A Smart Control Method for Slurry Level in Flotation Process

Abstract

This invention relates to an intelligent control method for slurry level in a flotation process, belonging to the field of mineral separation technology, and solves the problem of unsatisfactory control effect of existing slurry level control methods in flotation processes. The method includes: extracting and normalizing historical data from historical flotation processes to construct a historical database; during a single flotation process control operation, at each sampling moment, performing the following steps: collecting and normalizing measured data, performing nearest neighbor matching between the normalized measured data and each normalized historical data in the historical database to obtain the normalized nearest neighbor historical data; obtaining the upper and lower limits of valve opening at the corresponding sampling moment based on the normalized measured data and the normalized nearest neighbor historical data; at each control moment, performing the following steps: obtaining a control signal for valve opening based on the normalized liquid level height, normalized liquid level target value, and upper and lower limits of valve opening from the normalized measured data, to control the valve opening of the discharge valve.

Description

Technical Field

[0001] This invention relates to the field of mineral sorting technology, and in particular to an intelligent control method for the pulp level in a flotation process. Background Technology

[0002] Flotation technology is the most economical and effective method for separating fine minerals. The height of the pulp level in the flotation machine has a significant impact on the concentrate grade and recovery rate. If the pulp level is too high, some pulp will easily enter the concentrate product, affecting the concentrate grade; if the pulp level is too low, the concentrate froth will have difficulty entering the concentrate cell, leading to a decrease in recovery rate.

[0003] In flotation operations, due to the addition of surfactants such as frothers, collectors, and modifiers, the flotation foam layer is relatively thick, making it difficult for operators to accurately judge the slurry level. Traditional level control mainly relies on the observation and personal experience of flotation operators, which cannot meet the needs of today's refined and information-based industrial production.

[0004] Current flotation liquid level control needs to achieve rapid, automatic, and precise control of the entire process loop, enabling comprehensive monitoring and refined management of flotation parameters. The flotation machine liquid level is affected by factors such as pulp volume and concentration. Currently, in flotation process industrial liquid level control systems, due to the influence of pipeline transmission time on measured variables, there is a certain lag in flotation machine liquid level control, which easily leads to problems such as overshooting and undershooting of the flotation machine liquid level.

[0005] Meanwhile, due to the complexity of factors affecting liquid level in industrial processes and the inability to clearly define quantitative relationships, PID control algorithms are often used in conjunction with liquid level detection systems to achieve liquid level control. However, due to the characteristics of proportional controllers and the delayed effect of flotation machine discharge on liquid level, traditional PID algorithms are not ideal for controlling conditions such as flotation slurry levels that are prone to sudden fluctuations. Summary of the Invention

[0006] Based on the above analysis, the embodiments of the present invention aim to provide an intelligent control method for the pulp level in the flotation process, in order to solve the problems of lag and unsatisfactory control effect of the existing pulp level control methods in the flotation process.

[0007] This invention provides an intelligent control method for pulp level in a flotation process, comprising:

[0008] Historical data is extracted from historical flotation processes and normalized to construct a historical database;

[0009] During the control of a single flotation process, at each sampling moment, the following steps are performed: Measured data is collected and normalized; the normalized measured data is then matched with each normalized historical data in the historical database to obtain the normalized nearest neighbor historical data; based on the normalized measured data and the normalized nearest neighbor historical data, the upper and lower limits of the valve opening at the corresponding sampling moment are obtained; both the historical data and the real-time data include the following elements: valve opening of the drain valve, target liquid level value, liquid level height, slurry flow rate, and slurry concentration; the target liquid level value remains unchanged during the control of the single flotation process.

[0010] During the implementation of this flotation process control, at each control moment, the following steps are performed: based on the normalized liquid level height, normalized liquid level target value, upper limit of valve opening, and lower limit of valve opening in the normalized measured data, the control signal of valve opening is obtained; and based on the control signal of valve opening, the valve opening of the drain valve is controlled.

[0011] Based on the above solution, the present invention also makes the following improvements:

[0012] Furthermore, the nearest historical data is obtained by performing the following operations:

[0013] According to formula (1), the normalized measured data are matched with each normalized historical data in the historical database using the nearest neighbor method:

[0014]

[0015] Among them, L i L represents the normalized measured data at the i-th sampling time. j This represents the j-th normalized historical data entry in the historical database; This represents the m-th element in the normalized measured data at the i-th sampling time. This represents the m-th element in the j-th normalized historical data in the historical database; L represents i and The similarity of the m-th element in the dataset; ω m This indicates the weight of the m-th element; the normalized valve opening, normalized liquid level target value, normalized liquid level height, normalized slurry flow rate, and normalized slurry concentration correspond to the 1st to 5th elements respectively.

[0016] The normalized historical data corresponding to the minimum value of the nearest neighbor matching result is used as the normalized nearest neighbor historical data.

[0017] Furthermore, the upper limit of the valve opening at the i-th sampling time is obtained according to the following formula. and lower limit of valve opening

[0018]

[0019]

[0020] Where L0 represents the normalized nearest historical data, α represents the m-th element in the normalized nearest neighbor historical data; m This represents the correction coefficient for the m-th element.

[0021] Furthermore, the control signal for the valve opening is obtained by performing the following operations:

[0022] The deviation between the normalized liquid level height at the current control moment and the normalized liquid level target value is taken as the liquid level deviation at the current control moment.

[0023] Based on the liquid level deviation at the current control moment and the control signal of the valve opening at the previous control moment, the initial control signal of the valve opening at the current control moment is obtained.

[0024] Based on the relationship between the initial control signal of the valve opening at the current control moment and the upper and lower limits of the valve opening at the current control moment, the control signal of the valve opening at the current control moment is determined.

[0025] Furthermore, the control signal for the valve opening is obtained by performing the following operations:

[0026] Determine the relationship between the initial control signal for the valve opening at the current control moment and the upper and lower limits of the valve opening at the current control moment:

[0027] If the initial control signal is between the upper limit and the lower limit of valve opening, then the initial control signal is used as the control signal for the valve opening at the current control moment.

[0028] If the initial control signal is greater than the upper limit of valve opening, then the upper limit of valve opening is used as the control quantity signal of valve opening at the current control moment;

[0029] If the initial control signal is less than the lower limit of valve opening, then the lower limit of valve opening is used as the control signal for the valve opening at the current control moment.

[0030] Furthermore, based on the liquid level deviation at the current control moment and the control signal of the valve opening at the previous control moment, the initial control signal of the valve opening at the current control moment is obtained, and then executed:

[0031] The kth control time t k The initial control signal U(t) for the valve opening k ):

[0032] U(t k )=U(t k-1 )+ΔU(t k (4)

[0033] Among them, U(t) k-1 ) represents the (k-1)th control time t k-1 The control signal for the valve opening degree;

[0034] ΔU(t k ) = K k ·e(t k (5)

[0035] Among them, K k E(t) represents the proportional coefficient at the k-th control time. k ) represents the k-th control time t k The liquid level deviation, k≥2 and k is an integer; K1 is a preset initial proportional coefficient.

[0036] Furthermore, at the k-th control time t k Liquid level deviation e(t) k ) is represented as:

[0037] e(t k ) = PV(t k )-SP (6)

[0038] Among them, PV(t) k ) represents the normalized liquid level height at the k-th control moment, and SP represents the normalized liquid level target value in this flotation process control.

[0039] Furthermore, the proportional coefficient K at the k-th control time... k Represented as:

[0040]

[0041] Among them, PV(t) k-1 ) represents the normalized liquid level height at the (k-1)th control time.

[0042] Furthermore, the following conditions are met between the (k-1)th and kth control moments:

[0043] t k =t k-1 +T k-1 (8)

[0044] in, T1 is the preset initial control time deviation.

[0045] Furthermore, each control time is consistent with a sampling time.

[0046] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects:

[0047] The intelligent control method for slurry level in the flotation process provided in this embodiment of the invention can obtain the upper limit and lower limit of valve opening at each sampling time based on historical sample data and measured data, thereby realizing the dynamic adjustment of the upper limit and lower limit of valve opening.

[0048] Meanwhile, based on the relationship between the normalized liquid level height and the normalized liquid level target value at two adjacent control moments, the control moment is dynamically determined, thereby achieving better control results by executing fewer control operations.

[0049] During the control process at each control moment, the initial control signal of the valve opening is first calculated, and then the final control signal is determined based on the calculated upper and lower limits of the valve opening to obtain the final control effect. This effectively prevents under-adjustment, over-adjustment, and oscillation phenomena, and achieves advanced and rapid regulation of liquid level under multiple working conditions.

[0050] In summary, the intelligent control method for slurry level in the flotation process provided in this embodiment can effectively solve the problems of lag and unsatisfactory control effect of existing slurry level control methods in the flotation process.

[0051] 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 description or be learned by practicing the invention. The objects and other advantages of this invention can be realized and obtained from what is particularly pointed out in the description and drawings. Attached Figure Description

[0052] 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.

[0053] Figure 1 A flowchart illustrating the intelligent control method for slurry level in the flotation process provided in this embodiment of the invention. Detailed Implementation

[0054] 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.

[0055] A specific embodiment of the present invention discloses an intelligent control method for the pulp level in a flotation process, the flowchart of which is shown below. Figure 1 As shown, it includes the following steps:

[0056] Step S1: Extract historical data from the historical flotation process and normalize it to construct a historical database;

[0057] In this embodiment, the historical data includes the following elements: valve opening degree of the drain valve, target liquid level value, liquid level height, slurry flow rate, and slurry concentration;

[0058] Specifically, during the historical flotation process, historical data can be generated for extraction by performing the following operations:

[0059] Step S11: Set the target liquid level value, adjust the valve opening of the drain valve of the flotation machine, and control the liquid level height of the flotation machine by increasing or decreasing the amount of slurry discharged from the flotation machine;

[0060] Step S12: Real-time detection of liquid level height using a liquid level sensor in the flotation machine;

[0061] It should be noted that the controlled quantity of the liquid level system during the flotation process is the liquid level height, which refers to the vertical distance from the contact surface between the flotation machine foam and the pulp to the contact point between the pulp and the bottom of the flotation machine.

[0062] Step S13: Real-time detection of pulp concentration using a concentration meter in the flotation machine;

[0063] Step S14: Detect the flow rate of the slurry entering the flotation machine in real time using the flow meter in the flotation machine feed pipeline;

[0064] By performing the above steps S11-S14, multiple historical data entries can be obtained.

[0065] Step S2: During the implementation of a flotation process control, at each sampling time, the following steps are performed: collect measured data and normalize it; perform nearest neighbor matching between the normalized measured data and each normalized historical data in the historical database to obtain the normalized nearest neighbor historical data; based on the normalized measured data and the normalized nearest neighbor historical data, obtain the upper limit and lower limit of valve opening at the corresponding sampling time.

[0066] It should be noted that real-time data and historical data include the same elements. Furthermore, after normalization, the elements included in both historical and measured data can be termed: normalized valve opening of the drain valve, normalized target liquid level value, normalized liquid level height, normalized slurry flow rate, and normalized slurry concentration. Simultaneously, the target liquid level value remains unchanged during the primary flotation process control.

[0067] In step S2, the nearest historical data can be obtained by performing the following operations:

[0068] Step S21: According to formula (1), perform nearest neighbor matching between the normalized measured data and each normalized historical data in the historical database:

[0069]

[0070] Among them, L i L represents the normalized measured data at the i-th sampling time. j This represents the j-th normalized historical data entry in the historical database; This represents the m-th element in the normalized measured data at the i-th sampling time. This represents the m-th element in the j-th normalized historical data in the historical database; L represents i and The similarity of the m-th element in the dataset, with a value range of [0,1]. The larger the value, the stronger the similarity of L. i and The more similar the m-th element is, the lower the similarity; conversely, the more similar the elements are, the lower the similarity. ω m The value represents the weight of the m-th element, ranging from 0 to 1; the normalized valve opening, normalized liquid level target value, normalized liquid level height, normalized slurry flow rate, and normalized slurry concentration correspond to the 1st to 5th elements respectively.

[0071] Step S22: Use the normalized historical data corresponding to the minimum value of the nearest neighbor matching result as the normalized nearest neighbor historical data.

[0072] The upper limit of the valve opening at the i-th sampling time can be obtained using the following formula. and lower limit of valve opening

[0073]

[0074]

[0075] Where L0 represents the normalized nearest historical data, α represents the m-th element in the normalized nearest neighbor historical data; m This represents the correction factor for the m-th element. In practice, the correction factor can be set according to the actual situation.

[0076] Step S3: During the implementation of this flotation process control, at each control moment, the following steps are performed: Based on the normalized liquid level height, normalized liquid level target value, upper limit of valve opening, and lower limit of valve opening in the normalized measured data, obtain the control signal of valve opening; and based on the control signal of valve opening, control the valve opening of the drain valve.

[0077] In step S3, the control signal for the valve opening is obtained by performing the following operations:

[0078] Step S31: Take the deviation between the normalized liquid level height at the current control moment and the normalized liquid level target value as the liquid level deviation at the current control moment;

[0079] The kth control time t k Liquid level deviation e(t) k ) is represented as:

[0080] e(t k ) = PV(t k )-SP (4)

[0081] Among them, PV(t) k ) represents the normalized liquid level height at the k-th control moment, and SP represents the normalized liquid level target value in this flotation process control.

[0082] Step S32: Based on the liquid level deviation at the current control moment and the control signal of the valve opening at the previous control moment, obtain the initial control signal of the valve opening at the current control moment.

[0083] The kth control time t k The initial control signal U(t) for the valve opening k ):

[0084] U(t k )=U(t k-1 )+ΔU(t k (5)

[0085] Among them, U(t) k-1 ) represents the (k-1)th control time t k-1 The control signal for the valve opening degree;

[0086] ΔU(t k ) = K k ·e(t k (6)

[0087] Among them, K k E(t) represents the proportional coefficient at the k-th control time. k ) represents the k-th control time t k The liquid level deviation, k≥2 and k is an integer; K1 is a preset initial proportional coefficient.

[0088] Here, the proportional coefficient K at the k-th control time is... k Represented as:

[0089]

[0090] Among them, PV(t) k-1 ) represents the normalized liquid level height at the (k-1)th control time.

[0091] The following condition is satisfied between the (k-1)th and kth control moments:

[0092] t k =t k-1 +T k-1 (8)

[0093] in, T1 is the preset initial control time deviation.

[0094] In the specific implementation process, firstly, determine the first control time t1. Substitute t1 and T1 into formula (8) to obtain the second control time t2. Then, substitute k=2 into the formula. Right now Then, the third control time t3 can be obtained according to Formula 8. This process is repeated for each subsequent control time.

[0095] It is important to emphasize that, in the specific implementation of this embodiment, it is necessary to ensure that corresponding measured data exists at each control moment to obtain the upper and lower limits of valve opening at that control moment, and to calculate the control signal based on the normalized liquid level height at that control moment. Therefore, it is necessary to ensure that each control moment is consistent with a sampling moment. In specific implementation, the precision of the control moment and the sampling moment can be set to be consistent to ensure the above requirements. For example, the sampling moment interval is set to 0.01s, and the control moment value is retained to two decimal places to ensure that each control moment is consistent with a sampling moment.

[0096] In the above implementation process, the next control time can be determined based on the normalized liquid level height of two adjacent control times and the normalized liquid level target value, thereby achieving the adjustability of the control process. According to the formula... It can be known that:

[0097] If PV(t) k-1 )-SP>PV(t k )-SP, indicating t k A better control effect at the control timing point results in a level closer to the normalized target liquid level. In this case, it is necessary to increase the control timing deviation T. k This extends the time interval between two control moments. Conversely, it indicates that t... k If the control effect at the control time is poor and deviates further from the normalized liquid level target value, then it is necessary to reduce the control time deviation T. k This shortens the time interval between two control moments.

[0098] By controlling the time interval, better control can be achieved with fewer control operations.

[0099] Step S33: Based on the relationship between the initial control signal of the valve opening at the current control moment and the upper and lower limits of the valve opening at the current control moment, determine the control signal of the valve opening at the current control moment. Specifically:

[0100] Determine the relationship between the initial control signal for the valve opening at the current control moment and the upper and lower limits of the valve opening at the current control moment:

[0101] Step S331: If the initial control signal is between the upper limit of valve opening and the lower limit of valve opening, then the initial control signal is used as the control signal for the valve opening at the current control moment;

[0102] Step S332: If the initial control signal is greater than the upper limit of valve opening, then the upper limit of valve opening is used as the control quantity signal of valve opening at the current control moment;

[0103] Step S333: If the initial control signal is less than the lower limit of valve opening, then the lower limit of valve opening is used as the control quantity signal of valve opening at the current control moment.

[0104] Once the control signal of the valve opening at the current control moment is obtained, the valve opening of the drain valve can be controlled based on the control signal of the valve opening, effectively preventing under-adjustment, over-adjustment and oscillation, and realizing advanced and rapid regulation of liquid level under multiple working conditions.

[0105] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware, and the program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0106] 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 method for intelligent control of slurry level in a flotation process, characterized in that, include: Historical data is extracted from historical flotation processes and normalized to construct a historical database; During the control of a single flotation process, at each sampling moment, the following steps are performed: Measured data is collected and normalized; the normalized measured data is then matched with each normalized historical data in the historical database to obtain the normalized nearest neighbor historical data; based on the normalized measured data and the normalized nearest neighbor historical data, the upper and lower limits of the valve opening at the corresponding sampling moment are obtained; both the historical data and the real-time data include the following elements: valve opening of the drain valve, target liquid level value, liquid level height, slurry flow rate, and slurry concentration; the target liquid level value remains unchanged during the control of the single flotation process. During the implementation of this flotation process control, at each control moment, the following steps are performed: based on the normalized liquid level height, normalized liquid level target value, upper limit of valve opening, and lower limit of valve opening in the normalized measured data, the control quantity signal of valve opening is obtained; and based on the control quantity signal of valve opening, the valve opening of the drain valve is controlled. According to the following formula, the first... Upper limit of valve opening at each sampling time and lower limit of valve opening : （1） （2） in, This represents the normalized nearest-neighbor historical data. Represents the first nearest neighbor in the normalized historical data. Item element; Indicates the first The first normalized measured data at the sampling time point Item element; Indicates the first Correction factor for the item element; The control signal for valve opening is obtained by performing the following operations: The deviation between the normalized liquid level height at the current control moment and the normalized liquid level target value is taken as the liquid level deviation at the current control moment. Based on the liquid level deviation at the current control moment and the control signal of the valve opening at the previous control moment, the initial control signal of the valve opening at the current control moment is obtained. Based on the relationship between the initial control signal of the valve opening at the current control moment and the upper and lower limits of the valve opening at the current control moment, the control signal of the valve opening at the current control moment is determined.

2. The intelligent control method for slurry level in the flotation process according to claim 1, characterized in that, The nearest historical data is obtained by performing the following operations: According to formula (3), the normalized measured data are matched with each normalized historical data in the historical database using the nearest neighbor method: （3） in, Indicates the first Normalized measured data at each sampling time, Represents the first in the historical database Normalized historical data; Indicates the first in the historical database The first normalized historical data Item element; express and The first in Similarity of item elements; Indicates the first The weights of the elements; normalized valve opening, normalized target liquid level, normalized liquid level height, normalized slurry flow rate, and normalized slurry concentration correspond to the first to fifth elements respectively; The normalized historical data corresponding to the minimum value of the nearest neighbor matching result is used as the normalized nearest neighbor historical data.

3. The intelligent control method for slurry level in the flotation process according to claim 1 or 2, characterized in that, The control signal for valve opening is obtained by performing the following operations: Determine the relationship between the initial control signal for the valve opening at the current control moment and the upper and lower limits of the valve opening at the current control moment: If the initial control signal is between the upper limit and the lower limit of valve opening, then the initial control signal is used as the control signal for the valve opening at the current control moment. If the initial control signal is greater than the upper limit of valve opening, then the upper limit of valve opening is used as the control quantity signal of valve opening at the current control moment; If the initial control signal is less than the lower limit of valve opening, then the lower limit of valve opening is used as the control signal for the valve opening at the current control moment.

4. The intelligent control method for slurry level in the flotation process according to claim 3, characterized in that, Based on the liquid level deviation at the current control moment and the control signal of the valve opening at the previous control moment, the initial control signal of the valve opening at the current control moment is obtained, and then executed: No. Control time The initial control signal for the valve opening : （4） in, Indicates the first Control time The control signal for the valve opening degree; （5） in, Indicates the first The proportional coefficient at each control moment Indicates the first Control time Liquid level deviation, and It is an integer; This is the preset initial scaling factor.

5. The intelligent control method for slurry level in the flotation process according to claim 4, characterized in that, No. Control time Liquid level deviation Represented as: （6） in, Indicates the first Normalized liquid level height at each control moment This represents the normalized liquid level target value in the control of this flotation process.

6. The intelligent control method for slurry level in the flotation process according to claim 5, characterized in that, No. The proportional coefficient at each control moment Represented as: （7） in, Indicates the first Normalized liquid level height at each control moment.

7. The intelligent control method for slurry level in the flotation process according to claim 6, characterized in that, No. , No. Between control moments, the following conditions must be met: （8） in, , This is the preset initial control time deviation.

8. The intelligent control method for slurry level in the flotation process according to claim 7, characterized in that, Each control moment is consistent with a sampling moment.

Images