Intelligent flotation control system, device and method based on multi-class parameter model

Abstract

The invention provides an intelligent flotation control system, device and method based on a multi-class parameter model, and relates to the technical field of flotation systems.The system comprises a control module, an agent module and a parameter module, and the control module, the agent module and the parameter module are connected with a flotation machine; the parameter module comprises a feeding unit, an ore pulp unit, an air inflation unit, a liquid level unit and a foam unit; the control module is used for acquiring regulation and control parameters in the flotation machine, and the regulation and control parameters comprise a feeding concentration and flow parameter, an ash content parameter, an inflation volume parameter, a liquid level parameter and a thickness parameter of a foam layer; based on a preset chemical adding strategy and the regulation and control parameters, the target chemical adding amount needed by the flotation machine is determined; and the reagent module is controlled to add the target required dosage into the flotation machine, so that real-time monitoring and automatic adjustment of multiple parameters are realized, the flotation efficiency and the product quality are improved, and reagent consumption and environmental pollution are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of flotation systems, and in particular to an intelligent flotation control system, device and method based on a multi-type parameter model. Background Art

[0002] Traditional flotation technology is a physical and chemical process that uses bubbles to separate mineral particles from water. It is mainly operated manually and relies on the experience and technical level of the operator, which results in the flotation effect being greatly affected by human factors and poor stability. With the development of technology, automated flotation technology can achieve real-time monitoring and control of individual parameters of the flotation process. Among them, individual parameters in the flotation process, such as pulp concentration and reagent addition amount, can be obtained through sensors and control systems, and can be regulated to a certain extent.

[0003] The inventors found in their research that the existing automated flotation technology still has the following problems for multi-parameter detection and multi-variable adjustment under complex working conditions: there is no scientific basis for production control, parameter detection is not comprehensive enough, control accuracy is low, control efficiency based on experience is low, and the pollution to the environment is large; the consumption of reagents is unstable, and it is easy to have large reagent consumption and large and unstable indicator errors, and the cost of reagent consumption is high; manual participation is required, the efficiency is low, and the labor force is large; the indicators are unstable, and the production control cannot achieve the maximum economic benefits, which will cause economic losses to the enterprise; the on-site environment is harsh, and the chemical composition of the reagents is harmful to humans, which can easily cause occupational health problems. Summary of the invention

[0004] In view of this, an object of the present invention is to provide an intelligent flotation control system, device and method based on a multi-parameter model to improve flotation efficiency and product quality and reduce reagent consumption and environmental pollution.

[0005] In a first aspect, the present invention provides an intelligent flotation control system based on a multi-type parameter model, comprising:

[0006] A control module, a reagent module and a parameter module, wherein the control module, the reagent module and the parameter module are respectively connected to the flotation machine, and the parameter module comprises a feeding unit, a slurry unit, an aeration unit, a liquid level unit and a foam unit;

[0007] The feeding unit is connected to the control module and the reagent module respectively. The feeding unit is arranged on the flotation feeding pipe and is used to detect the concentration parameters and flow parameters of the feeding material.

[0008] A slurry unit, connected to the control module, is used to detect ash parameters of flotation concentrate and flotation tailings;

[0009] The air filling unit is connected to the control module and the reagent module respectively, and is used to detect the air filling volume parameters of the air filling pipe of each tank in the flotation machine;

[0010] The liquid level unit is connected to the control module and the reagent module respectively, and is used to detect the liquid level parameters of the tailings in the flotation machine;

[0011] The foam unit is connected to the control module and the reagent module respectively, and is used to detect the thickness parameters of the foam layer of each tank in the flotation machine;

[0012] The reagent module is used to determine the initial dosage of the flotation machine based on the reagent dosing control model, where the reagent dosing control model is:

[0013] Output=K p *E+K i *∫Ed t +K d *d E / d t +Base+f(Q gas , H liquid , T foam , C feed , A concentrate , A tailing , W dilution )

[0014] Where, Output is the control signal of the metering pump, K p is the proportional coefficient, E is the error value, K i is the integration coefficient, ∫Ed t is the integral of the deviation, K d is the differential coefficient, d E / d t is the derivative of the deviation, Base is the feedforward value; f is the function; Q gas is the inflation volume parameter; H liquid is the liquid level parameter; T foam is the thickness parameter of the foam layer; C feed is the concentration parameter of the feed; A concentrate is the concentrate ash parameter; A tailing is the tailings ash parameter; W dilution For dilution water volume;

[0015] The control module is used to: obtain the control parameters in the flotation machine, which include the concentration parameter and flow parameter of the feed, ash parameter, aeration parameter, liquid level parameter and thickness parameter of the foam layer; determine the target dosage of the flotation machine based on the preset dosing strategy and control parameters; and control the reagent module to add the target dosage into the flotation machine.

[0016] Optionally, the drug module includes a construction unit, a feedback unit and an optimization unit;

[0017] The construction unit is used to construct a dosing control model based on real-time control parameters and preset dosing strategies;

[0018] The feedback unit is connected with the building unit and is used to correct the feedforward value and the error value in the dosing control model;

[0019] The optimization unit is connected with the construction unit and is used for optimizing the dosing control model based on historical data.

[0020] Optionally, the medicine module further includes a medicine impurity removal unit, an emulsification unit, a medicine barrel and a quantitative addition unit;

[0021] The quantitative adding unit is connected to the reagent barrel and the control module respectively, and is used to add the required amount of reagent to the flotation machine;

[0022] The medicine impurity removal unit is connected to the medicine barrel and is used to remove impurities in the medicine of the required dosage;

[0023] The emulsification unit is connected to the medicine barrel and is used to emulsify the medicine in the required dosage.

[0024] Optionally, the gas charging unit includes a gas flow meter and a first regulating subunit;

[0025] The gas flow meter is arranged in the gas filling pipe of the tank body and connected to the control module, and is used to detect the gas filling amount in the tank body;

[0026] The regulating subunit is connected to the control module and is used to regulate the air intake volume of the inflation pipe based on the air volume in the tank body.

[0027] Optionally, the liquid level unit includes a sensor and a second regulating subunit;

[0028] The sensor is arranged in the tank body and connected to the control module, and is used to detect the liquid level parameters in the tank body;

[0029] The second regulating subunit is connected to the control module, and is used to adjust the liquid level parameters in the tank body based on the liquid level adjustment strategy.

[0030] Optionally, the foam unit includes a laser level gauge and a defoaming subunit;

[0031] The laser level meter is arranged in the tank body and connected to the control module, and is used to detect the thickness of the foam layer in the tank body;

[0032] The defoaming subunit is connected to the control module and is used to eliminate foam when a high liquid level is detected.

[0033] Optionally, the slurry unit includes a detection subunit and an alarm subunit;

[0034] The detection subunit is connected to the control module and is used to obtain the grayscale value of the current tailings and perform rough detection based on the image grayscale algorithm;

[0035] The alarm subunit is connected to the detection subunit and is used to issue corresponding alarms based on the rough detection results.

[0036] Optionally, the feeding unit includes a concentration subunit, a flow subunit and a third regulating subunit;

[0037] The concentration subunit is connected to the control module and is used to detect the concentration parameters of the input material;

[0038] The flow subunit is connected to the control module and is used to detect the flow parameters of the feed;

[0039] The third regulating subunit is arranged on the flotation feed pipe and is connected to the control module for adjusting the concentration parameters of the feed.

[0040] In a second aspect, the present invention provides a control device suitable for an intelligent flotation control system based on a multi-type parameter model, the device comprising:

[0041] The flotation machine comprises a plurality of tank bodies, a foam mechanism and a liquid level mechanism, wherein the foam mechanism and the liquid level mechanism are arranged in the tank body;

[0042] A medicine mechanism, the medicine mechanism includes a medicine unit and a medicine barrel, the medicine barrel is connected to the flotation machine through the medicine unit, and is used to determine the initial required dosage of the flotation machine based on the medicine dosing control model;

[0043] The slurry mechanism is connected to the flotation machine through a slurry unit and is used to detect the concentration parameters and flow parameters of the feed;

[0044] Slurry ash analyzer, which is connected to the flotation machine through a slurry unit and is used to detect the ash parameters of flotation concentrate and flotation tailings;

[0045] An air filling mechanism, which is connected to the flotation machine through an air filling unit and is used to detect the air filling volume parameters of the air filling pipe of each tank in the flotation machine;

[0046] The controller is respectively connected with the flotation machine, the reagent mechanism, the slurry mechanism, the slurry ash meter, the aeration mechanism, the foam mechanism and the liquid level mechanism. The controller is used to: obtain the control parameters in the flotation machine, the control parameters include the concentration parameter and flow parameter of the feed, the ash parameter, the aeration parameter, the liquid level parameter and the thickness parameter of the foam layer; determine the target dosage of the flotation machine based on the preset dosage strategy and the real-time control parameters; control the reagent module to add the target dosage into the flotation machine.

[0047] In a third aspect, the present invention further provides a control method for a control module in an intelligent flotation control system based on a multi-type parameter model, the method comprising:

[0048] Real-time acquisition of control parameters in the flotation machine, including feed concentration parameters and flow parameters, ash parameters, aeration parameters, liquid level parameters and thickness parameters;

[0049] Determine the required dosage of the flotation machine based on the preset dosing strategy and real-time control parameters;

[0050] Control the reagent module to add the target required dosage into the flotation machine.

[0051] The intelligent flotation control system, device and method based on multi-type parameter models provided by the present invention are connected to the flotation machine through a control module, a reagent module and a parameter module, and the control module, the reagent module and the parameter module are respectively connected to the flotation machine, and the parameter module includes a feed unit, a slurry unit, an aeration unit, a liquid level unit and a foam unit; the feed unit is respectively connected to the control module and the reagent module, and the feed unit is arranged on the flotation feed pipe to detect the concentration parameter and flow parameter of the feed; the slurry unit is connected to the control module to detect the ash parameters of the flotation concentrate and the flotation tailings; the aeration unit is respectively connected to the control module and the reagent module to detect the aeration volume parameter of the aeration pipe of each tank in the flotation machine; the liquid level unit is respectively connected to the control module and the reagent module The control module is used to detect the liquid level parameters of the tailings in the flotation machine; the foam unit is connected to the control module and the reagent module respectively, and is used to detect the thickness parameters of the foam layer of each tank in the flotation machine; the reagent module is used to determine the initial required dosage of the flotation machine based on the dosing control model; the control module is used to: obtain the control parameters in the flotation machine, the control parameters include the concentration parameter and flow parameter of the feed, the ash parameter, the inflation volume parameter, the liquid level parameter and the thickness parameter of the foam layer; determine the required dosage of the flotation machine based on the preset dosing strategy and control parameters; control the reagent module to add the required dosage of the target into the flotation machine, thereby realizing real-time monitoring and automatic adjustment of multiple parameters, improving flotation efficiency and product quality, and reducing reagent consumption and environmental pollution.

[0052] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0054] Figure 1 A schematic diagram of the structure of an intelligent flotation control system based on a multi-type parameter model provided by an embodiment of the present invention is shown;

[0055] Figure 2 A schematic diagram of the structure of an intelligent flotation control device based on a multi-type parameter model provided by an embodiment of the present invention is shown;

[0056] Figure 3 A schematic flow chart of an intelligent flotation control method based on a multi-type parameter model provided in an embodiment of the present invention is shown;

[0057] Figure 4 A schematic structural diagram of an electronic device provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present invention.

[0059] Flotation technology is an important means to improve recovery rate and reduce environmental pollution in the development of mineral resources. Its effect is affected by many factors, including feed concentration, flow rate, concentrate tailings ash content, foam layer thickness, flotation level and aeration volume. The traditional flotation process relies on manual experience and offline detection, and has problems such as large errors, low efficiency and high cost. Based on this, the embodiment of the present invention provides an intelligent flotation control system, device and method based on a multi-parameter model, which can realize real-time monitoring and automatic adjustment of parameters such as feed concentration, flow rate, concentrate tailings ash content, foam layer thickness, flotation level and aeration volume, improve flotation efficiency and product quality, and reduce reagent consumption and environmental pollution.

[0060] Figure 1 The present invention provides a schematic diagram of a multi-parameter model-based intelligent flotation control system, which can be widely used in flotation processes in the fields of coal, metal minerals, and chemical industry. Figure 1As shown, the system mainly includes: a control module, a reagent module and a parameter module, the control module, the reagent module and the parameter module are respectively connected to the flotation machine, and the parameter module includes a feeding unit, a slurry unit, an aeration unit, a liquid level unit and a foam unit;

[0061] The feeding unit is connected to the control module and the reagent module respectively. The feeding unit is arranged on the flotation feeding pipe and is used to detect the concentration parameters and flow parameters of the feeding material.

[0062] A slurry unit, connected to the control module, is used to detect ash parameters of flotation concentrate and flotation tailings;

[0063] The air filling unit is connected to the control module and the reagent module respectively, and is used to detect the air filling volume parameters of the air filling pipe of each tank in the flotation machine;

[0064] The liquid level unit is connected to the control module and the reagent module respectively, and is used to detect the liquid level parameters of the tailings in the flotation machine;

[0065] The foam unit is connected to the control module and the reagent module respectively, and is used to detect the thickness parameters of the foam layer of each tank in the flotation machine;

[0066] The reagent module is used to determine the initial dosage of the flotation machine based on the reagent dosing control model, where the reagent dosing control model is:

[0067] Output=K p *E+K i *∫Ed t +K d *d E / d t +Base+f(Q gas , H liquid , T foam , C feed , A concentrate , A tailing , W dilution )

[0068] Where, Output is the control signal of the metering pump, K p is the proportional coefficient, E is the error value, K i is the integration coefficient, ∫Ed t is the integral of the deviation, K d is the differential coefficient, d E / d t is the derivative of the deviation, Base is the feedforward value; f is the function; Q gas is the inflation volume parameter; H liquid is the liquid level parameter; T foam is the thickness parameter of the foam layer; C feed is the concentration parameter of the feed; Aconcentrate is the concentrate ash parameter; A tailing is the tailings ash parameter; W dilution For dilution water volume;

[0069] The control module is used to: obtain the control parameters in the flotation machine, which include the concentration parameter and flow parameter of the feed, ash parameter, aeration parameter, liquid level parameter and thickness parameter of the foam layer; determine the target dosage of the flotation machine based on the preset dosing strategy and control parameters; and control the reagent module to add the target dosage into the flotation machine.

[0070] The present invention adjusts the parameters of the reagent module and the parameter module in real time through the control module, thereby realizing real-time monitoring and automatic adjustment of parameters such as feed concentration, flow rate, concentrate tailings ash content, foam layer thickness, flotation liquid level and inflation volume, improving flotation efficiency and product quality, reducing reagent consumption and environmental pollution, and improving flotation efficiency and product quality.

[0071] In an optional embodiment, the drug module includes a construction unit, a feedback unit and an optimization unit;

[0072] The construction unit is used to construct a dosing control model based on real-time control parameters and preset dosing strategies;

[0073] The feedback unit is connected with the building unit and is used to correct the feedforward value and the error value in the dosing control model;

[0074] The optimization unit is connected with the construction unit and is used for optimizing the dosing control model based on historical data.

[0075] Specifically, the drug module provided by the present invention can achieve precise control of drug addition through the following process:

[0076] First, the construction unit is based on a large amount of laboratory and industrial test data to establish a mathematical model between the flotation reagent dosage (that is, the preset dosing strategy) and the concentration parameters and flow parameters of the feed, ash parameters, aeration parameters, liquid level parameters and thickness parameters, and obtain the dosing control model. The mathematical expression of the dosing control model is:

[0077] Output=K p *E+K i *∫Ed t +K d *d E / d t +Base+f(Q gas , H liquid , T foam , C feed , A concentrate , A tailing , Wdilution )

[0078] Where, Output is the control signal of the metering pump, K p is the proportional coefficient, E is the error value, K i is the integration coefficient, ∫Ed t is the integral of the deviation, K d is the differential coefficient, d E / d t is the derivative of the deviation, Base is the feedforward value; f is the function; Q gas is the inflation volume parameter; H liquid is the liquid level parameter; T foam is the thickness parameter of the foam layer; C feed is the concentration parameter of the feed; A concentrate is the concentrate ash parameter; A tailing is the tailings ash parameter; W dilution For dilution water.

[0079] The f parameter function in the dosing control model can be modified according to actual conditions.

[0080] In order to simplify the model, we can assume that the f parameter function is linear, that is:

[0081] f(Q gas , H liquid , T foam , C feed , A concentrate , A tailing , W dilution )

[0082] =∑K i *x i

[0083] Among them, K i is the weight coefficient of each parameter, x i is the corresponding parameter value, i.e. Q gas , H liquid , T foam , C feed , A concentrate , A tailing , W dilution .

[0084] Furthermore, in the present invention, a PID (proportional-integral-differential) control algorithm or a neural network analysis control algorithm can be used to realize automatic dosing control.

[0085] Secondly, the feedback unit corrects the feedforward value and error parameter in the dosing control model according to the real-time ash content parameter of the slurry, thereby forming a closed-circuit flotation intelligent dosing method combining feedforward and feedback. The correction parameter can be adjusted step by step within a reasonable range based on machine learning or equipment debugging to adjust the error parameter and basic feedforward adjustment parameter in the model, so as to obtain a control model that meets the current qualified index requirements;

[0086] Finally, the optimization unit optimizes the dosing control model based on historical data to make its dosing control module more in line with current production conditions. The dosing control model can be matched and optimized based on manually trained data and various data collected daily during the production process. That is, the types of coal with different properties and the dosing control model are matched and matched, and the dosing control model is continuously optimized to achieve precise control, thereby making the dosing control model more adaptable to various production conditions.

[0087] In an optional embodiment, the medicine module further includes a medicine impurity removal unit, an emulsification unit, a medicine barrel and a quantitative addition unit;

[0088] The quantitative adding unit is connected to the reagent barrel and the control module respectively, and is used to add the required amount of reagent to the flotation machine;

[0089] The medicine impurity removal unit is connected to the medicine barrel and is used to remove impurities in the medicine of the required dosage;

[0090] The emulsification unit is connected to the medicine barrel and is used to emulsify the medicine in the required dosage.

[0091] Specifically, the reagent barrel is connected to the flotation machine through a quantitative adding unit. During the reagent adding process, the quantitative adding unit adds the required amount of reagent into the flotation machine according to the instructions issued by the control module. Before adding the reagent to the flotation machine, the reagent removal unit and the emulsification unit are required to remove impurities and emulsify the reagent, thereby achieving precise control of the reagent addition amount, reducing reagent consumption and energy consumption, and improving flotation efficiency.

[0092] In an optional embodiment, the gas charging unit includes a gas flow meter and a first regulating subunit;

[0093] The gas flow meter is arranged in the tank body gas filling pipe and connected to the control module, and is used to detect the gas filling amount in the tank body;

[0094] The regulating subunit is connected to the control module and is used to regulate the air intake volume of the inflation pipe based on the air volume in the tank body.

[0095] Specifically, since the flotation machine completes the mineralization, foaming and mineral sorting of reagents and materials through negative pressure inflation, it is necessary to detect the working conditions of flotation inflation through the inflation unit to determine the matching between the current inflation volume and the current production feed volume, sorting indicators, foam layer, liquid level status, etc., so as to achieve the best inflation range adjustment and ensure the stability of flotation indicators.

[0096] The gas flow meter in the present invention can use an integrated gas mass flow meter, a vortex flow meter or other effective detection devices to measure the inflation volume in real time to ensure that the data is accurate and reliable, wherein a 4-20mA signal can be output to the control module for monitoring; the first regulating subunit adjusts the valve opening parameters of the inflation pipe according to the detection result of the gas flow meter to ensure the stability of the inflation volume, thereby ensuring that the flotation machine is in the optimal inflation range.

[0097] In an optional embodiment, the liquid level unit includes a sensor and a second regulating subunit;

[0098] The sensor is arranged in the tank body and connected to the control module, and is used to detect the liquid level parameters in the tank body;

[0099] The second regulating subunit is connected to the control module, and is used to adjust the liquid level parameters in the tank body based on the liquid level adjustment strategy.

[0100] Specifically, the liquid level unit is mainly used to detect the height of the tailings page of the flotation machine and adjust and control the tailings gate to control the liquid level.

[0101] The sensor of the present invention can use a float rod laser level meter to detect the change of the liquid level in the flotation tank in real time. The level meter is composed of a float, a laser level measuring instrument and a bracket, and can accurately measure the slurry level. The sensor transmits the detected liquid level parameters to the control module, and the control module sends to the second regulating subunit to adjust the slurry feed speed or drainage speed to maintain the stability of the liquid level. The sensor and the flotation machine tailings gate are linked based on a comprehensive logic algorithm. The comprehensive logic algorithm determines the adjustment of the liquid level height based on comprehensive factors such as the detected liquid level height, foam layer thickness, feed conditions, and product ash content. When the detected liquid level height parameter is lower than the threshold, the flotation machine tailings gate is lifted. If the liquid level height parameter is higher than the threshold, the flotation machine tailings gate is lowered. By setting normal threshold protection, control abnormalities caused by abnormal working conditions can be avoided.

[0102] In one possible embodiment, the foam unit includes a laser level meter and a defoaming subunit;

[0103] The laser level meter is arranged in the tank body and connected to the control module, and is used to detect the thickness of the foam layer in the tank body;

[0104] The defoaming subunit is connected to the control module and is used to eliminate foam when a high liquid level is detected.

[0105] Specifically, in the present invention, the liquid level and foam thickness of the slurry in the flotation tank are monitored in real time by using a radar or ultrasonic level meter, and the foam layer thickness information is obtained by calculating the difference between the liquid level and the foam layer thickness, that is, the foam layer thickness is obtained by the difference between the total height of the liquid surface and the foam layer and the liquid surface height. Then, according to the change of the foam layer thickness, the control module automatically adjusts the parameters such as the inflation unit or the stirring speed to optimize the flotation effect.

[0106] Furthermore, the laser level meter of the present invention can adopt a non-contact ultrasonic level meter, a magnetostrictive level meter or a laser radar rangefinder, which can penetrate the foam layer cake to accurately measure its thickness or accurately calculate the foam layer thickness by detecting the foam layer level and the actual flotation level.

[0107] Furthermore, the defoaming subunit of the foam unit is a flushing water device, and a flushing water device is added to the measuring cylinder to eliminate the influence of bubbles and pulp foam on the measurement, wherein the measuring cylinder is used to accurately detect the liquid level. After the foam in the measuring cylinder is defoamed by the defoaming subunit (flushing water device), the liquid level is detected.

[0108] In an optional embodiment, the slurry unit includes a detection subunit and an alarm subunit;

[0109] The detection subunit is connected to the control module and is used to obtain the grayscale value of the current tailings and perform rough detection based on the image grayscale algorithm;

[0110] The alarm subunit is connected to the detection subunit and is used to issue corresponding alarms based on the rough detection results.

[0111] In the present invention, the detection subunit adopts an online slurry ash detector (such as DSIA100), uses X-ray technology to directly detect slurry samples, and obtains ash parameters in real time. Its detection accuracy can reach ±0.25% (σ), meeting the requirements of the flotation system.

[0112] Furthermore, the online detector for slurry ash mainly adopts tailings ash image detection, and performs image recognition detection on flotation tailings to perform grayscale recognition on tailings coal slurry water. Through image grayscale recognition training, it adapts tailings ash detection algorithms based on different types of coal and uses image recognition technology to detect the coarseness of tailings, which can realize coarseness recognition alarm. The alarm threshold of the coarse particle size is set in the alarm subunit. When the coarse particles exceed the threshold, an alarm is issued. The alarm subunit is connected to the control module, and the control module can adjust the alarm threshold of the coarse particle size according to the actual working conditions.

[0113] Furthermore, the tailings ash detection algorithm is to pre-process the coal slime water by image acquisition, noise removal, image enhancement, etc., and extract image features, including color, texture and shape features, and use machine learning algorithms including support vector machine (SVM), artificial neural network (ANN) and adaptive particle swarm optimization (APSO) to identify the image features. Finally, the model combination of the integrated algorithm, such as the use of integrated learning frameworks (such as Bagging, Boosting, etc.) to complete data processing and analysis. Ensure data accuracy through image acquisition and processing, intelligent recognition and analysis algorithms.

[0114] In an optional embodiment, the feeding unit includes a concentration subunit, a flow subunit and a third regulating subunit;

[0115] The concentration subunit is connected to the control module and is used to detect the concentration parameters of the input material;

[0116] The flow subunit is connected to the control module and is used to detect the flow parameters of the feed;

[0117] The third regulating subunit is arranged on the flotation feed pipe and is connected to the control module for adjusting the concentration parameters of the feed.

[0118] Specifically, the concentration subunit in the feed unit is used to detect the concentration parameters of the feed. In the present invention, a concentration sensor, such as an ultrasonic concentration meter, an isotope concentration meter, a photoelectric or double-diaphragm box (pressure difference) concentration meter, etc., is used to measure the concentration of the flotation feed in real time. The concentration sensor can accurately measure the concentration of solid particles in the slurry;

[0119] The concentration sensor transmits the detected concentration data to the control module. The control module compares the actual concentration with the set concentration and adds water or adjusts other parameters through the third regulating subunit to maintain the stability of the feed concentration.

[0120] The flow subunit is used to detect the flow parameters of the feed material. In the present invention, a flow meter, such as an electromagnetic flow meter, an ultrasonic flow meter, or a vortex flow meter, etc., can be used to measure the flow of the slurry;

[0121] The flow meter transmits real-time flow data to the control module, which adjusts the feed speed or pump speed according to the flow data to ensure stable flow.

[0122] In an optional embodiment, the control system further includes a video monitoring module, which is connected to the control module, and each flotation machine is equipped with a video monitoring camera for remotely viewing on-site production conditions.

[0123] In an optional embodiment, the control module mainly provides power distribution, signal control, PLC control system, server system, data acquisition engine, intelligent flotation system server and intelligent flotation system platform for various sensor devices.

[0124] The parameters of various instruments are connected to the intelligent flotation system server for data collection, storage, processing, analysis, calculation and logic control. The intelligent flotation system platform continuously monitors the various parameters in the flotation process through the control system, such as ash content, feed coal slime amount, foam characteristics and other comprehensive information changes, and real-time monitoring of on-site production conditions through cameras. The on-site production screen can be viewed remotely and the dosage of reagents can be adjusted in real time as needed. The intelligent flotation system platform has technical attributes such as PLC system data collection, machine learning algorithms, artificial intelligence, and neural network optimization algorithms.

[0125] Furthermore, the intelligent flotation system platform is connected to the cloud management platform, and the control system can upload real-time data to the cloud for storage and analysis, further optimizing the flotation process, and the system can be remotely viewed and controlled through the mobile terminal. The flotation system platform integrates a variety of high-precision sensors and intelligent control algorithms to achieve real-time monitoring and automatic adjustment of key parameters in the flotation process, thereby improving flotation efficiency and product quality.

[0126] In an optional embodiment, the specific operation steps of the intelligent flotation control system when detecting the slurry are as follows:

[0127] 1. After all equipment is started, set the dosage according to the current production demand;

[0128] 2. Through the reagent module, the set reagent amount is added to the slurry preparation device and each tank of the flotation machine through the quantitative addition unit, the reagent impurity removal unit and the emulsification unit. After impurities are removed and emulsified, the reagent in the reagent barrel is added to the flotation machine;

[0129] 3. The concentration and flow parameters of the material in the flotation machine feed pipe are collected through the feed module, the ash parameters of the material in the concentrate and tailings pipes are collected through the slurry unit, the liquid level parameters in the tank body are detected through the liquid level unit, the inflation volume parameters in the tank body are detected through the inflation unit, and the thickness parameters of the foam layer of the tank body are detected through the foam unit, and the concentration and flow parameters of the feed, ash parameters, liquid level parameters, inflation volume parameters and foam thickness parameters are fed back to the control module;

[0130] 4. The control module determines whether each parameter and reagent meets the current working conditions based on the real-time obtained feed concentration and flow parameters, ash parameters, liquid level parameters, inflation volume parameters and foam thickness parameters and the preset dosing strategy. If not, the control module adjusts each parameter and reagent. If yes, the control module enters the real-time monitoring mode.

[0131] An intelligent flotation machine control system based on a multi-type parameter model provided by an embodiment of the present invention has the following beneficial effects:

[0132] 1. It can realize comprehensive real-time monitoring of key parameters such as feed concentration, flow rate, concentrate tailings ash content, foam layer thickness, flotation level and aeration volume;

[0133] 2. Based on big data and artificial intelligence algorithms, establish a dosing control model and realize automatic adjustment to reduce human intervention and errors;

[0134] 3. By accurately controlling the amount of reagent added and the amount of aeration, the reagent consumption and energy consumption can be reduced and the flotation efficiency can be improved;

[0135] 4. Optimize the flotation process, reduce wastewater and tailings discharge, and reduce environmental pollution.

[0136] Figure 2 A schematic diagram of the structure of an intelligent flotation control device based on a multi-type parameter model provided by an embodiment of the present invention, such as Figure 2 As shown, the device comprises:

[0137] The flotation machine 100 includes a plurality of tank bodies, a foam mechanism and a liquid level mechanism, wherein the foam mechanism and the liquid level mechanism are arranged in the tank body;

[0138] The medicine mechanism 200 includes a medicine unit and a medicine barrel, wherein the medicine barrel is connected to the flotation machine through the medicine unit, and is used to determine the initial required dosage of the flotation machine based on the medicine dosing control model;

[0139] The slurry mechanism 300 is connected to the flotation machine through the slurry unit and is used to detect the concentration parameters and flow parameters of the feed;

[0140] The slurry ash analyzer 400 is connected to the flotation machine through the slurry unit to detect the ash parameters of the flotation concentrate and flotation tailings;

[0141] The inflation mechanism 500 is connected to the flotation machine through the inflation unit and is used to detect the inflation volume parameters of the inflation pipe of each cell in the flotation machine;

[0142] The controller 600 is respectively connected to the flotation machine, the reagent mechanism, the slurry mechanism, the slurry ash meter, the aeration mechanism, the foam mechanism and the liquid level mechanism. The controller is used to: obtain the control parameters in the flotation machine, the control parameters include the concentration parameter and flow parameter of the feed, the ash parameter, the aeration parameter, the liquid level parameter and the thickness parameter of the foam layer; determine the target dosage of the flotation machine based on the preset dosage strategy and the real-time control parameters; control the reagent module to add the target dosage into the flotation machine.

[0143] In a possible embodiment, the device further includes a clean water tank 700, which is connected to the reagent mechanism and is used to adjust the concentration of the reagent, and to add clean water to the slurry mechanism through the reagent mechanism to adjust the concentration of the slurry.

[0144] The device provided in the embodiment of the present application has the same implementation principle and technical effects as those of the aforementioned system embodiment. For the sake of brief description, for matters not mentioned in the device embodiment, reference can be made to the corresponding contents in the aforementioned system embodiment.

[0145] Figure 3 A schematic diagram of the structure of an intelligent flotation control method based on a multi-type parameter model provided by an embodiment of the present invention, such as Figure 3 As shown, the method includes:

[0146] Step S210, obtaining control parameters in the flotation machine, the control parameters including feed concentration parameter and flow parameter, ash parameter, aeration parameter, liquid level parameter and foam layer thickness parameter;

[0147] Step S220, based on the preset dosing strategy and real-time control parameters, determine the dosing amount required for the flotation machine target;

[0148] Step S230: Control the reagent module to add the target required reagent amount into the flotation machine.

[0149] In a possible embodiment, the method further includes:

[0150] Detect ash parameters of flotation concentrate and flotation tailings through slurry unit;

[0151] Detect the inflation volume parameters of the inflation pipe of each cell in the flotation machine through the inflation unit;

[0152] Detect the liquid level parameters of tailings in the flotation machine through the liquid level unit;

[0153] The thickness parameters of the foam layer of each cell in the flotation machine are detected by the foam unit.

[0154] The method provided in the embodiment of the present application has the same implementation principle and technical effects as those in the aforementioned system embodiment. For the sake of brief description, for matters not mentioned in the method embodiment, reference may be made to the corresponding contents in the aforementioned system embodiment.

[0155] like Figure 4 As shown, an electronic device 600 provided in an embodiment of the present application includes: a processor 601, a memory 602 and a bus, the memory 602 stores machine-readable instructions executable by the processor 601, when the electronic device is running, the processor 601 and the memory 602 communicate through the bus, the processor 601 executes the machine-readable instructions to perform the steps of the above-mentioned intelligent flotation control method based on multiple parameter models.

[0156] Specifically, the memory 602 and the processor 601 can be general-purpose memories and processors, which are not specifically limited here. When the processor 601 runs the computer program stored in the memory 602, the intelligent flotation control method based on the multi-type parameter model can be executed.

[0157] The processor 601 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit or software instructions in the processor 601. The above processor 601 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in the embodiments of the present application can be directly embodied as a hardware decoding processor for execution, or a combination of hardware and software modules in the decoding processor for execution. The software module may be located in a storage medium mature in the art, such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 602, and the processor 601 reads the information in the memory 602 and completes the steps of the above method in combination with its hardware.

[0158] Corresponding to the above-mentioned intelligent flotation control method based on a multi-category parameter model, an embodiment of the present application also provides a computer-readable storage medium, which stores machine-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to execute the steps of the above-mentioned intelligent flotation control method based on a multi-category parameter model.

[0159] The intelligent flotation control system based on the multi-class parameter model provided in the embodiment of the present application can be specific hardware on the device or software or firmware installed on the device. The device provided in the embodiment of the present application has the same implementation principle and technical effects as the aforementioned method embodiment. For the sake of brief description, the parts not mentioned in the device embodiment can refer to the corresponding contents in the aforementioned method embodiment. It can be clearly understood by technicians in the relevant field that for the convenience and simplicity of description, the specific working processes of the systems, devices and units described above can all refer to the corresponding processes in the aforementioned method embodiment, and will not be repeated here.

[0160] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0161] For another example, the flowchart and block diagram in the accompanying drawings show the possible architecture, functions and operations of the device, method and computer program product according to multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and a part of the module, program segment or code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0162] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0163] In addition, each functional unit in the embodiments provided in the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0164] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a number of instructions for an electronic device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the vehicle marking method of each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0165] It should be noted that similar numbers and letters represent similar items in the following figures. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. In addition, the terms "first", "second", "third", etc. are only used to distinguish the description and are not to be understood as indicating or implying relative importance.

[0166] Finally, it should be noted that the above embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The protection scope of the present application is not limited thereto. Although the present application is described in detail with reference to the above embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above embodiments within the technical scope disclosed in the present application, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application. They should all be covered within the protection scope of the present application.

Claims

1. An intelligent flotation control system based on a multi-parameter model, characterized in that: include: A control module, a reagent module and a parameter module, wherein the control module, the reagent module and the parameter module are respectively connected to the flotation machine, and the parameter module includes a feeding unit, a slurry unit, an aeration unit, a liquid level unit and a foam unit; The feeding unit is connected to the control module and the reagent module respectively, and the feeding unit is arranged on the flotation feeding pipe to detect the concentration parameter and flow parameter of the feeding material; The slurry unit is connected to the control module and is used to detect ash parameters of flotation concentrate and flotation tailings; The inflation unit is connected to the control module and the reagent module respectively, and is used to detect the inflation volume parameters of the inflation pipe of each cell in the flotation machine; The liquid level unit is connected to the control module and the reagent module respectively, and is used to detect the liquid level parameters of the tailings in the flotation machine; The foam unit is connected to the control module and the reagent module respectively, and is used to detect the thickness parameter of the foam layer of each cell in the flotation machine; The reagent module is used to determine the initial required reagent dosage of the flotation machine based on a reagent dosage control model, wherein the reagent dosage control model is: Output=K p *E+K i *∫Ed t +K d *d E / d t +Base+f(Q gas ,H liquid ,T foam ,C feed ,A concentrate ,A tailing ,W dilution ) Where, Output is the control signal of the metering pump, K p is the proportional coefficient, E is the error value, K i is the integration coefficient, ∫Ed t is the integral of the deviation, K d is the differential coefficient, d E / d t is the derivative of the deviation, Base is the feedforward value; f is the function; Q gas is the inflation volume parameter; H liquid is the liquid level parameter; T foam is the thickness parameter of the foam layer; C feed is the concentration parameter of the feed; A concentrate is the concentrate ash parameter; A tailing is the tailings ash parameter; W dilution For dilution water volume; The control module is used to: obtain the control parameters in the flotation machine, the control parameters include the concentration parameter and flow parameter of the feed, the ash parameter, the inflation volume parameter, the liquid level parameter and the thickness parameter of the foam layer; determine the target dosage required for the flotation machine based on a preset dosage strategy and the control parameters; and control the reagent module to add the target dosage required into the flotation machine.

2. The intelligent flotation control system based on a multi-class parameter model according to claim 1 is characterized in that: The drug module includes a construction unit, a feedback unit and an optimization unit; The construction unit is used to construct a dosing control model based on the real-time control parameters and the preset dosing strategy; The feedback unit is connected to the construction unit and is used to correct the feedforward value and the error value in the dosing control model; The optimization unit is connected to the construction unit and is used to optimize the dosing control model based on historical data.

3. The intelligent flotation control system based on a multi-class parameter model according to claim 1 or 2, characterized in that: The medicine module also includes a medicine impurity removal unit, an emulsification unit, a medicine barrel and a quantitative addition unit; The quantitative addition unit is connected to the reagent barrel and the control module respectively, and is used to add the required amount of reagent to the flotation machine; The medicine impurity removal unit is connected to the medicine barrel and is used to remove impurities in the medicine of the required dosage; The emulsification unit is connected to the medicine barrel and is used to emulsify the medicine with the required dosage.

4. The intelligent flotation control system based on a multi-class parameter model according to claim 1 is characterized in that: The charging unit includes a gas flow meter and a first regulating subunit; The gas flow meter is arranged in the gas filling pipe of the tank body and connected to the control module, and is used to detect the gas filling amount in the tank body; The regulating subunit is connected to the control module and is used to regulate the air intake volume of the inflation pipe based on the air volume in the tank body.

5. The intelligent flotation control system based on a multi-class parameter model according to claim 1 is characterized in that: The liquid level unit includes a sensor and a second regulating subunit; The sensor is disposed in the tank body and connected to the control module, and is used to detect the liquid level parameters in the tank body; The second regulating subunit is connected to the control module, and is used to adjust the liquid level parameters in the tank based on a liquid level adjustment strategy.

6. The intelligent flotation control system based on a multi-parameter model according to claim 1, characterized in that: The foam unit includes a laser level meter and a defoaming subunit; The laser level meter is arranged in the tank body and connected to the control module, and is used to detect the thickness of the foam layer in the tank body; The defoaming subunit is connected to the control module and is used to eliminate foam when a high liquid level is detected.

7. The intelligent flotation control system based on a multi-parameter model according to claim 1 is characterized in that: The slurry unit includes a detection subunit and an alarm subunit; The detection subunit is connected to the control module and is used to obtain the gray value of the current tailings and perform rough detection based on the image gray algorithm; The alarm subunit is connected to the detection subunit and is used to issue a corresponding alarm based on the rough detection result.

8. The intelligent flotation control system based on a multi-parameter model according to claim 1 is characterized in that: The feeding unit includes a concentration subunit, a flow subunit and a third regulating subunit; The concentration subunit is connected to the control module and is used to detect the concentration parameters of the input material; The flow subunit is connected to the control module and is used to detect the flow parameters of the feed; The third regulating subunit is arranged on the flotation feed pipe and connected to the control module, and is used for adjusting the concentration parameters of the feed.

9. A control device for an intelligent flotation control system based on a multi-parameter model as claimed in any one of claims 1 to 8, characterized in that: include: A flotation machine comprises a plurality of tank bodies, a foam mechanism and a liquid level mechanism, wherein the foam mechanism and the liquid level mechanism are arranged in the tank body; A medicine mechanism, the medicine mechanism comprising a medicine unit and a medicine barrel, the medicine barrel being connected to the flotation machine via the medicine unit, and being used to determine the initial required medicine dosage of the flotation machine based on a medicine dosing control model; A slurry mechanism, which is connected to the flotation machine through a slurry unit and is used to detect concentration parameters and flow parameters of the feed; A slurry ash meter, which is connected to the flotation machine through a slurry unit and is used to detect ash parameters of flotation concentrate and flotation tailings; An air filling mechanism, which is connected to the flotation machine via an air filling unit and is used to detect the air filling volume parameters of the air filling pipe of each cell in the flotation machine; A controller is connected to the flotation machine, the reagent mechanism, the slurry mechanism, the slurry ash meter, the aeration mechanism, the foam mechanism and the liquid level mechanism respectively, and the controller is used to: obtain the control parameters in the flotation machine, the control parameters include the concentration parameter and flow parameter of the feed, the ash parameter, the aeration parameter, the liquid level parameter and the thickness parameter of the foam layer; Based on the preset dosing strategy and real-time control parameters, the target dosing amount of the flotation machine is determined; and the reagent module is controlled to add the target dosing amount into the flotation machine.

10. A control method for a control module in an intelligent flotation control system based on a multi-type parameter model as claimed in any one of claims 1 to 8, characterized in that: include: Obtaining control parameters in the flotation machine, wherein the control parameters include a concentration parameter and a flow parameter of the feed material, an ash parameter, an aeration parameter, a liquid level parameter, and a thickness parameter of the foam layer; Determine the target dosage of the flotation machine based on the preset dosage strategy and real-time control parameters; The reagent module is controlled to add the target required reagent amount into the flotation machine.

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