase in metal content per unit yield and a slower growth rate in the overall recovery rate. Therefore, using a logarithmic function ε=a·lnγ+b to regress the relationship between yield and recovery rate not only conforms to the basic physical logic of the flotation process but also accurately describes the trend of recovery rate increasing with yield but at a decreasing rate of increase mathematically.

[0033] Using the data obtained in step S2.2, a regression analysis was performed using the least squares method, with the oxide concentrate yield as the metric. c Copper recovery rate of oxide concentrate is the independent variable. e CuA nonlinear regression was performed on the dependent variable to obtain a quantitative correlation model between oxide concentrate yield and oxide concentrate copper recovery rate: ; Where 0.1659 represents the slope and 0.8591 represents the intercept. e Cu The copper recovery rate of oxide concentrate is %; c The yield of oxide concentrate is %.

[0034] Based on oxide concentrate yield c Cobalt recovery rate in oxide concentrate is the independent variable. e Cu A nonlinear regression was performed on the dependent variable to obtain a quantitative correlation model between oxide concentrate yield and cobalt recovery rate of oxide concentrate: ; Where 0.2174 represents the slope and 0.8208 represents the intercept. e Co The cobalt recovery rate of oxide concentrate is %; c The yield of oxide concentrate is %.

[0035] The correlation coefficient R was obtained by fitting. 2 A value >0.80 indicates a good model fit. Figure 2 , 3 As shown.

[0036] The established quantitative correlation model between oxide concentrate yield and copper and cobalt recovery rates reflects the basic law of flotation operation: as the yield increases from low to high, the copper and cobalt recovery rates also increase, but the rate of increase gradually decreases. This law conforms to the characteristic of "flotation priority," that is, easily floatable minerals preferentially enter the concentrate, while difficult-to-float minerals require higher yields to be recovered.

[0037] Step S3: Establish an economic benefit evaluation model: Cathode copper production = Annual ore processing volume * Raw ore copper grade * Oxide concentrate copper recovery rate * (Leaching rate * Washing efficiency * Extraction and electrowinning recovery rate); Cobalt metal production = annual ore processing volume * raw ore cobalt grade * oxide concentrate cobalt recovery rate * (leaching rate * washing efficiency * cobalt system recovery rate); Cash cost of cathode copper production = mining cost + grinding cost + flotation cost + leaching cost + copper smelting cost + management expenses + manufacturing expenses + sales expenses; Cash cost of cobalt metal production = mining cost + grinding cost + flotation cost + leaching cost + cobalt system cost + management expenses + manufacturing expenses + sales expenses; Cathode copper profit = Cathode copper output * (Cathode copper price - discount) - Cathode copper production cash cost; Cobalt metal profit = Cobalt metal production * (Cobalt metal price * Cobalt pricing factor in cobalt hydroxide) - Cobalt production cash cost; Step S4: Determine the target oxide concentrate yield based on optimal economic benefits: Sulfuric acid cost is included in leaching cost. Based on current sulfuric acid price ($570 / t), copper price ($11500 / t), cobalt metal price ($25 / lb), and other parameters, the economic benefit evaluation model constructed in step S3 is used to solve the problem according to the constraints. The optimal yield control target under the condition of sulfuric acid price of $570 / t is 16.40% when the acid consumption of raw ore is 200 kg / t.

[0038] It can also solve for the optimal yield of oxidized concentrate under varying sulfuric acid prices and raw ore acid consumption. When the raw ore acid consumption is 250 kg / t, the optimal yield control target under a sulfuric acid price of $285 / t is 26.40%; when the raw ore acid consumption is 300 kg / t, the optimal yield control target under a sulfuric acid price of $285 / t is 22.00%; and when the raw ore acid consumption is 500 kg / t, the optimal yield control target under a sulfuric acid price of $285 / t is 13.20%. Figure 3 As shown.

[0039] The constraints for the planning solution include: the copper enrichment ratio of the oxide concentrate is ≤4, and the copper grade of the oxide concentrate is between 10% and 50%.

[0040] Step S5: Calculation and analysis of optimal yield under different sulfuric acid unit prices and raw ore acid consumption conditions: Based on multiple sets of calculation results, a corresponding mapping relationship between different sulfuric acid unit prices, raw ore acid consumption and optimal oxide concentrate yield is established. This facilitates on-site production personnel to quickly determine the optimal oxide concentrate yield control value under current production conditions based on real-time sulfuric acid market prices and raw ore property parameters, thereby achieving dynamic benefit optimization of the beneficiation and smelting combined production process.

[0041] Specifically, in establishing the corresponding mapping relationship between different sulfuric acid unit prices, raw ore acid consumption and optimal oxidized concentrate yield, the different sulfuric acid unit prices include at least $285 / t, $570 / t, $716 / t, and $840 / t; the different raw ore acid consumption includes at least 150 kg / t ore, 200 kg / t ore, 250 kg / t ore, 300 kg / t ore, 350 kg / t ore, 400 kg / t ore, 500 kg / t ore, 600 kg / t ore, 700 kg / t ore and 800 kg / t ore.

[0042] Based on the determined optimal yield control target, the oxide concentrate yield is controlled near the target value by adjusting flotation process parameters (flotation time, collector dosage, aeration rate, etc.). After implementation, the overall economic benefits of the beneficiation system are significantly improved compared to the traditional fixed yield control method. Taking a flotation ore acid consumption of 300 kg / t ore and a sulfuric acid price of $285 / t as an example, the metal recovery revenue under different oxide concentrate yield control is shown in Table 1: Table 1

[0043] The above embodiments demonstrate that the method of this embodiment can dynamically adjust the oxide concentrate yield control target according to the fluctuation of sulfuric acid market price and changes in the properties of raw ore, thereby optimizing the overall economic benefits of the beneficiation system under different market conditions.

[0044] For those skilled in the art, various corresponding changes and modifications can be made based on the above technical solutions and concepts, and all such changes and modifications should be included within the protection scope of the claims of this invention.

Claims

1. A method for controlling the yield of oxidized concentrate under different acid consumption conditions of raw flotation ore, characterized in that, Includes the following steps: S1. Based on the properties of the raw ore, the relationship between acid consumption of flotation oxidation concentrate and acid consumption of raw ore is regressed: Based on the properties of the feed ore and the actual production performance of flotation, the acid consumption data of the raw ore and the acid consumption data of the oxide concentrate obtained after flotation of the raw ore are statistically analyzed. The least squares method is used to conduct regression analysis to establish a quantitative correlation model between the acid consumption of the oxide concentrate obtained after flotation and the acid consumption of the raw ore, so as to realize the rapid prediction of the acid consumption of the oxide concentrate from the known acid consumption of the raw ore. Step S2: Relationship between flotation oxide concentrate yield and copper and cobalt recovery rates: Based on flotation production data, we analyzed the copper and cobalt recovery rates of oxide concentrate under different oxide concentrate yields. Then, we used the least squares method to conduct regression analysis and established a quantitative correlation model between oxide concentrate yield and copper and cobalt recovery rates of oxide concentrate, thus clarifying the copper and cobalt metal recovery levels of flotation operations under different oxide concentrate yields. Step S3: Establish an economic benefit evaluation model: Cathode copper production = Annual ore processing volume * Raw ore copper grade * Oxide concentrate copper recovery rate * (Leaching rate * Washing efficiency * Extraction and electrowinning recovery rate); Cobalt metal production = annual ore processing volume * raw ore cobalt grade * oxide concentrate cobalt recovery rate * (leaching rate * washing efficiency * cobalt system recovery rate); Cash cost of cathode copper production = mining cost + grinding cost + flotation cost + leaching cost + copper smelting cost + management expenses + manufacturing expenses + sales expenses; Cash cost of cobalt metal production = mining cost + grinding cost + flotation cost + leaching cost + cobalt system cost + management expenses + manufacturing expenses + sales expenses; Cathode copper profit = Cathode copper output * (Cathode copper price - discount) - Cathode copper production cash cost; Cobalt metal profit = Cobalt metal production * (Cobalt metal price * Cobalt pricing factor in cobalt hydroxide) - Cobalt production cash cost; Step S4: Determine the target oxide concentrate yield based on optimal economic benefits: Sulfuric acid cost is included in leaching cost. Combining the current market price of sulfuric acid and the acid consumption of the raw ore to be floated, the economic benefit evaluation model constructed in step S3 is used to solve the problem one by one according to the constraints. With the goal of maximizing the benefit per ton of flotation, the optimal oxide concentrate yield is obtained by changing the oxide concentrate yield under the condition of maximizing the benefit per ton of flotation. Step S5: Calculation and analysis of optimal yield under different sulfuric acid unit prices and raw ore acid consumption conditions: Based on multiple sets of calculation results, a corresponding mapping relationship between different sulfuric acid unit prices, raw ore acid consumption and optimal oxide concentrate yield is established. This facilitates on-site production personnel to quickly determine the optimal oxide concentrate yield control value under current production conditions based on real-time sulfuric acid market prices and raw ore property parameters, thereby achieving dynamic benefit optimization of the beneficiation and smelting combined production process.

2. The method according to claim 1, characterized in that, The specific process of step S1 includes: S1.1 Collection of production data: During a continuous six-month production cycle, for copper-cobalt oxide ore processed by the beneficiation and smelting combined system, the acid consumption data per ton of raw copper-cobalt oxide ore and the corresponding acid consumption data per ton of oxide concentrate obtained after flotation are collected daily, and finally, valid data pairs of the set quantity are obtained. S1.

2. The regression analysis uses the least squares method, with the acid consumption n of the raw ore as the independent variable and the acid consumption m of the oxide concentrate obtained after flotation as the dependent variable. The resulting univariate linear regression model is as follows: ； Where m is the acid consumption per ton of oxide concentrate obtained after flotation, in kg / t ore; n is the acid consumption of the raw ore, in kg / t ore. k 1 represents the slope. k 2 represents the intercept; The above univariate linear regression model is a quantitative correlation model between the acid consumption of the oxide concentrate obtained after flotation and the acid consumption of the raw ore.

3. The method according to claim 2, characterized in that, In step S1.1, the daily data collection process is as follows: the daily production time is divided into two shifts. Every 4 hours in each shift, the acid consumption data per ton of raw copper-cobalt oxide ore and the corresponding acid consumption data per ton of oxide concentrate obtained after flotation are collected and tested. Then, the data collected in each shift are weighted and averaged to obtain the average acid consumption data per ton of raw copper-cobalt oxide ore and the average acid consumption data per ton of oxide concentrate obtained after flotation for that shift. Then, the average acid consumption data per ton of raw copper-cobalt oxide ore and the average acid consumption data per ton of oxide concentrate obtained after flotation for each shift are weighted and averaged according to the amount of ore in each shift, and finally, the acid consumption data per ton of raw copper-cobalt oxide ore and the corresponding acid consumption data per ton of oxide concentrate obtained after flotation for that day are obtained.

4. The method according to claim 1, characterized in that, The specific process of step S2 is as follows: S2.1 Obtain daily production data of the combined beneficiation and metallurgical system for six months, including the raw ore feed grade, sulfide concentrate grade, and sulfide tailings grade data of the flotation sulfidation section; and the raw oxidation section feed grade, oxidation section tailings grade, and oxidation concentrate grade data of the flotation oxidation section. S2.

2. Based on the production data collected in step S2.1, the oxide concentrate yield is calculated using the following formula. γ Copper recovery rate of oxide concentrate ε Cu Cobalt recovery rate from oxide concentrate ε Co : Sulfide concentrate yield = (copper grade of raw ore entering the beneficiation process - copper grade of tailings from the sulfide section) / (copper grade of sulfide concentrate - copper grade of tailings from the sulfide section); Oxide concentrate yield γ = (Copper grade of the original oxidation section - Copper grade of the oxidation section tailings) / (Copper grade of the oxidation concentrate - Copper grade of the oxidation section tailings) * (1 - Copper yield of the sulfide concentrate); Copper recovery rate of oxide concentrate ε Cu = γ *Copper grade of oxide concentrate / Copper grade of the original oxide section; Cobalt recovery rate in oxide concentrate ε Co = γ *Cobalt grade in oxide concentrate / Cobalt grade in the original oxide section; S2.3 Using the data obtained in step S2.2, perform regression analysis using the least squares method, with the oxide concentrate yield as the metric. γ As independent variables, and respectively using the copper recovery rate of oxide concentrate... ε Cu Cobalt recovery rate from oxide concentrate ε Co Nonlinear regression was performed on the dependent variable to obtain quantitative correlation models between oxide concentrate yield and copper recovery rate, and between oxide concentrate yield and cobalt recovery rate: ； ； in, k 3. k 5 represents the slope. k 4. k 6 represents the intercept. ε Cu The copper recovery rate of oxide concentrate is %; ε Co The cobalt recovery rate of oxide concentrate is %; γ The yield of oxide concentrate is %.

5. The method according to claim 4, characterized in that, In step S2.1, the daily production data collection process is as follows: the daily production time is divided into two shifts, and production data is collected and analyzed every 4 hours in each shift; in step S2.2, the oxide concentrate yield is calculated based on the production data collected for each shift. γ Copper recovery rate of oxide concentrate ε Cu 、 Cobalt recovery rate in oxide concentrate ε Co The average oxide concentrate yield for each shift was obtained through weighted calculation. γ Average copper recovery rate of oxide concentrate ε Cu and average cobalt recovery rate of oxide concentrate ε Co Finally, the average oxide concentrate yield for each shift was calculated based on the amount of ore produced in each shift. γ Average copper recovery rate of oxide concentrate ε Cu 、 Average cobalt recovery rate in oxide concentrate ε Co A weighted average is then performed to obtain the oxide concentrate yield for that day. γ Copper recovery rate of oxide concentrate ε Cu Cobalt recovery rate from oxide concentrate ε Co .

6. The method according to claim 1, characterized in that, In step S4, the constraints for the planning solution include: the enrichment ratio of copper and cobalt in the oxide concentrate is ≤4, and the copper grade in the oxide concentrate is between 10% and 50%.

7. The method according to claim 1, characterized in that, In step S5, the corresponding mapping relationship between different sulfuric acid unit prices, raw ore acid consumption and optimal oxidized concentrate yield is established. The different sulfuric acid unit prices include at least $285 / t, $570 / t, $716 / t and $840 / t; the different raw ore acid consumption includes at least 150 kg / t ore, 200 kg / t ore, 250 kg / t ore, 300 kg / t ore, 350 kg / t ore, 400 kg / t ore, 500 kg / t ore, 600 kg / t ore, 700 kg / t ore and 800 kg / t ore.

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