CN110918266A - Control device and method for improving flotation froth quality - Google Patents
Control device and method for improving flotation froth quality Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B03—SEPARATION OF SOLID MATERIALS USING LIQUIDS OR USING PNEUMATIC TABLES OR JIGS; MAGNETIC OR ELECTROSTATIC SEPARATION OF SOLID MATERIALS FROM SOLID MATERIALS OR FLUIDS; SEPARATION BY HIGH-VOLTAGE ELECTRIC FIELDS
- B03D—FLOTATION; DIFFERENTIAL SEDIMENTATION
- B03D1/00—Flotation
- B03D1/02—Froth-flotation processes
- B03D1/028—Control and monitoring of flotation processes; computer models therefor
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B03—SEPARATION OF SOLID MATERIALS USING LIQUIDS OR USING PNEUMATIC TABLES OR JIGS; MAGNETIC OR ELECTROSTATIC SEPARATION OF SOLID MATERIALS FROM SOLID MATERIALS OR FLUIDS; SEPARATION BY HIGH-VOLTAGE ELECTRIC FIELDS
- B03D—FLOTATION; DIFFERENTIAL SEDIMENTATION
- B03D1/00—Flotation
- B03D1/14—Flotation machines
- B03D1/16—Flotation machines with impellers; Subaeration machines
- B03D1/22—Flotation machines with impellers; Subaeration machines with external blowers
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Abstract
The invention discloses a control device and a control method for improving flotation froth quality. The control device consists of a controller, an air regulating valve, a mineral aggregate regulating valve, a motor driver, a motor, an industrial camera and a stirring impeller, wherein foam means that ore pulp and air are mixed by the stirring impeller and rise to the liquid surface to form a flotation foam layer, the conveying speed and the air inlet speed of the mineral aggregate are respectively controlled by the mineral aggregate regulating valve and the air regulating valve, and the rotating speed of the stirring impeller is controlled by the motor driver to control the motor. Mineral aggregate refers to a hydrated mixture of minerals and flotation agents. The invention collects the surface foam image through the industrial camera, sends the surface foam image into the controller to analyze the foam characteristic, and calculates and controls the output of the motor driver and the rotating speed of the motor, and the opening of the air regulating valve and the mineral aggregate regulating valve according to the database collected by the test by using the optimal solution matching algorithm based on least square, thereby obtaining the flotation foam with better quality.
Description
Technical Field
The invention relates to the technical field of mineral froth flotation, in particular to a control device and a control method for improving the quality of mineral flotation froth.
Background
Mineral separation is an essential important link in mineral resource processing, and froth flotation is the most important mineral separation method and is widely applied to industrial departments such as steel, nonferrous metals, coal, chemical industry, environmental protection and the like. The froth flotation is a separation method which is characterized in that flotation reagents are added into ore pulp, air is filled into the ore pulp, the ore pulp is stirred to generate bubbles, hydrophobic useful minerals are adhered to the bubbles according to the surface wettability difference of the minerals, and hydrophilic gangue minerals are retained in water, so that the useful minerals and the gangue are separated.
In mineral froth flotation, froth is mainly created by mixing mineral material and air with a stirring impeller. There are many factors that affect the quality of the flotation froth, which the process of generation has a crucial impact on. Rotating speed v of stirring impeller in traditional process of froth flotationγAir intake velocity vαAnd the mineral material entry velocity vβIs constant and not adjustable.
In the past, the chemical adding amount of ore pulp is usually adjusted manually when the flotation froth quality changes, the adjusting method is too single and cannot be adjusted finely, the adjusting effect cannot reach the optimum, manual adjustment according to experience is not beneficial to automation of equipment, the production efficiency is limited to be improved, waste is possibly caused, and the like; the flexible reaction cannot be realized when the relevant factors are changed, and the regulation speed is delayed.
It is known that under the same conditions, different flotation foams are generated due to different environmental factors or different ore feeding conditions, and the quality of the flotation foams is also different. When environmental factors or ore feeding conditions change in actual production, the rotating speed v of the stirring impellerγAir intake velocity vαAnd the mineral material entry velocity vβIs constant and non-adjustable, and therefore cannot resist changes in the conditions of entry into the mineAnd environmental disturbances, the quality of the flotation froth produced will be uneven, and when the quality of the flotation froth is poor, low mineral extraction will result.
Experiments show that the rotational speeds v of the different mixing impellersγAir intake velocity vαAnd the mineral material entry velocity vβThe quality of the flotation froth produced under the conditions was not the same.
The invention controls the air inlet speed, the mineral aggregate conveying speed and the rotating speed of the stirring impeller by additionally arranging an air regulating valve, a mineral aggregate regulating valve and a motor driver so that the rotating speed v of the stirring impellerγAir intake velocity vαAnd the mineral material entry velocity vβCan be adjusted, the flotation froth quality can be better under proper parameter values by adjusting the equipment parameters to cause the flotation froth to correspondingly change.
According to the method, a mapping model for foam generation is established according to experimental data, the optimal solution matching algorithm based on least square is utilized to judge the corresponding variable quantity of each parameter according to the image characteristic difference of the flotation foam, better flotation foam can be obtained by automatically adjusting equipment parameters when the ore entering condition and the environment change, and the total recovery rate of minerals is improved by 1-2%.
Disclosure of Invention
In order to overcome the disadvantages of the prior art, the invention provides a control system for improving the quality of flotation froth by adjusting the rotating speed v of a stirring impellerγAir intake velocity vαAnd the mineral material entry velocity vβThe quality of the flotation froth tends to be better.
The technical scheme adopted by the invention is as follows:
the control device comprises a controller, an air inlet valve, a mineral aggregate adjusting valve, a motor driver, a motor, an industrial camera, a stirring impeller and a flotation tank, wherein the flotation tank is cylindrical or cuboid, the side surface of the flotation tank is provided with a mineral aggregate inlet, the stirring impeller is horizontally arranged at the bottom of the flotation tank and driven by the motor, the motor driver controls the rotating speed of the motor according to a control signal of the controller, and the rotating speed of the stirring impeller is adjustedvγThe outlet of the air inlet device is connected with an air conveying pipeline through an air regulating valve, the tail end of the air conveying pipeline is arranged in the center of a stirring impeller at the bottom of the flotation tank, air is conveyed to the bottom of the flotation tank through the air conveying pipeline, mineral aggregate is connected to the mineral aggregate inlet through the mineral aggregate regulating valve, the air regulating valve and the mineral aggregate regulating valve respectively control the air inlet speed and the mineral aggregate conveying speed through opening degrees, the two valves are electrically operated valves, the opening degrees control signals from a controller, and the opening degree of the air regulating valve is ηαCoefficient of valve kαAir flow rate vα=kαηαThe opening of the mineral aggregate regulating valve is ηβCoefficient of valve kβAt a mineral flow rate vβ=kβηβ(ii) a The industrial camera is installed above the flotation tank and is connected to the input end of the controller through a video coaxial cable, and the output end of the controller is respectively connected to the motor driver, the air-conditioning electric valve and the mineral aggregate-conditioning electric valve.
An image X of the foam collected by the industrial camera is sent to a controller for feature analysis, and the result of the feature analysis is D ═ ξ1ξ2... ξn]Wherein ξnFor the nth feature variable extracted from the image, the optimal froth image expected in the flotation process is characterized by Dm=[ξ1mξ2m... ξnm]The difference Δ D between the two is D-Dm。
The controller calculates an optimal control strategy according to the delta D and outputs a control signal vα、vβAnd vγThe rotation speed, the air inlet speed and the mineral material inlet speed of the stirring impeller are controlled, mineral materials and appropriate amount of air are stirred and mixed through the stirring impeller to generate bubbles, the bubbles move upwards and are gathered on the surface of the liquid to form a flotation foam layer, and then excellent flotation foam is obtained.
The control flow steps of the invention are as follows:
step 1: the rotation speed of a motor, the opening of an air inlet valve and the opening of a mineral aggregate valve of the flotation device are continuously adjusted for 1000 times, and image data are recorded at the same timeFlow rate v of mineral materialβ(t) air flow velocity vα(t) and the rotational speed v of the stirrerγ(t)。
Step 2: extracting image dataImage feature ofRespectively with the optimal image characteristics DmAre subtracted to obtain
And step 3: according to data vα(t) obtaining Δ vα(t) of (d). Wherein:
Δvβ(t) and Δ vγ(t) is the same as the above formula.
And 4, step 4: according to a databaseMapping corresponding data to obtain a foam generation mapping modelIs expressed as Δ D ═ f (Δ v)α,Δvβ,Δvγ) (ii) a The function is a complex non-linear mapping relationship.
And 5, sending the zinc flotation froth image X obtained by the industrial camera into a controller to extract a characteristic D ═ ξ1ξ2...ξn]The process is Φ (), where D ═ Φ (X).
Step 6: the controller is based on Δ D ═ D-DmAnd the mapping relation is reversely deduced to obtainActually function solving. The solving process adopts an optimal solution matching algorithm based on least square, and the specific process is as follows:
s 1: in Data setCorrelation coefficient ρ with current data Δ DtAnd t represents the number of the t-th group of data in the data set.
s 2: the last 3 columns of Data J [ Delta v ] in Data corresponding to the first 3 groups of Data with the correlation coefficients arranged from large to small are calculatedαΔvβΔvγ]。
s 3: solving a least squares matching solution, i.e. min (J)2),J2Is determined by the following formula:
J2=J·JT=(Δvα)2+(Δvβ)2+(Δvγ)2
s4:min(J2) The corresponding data is the final result, and the significance is to reduce the flow velocity v of the mineral aggregate controlled by the controller as much as possible on the premise of ensuring that the characteristic difference is most similar to the data setβ(t) air flow velocity vα(t) and the rotational speed v of the stirrerγ(t) amount of change in output [ Δ v [ ]αΔvβΔvγ]。
And 7: controller calculates the result multiplied byAnd obtaining the corresponding valve opening and the change of the stirring impeller speed to output a control signal.
And 8: the change of the valve opening and the stirring impeller speed causes the corresponding change of the flotation froth, and the froth quality becomes better.
Step 9: and jumping to the step 5 and repeatedly executing.
Compared with the prior art, the invention utilizes the motor and the electric regulating valve to ensure that the rotating speed v of the stirring impellerγAir intake velocity vαAnd the mineral material entry velocity vβThe method can adjust and utilize experimental data to establish a mapping model, and adopts an optimal solution matching algorithm based on least square according to the floatingThe image characteristic difference of the flotation foam is solved from the mapping model to obtain the corresponding variable quantity of each parameter, so that the equipment parameters are adjusted to ensure that the flotation foam quality is more excellent, and the total recovery rate of minerals is improved by more than 5 percent under the condition of ensuring that the concentrate taste meets the requirements and the dosing cost is not changed.
Drawings
FIG. 1 is a block diagram of the apparatus of the present invention;
FIG. 2 is a flow chart of a control method of the present invention.
Reference numerals: 1-controller, 2-industrial camera, 3-motor driver, 4-motor, 5-air regulating valve, 6-mineral aggregate regulating valve, 7-stirring impeller, 8-flotation tank, 9-flotation foam layer, 10-air inlet device, 11-mineral aggregate, 12-concentrate, 13-tailing, 14-air conveying pipeline.
Detailed Description
In order to more fully explain the structure, flow and advantages of the present invention, the following description is further provided in conjunction with the accompanying drawings and examples.
The system structure is shown in figure 1, the quality of the flotation froth largely determines the extraction rate of mineral flotation, and the quality of the flotation froth can be judged through froth images.
The control device comprises a controller 1, an air inlet valve 5, a mineral aggregate adjusting valve 6, a motor driver 3, a motor 4, an industrial camera 2, a stirring impeller 7 and a flotation tank 8, wherein the flotation tank 8 is cylindrical or cuboid, the side surface of the flotation tank is provided with a mineral aggregate inlet, the stirring impeller 7 is horizontally arranged at the bottom of the flotation tank and driven by the motor 4, the motor driver 3 controls the rotating speed of the motor 4 according to a control signal of the controller 1, and the rotating speed v of the stirring impeller 7 is adjustedγ(ii) a The outlet of the air inlet device 10 is connected with an air conveying pipeline 14 through an air regulating valve 5, the tail end of the air conveying pipeline 14 is arranged in the center of a stirring impeller 7 at the bottom of a flotation tank 8, and air is conveyed to the bottom of the flotation tank through the air conveying pipeline 14; the mineral aggregate is connected to the mineral aggregate inlet through the mineral aggregate adjusting valve 6, the air inlet speed and the mineral aggregate conveying speed are respectively controlled through the opening degree of the air adjusting valve 5 and the mineral aggregate adjusting valve 6, and the two valves are electric valvesThe opening degree of the air adjusting valve 5 is ηαCoefficient of valve kαAir flow rate vα=kαηαThe opening degree of the mineral aggregate adjusting valve 6 is ηβCoefficient of valve kβAt a mineral flow rate vβ=kβηβ(ii) a The industrial camera 2 is arranged above the flotation tank 8 and is connected to the input end of the controller 1 through a video coaxial cable, the output end of the controller 1 is respectively connected to the motor driver 3, the air adjusting electric valve 5 and the mineral aggregate adjusting electric valve 6, 9 is a flotation foam layer, 11 is mineral aggregate, 12 is concentrate, and 13 is tailings.
An image X of the foam collected by the industrial camera 2 is sent to the controller 1 for feature analysis, and the result of the feature analysis is D ═ ξ1ξ2... ξn]Wherein ξnFor the nth feature variable extracted from the image, the optimal froth image expected in the flotation process is characterized by Dm=[ξ1mξ2m... ξnm]The difference Δ D between the two is D-Dm。
The controller calculates an optimal control strategy according to the delta D and outputs a control signal vα、vβAnd vγThe rotation speed, the air inlet speed and the mineral feeding speed of the stirring impeller 7 are controlled, mineral materials and appropriate amount of air are stirred and mixed by the stirring impeller 7 to generate bubbles, and the bubbles move upwards to be gathered on the surface of the liquid to form a flotation foam layer 9, so that excellent flotation foam is obtained.
According to the flotation froth generation process of the zinc roughing tank as an example, as shown in fig. 2, the specific flow is as follows:
step 1: the rotation speed of a motor, the opening of an air inlet valve and the opening of a mineral aggregate valve of a zinc roughing tank device are continuously adjusted for 1000 times, and image data are recorded at the same timeFlow rate v of mineral materialβ(t) air flow velocity vα(t) and the rotational speed v of the stirrerγ(t), 1000 sets of data were finally obtained.
Step 2: extracting image dataImage feature ofRespectively with the optimal image characteristics DmAre subtracted to obtainHere, 3 features including foam size, gray scale and entropy are selected as main discriminating features. The 3 characteristics have a key effect on judging the quality of the zinc flotation froth, the quality of the zinc flotation froth can be most obviously represented, and for the flotation of other minerals, 3 or more other key characteristics can be selected according to different flotation minerals for distinguishing.
And step 3: according to data vα(t) obtaining Δ vα(t) of (d). Wherein:
Δvβ(t) and Δ vγ(t) the same as the above formula;
and 4, step 4: according to a databaseMapping corresponding data to obtain a foam generation mapping modelIs expressed as Δ D ═ f (Δ v)α,Δvβ,Δvγ) (ii) a The function is a complex nonlinear mapping relation;
and 5, sending the zinc flotation froth image X obtained by the industrial camera into a controller to extract a characteristic D ═ ξ1ξ2...ξn]The process is Φ (), wherein D ═ Φ (X);
step 6: the controller is based on Δ D ═ D-DmAnd the mapping relation is reversely deduced to obtainIn effect, a function solution. The solving process adopts an optimal solution matching algorithm based on least square, and the specific process is as follows:
s 1: in Data setCorrelation coefficient ρ with current data Δ DtAnd t represents the number of the t-th group of data in the data set;
s 2: the last 3 columns of Data J [ Delta v ] in Data corresponding to the first 3 groups of Data with the correlation coefficients arranged from large to small are calculatedαΔvβΔvγ];
s 3: solving a least squares matching solution, i.e. min (J)2),J2Is determined by the following formula:
J2=J·JT=(Δvα)2+(Δvβ)2+(Δvγ)2
s4:min(J2) The corresponding data is the final result, and the significance is to reduce the flow velocity v of the mineral aggregate controlled by the controller as much as possible on the premise of ensuring that the characteristic difference is most similar to the data setβ(t) air flow velocity vα(t) and the rotational speed v of the stirrerγ(t) amount of change in output [ Δ v [ ]αΔvβΔvγ];
And 7: controller calculates the result multiplied byObtaining corresponding valve opening and the change output control signal of the speed of the stirring impeller;
and 8: the change of the valve opening and the speed of the stirring impeller causes the flotation froth to generate corresponding change, and the froth quality becomes more excellent;
and step 9: and jumping to the step 5 and repeatedly executing.
The present invention is not limited to the above-described embodiments, and other structural designs that are the same as or similar to the above-described embodiments of the present invention are within the scope of the present invention.
Claims (3)
1. A control device for improving the quality of flotation froth is characterized in that: the device comprises a controller (1), an air inlet valve (5), a mineral aggregate adjusting valve (6), a motor driver (3), a motor (4), an industrial camera (2), a stirring impeller (7) and a flotation tank (8), wherein the flotation tank (8) is cylindrical or rectangular, a mineral aggregate inlet is formed in the side surface of the flotation tank, the stirring impeller (7) is horizontally arranged at the bottom of the flotation tank and driven by the motor (4), the motor driver (3) controls the rotating speed of the motor (4) according to a control signal of the controller (1), and the rotating speed v of the stirring impeller (7) is adjustedγThe outlet of the air inlet device (10) is connected with an air conveying pipeline (14) through an air adjusting valve (5), the tail end of the air conveying pipeline (14) is arranged in the center of a stirring impeller (7) at the bottom of a flotation tank (8), air is conveyed to the bottom of the flotation tank through the air conveying pipeline (14), mineral aggregate is connected to an inlet of the mineral aggregate through a mineral aggregate adjusting valve (6), the air adjusting valve (5) and the mineral aggregate adjusting valve (6) respectively control air inlet speed and mineral aggregate conveying speed through opening degrees, the two valves are electric valves, the opening degrees control signals from a controller (1), and the opening degree of the air adjusting valve (5) is ηαCoefficient of valve kαAir flow rate vα=kαηαThe opening degree of the mineral aggregate adjusting valve (6) is ηβCoefficient of valve kβAt a mineral flow rate vβ=kβηβ(ii) a The industrial camera (2) is arranged above the flotation tank (8) and is connected to the input end of the controller (1) through a video coaxial cable, and the output end of the controller (1) is respectively connected to the motor driver (3), the air conditioning electric valve (5) and the mineral aggregate conditioning electric valve (6).
2. A control method of a control device for upgrading flotation froth according to claim 1, characterized by comprising the steps of:
step 1: adjusting the rotation speed of a motor, the opening of an air inlet valve and the opening of a mineral aggregate valve of the flotation device for 1000 times continuously, and recording image dataFlow rate v of mineral materialβ(t) air flow velocity vα(t) and the rotational speed v of the stirrerγ(t); t 1,2, 3.. and 1000 are integers, which represent the sampling order;representing image data obtained by the t-th sampling; v. ofβ(t) represents the flow rate of the mineral aggregate obtained by the sampling at the t time; v. ofα(t) represents the air flow rate obtained by the t-th sampling; v. ofγ(t) the rotating speed of the stirring impeller obtained by the sampling at the t-th time is represented;
step 2: extracting image dataImage feature matrix ofξn(t) is image data obtained from the t-th samplingThe value of the nth characteristic variable extracted in (a); taking t as 1,2,3, 1000, and sampling the image data obtained from the t-th samplingCorresponding image feature matrixAnd the optimal image feature matrix Dm=[ξ1mξ2m...ξnm]Subtracting to obtain a feature difference matrix
And step 3: according to the velocity v of the air flowα(t) obtaining a variation Deltav of the air flow rateα(t):
The change delta v of the flow velocity of the mineral aggregate is obtained by the same methodβ(t) and the variation Deltav of the rotational speed of the impellerγ(t):
And 4, step 4: establishing a flotation froth reference database Data ═ TD V, TD representing an image characteristic difference database, V representing an equipment parameter change database, and TD and V respectively defined as:
the flotation froth reference database Data comprises 1000 groups of Data in common, and TD and V correspondingly form a mapping relation line by line and are marked as f ();
and 5, extracting a current image characteristic matrix D (ξ) from current flotation froth image data X obtained by the industrial camera by using a controller1ξ2...ξn];
Step 6: calculating a current image characteristic matrix D and an optimal image characteristic matrix Dm=[ξ1mξ2m...ξnm]Is given as D-DmThe controller performs inverse solution according to the current characteristic difference matrix delta D and the flotation froth reference database DataAn optimal solution matching algorithm based on least square is adopted, and the specific flow is as follows:
s 1: finding T in flotation froth reference database DataD, the correlation coefficient rho of each group of data of the D and the current characteristic difference matrix Delta Dt,ρtRepresenting the t-th group of data in the image feature difference database TD, i.e. the feature difference matrixCorrelation coefficients with the current feature difference matrix Δ D;
s 2: correlation coefficient ρtArranging from big to small; the first 3 data are ρi、ρjAnd ρkThe parameter change data matrix in the equipment parameter change database V is corresponding to:
Ji=[Δvα(i) Δvβ(i) Δvγ(i)]
Jj=[Δvα(j) Δvβ(j) Δvγ(j)]
Jk=[Δvα(k) Δvβ(k) Δvγ(k)]
Ji、Jjand JkRespectively representing the ith, j and k groups of data of the equipment parameter change database V, namely a matrix consisting of air flow velocity change data, mineral aggregate flow velocity change data and stirring pinch roller rotating speed change data obtained by sampling calculation for the ith, j and k times;
s 3: solving least square matching solution J ═ Δ vαΔvβΔvγ],J=JiOr J ═ JjOr J ═ JkAnd J satisfies J2=min(Ji 2,Jj 2,Jk 2),J2、Ji 2、Jj 2And Jk 2Is determined by the following formula:
J2=J·JT=(Δvα)2+(Δvβ)2+(Δvγ)2
Ji 2=Ji·Ji T=[Δvα(i)]2+[Δvβ(i)]2+[Δvγ(i)]2
Jj 2=Jj·Jj T=[Δvα(j)]2+[Δvβ(j)]2+[Δvγ(j)]2
Jk 2=Jk·Jk T=[Δvα(k)]2+[Δvβ(k)]2+[Δvγ(k)]2
s 4: the least square matching solution J obtained by s3 is the final result of the equipment parameter change data matrix, and J comprises three variables which respectively correspond to the variation of the mineral aggregate flow rate, the air flow rate and the stirring impeller rotation speed;
and 7: the controller calculates the value of [ Δ v ] according to the calculation result of step 6αΔvβΔvγ]Multiplying coefficient matrixObtaining corresponding valve opening and the change of the speed of the stirring impeller to output a control signal;
and 8: the air regulating valve, the mineral aggregate regulating valve and the motor driver receive control signals to regulate the opening of the valve and the speed of the stirring impeller so as to cause the flotation froth to generate corresponding changes;
and step 9: and jumping to the step 5 and repeatedly executing.
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CN111709942B (en) * | 2020-06-29 | 2022-04-12 | 中南大学 | Zinc flotation dosing amount prediction control method based on texture degree optimization |
CN113731645A (en) * | 2021-09-07 | 2021-12-03 | 招金矿业股份有限公司大尹格庄金矿 | Froth flotation concentrate scraping system |
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