Intelligent control system of concrete admixture compounding production line

Abstract

The invention discloses an intelligent control system of a concrete admixture compounding production line, and relates to the field of intelligent control, and the main scheme is as follows: judging whether feeding meets the standard or not according to a liquid raw material feeding difference WAa, a solid raw material feeding difference WBc and raw material difference data; whether the stirring process meets the standard or not is judged according to the stirring process deviation index RA and the stirring process deviation threshold RB, whether preset parameters need to be adjusted or not is judged according to the sample qualification rate YB, the comprehensive performance deviation index P, the qualification rate threshold RC and the comprehensive performance deviation threshold RD, different control signals are sent out according to the judgment result, and real-time adjustment is conducted. The problems that whether feeding meets the standard or not cannot be judged in real time, the stirring process deviation is difficult to accurately evaluate, the quality problem cannot be found in time, and whether preset parameters need to be adjusted or not cannot be rapidly and accurately judged are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent control, and specifically to an intelligent control system for a concrete admixture compounding production line. Background Art

[0002] In the field of water conservancy projects, an intelligent control system can accurately control the addition amounts of various admixture raw materials such as water reducers, retarders, and air-entraining agents, so that the component ratios of the compounded admixtures precisely meet the design requirements. At the same time, the intelligent control system can realize the full-automatic operation of the admixture compounding production line, improve production efficiency, and optimize cost management.

[0003] The traditional method for controlling an admixture compounding production line is as follows: in the feeding link, operators measure raw materials using simple measuring tools such as scales and graduated cylinders; in the stirring link, fixed stirring duration and speed are set according to experience; in the quality inspection link, quality inspection is carried out after a batch of products is produced, and production parameters are adjusted manually according to the quality inspection results.

[0004] The existing technology still has the following deficiencies: measuring raw materials using simple measuring tools such as scales and graduated cylinders is prone to large human errors, and it is impossible to calculate the feeding difference in real time to determine whether the feeding meets the standard. At the same time, it is impossible to dynamically calculate preset parameters based on the feeding data and the actual situation during the stirring process, and it is also difficult to accurately evaluate the deviation during the stirring process. For quality inspection, the inspection time interval is long, quality problems cannot be detected in a timely manner, and the statistics and analysis of unqualified samples are not detailed enough to quickly and accurately determine whether preset parameters need to be adjusted. Summary of the Invention

[0005] (1) Technical Problems to be Solved

[0006] In view of the deficiencies of the existing technology, the present invention provides an intelligent control system for a concrete admixture compounding production line. According to the feeding difference WA of liquid raw materials a , the feeding difference WB of solid raw materials cJudge whether the feed meets the standard based on the feed data and raw material difference data, solving the problem of being unable to calculate the feed difference in real time to judge whether the feed meets the standard. Calculate the preset stirring duration WC, preset stirring speed WD, and preset motor torque WE based on the feed data and stirring data. Judge whether the stirring process meets the standard according to the stirring process deviation index RA and the stirring process deviation threshold RB, solving the problems of being unable to dynamically calculate the preset parameters according to the feed data and the actual situation during the stirring process, and being difficult to accurately evaluate the stirring process deviation. Judge whether it is necessary to adjust the preset parameters according to the sample qualification rate YB, comprehensive performance deviation index P, qualification rate threshold RC, and comprehensive performance deviation threshold RD, solving the problems of long quality inspection time interval, being unable to detect quality problems in time, and not being meticulous enough in the statistics and analysis of unqualified samples, and being unable to quickly and accurately judge whether it is necessary to adjust the preset parameters.

[0007] (II)Technical solutions

[0008] To achieve the above objectives, the present invention is realized through the following technical solutions: An intelligent control system for a concrete admixture compounding production line, including:

[0009] A data acquisition module for collecting feed data, raw material difference data, stirring data, sampling inspection data, and quality requirement data;

[0010] A metering and batching module capable of calculating the liquid raw material feed difference WA a and the solid raw material feed difference WB c ; Judge whether the feed meets the standard based on the liquid raw material feed difference WA a , the solid raw material feed difference WB c and the raw material difference data; When the feed meets the standard, send control signal 1; When the feed does not meet the standard, send control signal 2;

[0011] A mixing and stirring module capable of calculating the preset stirring duration WC and preset stirring speed WD based on the feed data and stirring data, calculating the preset motor torque WE according to the preset stirring speed WD and stirring data, calculating the stirring process deviation index RA according to the preset stirring duration WC, preset stirring speed WD, preset motor torque WE, and stirring data; Preset stirring process deviation threshold RB; Judge whether the stirring process meets the standard according to the stirring process deviation index RA and the stirring process deviation threshold RB; When the stirring process meets the standard, send control signal 3; When the stirring process does not meet the standard, send control signal 4;

[0012] A quality inspection module capable of calculating the performance deviation index SA n based on the sampling inspection data and quality requirement data; Preset performance deviation threshold SD; According to the performance deviation index SA nJudge whether the sample performance is qualified according to the performance deviation threshold SD; count the number of unqualified samples v and the density value PA of the unqualified samples u , pH value PB u , water reduction rate PC u and setting time PD u ; calculate the sample pass rate YB according to the number of unqualified samples v; according to the density value PA of the unqualified samples u , pH value PB u , water reduction rate PC u , setting time PD u and quality requirement data to calculate the comprehensive performance deviation index P; preset the pass rate threshold RC and the comprehensive performance deviation threshold RD; judge whether it is necessary to adjust the preset parameters according to the sample pass rate YB, the comprehensive performance deviation index P, the pass rate threshold RC and the comprehensive performance deviation threshold RD. When it is necessary to adjust the preset parameters, send control signal five; when it is not necessary to adjust the preset parameters, send control signal six;

[0013] The intelligent control module is used to receive different control signals and send control instructions for real-time adjustment according to the received control signals.

[0014] In the preferred scheme of the intelligent control system of the above concrete admixture compounding production line: calculate the liquid raw material feeding difference WA a and the solid raw material feeding difference WB c The method is as follows:

[0015] The feeding data includes the preset feeding amount AA of the liquid raw material a , the preset feeding time AB of the liquid raw material a , the actual feeding flow rate AC a (t), the preset feeding amount AD of the solid raw material c , the actual feeding speed AE of the solid raw material c (t) and the average density DB of the solid raw material;

[0016] According to the preset feeding amount AA of the liquid raw material a , the preset feeding time AB of the liquid raw material a and the actual feeding flow rate AC a (t) to calculate the liquid raw material feeding difference WA at , the formula is:

[0017] ;

[0018] Among them, WA at is the feeding difference of the a-th liquid raw material at time t, a is the serial number corresponding to different liquid raw materials, and the value is a positive integer; t is the serial number corresponding to different feeding times, and the value is a positive integer; AA ais the preset feeding amount of the a-th liquid raw material; AB a is the preset feeding time of the a-th liquid raw material; AC a F(a)(t) is the actual feeding flow rate of the a-th liquid raw material at time t;

[0019] According to the preset feeding amount of the solid raw material AD c and the actual feeding speed AE of the solid raw material c F(c)(t) and the average density DB of the solid raw material to calculate the feeding difference WB of the solid raw material ct , and the formula is:

[0020] ;

[0021] where WB ct is the feeding difference of the c-th solid raw material at time t, c is the serial number corresponding to different solid raw materials, and the value is a positive integer; AD c is the preset feeding amount of the c-th solid raw material; AE c F(c)(t) is the actual feeding speed of the c-th solid raw material at time t.

[0022] In the preferred scheme of the intelligent control system of the above concrete admixture compounding production line: the method for judging whether the feeding meets the standard is:

[0023] The raw material difference data includes the liquid raw material difference range [BA, BB] and the solid raw material difference range [CA, CB];

[0024] According to the liquid raw material feeding difference WA at , the solid raw material feeding difference WB ct and the raw material difference data to judge whether the feeding meets the standard, and the formula is:

[0025] ;

[0026] When the feeding meets the standard, send a control signal 1 to stop transporting the raw materials;

[0027] When the feeding does not meet the standard, send a control signal 2. When WA at < BA or WB ct < CA, continue feeding until it meets the standard; when WA at > BA or WB ct > CA, immediately stop feeding, and take out the excess raw materials and transport them to the storage container until it meets the standard.

[0028] In the preferred scheme of the intelligent control system of the above concrete admixture compounding production line: the method for calculating the preset stirring duration WC is:

[0029] The feed data also includes the total mass DA of the solid raw materials, the total volume DC of the liquid raw materials, the average diffusion coefficient DD of the liquid raw materials, and the average density DE of the liquid raw materials;

[0030] The stirring data includes the effective shear area DF of the stirring blade;

[0031] The preset stirring duration WC is calculated based on the total mass DA of the solid raw materials, the average density DB of the solid raw materials, the total volume DC of the liquid raw materials, the average diffusion coefficient DD of the liquid raw materials, the average density DE of the liquid raw materials, and the stirring data. The formula is:

[0032] ;

[0033] where k 1 is the solid dissolution time coefficient, with a value ranging from 2 to 6; k 2 is the liquid mixing time coefficient, with a value ranging from 0.3 to 1.5; k 3 is the system gravity influence coefficient, with a value ranging from 0.5 to 1.2; g is the acceleration due to gravity, with a value of 9.8 m / s 2 .

[0034] In the preferred solution of the intelligent control system for a concrete admixture compounding production line described above: The method for calculating the preset stirring speed WD is:

[0035] The stirring data also includes the Reynolds number EA, the dynamic viscosity EB of the liquid mixture, and the diameter EC of the stirring blade;

[0036] The preset stirring speed WD is calculated based on the average density DE of the liquid raw materials, the Reynolds number EA, the dynamic viscosity EB of the liquid mixture, and the diameter EC of the stirring blade. The formula is:

[0037] ;

[0038] In the preferred solution of the intelligent control system for a concrete admixture compounding production line described above: The method for calculating the preset motor torque WE is:

[0039] The stirring data also includes the motor voltage FA, the motor current FB, and the motor speed FC;

[0040] The preset motor torque WE is calculated based on the preset stirring speed WD, the motor voltage FA, the motor current FB, and the motor speed FC. The formula is:

[0041] ;

[0042] In the preferred solution of the intelligent control system for a concrete admixture compounding production line described above: The method for calculating the stirring process deviation index RA is:

[0043] The mixing data also includes the actual mixing duration HA, the actual mixing speed HB, and the actual motor torque HC;

[0044] Calculate the mixing process deviation index RA based on the preset mixing duration WC, the preset mixing speed WD, the preset motor torque WE, the actual mixing duration HA, the actual mixing speed HB, and the actual motor torque HC. The formula is:

[0045] ;

[0046] where ɑ 1 is the weight coefficient of the mixing duration deviation index, with a value ranging from 0.2 to 0.5; ɑ 2 is the weight coefficient of the mixing speed deviation index, with a value ranging from 0.3 to 0.5; ɑ 3 is the weight coefficient of the motor torque deviation index, with a value ranging from 0.2 to 0.5; and ɑ 1 + ɑ 2 + ɑ 3 = 1.

[0047] In the preferred solution of the intelligent control system for the above concrete admixture compounding production line: The method for judging whether the mixing process meets the standard is:

[0048] Judge whether the mixing process meets the standard according to the mixing process deviation index RA and the mixing process deviation threshold RB. The formula is:

[0049] ;

[0050] When the mixing process meets the standard, send control signal three and continue to execute according to the current parameters;

[0051] When the mixing process does not meet the standard, send control signal four and adjust the operating parameters to the preset operating parameters.

[0052] In the preferred solution of the intelligent control system for the above concrete admixture compounding production line: The method for judging whether the sample performance is qualified is:

[0053] The sampling detection data includes the density value LA n , the pH value LB n , the water reduction rate LC n , and the setting and retarding time LD n ;

[0054] The quality requirement data includes the standard density value MA, the standard pH value MB, the standard water reduction rate MC, and the standard setting and retarding time MD;

[0055] Calculate the performance deviation index SA n based on the sampling detection data and the quality requirement data. The formula is:

[0056] ;

[0057] Among them, SA n is the performance deviation index of the nth test sample, where n is the serial number corresponding to different test samples and takes positive integer values; LA n is the density value of the nth test sample; LB n is the pH value of the nth test sample; LC n is the water reduction rate of the nth test sample; LD n is the setting time retardation of the nth test sample;

[0058] According to the performance deviation index SA n and the performance deviation threshold SD to judge whether the sample performance is qualified, the formula is:

[0059] ;

[0060] In the preferred scheme of the intelligent control system of the above concrete admixture compounding production line: The method for judging whether to adjust the preset parameters is:

[0061] Calculate the sample qualification rate YB according to the number v of unqualified samples, and the formula is:

[0062] ;

[0063] Among them, YA is the total number of test samples and takes positive integer values;

[0064] According to the density value PA u of the unqualified sample, the pH value PB u , the water reduction rate PC u , the setting time retardation PD u and the quality requirement data to calculate the comprehensive performance deviation degree index P, the formula is:

[0065] ;

[0066] Among them, PA u is the density value of the u-th unqualified sample, where u is the serial number corresponding to different unqualified samples and takes values in [1, v]; PB u is the pH value of the u-th unqualified sample; PC u is the water reduction rate of the u-th unqualified sample; PD u is the setting time retardation of the u-th unqualified sample;

[0067] According to the sample qualification rate YB, the comprehensive performance deviation degree index P, the qualification rate threshold RC and the comprehensive performance deviation threshold RD to judge whether to adjust the preset parameters, the formula is:

[0068] ;

[0069] When it is necessary to adjust the preset parameters, a control signal five is issued, and the metering and batching module adjusts the raw material ratio according to the control instruction; the mixing and stirring module adjusts the stirring time, stirring speed or motor torque according to the control instruction.

[0070] When it is not necessary to adjust the preset parameters, a control signal six is issued, and the mixing continues according to the current parameters.

[0071] (III) Beneficial effects

[0072] The present invention provides an intelligent control system for a compound production line of concrete admixtures, which has the following beneficial effects:

[0073] (1) By collecting feeding data, raw material difference data, stirring data, sampling inspection data and quality requirement data, it is beneficial to improve the accuracy of control, thereby improving the product quality.

[0074] (2) According to the feeding difference WA of liquid raw materials a , the feeding difference WB of solid raw materials c and the raw material difference data to judge whether the feeding meets the standard, it is possible to realize real-time monitoring of the feeding quality, and solve the problem that the feeding difference cannot be calculated in real time to judge whether the feeding meets the standard.

[0075] (3) Based on the feeding data and stirring data, calculate the preset stirring duration WC, preset stirring speed WD and preset motor torque WE, and judge whether the stirring process meets the standard according to the stirring process deviation index RA and the stirring process deviation threshold RB, it is possible to timely detect abnormal situations in the stirring process, which helps to produce products with more stable quality, and solves the problems that the preset parameters cannot be dynamically calculated according to the feeding data and the actual situation in the stirring process, and it is also difficult to accurately evaluate the stirring process deviation.

[0076] (4) According to the sample qualification rate YB, comprehensive performance deviation degree index P, qualification rate threshold RC and comprehensive performance deviation threshold RD to judge whether it is necessary to adjust the preset parameters, it is possible to accurately judge whether the product quality is within the acceptable range, which helps to maintain the consistency of product quality, effectively reduce the rework situation, and solves the problems of long quality inspection time interval, inability to timely detect quality problems, and insufficient statistical analysis of unqualified samples, and inability to quickly and accurately judge whether it is necessary to adjust the preset parameters.

[0077] (5) Receive different control signals, issue control instructions according to the received control signals for real-time adjustment, and can accurately control each link in the production process, which is beneficial to improving production efficiency and raw material utilization rate. Description of the drawings

[0078] Figure 1 It is a schematic diagram of the system composition of an intelligent control system for a concrete admixture compounding production line of the present invention. Specific implementation manners

[0079] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0080] Please refer to Figure 1 , the present invention provides an intelligent control system for a concrete admixture compounding production line, including:

[0081] A data acquisition module, configured to acquire feeding data, raw material difference data, mixing data, sampling detection data, and quality requirement data.

[0082] In the above solution, by acquiring feeding data, raw material difference data, mixing data, sampling detection data, and quality requirement data, it is beneficial to improve the accuracy of control, thereby improving product quality.

[0083] A metering and batching module, capable of calculating the feeding difference WA a of liquid raw materials and the feeding difference WB c of solid raw materials based on the feeding data; judging whether the feeding meets the standard according to the feeding difference WA a of liquid raw materials, the feeding difference WB c of solid raw materials, and the raw material difference data; when the feeding meets the standard, sending a control signal one; when the feeding does not meet the standard, sending a control signal two.

[0084] Specifically, the method for calculating the feeding difference WA a of liquid raw materials and the feeding difference WB c of solid raw materials is as follows:

[0085] The feeding data includes the preset feeding amount AA a of liquid raw materials, the preset feeding time AB a of liquid raw materials, the actual feeding flow rate AC a (t) of liquid raw materials, the preset feeding amount AD c of solid raw materials, the actual feeding speed AE c (t) of solid raw materials, and the average density DB of solid raw materials.

[0086] It should be noted that the preset feeding amount AA aRefers to the quantity of a certain liquid raw material that needs to be added during the production of admixtures as preset according to the formulation requirements, with the unit being liters or cubic meters and other volume units, determined by the design formulation of the admixture. Specifically: Based on the performance indicators required for the product, calculate the proportion of various liquid raw materials in the formulation, and multiply this proportion by the total mass or total volume of the produced admixture to obtain the preset feed quantity AA of the liquid raw material a , where the design formulation is based on a large number of experiments and theoretical studies, and according to the required admixture properties, such as water reduction rate, setting retardation time, etc., calculates the dosage of various raw materials using stoichiometric relationships. The preset feed time AB of the liquid raw material a Refers to the time required for the preset feeding process of the liquid raw material. The acquisition method is: Collect the historical feeding speed of the feed pump and calculate its average value, and calculate the preset feed quantity AA of the liquid raw material a The ratio to the average value of the historical feeding speed is used as the preset feed time AB of the liquid raw material a ; The actual feed flow rate AC a (t) During the feeding process of the liquid raw material, it is the speed at which the liquid raw material actually enters the production system at time t, reflecting the real-time state of the feeding process, with the unit being liters per minute or cubic meters per hour, obtained by installing a flow meter on the conveying pipeline of the liquid raw material for measurement; The preset feed quantity AD of the solid raw material c Is the quantity of the solid raw material that needs to be added as preset according to the admixture formulation, determined by the formulation composition of the admixture and the theoretical chemical reaction stoichiometric relationship, with the unit being kilograms or tons and other mass units. Specifically: Based on the performance indicators required for the product, calculate the proportion of various solid raw materials in the formulation, and multiply this proportion by the total mass or total volume of the produced admixture to calculate the preset feed quantity AD of the solid raw material c . The actual feeding speed AE of the solid raw material c (t) Refers to the speed at which the volume actually enters the production system at time t, with the unit being kilograms per minute or tons per hour. The acquisition method is: Consult the equipment specification manual of the screw feeder to obtain the outer diameter QA, inner diameter QB, and pitch QC of the screw, measure the rotation speed QD of the screw feeder through a rotation speed sensor installed on the screw shaft, and calculate the actual feeding speed AE of the solid raw material according to the formula π / 4(QA 2 -QB 2 )×QC×QD×QE. Among them, QE is the filling coefficient, and the acquisition method is: Under the normal working condition of the screw feeder, collect the solid raw material coming out of the screw feeder within the unit time QF, put the solid raw material into a graduated measuring tool such as a graduated cylinder or measuring cup, read the corresponding scale value on the container to obtain the volume QG of the solid raw material, and according to the formula QG / (π / 4(QA c -QB 2 -QB 2) QE is calculated by (×QC×QD×QF). The average density DB of solid raw materials refers to the average density of different solid raw materials, which reflects the compactness of solid particles. The unit is kg / m³, and the acquisition method is: obtain the density DQ of each solid raw material by referring to the data materials provided by the supplier c , according to the formula the average density DB of solid raw materials is calculated, where DQ c is the density of the c-th solid raw material.

[0087] According to the preset feed quantity AA of liquid raw materials a , the preset feed time AB of liquid raw materials a and the actual feed flow rate AC a (t) calculate the feed difference WA of liquid raw materials at , and the formula is:

[0088] ;

[0089] where WA at is the feed difference of the a-th liquid raw material at time t, a is the serial number corresponding to different liquid raw materials, and the value is a positive integer; t is the serial number corresponding to different feed times, and the value is a positive integer; AA a is the preset feed quantity of the a-th liquid raw material; AB a is the preset feed time of the a-th liquid raw material; AC a (t) is the actual feed flow rate of the a-th liquid raw material at time t.

[0090] It should be noted that the operating principle of this formula is: represents the integral of the actual feed flow rate of liquid raw materials from the initial time 0 to time t. The physical meaning of the integral is to calculate the total actual feed quantity of liquid raw materials at time t, represents the theoretical feed quantity calculated according to the preset feed quantity and preset feed time at time t. Subtracting the theoretical feed quantity from the total actual feed quantity, the feed difference WA of liquid raw materials is obtained at .

[0091] According to the preset feed quantity AD of solid raw materials c , the actual feed speed AE of solid raw materials c (t) and the average density DB of solid raw materials calculate the feed difference WB of solid raw materials ct , and the formula is:

[0092] ;

[0093] where WB ctThe feeding difference of the c-th solid raw material at time t, where c is the serial number corresponding to different solid raw materials and takes positive integer values; AD c is the preset feeding amount of the c-th solid raw material; AE c The actual feeding speed of the c-th solid raw material at time t is (t).

[0094] It should be noted that the operating principle of this formula is as follows: represents the actual feeding amount calculated based on the actual feeding speed, time, and average density of the solid raw material at time t. Subtracting the preset feeding amount from the actual feeding amount gives the feeding difference of the solid raw material at time t, WB ct .

[0095] Specifically, the method for judging whether the feeding meets the standard is as follows:

[0096] The raw material difference data includes the liquid raw material difference range [BA, BB] and the solid raw material difference range [CA, CB].

[0097] It should be noted that the liquid raw material difference range [BA, BB] refers to the allowable deviation range between the actual feeding amount and the preset feeding amount of the liquid raw material during the production process. The acquisition method is as follows: collect the historical data during the compounding of qualified admixture products, calculate the liquid raw material feeding difference data of different products according to the above method, calculate the average value and standard deviation of the liquid raw material feeding difference data, calculate the value of the average value plus twice the standard deviation as the upper limit value BB of the liquid raw material difference range, and calculate the value of the average value minus twice the standard deviation as the lower limit value BA of the liquid raw material difference range. The solid raw material difference range [CA, CB] refers to the allowable deviation interval between the actual feeding amount and the preset feeding amount of the solid raw material. The acquisition method is as follows: collect the historical data during the compounding of qualified admixture products, calculate the solid raw material feeding difference data of different products according to the above method, calculate the average value and standard deviation of the solid raw material feeding difference data, calculate the value of the average value plus twice the standard deviation as the upper limit value CB of the solid raw material difference range, and calculate the value of the average value minus twice the standard deviation as the lower limit value CA of the solid raw material difference range.

[0098] According to the liquid raw material feeding difference WA at , the solid raw material feeding difference WB ct and the raw material difference data to judge whether the feeding meets the standard. The formula based on this is:

[0099] ;

[0100] When the feeding meets the standard, a control signal one is issued to stop transporting the raw materials;

[0101] When the feeding does not meet the standard, a control signal two is issued. When WAat <BA or WB ct <When CA, continue feeding until the standard is met; when WA at >BA or WB ct >CA, immediately stop feeding and remove the excess raw materials, and transport them to the storage container until the standard is met.

[0102] In the above solution, according to the liquid raw material feeding difference WA a and the solid raw material feeding difference WB c and the raw material difference data to judge whether the feeding meets the standard, it is possible to realize real-time monitoring of the feeding quality, and solve the problem that it is impossible to calculate the feeding difference in real time to judge whether the feeding meets the standard.

[0103] The mixing and stirring module can calculate the preset stirring duration WC and the preset stirring speed WD based on the feeding data and the stirring data, calculate the preset motor torque WE according to the preset stirring speed WD and the stirring data, and calculate the stirring process deviation index RA according to the preset stirring duration WC, the preset stirring speed WD, the preset motor torque WE and the stirring data; the preset stirring process deviation threshold RB; judge whether the stirring process meets the standard according to the stirring process deviation index RA and the stirring process deviation threshold RB; when the stirring process meets the standard, send control signal three; when the stirring process does not meet the standard, send control signal four.

[0104] Specifically, the method for calculating the preset stirring duration WC is:

[0105] The feeding data also includes the total mass DA of the solid raw materials, the total volume DC of the liquid raw materials, the average diffusion coefficient DD of the liquid raw materials and the average density DE of the liquid raw materials.

[0106] It should be noted that the total mass DA of the solid raw materials refers to the total mass of all solid raw materials planned to be used in the entire production process of the admixture. The acquisition method is: place a weighing device, such as an electronic scale, under the solid raw material feeding port, and after the feeding stops, use the weighing device to measure the total mass DA of the solid raw materials. The total volume DC of the liquid raw materials refers to the sum of the volumes of all liquid raw materials required in the production of the admixture, and is calculated according to the formula where t 1is the time when the feeding stops. The average diffusion coefficient DD of the liquid raw materials is a physical quantity that describes the diffusion ability of the liquid raw materials during the mixing process, reflecting the diffusion speed of the liquid raw material molecules in other liquid raw materials or solutions. The unit is square meters per second. The acquisition method is as follows: According to the formula ratio, use a measuring cylinder or pipette to measure a small amount of various liquid raw materials. Place the measured small amount of liquid raw material samples in a diffusion experiment device under standard temperature and pressure conditions, such as a horizontal diffusion cell. Then use an infrared spectrometer to measure its diffusion rate. Finally, calculate the average diffusion coefficient DD of the liquid raw materials according to Fick's first law. Among them, Fick's first law means that under steady-state diffusion conditions, the flux of matter diffusing through the medium is proportional to the concentration gradient. The average density DE of the liquid raw materials refers to the average density of different liquid raw materials. The unit is kilograms per cubic meter. The acquisition method is as follows: According to the formula ratio, use a measuring cylinder or pipette to measure a small amount of various liquid raw materials. Pour these raw materials into the same small beaker in sequence for mixing. Then vertically place a densitometer into the mixed liquid. After waiting for the densitometer to stabilize, read the density value displayed on the densitometer and use this value as the average density DE of the liquid raw materials.

[0107] The stirring data includes the effective shear area DF of the stirring impeller.

[0108] It should be noted that the effective shear area DF of the stirring impeller refers to the area where the impeller can produce an effective shear effect on the fluid during the stirring process. The shear effect refers to the relative movement between the impeller and the fluid, which causes relative sliding between the fluid layers, thereby promoting processes such as mixing and dispersion. It is obtained by simulating and calculating using CFD software such as ANSYS Fluent and Flow-3D. Among them, CFD is computational fluid dynamics, which is a discipline that uses numerical calculation methods to solve physical problems related to fluid flow and heat transfer.

[0109] Calculate the preset stirring duration WC based on the total mass DA of the solid raw materials, the average density DB of the solid raw materials, the total volume DC of the liquid raw materials, the average diffusion coefficient DD of the liquid raw materials, the average density DE of the liquid raw materials, and the stirring data. The formula is as follows:

[0110] ;

[0111] Among them, k 1 is the solid dissolution time coefficient, with a value range of 2 to 6, which is determined according to the chemical properties and particle morphology of the solid raw materials. The higher the chemical stability and the more irregular the shape, the larger the solid dissolution time coefficient; k 2 is the liquid mixing time coefficient, with a value range of 0.3 to 1.5, which is determined according to the viscosity of the liquid raw materials. The higher the viscosity, the larger the liquid mixing time coefficient; k 3is the system gravity influence coefficient, with a value range of 0.5 - 1.2, which is determined according to the installation form of the mixing equipment and the structural characteristics of the mixing tank. When the mixing equipment is vertically installed and the mixing tank is relatively tall, the system gravity influence coefficient is relatively large; when the mixing equipment is horizontally installed or the mixing tank is short and stout, the system gravity influence coefficient is relatively small; g is the acceleration due to gravity, with a value of 9.8 m / s 2 .

[0112] It should be noted that the operating principle of this formula is as follows: Focus on the characteristics of solid raw materials. The greater the total mass DA of solid raw materials, the longer the time required to achieve full dissolution and uniform dispersion; the average density DB of solid raw materials determines the compactness of solid particles. The higher the density, the stronger the interaction force between particles, the greater the difficulty of dissolution, and the longer the required mixing time; the larger the effective shear area DF of the mixing impeller, the higher the crushing and dispersion efficiency of solid particles, and it can more efficiently promote the integration of solids into the liquid system, accelerating the mixing process, and the shorter the required mixing time; Focus on the factors of liquid raw materials. The larger the total volume DC of liquid raw materials, the more time it takes to reach a uniform mixing state, and the longer the required mixing time. The larger the average diffusion coefficient DD of liquid raw materials, it means that the diffusion speed of liquid molecules in the system is faster, and the shorter the required mixing time, represents the total mass of the compound. As the total mass of the system increases, the time required to overcome the gravity effect to fully mix the materials will increase correspondingly, and the longer the required mixing time. This formula comprehensively considers the above three factors to obtain the preset mixing duration WC.

[0113] Specifically, the method for calculating the preset mixing speed WD is as follows:

[0114] The mixing data also includes the Reynolds number EA, the dynamic viscosity EB of the liquid mixture, and the diameter EC of the mixing impeller.

[0115] It should be noted that the acquisition methods are as follows: The Reynolds number EA is a dimensionless number used to characterize whether the fluid flow state is laminar or turbulent, reflecting the relative magnitude of inertial force and viscous force, and is obtained by simulation and calculation using CFD software such as ANSYS Fluent and Flow - 3D, generally with a value range of 10 - 1000. The dynamic viscosity EB of the liquid mixture is a measure of the property of a liquid to resist flow, with the unit of Pascal·second. It represents the internal friction force received by a liquid layer with a unit area under a unit velocity gradient and is measured using the rotational viscometer method. Among them, the rotational viscometer method is a measurement method based on Newton's viscosity law and is used to measure the viscosities of various chemical raw materials and products, such as paints, concrete, admixtures, coatings, etc. The diameter EC of the mixing impeller refers to the maximum outer diameter size of the mixing impeller in the mixing equipment and is measured using measuring tools such as calipers and tape measures.

[0116] The preset stirring speed WD is calculated based on the average density DE of the liquid raw material, the Reynolds number EA, the dynamic viscosity EB of the liquid mixture, and the diameter EC of the stirring blade. The formula used is:

[0117] ;

[0118] It should be noted that this formula is based on the concept of Reynolds number in fluid mechanics. By presetting the Reynolds number EA and combining the average density DE of the liquid raw material, the dynamic viscosity EB of the liquid mixture, and the diameter EC of the stirring blade, the preset stirring speed WD is derived.

[0119] Specifically, the method for calculating the preset motor torque WE is as follows:

[0120] The stirring data also includes the motor voltage FA, the motor current FB, and the motor speed FC.

[0121] It should be noted that the motor voltage FA refers to the rated voltage at which the motor operates, with the unit of volts; the motor current FB refers to the rated current at which the motor operates, with the unit of amperes; the motor speed F refers to the rated speed at which the motor operates, with the unit of revolutions per second. The motor voltage FA, the motor current FB, and the motor speed FC are obtained by referring to the equipment manual or the nameplate.

[0122] The preset motor torque WE is calculated based on the preset stirring speed WD, the motor voltage FA, the motor current FB, and the motor speed FC. The formula used is:

[0123] ;

[0124] It should be noted that the operating principle of this formula is as follows: is the motor power. By calculating the ratio of the motor power to the preset stirring speed WD, the preset motor torque WE is obtained. Among them, 9550 is the conversion coefficient generated when converting the power unit from kilowatts to watts and the speed unit from revolutions per minute to radians per second.

[0125] Specifically, the method for calculating the deviation index RA of the stirring process is as follows:

[0126] The stirring data also includes the actual stirring duration HA, the actual stirring speed HB, and the actual motor torque HC.

[0127] It should be noted that the actual stirring duration HA refers to the time elapsed from the start to the end of the stirring operation. The method for obtaining it is as follows: query the start and stop times of the stirring equipment in the production record, and calculate the difference between the two as the actual stirring duration HA. The actual stirring speed HB refers to the rotational speed of the stirring paddle during the actual operation of the stirrer, which is measured using a tachometer. The actual motor torque HC refers to the torque actually output by the motor when driving the stirrer, which is measured by installing a torque sensor on the motor shaft or the stirring shaft.

[0128] Calculate the stirring process deviation index RA based on the preset stirring duration WC, preset stirring speed WD, preset motor torque WE, actual stirring duration HA, actual stirring speed HB, and actual motor torque HC. The formula is as follows:

[0129] ;

[0130] where ɑ 1 is the weight coefficient of the stirring duration deviation index, with a value ranging from 0.2 to 0.5, determined according to the influence degree of the stirring duration deviation index on the stirring process deviation index RA; ɑ 2 is the weight coefficient of the stirring speed deviation index, with a value ranging from 0.3 to 0.5, determined according to the influence degree of the stirring speed deviation index on the stirring process deviation index RA; ɑ 3 is the weight coefficient of the motor torque deviation index, with a value ranging from 0.2 to 0.5, determined according to the influence degree of the motor torque deviation index on the stirring process deviation index RA; and ɑ 1 + ɑ 2 + ɑ 3 = 1.

[0131] It should be noted that this formula uses a weighted formula to comprehensively consider the deviation degrees of the stirring duration, stirring speed, and motor torque to obtain the stirring process deviation index RA.

[0132] Specifically, the method for determining whether the stirring process meets the standard is as follows:

[0133] Determine whether the stirring process meets the standard based on the stirring process deviation index RA and the stirring process deviation threshold RB. The formula is as follows:

[0134] ;

[0135] When the stirring process meets the standard, send control signal three and continue to execute according to the current parameters;

[0136] When the stirring process does not meet the standard, send control signal four and adjust the operating parameters to the preset operating parameters.

[0137] It should be noted that the method for determining the deviation threshold RB of the stirring process is as follows: collect a large amount of historical data during the compounding of admixtures with qualified quality, calculate the deviation index of the stirring process according to the above method, screen out the lower 20% of the data and calculate their average value, which is used as the deviation threshold RB of the stirring process.

[0138] In the above solution, the preset stirring duration WC, the preset stirring speed WD, and the preset motor torque WE are calculated based on the feeding data and the stirring data. According to the stirring process deviation index RA and the stirring process deviation threshold RB, it is judged whether the stirring process meets the standard, which can timely detect abnormal situations in the stirring process, contribute to producing products with more stable quality, and solve the problems that the preset parameters cannot be dynamically calculated according to the feeding data and the actual situation in the stirring process, and it is also difficult to accurately evaluate the deviation of the stirring process.

[0139] A quality detection module that can calculate the performance deviation index SA based on the sampling detection data and the quality requirement data n ; a preset performance deviation threshold SD; according to the performance deviation index SA n and the performance deviation threshold SD to judge whether the sample performance is qualified; count the number of unqualified samples v, the density value PA u of the unqualified samples, the pH value PB u , the water reduction rate PC u and the setting retardation time PD u ; calculate the sample qualification rate YB according to the number of unqualified samples v; according to the density value PA u of the unqualified samples, the pH value PB u , the water reduction rate PC u and the setting retardation time PD u and the quality requirement data to calculate the comprehensive performance deviation degree index P; preset a qualification rate threshold RC and a comprehensive performance deviation threshold RD; judge whether it is necessary to adjust the preset parameters according to the sample qualification rate YB, the comprehensive performance deviation degree index P, the qualification rate threshold RC and the comprehensive performance deviation threshold RD. When it is necessary to adjust the preset parameters, send a control signal five; when it is not necessary to adjust the preset parameters, send a control signal six.

[0140] Specifically, the method for judging whether the sample performance is qualified is as follows:

[0141] The sampling detection data includes the density value LA n , the pH value LB n , the water reduction rate LC n and the setting retardation time LD n .

[0142] It should be noted that the density value LA n refers to the mass per unit volume of the sample, which is measured and obtained using a high-precision densitometer. The pH value LB nUsed to measure the acidity and alkalinity of the sample, obtained by measuring with a precision pH meter, water reduction rate LC n Refers to the ability of the admixture to reduce the water consumption of concrete. The acquisition method is as follows: First, prepare reference concrete, obtain the reference concrete mixture according to the mix ratio and mixing method specified in the "Code for Design of Ordinary Concrete Mix Ratio", control the water consumption to make the slump reach (80±10) mm, and record the unit water consumption ma at this time. Then, without changing the amounts of other materials such as cement, sand, and stone, add a certain amount of admixture, adjust the water consumption to make the slump of the freshly mixed concrete basically the same as that of the reference concrete, and record the unit water consumption mb at this time. Calculate the water reduction rate LC according to the formula (ma - mb) / ma n Setting retardation time LD n Refers to the time extended compared to the normal setting time of the concrete without adding admixtures after adding retarders and other admixtures. The acquisition method is as follows: First, prepare reference concrete and concrete with retarders. The reference concrete is prepared according to the standard mix ratio without adding retarders. The test concrete is prepared by adding retarders in accordance with the specified amount on the basis of the reference concrete mix ratio. Use a penetration resistance instrument to test the setting time of the two types of concrete. When the penetration resistance reaches 3.5 MPa, the concrete begins to lose its plasticity, and this time point is the initial setting time. Calculate the difference in the initial setting time of the two types of concrete as the setting retardation time LD n , where the penetration resistance instrument judges the setting state of the concrete by measuring the resistance of the measuring needle penetrating into the concrete mixture. As the concrete sets, its internal structure gradually forms, and the penetration resistance will gradually increase. The initial setting time refers to the time elapsed from the start of mixing cement with water to the time when the concrete mixture begins to lose its plasticity.

[0143] The quality requirement data include the standard density value MA, the standard pH value MB, the standard water reduction rate MC, and the standard setting retardation time MD.

[0144] It should be noted that the standard density value MA refers to the density value that the admixture should reach under specific conditions. It is an important physical index to measure whether the product quality is qualified, reflecting characteristics such as the compactness of the material or the uniformity of the material composition. The standard pH value MB is an index used to measure whether the acidity and alkalinity of the admixture meet the requirements. The standard water reduction rate MC refers to the standard ratio of the ability of the admixture to reduce the water consumption of concrete under specified test conditions, which is one of the key indexes to measure the performance of the admixture. The standard setting and retarding time MD refers to the standard time range in which the setting time of concrete after adding the admixture is extended or shortened compared with the setting time of the reference concrete without adding the admixture under specified test conditions, reflecting the influence degree of the admixture on the setting and hardening process of concrete. The standard density value MA, the standard pH value MB, the standard water reduction rate MC and the standard setting and retarding time MD are obtained by referring to the national or industry-specified standard documents, such as GB8076-2008 "Concrete Admixtures" and GB50119-2013 "Technical Specification for Application of Concrete Admixtures", etc.

[0145] Calculate the performance deviation index SA based on the sampling test data and the quality requirement data n , and the formula relied on is:

[0146] ;

[0147] Among them, SA n is the performance deviation index of the nth test sample, n is the serial number corresponding to different test samples, and the value is a positive integer; LA n is the density value of the nth test sample; LB n is the pH value of the nth test sample; LC n is the water reduction rate of the nth test sample; LD n is the setting and retarding time of the nth test sample.

[0148] It should be noted that the operating principle of this formula is: is the density value deviation index of the sample,

[0149] is the pH value deviation index of the sample, is the water reduction rate deviation index of the sample,

[0150] is the setting and retarding time deviation index of the sample. This formula obtains the performance deviation index SA by taking the square root of the sum of the squares of the four indexes n .

[0151] Judge whether the sample performance is qualified according to the performance deviation index SA n and the performance deviation threshold SD, and the formula relied on is:

[0152] ;

[0153] It should be noted that the method for determining the performance deviation threshold SD is as follows: collect a large amount of historical data during the compounding of qualified admixtures, calculate the performance deviation index according to the above method, screen out the lower 50% of the data and calculate its average value as the reference value of the performance deviation threshold SD.

[0154] Specifically, the method for determining whether to adjust the preset parameters is as follows:

[0155] Calculate the sample qualification rate YB based on the number of unqualified samples v, and the formula is:

[0156] ;

[0157] Among them, YA is the total number of test samples, and the value is a positive integer.

[0158] It should be noted that this formula obtains the sample qualification rate YB by calculating the proportion of the number of unqualified samples v in the total number of test samples.

[0159] According to the density value PA of the unqualified samples u , pH value PB u , water reduction rate PC u , setting retardation time PD u and the quality requirement data, calculate the comprehensive performance deviation degree index P, and the formula is:

[0160] ;

[0161] Among them, PA u is the density value of the u-th unqualified sample, u is the serial number corresponding to different unqualified samples, and the value range is [1, v]; PB u is the pH value of the u-th unqualified sample; PC u is the water reduction rate of the u-th unqualified sample; PD u is the setting retardation time of the u-th unqualified sample.

[0162] It should be noted that the operating principle of this formula is: represents the sum of the absolute deviations of the density values of all unqualified samples from the standard density value, represents the sum of the absolute deviations of the pH values of all unqualified samples from the standard pH value, represents the sum of the absolute deviations of the water reduction rates of all unqualified samples from the standard water reduction rate, represents the sum of the absolute deviations of the setting retardation times of all unqualified samples from the standard setting retardation time, is a normalization factor used to normalize the sum of deviations to a relative ratio for easier comparison under different sample quantities and standard values. This formula quantifies and normalizes the deviations of unqualified samples from the standard values on multiple key performance indicators to obtain the comprehensive performance deviation index P.

[0163] Based on the sample qualification rate YB, the comprehensive performance deviation index P, the qualification rate threshold RC, and the comprehensive performance deviation threshold RD, it is determined whether the preset parameters need to be adjusted. The formula used is:

[0164] ;

[0165] It should be noted that the determination methods for the qualification rate threshold RC and the comprehensive performance deviation threshold RD are as follows: Collect historical data during the compounding of a large number of qualified admixtures. Calculate the sample qualification rate according to the above method, screen out the higher 60% of the data and calculate their average value as the reference value for the qualification rate threshold RC. Collect historical data during the compounding of a large number of qualified admixtures. Calculate the comprehensive performance deviation index according to the above method, further calculate the average value and standard deviation of the comprehensive performance deviation index, and calculate the value of the average value minus twice the standard deviation as the reference value for the comprehensive performance deviation threshold RD.

[0166] When the preset parameters need to be adjusted, a control signal five is issued. The metering and batching module adjusts the raw material ratio according to the control instruction; the mixing and stirring module adjusts the stirring time, stirring speed, or motor torque according to the control instruction;

[0167] When the preset parameters do not need to be adjusted, a control signal six is issued, and the mixing continues according to the current parameters.

[0168] In the above solution, determining whether the preset parameters need to be adjusted based on the sample qualification rate YB, the comprehensive performance deviation index P, the qualification rate threshold RC, and the comprehensive performance deviation threshold RD can accurately judge whether the product quality is within the acceptable range, help maintain the consistency of product quality, effectively reduce rework situations, and solve the problems of long quality inspection time intervals, inability to detect quality problems in a timely manner, and insufficiently detailed statistics and analysis of unqualified samples, making it impossible to quickly and accurately judge whether the preset parameters need to be adjusted.

[0169] The intelligent control module is used to receive different control signals and issue control instructions for real-time adjustment according to the received control signals.

[0170] Specifically, when receiving control signal one, the intelligent control module sends a control instruction to the metering and batching module to stop feeding.

[0171] When receiving Control Signal 2, the intelligent control module will trigger the warning lights installed at the operation site to remind the on-site operators that there is a problem with the feeding. Meanwhile, it will send a control instruction to the metering and batching module. When WA at <BA or WB ct <CA, continue feeding until it meets the standard; when WA at >BA or WB ct >CA, immediately stop feeding and remove the excess raw materials, then transport them to the storage container until it meets the standard.

[0172] When receiving Control Signal 3, the intelligent control module sends a control instruction to the mixing and stirring module to make it continue stirring according to the current parameters.

[0173] When receiving Control Signal 4, the intelligent control module issues an audible alarm to remind the on-site operators that there is a problem during the stirring process. Meanwhile, it sends a control instruction to the timer of the mixing and stirring module. When the stirring time has not reached the preset value, it continues to run; when the stirring time reaches or exceeds the preset value, it immediately stops running; it sends an adjustment signal to the frequency converter to change the output frequency until the stirring speed reaches the preset value; it issues a control instruction to adjust the input current or voltage of the motor until the motor torque reaches the preset value.

[0174] When receiving Control Signal 5, the intelligent control module calls the corresponding new formula from the database, converts it into specific control instructions for each raw material conveying equipment, and transmits them to the metering and batching module; it sends a control instruction to the mixing and stirring module to make it recalculate the preset parameters such as the stirring time, stirring speed, and motor torque according to the new formula, and stir according to these parameters.

[0175] When receiving Control Signal 6, the intelligent control module sends control instructions to the metering and batching module and the mixing and stirring module to keep running with the current parameters.

[0176] In the above solution, by receiving different control signals and sending control instructions for real-time adjustment according to the received control signals, it can accurately control each link in the production process, which is beneficial to improving production efficiency and raw material utilization rate.

[0177] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware or a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution.

[0178] The unit described as a separation component may or may not be physically separated. The component shown as a unit may or may not be a physical unit, that is, it may be located in one place or may be distributed over multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0179] The above is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered within the protection scope of the present application.

Claims

1. An intelligent control system for a concrete admixture compounding production line, characterized in that: include: Data collection module, used to collect feed data, raw material difference data, mixing data, sampling test data and quality requirement data; The metering and batching module can calculate the liquid raw material feed difference WA based on the feed data a And solid raw material feed difference WB c ; According to the liquid raw material feed difference WA a , solid raw material feed difference WB c The difference data between the raw materials and the feed material determines whether the feed material meets the standard; when the feed material meets the standard, a control signal 1 is issued; when the feed material does not meet the standard, a control signal 2 is issued; The mixing and stirring module can calculate the preset stirring time WC and the preset stirring speed WD based on the feeding data and the stirring data, calculate the preset motor torque WE according to the preset stirring speed WD and the stirring data, and calculate the stirring process deviation index RA according to the preset stirring time WC, the preset stirring speed WD, the preset motor torque WE and the stirring data; Preset the mixing process deviation threshold RB; According to the mixing process deviation index RA and the mixing process deviation threshold RB, it is judged whether the mixing process meets the standard; when the mixing process meets the standard, a control signal three is issued; when the mixing process does not meet the standard, a control signal four is issued; The quality inspection module can calculate the performance deviation index SA based on the sampling inspection data and quality requirement data n ; Preset performance deviation threshold SD; According to the performance deviation indicator SA n And the performance deviation threshold SD is used to determine whether the sample performance is qualified; the number of unqualified samples v and the density value PA of unqualified samples are counted u , pH value PB u , water reduction rate PC u and PD u ; Calculate the sample pass rate YB based on the number of unqualified samples v; Calculate the sample pass rate YB based on the density value PA of the unqualified samples u , pH value PB u , water reduction rate PC u , PD u Calculate the comprehensive performance deviation index P based on the quality requirement data; Preset the pass rate threshold RC and the comprehensive performance deviation threshold RD; According to the sample qualified rate YB, the comprehensive performance deviation index P, the qualified rate threshold RC and the comprehensive performance deviation threshold RD, it is judged whether the preset parameters need to be adjusted. When the preset parameters need to be adjusted, a control signal five is issued; when the preset parameters do not need to be adjusted, a control signal six is ​​issued; The intelligent control module is used to receive different control signals and issue control instructions according to the received control signals for real-time adjustment.

2. The intelligent control system of a concrete admixture compounding production line according to claim 1 is characterized in that: Calculate the liquid raw material feed difference WA a And solid raw material feed difference WB c The method is: Feed data includes liquid raw material preset feed amount AA a , Liquid raw material preset feeding time AB a , actual feed flow AC a (t), preset feed amount AD of solid raw materials c , Actual feed rate AE of solid raw materials c (t) and the average density DB of the solid raw material; Preset feed volume AA according to liquid raw material a , Liquid raw material preset feeding time AB a and the actual feed flow AC a (t) Calculate the liquid raw material feed difference WA at , the formula based on is: ; Among them, WA at is the feed difference of the a-th liquid raw material at time t, a is the serial number corresponding to different liquid raw materials, and its value is a positive integer; t is the serial number corresponding to different feeding times, and its value is a positive integer; AA a is the preset feed amount of the a-th liquid raw material; AB a is the preset feeding time of the a-th liquid raw material; AC a (t) is the actual feed flow rate of the a-th liquid raw material at time t; Preset feed amount AD according to solid raw materials c , Actual feed rate AE of solid raw materials c (t) and the average density DB of the solid raw material to calculate the solid raw material feed difference WB ct , the formula based on is: ; Among them, WB ct AD is the feed difference of the cth solid raw material at time t, c is the serial number corresponding to different solid raw materials, and its value is a positive integer; c is the preset feed amount of the cth solid raw material; AE c (t) is the actual feed rate of the cth solid raw material at time t.

3. The intelligent control system of a concrete admixture compounding production line according to claim 2 is characterized in that: The method to judge whether the feed meets the standard is: The raw material difference data includes the liquid raw material difference range [BA, BB] and the solid raw material difference range [CA, CB]; According to the liquid raw material feed difference WA at , solid raw material feed difference WB ct The formula used to judge whether the feed meets the standard is: ; When the feed meets the standard, a control signal 1 is issued to stop conveying the raw materials; When the feed does not meet the standard, a control signal two is issued. When WA at <BA or WB ct <CA, continue feeding until the standard is met; when WA at >BA or WB ct >CA, immediately stop feeding and remove the excess raw materials and transport them to the storage container until the standard is met.

4. The intelligent control system of a concrete admixture compounding production line according to claim 3 is characterized in that: The method for calculating the preset mixing time WC is: The feed data also includes the total mass DA of solid raw materials, the total volume DC of liquid raw materials, the average diffusion coefficient DD of liquid raw materials and the average density DE of liquid raw materials; The stirring data include the effective shear area DF of the stirring blade; The preset stirring time WC is calculated based on the total mass DA of the solid raw material, the average density DB of the solid raw material, the total volume DC of the liquid raw material, the average diffusion coefficient DD of the liquid raw material, the average density DE of the liquid raw material and the stirring data, and the formula is: ; Among them, k1 is the solid dissolution time coefficient, which is 2 to 6; k2 is the liquid mixing time coefficient, which is 0.3 to 1.5; k3 is the system gravity influence coefficient, which is 0.5 to 1.2; g is the gravitational acceleration, which is 9.8 m / s 2 .

5. The intelligent control system of a concrete admixture compounding production line according to claim 4 is characterized in that: The method for calculating the preset stirring speed WD is: The stirring data also include the Reynolds number EA, the dynamic viscosity of the liquid mixture EB and the stirring blade diameter EC; The preset stirring speed WD is calculated based on the average density DE of the liquid raw material, the Reynolds number EA, the dynamic viscosity EB of the liquid mixture and the diameter EC of the stirring blade, according to the formula: 。 6. The intelligent control system of a concrete admixture compounding production line according to claim 5 is characterized in that: The method for calculating the preset motor torque WE is: The stirring data also includes the motor voltage FA, the motor current FB and the motor speed FC; The preset motor torque WE is calculated based on the preset stirring speed WD, the motor voltage FA, the motor current FB and the motor speed FC, according to the formula: 。 7. The intelligent control system of the concrete admixture compounding production line according to claim 6 is characterized by: The method for calculating the mixing process deviation index RA is: The stirring data also includes the actual stirring time HA, the actual stirring speed HB and the actual motor torque HC; The stirring process deviation index RA is calculated according to the preset stirring time WC, the preset stirring speed WD, the preset motor torque WE, the actual stirring time HA, the actual stirring speed HB and the actual motor torque HC, and the formula is as follows: ; Among them, ɑ1 is the weight coefficient of the stirring time deviation index, which takes a value of 0.2 to 0.5; ɑ2 is the weight coefficient of the stirring speed deviation index, which takes a value of 0.3 to 0.5; ɑ3 is the weight coefficient of the motor torque deviation index, which takes a value of 0.2 to 0.5; and ɑ1+ɑ2+ɑ3=1.

8. The intelligent control system of the concrete admixture compounding production line according to claim 7 is characterized in that: The method to judge whether the mixing process meets the standard is: The mixing process deviation index RA and the mixing process deviation threshold RB are used to determine whether the mixing process meets the standard. The formula is: ; When the mixing process meets the standard, control signal three is issued to continue to execute according to the current parameters; When the mixing process does not meet the standards, a control signal 4 is sent to adjust the operating parameters to the preset operating parameters.

9. The intelligent control system of a concrete admixture compounding production line according to claim 8 is characterized in that: The method to judge whether the sample performance is qualified is: Sampling test data includes density value LA n , pH value LB n , water reduction rate LC n and LD n ; The quality requirement data include standard density value MA, standard pH value MB, standard water reduction rate MC and standard setting delay time MD; Calculate the performance deviation index SA based on the sampling test data and quality requirement data n , the formula based on is: ； Among them, SA n is the performance deviation index of the nth test sample, n is the serial number corresponding to different test samples, and its value is a positive integer; LA n is the density value of the nth test sample; LB n is the pH value of the nth test sample; LC n is the water reduction rate of the nth test sample; LD n is the coagulation time of the nth test sample; According to the performance deviation indicator SA n The performance deviation threshold SD is used to determine whether the sample performance is qualified, and the formula is: 。 10. The intelligent control system for a concrete admixture compounding production line according to claim 9, characterized in that: The method to determine whether the preset parameters need to be adjusted is: The sample pass rate YB is calculated based on the number of unqualified samples v, and the formula is: ; Among them, YA is the total number of samples tested, which is a positive integer; According to the density value PA of the unqualified sample u , pH value PB u , water reduction rate PC u , PD u The comprehensive performance deviation index P is calculated based on the quality requirement data, and the formula is: ; Among them, PA u is the density value of the u-th unqualified sample, u is the serial number corresponding to different unqualified samples, and its value is [1, v]; PB u is the pH value of the uth unqualified sample; PC u is the water reduction rate of the uth unqualified sample; PD u is the setting time of the uth unqualified sample; The formula used to determine whether the preset parameters need to be adjusted is as follows: ; When the preset parameters need to be adjusted, a control signal 5 is issued, and the metering and batching module adjusts the raw material ratio according to the control instruction; the mixing and stirring module adjusts the stirring time, stirring speed or motor torque according to the control instruction; When there is no need to adjust the preset parameters, a control signal 6 is sent to continue mixing according to the current parameters.

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