A closed-loop fuzzy adjustment method for compound flotation reagent proportioning

Abstract

The present application relates to a kind of composite flotation reagent proportion closed-loop fuzzy adjustment method, belong to the field of flotation technology, solve the one of the problems of existing composite flotation reagent proportion lack of closed-loop control, difficult to dynamically match coal quality change and artificial intervention response lag.The closed-loop fuzzy adjustment method of the present application includes: establishing basic proportion model, calculating the basic proportion R of composite flotation reagent bf ;Using composite flotation reagent for flotation operation separates clean coal and tail coal, and continuously real-time detects the ash content G c And tail coal ash content G t ;According to the real-time data of G c And G t , establish the closed-loop fuzzy adjustment model of double variable, realize the online fuzzy adjustment of the basic proportion R of composite flotation reagent bf , get the adjusted proportion R na , and prepare composite flotation reagent according to R na The present application can realize the closed-loop fuzzy adjustment of composite flotation reagent proportion, so that composite flotation reagent proportion can dynamically adapt to actual coal quality change, without artificial intervention, improve the efficiency of flotation control response.

Description

Technical Field

[0001] This invention relates to the field of flotation technology, and in particular to a closed-loop fuzzy adjustment method for the ratio of composite flotation reagents. Background Technology

[0002] Low-rank coal slime has an abundance of oxygen-containing functional groups on its surface, resulting in poor natural floatability and high consumption when using traditional hydrocarbon flotation reagents. A composite flotation reagent is prepared by combining hydrocarbon oils with oxygen-containing polar organic compounds such as carboxylic acids, esters, ketones, and aldehydes. This composite reagent utilizes the selective adsorption of polar groups on the surface of coal particles to enhance the hydrophobicity of the coal slime, significantly reducing reagent consumption.

[0003] However, the industrial-scale application of flotation processes based on composite flotation reagents is still constrained by insufficient process stability and the lack of closed-loop control. The large fluctuations in the quality of low-rank coal are a common problem in the industry, and the response of coal quality changes and composite flotation reagent ratios to the characteristics of the flotation product (such as the ash content of clean coal and tailings) is complex and variable. Currently, in industrial flotation processes, the ratio of composite flotation reagents is still generally set manually, failing to establish a dynamic correlation model between the ratio of composite flotation reagents and the characteristics of the flotation product, and lacking closed-loop control capabilities based on the characteristics of the flotation product. When coal quality fluctuations cause the characteristics of the flotation product to deviate from the process parameters, existing methods lack the ability for autonomous decision-making and automatic correction based on real-time feedback. Adjustments to the ratio of composite flotation reagents still rely entirely on the experience and manual intervention of operators. This open-loop control mode not only has a delayed response, making it difficult to control the timeliness of control, but also has limitations in situations with multiple variables, making it difficult to stably control the indicators of the flotation product. This will directly cause fluctuations in flotation response efficiency, increased consumption of composite flotation reagents, and difficulty in stabilizing the ash content of clean coal, severely restricting the reliability and economy of composite flotation reagent technology in large-scale industrial applications. Summary of the Invention

[0004] Based on the above analysis, the embodiments of the present invention aim to provide a closed-loop fuzzy adjustment method for the ratio of composite flotation reagents, in order to solve one of the problems of existing composite flotation reagent ratios lacking closed-loop control, difficulty in dynamically matching coal quality changes, and lag in response to manual intervention.

[0005] The objective of this invention is mainly achieved through the following technical solutions: A closed-loop fuzzy adjustment method for the ratio of composite flotation reagents, comprising: S1: Establish a basic ratio model and calculate the basic ratio R of the composite flotation reagent. bf and in accordance with R bf Preparation of composite flotation reagents; S2: Using the aforementioned composite flotation reagent, flotation operations are performed to separate clean coal and tailings, and the ash content G of the clean coal is... c And tailings ash content Gt Perform continuous real-time detection; S3: Based on the ash content of clean coal G c And tailings ash content G t Based on real-time data, a bivariate closed-loop fuzzy adjustment model is established to achieve the adjustment of the basic ratio R of the composite flotation reagent. bf Online fuzzy adjustment yields the adjusted ratio R. na and in accordance with R na To prepare the next composite flotation reagent, continue with step S2.

[0006] Furthermore, the closed-loop fuzzy adjustment model includes a fine gray closed-loop adjustment model, a tail gray closed-loop adjustment model, and a comprehensive closed-loop adjustment model.

[0007] Further, step S3 includes: S31: Calculate the ash content deviation E of the clean coal respectively. c And tailings ash content deviation E t ; S32: E calculated according to step S31 c and E t The execution priority of the closed-loop fuzzy adjustment model is determined by a priority arbitration strategy. S33: Execute the fine ash closed-loop adjustment model, the tail ash closed-loop adjustment model, or the comprehensive closed-loop adjustment model according to the priority determined in step S32.

[0008] Furthermore, the priority arbitration strategy in step S32 includes: Define Y c Y is defined as the threshold for the deviation of ash content in clean coal. t The threshold for tailings ash content deviation; When E c >Y c When this happens, the fine gray closed-loop adjustment model is executed first.

[0009] Furthermore, the priority arbitration strategy in step S32 further includes: When 0<E c ≤Y c And E t >Y t When this happens, the tail ash closed-loop adjustment model is executed first.

[0010] Furthermore, the priority arbitration strategy in step S32 further includes: When 0<E c ≤Y c And 0 < E t ≤Y t At that time, the comprehensive closed-loop adjustment model is executed.

[0011] Furthermore, the priority arbitration strategy in step S32 further includes: When E c ≤0 and E t When the value is ≤0, the ratio of composite flotation reagents is not adjusted.

[0012] Furthermore, the composite flotation reagent comprises hydrocarbon oil components, carboxylic acid components, ester components, ketone components, and aldehyde components.

[0013] Further, step S33 includes: S331: Set the priority of deduction for each component ratio and establish priority deduction rules; when the ratio of a certain component is increased, the priority deduction rules are used to constrain the order of deduction for other components ratios.

[0014] Furthermore, in the priority deduction rule, the first priority deduction component is the ketone component, the second priority deduction component is the ester component, the third priority deduction component is the hydrocarbon oil component, the fourth priority deduction component is the aldehyde component, and the last deduction component is the carboxylic acid component.

[0015] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects: 1. The closed-loop fuzzy adjustment method for the compound flotation reagent ratio of the present invention establishes a bivariate closed-loop fuzzy adjustment model based on real-time data of clean coal ash content and tailings ash content. This model can automatically adjust the compound flotation reagent ratio when the clean coal ash content and / or tailings ash content does not meet the target value requirements, thus achieving closed-loop fuzzy adjustment of the compound flotation reagent ratio. This ensures that the clean coal ash content and tailings ash content meet the production target requirements, and dynamically adapts the compound flotation reagent ratio to changes in actual coal quality. Through real-time closed-loop response, manual adjustment of the ratio based on the characteristics of the flotation product is eliminated, improving the efficiency of flotation control response.

[0016] 2. The closed-loop fuzzy adjustment method for the compound flotation reagent ratio of the present invention obtains the deviation of clean coal ash content and tailings ash content based on real-time data of clean coal ash content and tailings ash content, respectively. A priority arbitration strategy is used to determine the execution priority of the closed-loop fuzzy adjustment model. The clean ash closed-loop adjustment model, tailings ash closed-loop adjustment model, or comprehensive closed-loop adjustment model is executed according to the priority, so that the loop with more serious deviation can be processed with higher priority, realizing dynamic coordination and improving the efficiency of automatically adjusting the compound flotation reagent ratio.

[0017] 3. The closed-loop fuzzy adjustment method for the ratio of composite flotation reagents of the present invention, when increasing the ratio of a certain component of the composite flotation reagent, adopts a priority deduction rule to reduce the ratio of other components, so that the adjustment of the ratio of composite flotation reagents can meet the normalization while each component can still exert its specific selectivity and collection efficiency, thereby realizing the dynamic matching of the ratio of composite flotation reagents to changes in coal quality.

[0018] In this invention, the above-described technical solutions can be combined with each other to achieve more preferred combinations. Other features and advantages of this invention will be set forth in the following description, and some advantages may become apparent from the specification or be learned by practicing the invention. The objectives and other advantages of this invention can be realized and obtained from the content specifically pointed out in the text and accompanying drawings. Attached Figure Description

[0019] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts. Figure 1 This is a logic block diagram of the closed-loop fuzzy adjustment method for the ratio of composite flotation reagents according to an embodiment of the present invention. Figure 2 This is a flowchart of the closed-loop fuzzy adjustment method for the ratio of composite flotation reagents according to an embodiment of the present invention; Figure 3 This is a flowchart illustrating closed-loop fuzzy adjustment in an embodiment of the present invention. Detailed Implementation

[0020] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0021] Example 1 To address the problems of lack of closed-loop control and difficulty in dynamically matching coal quality changes in existing composite flotation reagent ratios, a specific embodiment of the present invention discloses a closed-loop fuzzy adjustment method for composite flotation reagent ratios, such as... Figure 1 and Figure 2 As shown, based on real-time data of slurry ash content and slurry concentration, the basic ratio R of the composite flotation reagent is obtained through a basic ratio model. bf According to the basic ratio R bfA composite flotation reagent is prepared by mixing the various components of the reagent. After flotation operation using the prepared composite flotation reagent, clean coal and tailings are obtained. A bivariate closed-loop fuzzy adjustment model is established based on the real-time data of clean coal ash content and tailings ash content. When the clean coal ash content and / or tailings ash content do not meet the target value requirements, the ratio of the composite flotation reagent can be automatically adjusted so that the clean coal ash content and tailings ash content meet the production target requirements. The composite flotation reagent ratio can be dynamically adapted to changes in actual coal quality.

[0022] It should be noted that the components of the composite flotation reagent include hydrocarbon oil components, carboxylic acid components, ester components, ketone components, and aldehyde components; the ratio of the composite flotation reagent is the percentage of the mass of each component to the total mass of the composite flotation reagent. In this embodiment, the total mass of the composite flotation reagent is a fixed value, and the mass of each component can be obtained through the distribution ratio of each group.

[0023] The closed-loop fuzzy adjustment method for the ratio of composite flotation reagents in this embodiment includes: S1: Based on the slurry ash content G and slurry concentration L C Establish a basic ratio model and calculate the basic ratio R of the composite flotation reagent. bf and in accordance with R bf Preparation of composite flotation reagents.

[0024] It should be noted that a slurry concentration meter and a slurry ash meter are installed on the slurry inlet pipe to monitor the slurry concentration L in real time. C And ash content of slurry G.

[0025] Where G is in units of %, 0 < G < 100; L C The unit is g / L, L C >0.

[0026] Step S1 includes: S11: Establish a preset based on slurry ash content G and slurry concentration L C A two-dimensional hierarchical rule table; The ash content (G) of the slurry is classified according to its numerical range to form slurry ash content grades. The slurry ash content grades are arranged from smallest to largest ash content, including G... L Level, G M Level and G H class.

[0027] The slurry concentration L C The slurry concentration is classified according to the numerical range, forming a slurry concentration grade. The slurry concentration grades are divided into L1 grade and L2 grade according to the concentration value from small to large.

[0028] A two-dimensional classification rule table was established by relating each slurry ash content grade and each slurry concentration grade to the initial proportions of each flotation reagent component, denoted as the initial proportion rule table; in the initial proportion rule table, the initial proportion range of each flotation reagent component is denoted as [r]. ix r is ], where r ix r represents the lower limit of the initial proportion of this component. is The upper limit of the initial proportion of this component is represented by , where i is the component number (i.e., i = 1, 2, 3, 4, 5), representing hydrocarbon oil components, carboxylic acid components, ester components, ketone components, and aldehyde components, respectively; the median of the initial proportion of this component is denoted as r. iz r iz =(r is +r ix ) / 2; The i-th component corresponds to G L Level, G M Level and G H The median of the initial proportions of each grade is denoted as r. izL r izM and r izH .

[0029] G L Level, G M Level and G H The median matching vectors corresponding to each level are R ZL R ZM and R ZH ;R ZL = ;R ZM = ;R ZH = Where i is the group number (i=1, 2, 3, 4, 5).

[0030] The half-range of the distribution ratio range of the i-th group is denoted as sr. i =(r is -r ix ) / 2, the i-th component corresponds to G L Level, G M Level and G H The half-range of the initial proportions of each grade is denoted as sr. iL sr iM and sr iH Where i is the group number (i=1, 2, 3, 4, 5); G L Level, G M Level and G H The half-range vectors corresponding to each level are SR L SR M and SR H ;SR L = ;SR M = ;SR H = .

[0031] It should be noted that the union of the initial proportion ranges corresponding to the same ash content level in the initial proportion rule table is taken as [r ix r is ].

[0032] It should be noted that in practical applications, the initial proportion range of each component in the initial proportion rule table is set according to the coal quality characteristics of different mining areas.

[0033] S12: Calculate the basic proportion R bf ; Based on the real-time data of slurry ash content G, the trapezoidal fuzzy membership function is used to determine the slurry ash content level to which slurry ash content G belongs, resulting in the slurry ash content membership vector [μ]. L (G), μ M (G), μ H (G)];where, μ L (G), μ M (G) and μ H (G) represents the current ash content of the slurry, G in G L Level, G M Level and G H Membership degree of the level.

[0034] Based on the obtained slurry concentration L C Real-time data, determined by rules with hysteresis intervals. C The classification level determines the current slurry concentration level. A reference table of offset coefficients is established for each flotation reagent component corresponding to different slurry ash content grades and slurry concentration grades. Based on the current slurry concentration grade, the offset coefficient vector corresponding to different slurry ash grades is retrieved from the offset coefficient reference table, G. L Level, G M Level and G H The offset coefficient vectors corresponding to each level are denoted as D. L D M and D H .

[0035] The membership vector of slurry ash content [μ L (G), μ M (G), μ H (G)] and D L D M and D H The weighted average is used to obtain the composite component offset coefficient vector D; The membership vector of slurry ash content [μ L (G), μ M (G), μ H (G)] and R ZL R ZM and R ZH The weighted average is used to obtain the comprehensive median matching vector R. Z ; The membership vector of slurry ash content [μ L (G), μ M (G), μ H (G)] and SR L SR M and SR H The weighted average is used to obtain the comprehensive range half-range vector SR; The product of the composite component offset coefficient vector D and the composite range semi-range vector SR is used as the offset correction term, and R is adjusted accordingly. Z Compensation calculations are performed to obtain the preliminary matching vector R. w ; R w Normalization was performed to ensure that the sum of the proportions of each flotation reagent component was 100%, thus obtaining the basic ratio R of the composite flotation reagent. bf .

[0036] S13: According to R bf The proportions of each flotation reagent group were used to prepare composite flotation reagents.

[0037] S2: Use the composite flotation reagent prepared in step S13 to perform flotation separation operation, separating the slurry into clean coal and tailings; Analyze the ash content G of the separated clean coal. c And tailings ash content G t Perform continuous real-time monitoring.

[0038] It should be noted that a clean coal ash analyzer is installed on the clean coal collection pipeline to detect the clean coal ash content (G) in real time. c A tailings ash analyzer is installed on the tailings discharge pipeline to detect the tailings ash content (G) in real time. t .

[0039] Among them, G c and G t The unit is %, 0 < G c <100, 0<G t <100.

[0040] S3: To address the issue of delayed response in existing manual intervention methods, based on the ash content of clean coal G c And tailings ash content G t Based on real-time data, a bivariate closed-loop fuzzy adjustment model is established to achieve adjustment of the basic ratio R of the composite flotation reagent. bfOnline fuzzy adjustment yields the adjusted ratio R. na and in accordance with R na Perform step S13 to prepare the next composite flotation reagent, and continue with step S2; Real-time closed-loop response is achieved by using a bivariate closed-loop fuzzy adjustment model, eliminating the need for manual adjustments to the proportions based on the characteristics of the flotation product, thus improving the efficiency of flotation control response.

[0041] Due to the ash content of refined coal (G) c And tailings ash content G t Real-time data is acquired simultaneously to address the issue of order adjustments (e.g., "according to G"). c Adjust the ratio of composite flotation reagents → wait → according to G t To address the lag issues caused by adjusting the composite flotation reagent ratio and the conflict arising from simultaneous triggering of judgment conditions during synchronous adjustments, this embodiment employs a fuzzy control algorithm to address the following: bf Online adjustments are made to achieve closed-loop adjustment of both fine ash and tail ash variables; the fuzzy control algorithm includes synchronous calculation, priority arbitration strategy and weighted coordination strategy or fuzzy controller.

[0042] Furthermore, the bivariate closed-loop fuzzy adjustment model in this embodiment includes a fine gray closed-loop adjustment model, a tail gray closed-loop adjustment model, and a comprehensive closed-loop adjustment model.

[0043] like Figure 3 As shown, step S3 includes: S31: Calculate the ash content deviation E of the clean coal respectively. c And tailings ash content deviation E t It conforms to the following formula: E c =(G c -G c _target) / G c _target×100%(1-1) E t =(G t _target-G t ) / G t _target×100% (1-2) In equation (1-1), G c For real-time clean coal ash content; G c _target is the target value for the ash content of clean coal. For example, G c The target value is typically set between 7.5% and 9%, and adjusted according to the actual coal quality. In equation (1-2), G t For real-time tailings ash content; G t_target is the target value for tailings ash content. For example, G t The target value is usually set to 65%~75%, and adjusted according to the actual coal quality.

[0044] S32: E calculated based on S31 c and E t The execution priority of the closed-loop fuzzy adjustment model is determined by a priority arbitration strategy.

[0045] Define Y c For example, Y is typically set as the threshold for ash content deviation in clean coal. c =10%; Define Y t For example, Y is typically set as the threshold for tailings ash content deviation. t =15%; When E c >Y c At that time, the closed-loop adjustment model of fine ash should be implemented first to increase the proportion of carboxylic acid components.

[0046] When 0<E c ≤Y c And E t >Y t At that time, the tail ash closed-loop adjustment model should be implemented first to increase the proportion of hydrocarbon oil components.

[0047] When 0<E c ≤Y c And 0 < E t ≤Y t At that time, a comprehensive closed-loop adjustment model is executed, and a weighted coordination strategy or fuzzy controller is adopted to realize the adjustment direction and adjustment range of the composite flotation reagent ratio through comprehensive calculation.

[0048] When E c ≤0 and E t When the value is ≤0, the ratio of composite flotation reagents is not adjusted.

[0049] S33: Execute the fine ash closed-loop adjustment model, tail ash closed-loop adjustment model, or comprehensive closed-loop adjustment model according to the priority determined by S32.

[0050] Furthermore, since there is a strong coupling relationship between the components of the flotation reagent (i.e., the sum of the proportions of each group is 100%), increasing the proportion of a certain component requires reducing the proportions of other components. However, since the other components have different functions, it is not suitable to reduce them proportionally. In order to achieve normalization and solve the problem that proportional adjustment is not applicable, this embodiment adopts a priority deduction rule to reduce the proportions of other components, so that each component can still exert its specific selectivity and collection efficiency, while satisfying the condition that the sum of the proportions of all groups is 100%, thus achieving dynamic matching of the composite flotation reagent proportions to changes in coal quality.

[0051] It should be noted that the current allocation ratio vector for each group is R= Where i is the component number (i=1, 2, 3, 4, 5), r1 is the hydrocarbon oil group distribution ratio, r2 is the carboxylic acid group distribution ratio, r3 is the ester group distribution ratio, r4 is the ketone group distribution ratio, and r5 is the aldehyde group distribution ratio.

[0052] Step S33 includes: S331: Set the priority of deduction for each component ratio and establish priority deduction rules; when the ratio of a certain component is increased, the priority deduction rules are used to constrain the order of deduction for other components ratios, as shown in Table 1 below; Table 1 Priority Setting Table for Subtraction of Proportions of Each Component

[0053] S332: When E c >Y c At the same time, the closed-loop adjustment model of fine ash is implemented to increase the proportion of carboxylic acid components; Step S332 includes: S3321: Increase the basic ratio R bf The proportion of carboxylic acid components; The increase in the proportion of carboxylic acid components is denoted as Δr2 (positive value), which is usually set to 1%~2%.

[0054] S3322: Deduct the proportions of components that need to be reduced according to the priority deduction order in Table 1; the sum of the deduction values ​​is equal to Δr2; Calculate the deductible sum R of the allocation ratios of other groups. y , will R y Comparing the increase in the proportion of carboxylic acid components with the value Δr2, the proportions were adjusted and normalized according to the order in Table 1 based on the comparison results to obtain R. na .

[0055] R y According to the following formula: R y =(r1+r3+r4+r5)-(r 1x +r3x +r 4x +r 5x ), where r 1x r 3x r 4x and r 5x This represents the lower limit of the initial proportion of each component.

[0056] When R y When -Δr2≥0, the proportions of each component are adjusted according to the component deduction priority order in Table 1. The adjusted distribution ratio vector of each group is denoted as R. n =[r 1n r 2n r 3n r 4n r 5n ], where each component is the adjusted ratio of each component; r 2n =r1+Δr2.

[0057] Step S3322 includes: S33221: Check the current proportion of the first priority deductible component. If r4 ≥ r 4x If +Δr2, then all deductions are made from the first priority deduction component, i.e., r 4n =r4-Δr2, the remaining components are not adjusted, and R at this time n =[r1, r 2n r3, r 4n [r5], at this time R n The vector is R na If r4 < r 4x +Δr2, then r 4n =r 4x And calculate Δr4 = r4 - r 4x Proceed to the next step.

[0058] S33222: Check the current proportion of the second priority deduction component. If r3 ≥ r 3x +Δr4, then r 3n =r3-Δr4, the remaining components are not adjusted, and R at this time n =[r1, r 2n r 3n r 4n [r5], at this time R n The vector is R na If r3 < r 3x +Δr4, then r 3n =r 3x And calculate Δr3 = r3 - r 3x Proceed to the next step.

[0059] S33223: Perform the deduction of the third and fourth priority deduction components in the order of Table 1, with the deduction logic being the same as S33221 and S33222; complete the adjustment of the allocation ratio of all components.

[0060] When R y When -Δr2 < 0, it indicates that the proportions of the components other than the carboxylic acid components are insufficient to subtract Δr2. Therefore, the proportions of the remaining components should be adjusted to the corresponding lower limit values, i.e., r. 1n =r 1x r 3n =r 3x r 4n =r 4x r 5n =r 5x ;r 2n =r²+R y At this time, R n =[r 1n r 2n r 3n r 4n r 5n ]; Determine if the sum of all components equals 100%. If it does not equal 100%, then set R... n Normalization is performed to obtain ; (1-3) Where i and j are the group numbers, i = 1, 2, 3, 4, 5; j = 1, 2, 3, 4, 5.

[0061] Then according to the normalized R na The vector value is executed in step S13 to prepare the next composite flotation reagent, and then step S2 is executed to complete one fine ash closed-loop adjustment.

[0062] S333: When 0 < E c ≤Y c And E t >Y t At the same time, the tail ash closed-loop adjustment model is implemented to increase the proportion of hydrocarbon oil components; The logic of the tail ash closed-loop adjustment model is the same as that of S332. The increase in the hydrocarbon oil component ratio is Δr1, which is usually set to 1%~2%. Other components follow the execution logic of S3322, and the proportion of other components is reduced by the priority deduction rule. The sum of the deduction values ​​is equal to Δr1. The adjusted ratio R n Normalization yields R na ; Then according to the normalized R naThe vector value is executed in step S13 to prepare the next composite flotation reagent, and then step S2 is executed to complete one tailings ash closed-loop adjustment.

[0063] S334: When 0 < E c ≤Y c And 0 < E t ≤Y t At that time, a comprehensive closed-loop adjustment model is executed, and a weighted coordination strategy or fuzzy controller is adopted to realize the adjustment direction and adjustment range of the composite flotation reagent ratio through comprehensive calculation.

[0064] To mitigate the problem of high-dimensional fuzzy rule explosion, this embodiment employs a dual-input, dual-output fuzzy controller to achieve fuzzy control. The fuzzy controller includes two input variables and two output variables; the two input variables include the clean coal ash content deviation E. c And tailings ash content deviation E t The two output variables include the selectivity adjustment coefficient U_sel and the recovery rate adjustment coefficient U_rec.

[0065] S3341: Press E c and E t The numerical values ​​are used to classify the ash content deviation of clean coal and tailings into multiple levels, and the inference rule table of the fuzzy controller is formulated, for example, as shown in Table 2 below. It should be noted that the values ​​of U_sel and U_rec both range from [-1, 1]. A positive value of U_sel represents an increase in the proportion of carboxylic acid components and aldehyde components; a negative value of U_sel represents a decrease in the proportion of carboxylic acid components and aldehyde components; U_sel=0 means that the proportion of carboxylic acid components and aldehyde components is not adjusted. A positive value of U_rec represents an increase in the proportion of hydrocarbon oil components and ester components; a negative value of U_rec represents a decrease in the proportion of hydrocarbon oil components and ester components; U_rec=0 means that the proportion of hydrocarbon oil components and ester components is not adjusted.

[0066] Table 2. Inference Rules for Fuzzy Controllers

[0067] It should be noted that in Table 2, C-NB, C-NS, C-ZE, C-PS, and C-PB represent the deviation degree E of clean coal ash content. c The grades, T-NB, T-NS, T-ZE, T-PS, and T-PB, represent the tailings ash content deviation degree E. t The levels, and the value ranges for each level in Table 2 are set as examples, according to Y. c =10% and Y t =Set to 15%, but adjust according to coal quality.

[0068] S3342: Calculate the adjustment amount of the specific component based on U_sel and U_rec output by the fuzzy controller in Table 2.

[0069] According to the current E c and E t The values ​​of U_sel and U_rec are obtained by calling Table 2; the current allocation ratio vector for each group is R=[r1, r2, r3, r4, r5], and the adjusted allocation ratio vector for each group is denoted as R. n =[r 1n r 2n r 3n r 4n r 5n ], R n The adjustment calculation conforms to the following formula: Δr2=U_sel×Δr_max×w2 Δr5 = U_sel × Δr_max × w5 Δr1=U_rec×Δr_max Δr3 = U_rec × Δr_max × 0.3 r 2n =r² + Δr² r 5n =r5+Δr5 r 1n =r1+Δr1 r 3n =r3+Δr3 In the formula, Δr1 is the adjustment amount of the hydrocarbon oil component ratio, Δr2 is the adjustment amount of the carboxylic acid component ratio, Δr3 is the adjustment amount of the ester component ratio, and Δr5 is the adjustment amount of the aldehyde component ratio; Δr_max is the maximum adjustment range in a single instance, and for example, Δr_max is usually set to 2%~3%; w2 and w5 are the adjustment weights of the carboxylic acid component and the ester component ratio, respectively, and for example, w2=0.6 and w5=0.4.

[0070] S3343: After adjusting according to S3342, perform data verification and normalization to obtain R. na .

[0071] First, determine R. n =[r 1n r 2n r 3n r 4n r 5n If each component of [R] is within the range of the initial proportioning rule table, and a component value exceeds the corresponding lower or upper limit, then the lower or upper limit value is taken; then it is determined whether the sum of all components equals 100%. If it does not equal 100%, normalization is performed according to formula (1-3) to obtain R. naThen, according to the normalized R na The vector value is executed in step S13 to prepare the next composite flotation reagent, and then step S2 is executed, thus completing the comprehensive closed-loop adjustment of the composite flotation reagent ratio.

[0072] By establishing a dual-input, dual-output fuzzy controller, the two abstract variables of clean coal ash content and tailings ash content are mapped to specific adjustment amounts of the distribution ratio of each flotation reagent group, thereby achieving dynamic coordination and improving the efficiency of automatically adjusting the distribution ratio of composite flotation reagent groups.

[0073] The closed-loop fuzzy adjustment method for the compound flotation reagent ratio in this embodiment establishes a closed-loop fuzzy adjustment model based on the dual variables of clean coal ash content and tailings ash content. When it is detected that the clean coal ash content and / or tailings ash content does not meet the index requirements, the compound flotation reagent ratio is automatically adjusted, realizing closed-loop control of the compound flotation reagent ratio. This improves the adaptability of the compound flotation reagent ratio to actual coal quality fluctuations and the response efficiency of flotation control, while reducing errors caused by manual intervention and operation, and reducing the waste of compound flotation reagents.

[0074] Example 2 To improve the operational efficiency of closed-loop fuzzy adjustment and its adaptability to changes in coal quality, another specific embodiment of the present invention, based on Embodiment 1, further includes: recording and storing historical data, using the historical data to optimize the flotation results, thereby performing offline parameter optimization and iteration, so that the basic ratio R... bf It can adapt to changes in actual coal quality and reduce the adjustment burden of the closed loop through rule-based gradual correction.

[0075] Once the accumulated historical data records reach the set number, the key parameters in step S1 of Example 1 are optimized offline based on the historical data, and the basic ratio R is recalculated using the optimized key parameters. bf The calculation.

[0076] Meanwhile, historical data is used to continuously monitor the long-term adjustment trend of the closed-loop fuzzy adjustment model in step S3 of Example 1. When the proportion of a certain component is continuously and unidirectionally corrected, the corrected parameters are solidified into step S1.

[0077] The closed-loop fuzzy adjustment method for the composite flotation reagent ratio in Example 2 effectively reduces the frequency and magnitude of closed-loop adjustments through offline optimization and iteration. This ensures that the basic ratio model conforms to the actual fluctuation pattern of the current coal quality, improves the operating efficiency and index stability of the closed-loop fuzzy adjustment, and further enhances the long-term adaptability of the basic ratio model and the closed-loop fuzzy adjustment model to complex coal quality changes.

[0078] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A closed-loop fuzzy adjustment method for the ratio of composite flotation reagents, characterized in that, include: S1: Establish a basic ratio model and calculate the basic ratio R of the composite flotation reagent. bf and in accordance with R bf Preparation of composite flotation reagents; S2: Using the aforementioned composite flotation reagent, flotation operations are performed to separate clean coal and tailings, and the ash content G of the clean coal is... c And tailings ash content G t Perform continuous real-time detection; S3: Based on the ash content of clean coal G c And tailings ash content G t Based on real-time data, a bivariate closed-loop fuzzy adjustment model is established to achieve the adjustment of the basic ratio R of the composite flotation reagent. bf Online fuzzy adjustment yields the adjusted ratio R. na and in accordance with R na To prepare the next composite flotation reagent, continue with step S2.

2. The closed-loop fuzzy adjustment method for the ratio of composite flotation reagents according to claim 1, characterized in that, The closed-loop fuzzy adjustment model includes a fine gray closed-loop adjustment model, a tail gray closed-loop adjustment model, and a comprehensive closed-loop adjustment model.

3. The closed-loop fuzzy adjustment method for the ratio of composite flotation reagents according to claim 2, characterized in that, Step S3 includes: S31: Calculate the ash content deviation E of the clean coal respectively. c And tailings ash content deviation E t ; S32: E calculated according to step S31 c and E t The execution priority of the closed-loop fuzzy adjustment model is determined by a priority arbitration strategy. S33: Execute the fine ash closed-loop adjustment model, the tail ash closed-loop adjustment model, or the comprehensive closed-loop adjustment model according to the priority determined in step S32.

4. The closed-loop fuzzy adjustment method for the ratio of composite flotation reagents according to claim 3, characterized in that, The priority arbitration strategy in step S32 includes: Define Y c Y is defined as the threshold for the deviation of ash content in clean coal. t The threshold for tailings ash content deviation; When E c >Y c When this happens, the fine gray closed-loop adjustment model is executed first.

5. The closed-loop fuzzy adjustment method for the ratio of composite flotation reagents according to claim 4, characterized in that, The priority arbitration strategy in step S32 further includes: When 0<E c ≤Y c And E t >Y t When this happens, the tail ash closed-loop adjustment model is executed first.

6. The closed-loop fuzzy adjustment method for the ratio of composite flotation reagents according to claim 5, characterized in that, The priority arbitration strategy in step S32 further includes: When 0<E c ≤Y c And 0 < E t ≤Y t At that time, the comprehensive closed-loop adjustment model is executed.

7. The closed-loop fuzzy adjustment method for the ratio of composite flotation reagents according to claim 6, characterized in that, The priority arbitration strategy in step S32 further includes: When E c ≤0 and E t When the value is ≤0, the ratio of composite flotation reagents is not adjusted.

8. The closed-loop fuzzy adjustment method for the ratio of composite flotation reagents according to any one of claims 3-7, characterized in that, The composite flotation reagent comprises hydrocarbon oil components, carboxylic acid components, ester components, ketone components, and aldehyde components.

9. The closed-loop fuzzy adjustment method for the ratio of composite flotation reagents according to claim 8, characterized in that, Step S33 includes: S331: Set the priority of deduction for each component ratio and establish priority deduction rules; when the ratio of a certain component is increased, the priority deduction rules are used to constrain the order of deduction for other components ratios.

10. The closed-loop fuzzy adjustment method for the ratio of composite flotation reagents according to claim 9, characterized in that, In the priority deduction rule, the first priority deduction component is the ketone component, the second priority deduction component is the ester component, the third priority deduction component is the hydrocarbon oil component, the fourth priority deduction component is the aldehyde component, and the last deduction component is the carboxylic acid component.

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