CN110605178A - An intelligent control system and method for dense medium sorting process - Google Patents

Abstract

The invention relates to an intelligent control system and method for a dense medium sorting process, which belongs to the technical field of sorting and processing, and solves the problem that the existing sorting density setting relies heavily on experience and does not comprehensively consider other factors affecting the sorting density, product Quality control lags, problems with human intervention in control systems. The system includes: a first ash measurement device for measuring the ash content of raw coal; a second ash measurement device for real-time measurement of the ash content of clean coal obtained after the raw coal is sorted by circulating media; a production index prediction module for processing the raw coal The ash content and the ash content of the clean coal are used to obtain the set value of the density of the circulating medium; the density adjustment module of the circulating medium adjusts the density of the circulating medium based on the deviation between the set value of the density of the circulating medium and the measured value of the density of the circulating medium. The system effectively reduces the dependence of the sorting density setting process on experience, can make full use of historical data, and improves the timeliness of product quality control.

Description

An intelligent control system and method for dense medium sorting process

technical field

The invention relates to the technical field of sorting and processing, in particular to an intelligent control system and method for a dense medium sorting process.

Background technique

The dense medium coal preparation technology is an important separation technology in the coal preparation industry. It is widely used because of its good separation effect. The density of the dense medium determines the quality of the separation effect, so the separation of the dense medium can be controlled in real time. Density is essential. The density control method of the existing coal preparation plant is to manually set the circulating medium density value of the dense medium system (hereinafter referred to as the set density), and to use the PID algorithm to track the set density to carry out systematic density control; mainly there are the following defects: (1) The setting density is set by the operator, which largely depends on experience and is not necessarily the best; (2) The basis for setting the separation density is only the ash content of the product after inspection, without comprehensive consideration such as the raw coal situation (3) The adjustment of the set density lags behind, because the product quality is a manual inspection at a set time interval, and the value of the online inspection is not enough; therefore, in fact, the product quality control is also lagging behind; ( 4) Density tracking control requires manual remote adjustment of various valves, which affects the control quality.

Contents of the invention

In view of the above analysis, the present invention aims to provide an intelligent control system and method for the dense medium sorting process, which is used to solve the problem that the existing sorting density setting relies heavily on experience and does not comprehensively consider other factors affecting the sorting density, Product quality control lags behind, manual intervention control system problems.

The purpose of the present invention is mainly achieved through the following technical solutions:

An intelligent control system for dense medium sorting process, said system comprising:

The first ash measurement device is used to measure the ash content of raw coal;

The second ash content measurement device is used for real-time measurement of the ash content of the clean coal obtained after the raw coal is sorted by the circulating medium;

The production index prediction module is used to process the ash content of the raw coal and the ash content of the clean coal to obtain the set value of the circulating medium density;

The circulating medium density adjustment module adjusts the circulating medium density based on the deviation between the circulating medium density set value and the circulating medium density measured value.

On the basis of the foregoing scheme, the present invention has also made the following improvements:

Further, the production index prediction module obtains the set value of circulating medium density by performing the following operations:

Based on the real-time detected raw coal ash, clean coal ash, circulating medium density value and historical ups and downs information, the historical ups and downs information is corrected to obtain the ups and downs information at the current moment; based on the ups and downs information at the current moment, a fitting can be obtained Selective curve;

According to the measured value of circulating medium density at the current moment, the ash content of the clean coal and the selectivity curve, the theoretical separation density at the current moment is obtained;

According to the relationship curve between the theoretical sorting density and the circulating medium density, the set value of the circulating medium density at the current moment corresponding to the theoretical sorting density at the current moment is obtained.

Further, obtain the relational curve of described theoretical sorting density and circulating medium density in the following manner:

A plurality of actual circulating medium density values are extracted, corresponding to the clean coal ash content at that time, the corresponding theoretical sorting density is found, and the relationship curve between the theoretical sorting density and the circulating medium density is obtained by fitting.

Further, in the production index prediction module,

When the change value of the clean coal ash output by the second ash measuring device relative to the reference ash value is within the preset ash change range, update the circulating medium according to the relationship curve between the theoretical sorting density and the circulating medium density Density setpoint;

When the change value of the clean coal ash output by the second ash measurement device relative to the reference ash value is not within the preset ash change range, the relationship curve between the theoretical sorting density and the circulating medium density is updated and updated The final circulating medium density setting value.

Further, in the suspension density adjustment module, according to the deviation between the set value of the circulating medium density and the measured value of the circulating medium density, the action of replenishing water, diverting or adding concentrated medium is performed, so that the actual measured density of the circulating medium The value tracks the circulating media density setpoint in real time.

Further, in the suspension density adjustment module,

If the deviation between the set value of the circulating medium density and the measured value of the circulating medium density is Δδ≤0, replenish water to the feeding pipeline, and the amount of replenished water is ΔQ=Δδ/C;

If the deviation Δδ>0 between the set value of the circulating medium density and the measured value of the circulating medium density, then according to the liquid level of each medium barrel detected online and the content of magnetic substances in the circulating medium, a fuzzy control method is used to optimize Make sure to add concentrated medium or divert flow.

Further, it also includes an online evaluation module, which is used to calculate indicators including theoretical yield, actual yield, and quantity efficiency in real time based on the input and product data detected online, and the properties of raw materials provided by the production index prediction module , and carry out online evaluation according to the coal preparation effect evaluation method.

The present invention also provides an intelligent control method for dense medium sorting process, comprising the following steps:

Real-time detection of raw coal ash content, clean coal ash content and circulating medium density value at the current moment, and fitting the optional curve at the current moment;

According to the measured value of circulating medium density at the current moment, the ash content of the clean coal and the selectivity curve, the theoretical separation density at the current moment is obtained;

According to the relationship curve between the theoretical sorting density and the circulating medium density, the set value of the circulating medium density at the current moment corresponding to the theoretical sorting density at the current moment is obtained;

The density of the circulating medium is adjusted based on the deviation between the set value of the circulating medium density and the measured value of the circulating medium density.

On the basis of the foregoing scheme, the present invention has also made the following improvements:

Further, the real-time detection of raw coal ash content, clean coal ash content and circulating medium density value at the current moment, and fitting to obtain the selectability curve at the current moment include:

Based on the real-time detected raw coal ash content, clean coal ash content, circulating medium density value and historical ups and downs information, correct the historical ups and downs information to obtain the ups and downs information at the current moment; based on the ups and downs information at the current moment, fit the current The optionality curve for moments.

Further, the relationship curve between the theoretical sorting density and the circulating medium density is obtained in the following manner: extracting a plurality of actual circulating medium density values and corresponding theoretical sorting densities, and fitting to obtain the relationship between the theoretical sorting density and the circulating medium density Relationship lines.

The beneficial effects of the present invention are as follows: the intelligent control system and method for the dense medium sorting process provided by the present invention can obtain the corresponding relationship between the theoretical sorting density and the circulating medium density according to the feeding properties of the dense medium system, predict and specify The dense medium sorting process intelligently controls the circulating medium density setting value of the system, and adjusts the circulating medium density based on the circulating medium density setting value. It effectively reduces the dependence of the dense medium sorting process on experience, and realizes real-time control of product quality.

In the present invention, the above technical solutions can also be combined with each other to realize more preferred combination solutions. Additional features and advantages of the invention will be set forth in the description which follows, and some of the advantages will be apparent from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by what is particularly pointed out in the written description, claims as well as the appended drawings.

Description of drawings

The drawings are for the purpose of illustrating specific embodiments only and are not to be considered as limitations of the invention, and like reference numerals refer to like parts throughout the drawings.

Fig. 1 is a schematic structural diagram of the intelligent control system for the dense medium sorting process disclosed in Embodiment 1 of the present invention;

Fig. 2 is a schematic diagram of selectability curves in Example 1 of the present invention;

Fig. 3 is a flow chart of the intelligent control method for the dense medium sorting process disclosed in Embodiment 2 of the present invention.

Detailed ways

Preferred embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of the application and together with the embodiments of the present invention are used to explain the principle of the present invention and are not intended to limit the scope of the present invention.

A specific embodiment of the present invention discloses an intelligent control system for dense medium sorting process, the structure schematic diagram is shown in Fig. Raw coal ash; the second ash measuring device (such as ash measuring instrument 2#), used for real-time measurement of raw coal ash obtained after medium separation; production index prediction module, used to process the raw coal ash and the clean coal ash content to obtain the set value of the density of the circulating medium; the suspension density adjustment module adjusts the density of the circulating medium based on the deviation between the set value of the density of the circulating medium and the measured value of the density of the circulating medium (which can be measured by a densitometer).

Preferably, the production index prediction module obtains the set value of circulating medium density by performing the following operations:

(1) Based on the ash content of the raw coal detected in real time and the historical ups and downs data, correct the historical ups and downs data to obtain the ups and downs data at the current moment; based on the ups and downs data at the current moment, fit an optional curve; this implementation The example also gives the specific implementation of this process, as follows:

In the actual application process, it can be based on the real-time detection data of the dense medium system (feeding raw coal ash content, weight), historical data (raw coal floating and sinking data (also known as floating and sinking information), product output, yield and ash content, historical circulating medium density, etc. ) and rapid production inspection data (fast ash, fast floating), according to the online detection of ash, correct the historical data of floating and sinking, so as to predict the changing raw coal property data in real time (mainly real-time raw coal floating and sinking data, including the yield of different density levels and ash); the samples of historical ups and downs data are shown in Table 1.

Table 1 Sample of historical ups and downs data

Specific steps:

1) Compare the raw coal ash content Ai obtained by real-time detection with the raw coal ash content Ay in the historical raw coal floating and sinking data (see the sample of historical floating and sinking data in Table 1), and calculate ΔAi=Ai−Ay;

2) If the absolute value of ΔAi is less than 0.2, use the ash correction method to correct the ash content of the historical drift data; if the absolute value of ΔAi is greater than 0.2, use the output correction method to correct the historical drift data. In this way, new ups and downs data at the i-th moment are obtained, and this data may also be historical ups and downs data at the next moment.

Mathematical fitting is performed on the ups and downs data at the i-th moment to obtain a mathematical model (there can be 8 models), thereby obtaining an optional curve.

In the above method, using the online detection data and the properties of the raw materials obtained through prediction and optimization calculations, various indicators can be calculated online in real time without long-term experiments. The formula form of calculation is common, but the connotation is the real-time result of real-time data calculation.

The theoretical yield is obtained from the selectivity curve, and according to the current research results, the selectivity curve can be expressed by 8 mathematical models (all described in literature). The feature of this claim is that the parameters in the formula are real-time parameters after online real-time data fitting, rather than constants in general expressions.

For example the arctangent model:

y=100(t ₂ -arctan(k(xc)))/(t ₂ -t ₁ )

Among them, t ₁ , t ₂ , k, and c are all calculated from the detection data of the incoming ash content at the i-th moment. Then, when x1 expresses the required clean coal ash, calculate the yield y1, and then use this formula to take the calculated yield as x1, and calculate the corresponding theoretical separation density.

The calculation formula of actual yield is: γ1=Q2*100%/Q1

Among them, Q2 is the clean coal weight detected by the clean coal belt scale, and Q1 is the raw coal weight detected by the raw coal belt scale.

The formula for calculating the quantitative efficiency is:

Among them, γ1 is the calculated actual yield, and γ10 is the calculated theoretical yield.

The optional curves are a set of 5 curves, the basic two are the float yield-ash curve β and the float yield-density curve δ, from which the float yield-element ash curve λ, sink yield- Ash curve θ, and δ±0.1 content-density curve ε. as shown in picture 2.

(2) According to the actual circulating medium density at the current moment, the clean coal ash content and the selectivity curve, obtain the theoretical separation density at the current moment; specifically,

Detect the measured value of the circulating medium density and the corresponding clean coal ash, and according to the actual detected clean coal ash, obtain the theoretical separation density from the float yield-ash curve β and float yield-density curve δ (as shown in Figure 2) , according to the relationship curve between the theoretical sorting density and the circulating medium density, the set value of the circulating medium density at the current moment corresponding to the theoretical sorting density at the current moment is obtained.

In the actual application process, by changing the measured value of the circulating medium density many times through experiments, multiple corresponding theoretical sorting densities can be obtained (or similar data sorted out with the aforementioned historical data), and a series of circulating medium density measured The value corresponds to the theoretical separation density data, and the relationship curve between the theoretical separation density and the circulating medium density can be fitted (generally a linear equation, in the form of y=a+bx,);

In this way, if you want to change the ash content of the product, you must first check the corresponding theoretical separation density from the optional curve, so that the set density of the suspension in the dense medium system (that is, the density of the circulating medium) can be predicted according to the above relationship, so that the density of the suspension can be adjusted. The system has an adjustment basis.

Preferably, in the production index prediction module, when the change value of the clean coal ash output by the second ash measurement device relative to the reference ash value is within a preset change range of ash, the theoretical sorting Density and circulating medium density relationship curve, update the circulating medium density set value; when the change value of the clean coal ash output by the second ash measuring device relative to the reference ash value is not within the preset ash change range, it indicates The properties of the raw materials change greatly. At this time, the relationship curve between the theoretical separation density and the density of the circulating medium needs to be updated to ensure the consistency between the corresponding relationship and the properties of the raw coal. And after the above relationship curve is updated, the updated circulating medium density setting value is obtained. The specific method is: if the change value of the online product ash content ΔA∈{x1,x2}, according to the relationship curve between the theoretical sorting density and the circulating medium density mentioned above, directly predict and calculate the new circulating medium density setting value; if the online If the change value ΔA of product ash exceeds the value of {x1,x2}, recalculate the relational curve between theoretical sorting density and circulating medium density. Among them, {x1,x2} is an ash content variation range, which is determined by the actual situation of the enterprise.

The control strategy of the combination of feedforward control and feedback control, the relationship is: the feedforward control is mainly used to determine the density of raw coal according to the properties of raw materials when the production system starts to start, or when the properties of raw materials change greatly Composition and ash content, or determine the variation range of the circulating medium density, preliminarily set the set density of the circulating medium, and assist in the feedback control; and the feedback control is used in the production process, when the raw material properties change When it is large, according to the ash content of the product, within the adjustment range set by the feed-forward control, the set density is fine-tuned slightly.

Preferably, in the suspension density adjustment module, according to the deviation between the set value of the density of the circulating medium and the measured value of the density of the circulating medium, the action of replenishing water, diverting or adding concentrated medium is performed, so that the density of the circulating medium The measured value tracks the set value of the circulating medium density in real time. The specific process is: if the density setting value δ0-actual density measurement value δi=Δδ≤0, then add water to the feeding pipeline, and the amount of water replenishment ΔQ is determined according to the relationship of ΔQ=Δδ/C, and specific experiments are required. When Δδ>0, it needs to be based on the liquid level of each medium barrel (qualified medium barrel and dilute medium barrel in Fig. content meter), use fuzzy control method to decide whether to add concentrated medium or divert flow, for example, the barrel position of the qualified medium barrel is divided into 5 fuzzy sets, the valve opening of the feed pipe is divided into 9 levels, the fuzzy set of the example See Table 2 for set membership. When the grade value is negative, discharge material into the bucket, when the grade value is positive, open the shunt, that is, discharge material into the diluent tank. In this way, the density of the circulating medium is guaranteed to track the density setting value in real time; the suspension density adjustment system is composed of various actuators and their driving adjustment strategy software.

Table 2 Division table of control quantity change in fuzzy control method

The automatic adjustment of each valve and barrel position realizes the following functions through the optimized control package: according to the set value of the circulating medium density, the measured value of the circulating medium density and the actual barrel position of the medium barrel, the intelligent optimal control algorithm-fuzzy control can be adopted , specifically set the fuzzy membership degree table of the qualified medium bucket and the rare medium bucket as shown in the attached table 2, cooperate with expert knowledge, set the control rules for each fuzzy membership degree, and use the fuzzy control algorithm to calculate the optimal bucket position and Valve opening, direct the suspension density adjustment system to automatically adjust the valve opening to an appropriate value, to ensure that the liquid level of each barrel is appropriate, and the difference between the medium density and the set density is less than the user's specified value.

In order to be able to track and supervise the operation of the system, the system also sets up an online evaluation module. The online evaluation module can calculate the theoretical yield, actual yield, quantity efficiency and other indicators in real time according to the data of incoming materials and products detected online, as well as the properties of raw materials provided by the production index prediction system, and according to the coal preparation effect evaluation method Make an online evaluation. The evaluation of separation results is common in the field of coal preparation, and its evaluation methods and formulas can be found in coal preparation plant management textbooks. However, there is no precedent for online evaluation in the past. The difference between the form of the evaluation formula of the present invention and the original formula is that the time dimension is introduced. The data that can only be obtained after several days or even dozens of days of experiments and calculations are now used for online detection or prediction. The calculation is obtained in real time, and data of different time frequencies can be selected, so as to realize online evaluation. The online evaluation module can obtain corresponding data by means of the instruments marked in Figure 1 to realize the calculation of relevant indicators. The measuring elements selected in this embodiment are commonly used measuring elements in the field, and the functions of several main elements are only exemplified here. For example: Ash Meter 1# is used as the first ash measuring device to measure the ash content of raw coal, and belt scale 1# is used to measure the weight of raw coal; Ash Meter 2# is used as the second ash measuring device to measure the raw coal ash in real time. The ash content of clean coal is obtained after selection, and the weight of clean coal is measured by belt scale 2#; the weight of medium coal is also measured by belt scale 3#; a data acquisition module can also be specially set up to collect raw coal data, historical data, production inspection data, raw coal floating and sinking After the data are uniformly sent to the data acquisition module, they are then handed over to the production index prediction module for processing.

During the execution of the above-mentioned system, firstly, all kinds of data required are collectively collected through the data collection system. When the incoming raw coal starts to enter the process system, the data measured by the online detection instrument (that is, real-time detection data) enters the data acquisition system. The historical data, raw coal floating and sinking data, etc. are sent to the production index prediction system in real time; the production index prediction system calculates a reasonable setting density of the circulating medium (ie, the density setting value), and feeds it into the suspension density adjustment system; The liquid density adjustment system receives instructions from the optimization control package at the same time, adjusts various barrel positions, valves, splitter boxes, etc., and tracks the density setting value to ensure that the suspension density meets the set density. When the evaluation system points out that the quality of the clean coal product does not meet the requirements, or other evaluation indicators are unreasonable, the production index prediction system again fine-tunes the set density based on real-time detection data, historical data, and raw coal quality changes, and feeds back to the suspension density adjustment system. Start a new round of density adjustment.

Compared with the prior art, the intelligent control system for the dense medium sorting process disclosed in this embodiment can obtain the corresponding relationship between the theoretical sorting density and the circulating medium density according to the feeding properties of the dense medium system, predict and specify The dense medium sorting process intelligently controls the circulating medium density setting value of the system, and adjusts the circulating medium density based on the circulating medium density setting value. It effectively reduces the dependence of the dense medium sorting process on experience, and realizes real-time control of product quality.

Example 2

In Embodiment 2 of the present invention, an intelligent control method for a dense medium sorting process is disclosed, the flow chart of which is shown in Figure 3, including the following steps:

Step S1: Real-time detection of raw coal ash content, clean coal ash content and circulating medium density value at the current moment, and fitting to obtain the selectability curve at the current moment;

Step S2: Obtain the theoretical sorting density at the current moment according to the measured value of the circulating medium density at the current moment, the ash content of the clean coal and the selectivity curve;

Step S3: According to the relationship curve between the theoretical sorting density and the circulating medium density, the set value of the circulating medium density at the current moment corresponding to the theoretical sorting density at the current moment is obtained;

Step S4: Adjust the density of the circulating medium based on the deviation between the set value of the circulating medium density and the measured value of the circulating medium density.

Preferably, the real-time detection of raw coal ash content, clean coal ash content and circulating medium density value at the current moment, and fitting the optional curve at the current moment includes:

Based on the real-time detected raw coal ash content, clean coal ash content, circulating medium density value and historical ups and downs information, correct the historical ups and downs information to obtain the ups and downs information at the current moment; based on the ups and downs information at the current moment, fit the current The optionality curve for moments.

Preferably, the relationship curve between the theoretical sorting density and the circulating medium density is obtained by: extracting a plurality of actual circulating medium density values and corresponding theoretical sorting densities, and fitting the theoretical sorting density and circulating medium density relationship curve.

For the specific implementation process of the method embodiment of the present invention, refer to the above-mentioned system embodiment, and this embodiment will not be repeated here. Because the principle of this embodiment is the same as that of the above method embodiment, this system also has the corresponding technical effects of the above method embodiment.

Those skilled in the art can understand that all or part of the processes of the methods in the above embodiments can be implemented by instructing related hardware through computer programs, and the programs can be stored in a computer-readable storage medium. Wherein, the computer-readable storage medium is a magnetic disk, an optical disk, a read-only memory or a random access memory, and the like.

The above is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of changes or modifications within the technical scope disclosed in the present invention. Replacement should be covered within the protection scope of the present invention.

Claims (10)

1. A dense media sorting process intelligent control system, the system comprising:

a first ash content measuring device for measuring the ash content of the raw coal;

the second ash content measuring device is used for measuring the clean coal ash content obtained after the raw coal is separated by the circulating medium in real time;

the production index prediction module is used for processing the raw coal ash and the clean coal ash to obtain a circulating medium density set value;

and the circulating medium density adjusting module is used for adjusting the density of the circulating medium based on the deviation between the set value of the density of the circulating medium and the measured value of the density of the circulating medium.

2. The dense media separation process intelligent control system of claim 1, wherein the production index prediction module obtains a circulating media density setpoint by performing the following operations:

based on the real-time detected raw coal ash content, clean coal ash content, circulating medium density value and historical float and sink information, correcting the historical float and sink information to obtain float and sink information at the current moment; fitting to obtain a selectable curve based on the sinking and floating information at the current moment;

obtaining the theoretical separation density at the current moment according to the measured circulating medium density value at the current moment, the clean coal ash content and the selectivity curve;

and obtaining a circulating medium density set value at the current moment corresponding to the theoretical sorting density at the current moment according to a relation curve of the theoretical sorting density and the circulating medium density.

3. The dense media sorting process intelligence control system of claim 2, wherein the theoretical sorting density versus circulating media density curve is obtained by:

extracting a plurality of actual circulating medium density values, searching corresponding theoretical separation density by corresponding to the clean coal ash at that time, and fitting to obtain a relation curve between the theoretical separation density and the circulating medium density.

4. The intelligent heavy media sorting process control system according to claim 2 or 3, wherein, in the production indicator prediction module,

when the change value of the clean coal ash output by the second ash content measuring device relative to the reference ash content is within a preset ash content change range, updating a circulating medium density set value according to the relation curve of the theoretical separation density and the circulating medium density;

and when the change value of the clean coal ash output by the second ash content measuring device relative to the reference ash content is not within the preset ash content change range, updating the relation curve of the theoretical separation density and the circulating medium density, and obtaining an updated circulating medium density set value.

5. The intelligent dense-media separation process control system according to claim 1, wherein in the suspension density adjustment module, according to a deviation between the circulating medium density set value and a circulating medium density measured value, a water supplementing, a shunting, or a concentrated medium supplementing operation is performed, so that the circulating medium density measured value tracks the circulating medium density set value in real time.

6. The dense-media sorting process intelligence control system of claim 5, wherein, in the suspension density adjustment module,

if the deviation delta between the set value of the density of the circulating medium and the measured value of the density of the circulating medium is less than or equal to 0, supplementing water to a feeding pipeline, wherein the water supplementing quantity delta Q is delta/C;

if the deviation delta between the set value of the density of the circulating medium and the measured value of the density of the circulating medium is larger than 0, the enriched medium or the shunt is optimally determined by adopting a fuzzy control method according to the liquid level of each medium barrel and the content of the magnetic substance in the circulating medium which are detected on line.

7. The intelligent control system according to claim 1, further comprising an online evaluation module for calculating in real time indicators including theoretical yield, actual yield, and quantity efficiency according to the online detected feed and product data and the material properties provided by the production indicator prediction module, and performing online evaluation according to a coal dressing effect evaluation method.

8. An intelligent control method for a dense medium sorting process is characterized by comprising the following steps:

detecting the density values of the raw coal ash, the clean coal ash and the circulating medium at the current moment in real time, and fitting to obtain a selectable curve at the current moment;

obtaining the theoretical separation density at the current moment according to the measured circulating medium density value at the current moment, the clean coal ash content and the selectivity curve;

obtaining a circulating medium density set value at the current moment corresponding to the theoretical sorting density at the current moment according to a relation curve of the theoretical sorting density and the circulating medium density;

and adjusting the density of the circulating medium based on the deviation between the set value of the density of the circulating medium and the measured value of the density of the circulating medium.

9. The intelligent control method for the dense-medium separation process according to claim 8, wherein the real-time detection of the values of the density of the raw coal ash, the clean coal ash and the circulating medium at the current moment is performed to obtain a selectable curve at the current moment by fitting, and the method comprises the following steps:

based on the real-time detected raw coal ash content, clean coal ash content, circulating medium density value and historical float and sink information, correcting the historical float and sink information to obtain float and sink information at the current moment; and fitting to obtain a selectable curve at the current moment based on the sinking and floating information at the current moment.

10. The intelligent heavy-media sorting process control method according to claim 8, wherein the theoretical sorting density versus circulating medium density curve is obtained by:

and extracting a plurality of actual circulating medium density values and corresponding theoretical sorting densities, and fitting to obtain a relation curve between the theoretical sorting densities and the circulating medium densities.