A limestone calcination quality optimization analysis method based on particle shape and particle size control

Abstract

The present application relates to the technical field of calcination quality optimization, and particularly relates to a limestone calcination quality optimization analysis method based on particle shape and particle size control. The present application collects particle shape data, particle size distribution data and chemical component data of the raw material entering the kiln, calculates particle shape influence factors, particle size dispersion coefficients and chemical activity indexes, and fuses them to generate a comprehensive quality coefficient, thereby realizing real-time quantitative evaluation based on particle shape, particle size and chemical component multi-source parameters. The present application constructs a calcination parameter matching model, takes the comprehensive quality coefficient as input, and outputs target combustion-supporting air volume, target coal gas flow and target channel temperature, thereby realizing feedforward control based on the characteristics of the raw material, dynamically responding to real-time fluctuations of the raw material entering the kiln, and avoiding regulation and control lag.

Description

Technical Field

[0001] This invention relates to the field of calcination quality optimization technology, specifically to a method for optimizing limestone calcination quality based on particle shape and particle size control. Background Technology

[0002] The quality of limestone calcination is affected by both the physical properties and chemical composition of the raw materials fed into the kiln. Among them, particle shape and particle size directly affect the permeability of the material layer, specific surface area, and heat and mass transfer efficiency inside the particles, while chemical composition directly determines the theoretical yield and reactivity of the raw materials.

[0003] Existing technology, such as Chinese invention patent publication number CN121202464A, discloses a method for optimizing the particle size range of raw materials for lime rotary kilns. This method involves classifying lime products by particle size, detecting the ratio of hydration residues in each particle size product, and comparing and analyzing the residue color characteristics, thereby providing a basis for optimizing the particle size range of raw materials for lime rotary kilns.

[0004] However, the existing technologies described above have the following problems: 1. The optimization process is mainly based on offline detection and analysis of the produced lime products. Adjusting the particle size range of subsequent raw materials by analyzing the calcination results of historical batches is a feedback optimization. When the particle shape, particle size distribution, or chemical composition of the limestone entering the kiln fluctuates, it is difficult to respond promptly to changes in the current raw material characteristics, resulting in a lag in control. 2. There is a lack of real-time analysis methods based on multiple parameters such as particle shape, particle size, and chemical composition. It is difficult to comprehensively quantify the impact of raw material fluctuations on the calcination process, and it is even more impossible to quickly match corresponding parameters such as air volume and gas flow rate for dynamic compensation during the calcination process. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art, and to solve the problems of the difficulty in dynamically responding to real-time fluctuations in raw materials entering the kiln and the lag in control caused by complex operating conditions, as well as the lack of real-time analysis and quantification of the impact of raw material fluctuations on the calcination process based on multi-source parameters such as particle shape, particle size, and chemical composition, and the lack of rapid matching of dynamic compensation strategies.

[0006] The technical solution adopted by this invention to solve its technical problem is: a limestone calcination quality optimization analysis method based on particle shape and particle size control, including the following steps: calculating the comprehensive quality coefficient of the current raw material entering the kiln based on the particle shape data, particle size distribution data and chemical composition data of the raw material entering the kiln.

[0007] The comprehensive quality coefficient is input into the pre-constructed calcination parameter matching model, and the target calcination parameter combination that matches the current raw material entering the kiln is output. The target calcination parameter combination includes the target combustion air volume, the target gas flow rate, and the target channel temperature.

[0008] Based on the real-time pressure difference between the kiln head and the kiln tail and the air volume entering the kiln during the calcination process, the air leakage rate of the kiln body is calculated; the target combustion air volume is compensated based on the air leakage rate of the kiln body to obtain the corrected combustion air volume; the excess air coefficient of the current calcination condition is calculated based on the corrected combustion air volume and the target gas flow rate.

[0009] Based on the difference between the target channel temperature and the real-time channel temperature and the excess air coefficient, the adjustment direction of the target gas flow rate is determined, and a control command is generated based on the adjusted gas flow rate and the corrected combustion air volume; the adjustment direction includes forward adjustment and reverse adjustment.

[0010] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention collects particle shape data, particle size distribution data and chemical composition data of raw materials entering the kiln, calculates particle shape influence factor, particle size dispersion coefficient and chemical activity index and integrates them to generate comprehensive quality coefficient, thereby realizing real-time quantitative evaluation based on multi-source parameters of particle shape, particle size and chemical composition.

[0011] 2. This invention constructs a calcination parameter matching model, which takes the comprehensive quality coefficient as input and outputs the target combustion air volume, target gas flow rate and target channel temperature, thereby realizing feedforward control based on raw material characteristics, so as to dynamically respond to the real-time fluctuations of raw materials entering the kiln and avoid control lag.

[0012] 3. This invention obtains the kiln leakage rate by calculating the pressure difference between the kiln head and the kiln tail and the air volume entering the kiln in real time, and compensates for the target combustion air volume to obtain the corrected combustion air volume, thus eliminating the interference of air leakage on the air volume balance in the kiln; and determines the direction of gas flow adjustment and generates control commands based on the deviation between the target channel temperature and the real-time channel temperature and the excess air coefficient, which can quickly match the corresponding air volume, gas flow and other parameters for dynamic compensation during the calcination process. Attached Figure Description

[0013] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1 This is a schematic diagram of the optimization analysis method of the present invention;

[0015] Figure 2 A schematic diagram illustrating the process for determining the overall quality coefficient in this invention;

[0016] Figure 3 This is a schematic diagram of the process for calculating the air leakage rate of the kiln body according to the present invention;

[0017] Figure 4This is a schematic diagram of the process for calculating the excess air coefficient according to the present invention. Detailed Implementation

[0018] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the invention. Furthermore, it should be understood that, for ease of description, the dimensions of the various parts shown in the drawings are not drawn to actual scale.

[0019] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the invention or its application or use. Techniques, methods, and apparatus known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and apparatus should be considered part of the specification.

[0020] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0022] The following description, in conjunction with the accompanying drawings, details a specific scheme for the limestone calcination quality optimization analysis method based on particle shape and particle size control provided by the present invention.

[0023] Please see Figure 1 The diagram illustrates a flowchart of a limestone calcination quality optimization analysis method based on particle shape and size control provided by the present invention, specifically including the following steps: Please refer to... Figure 2 Step S1: Calculate the comprehensive quality coefficient of the raw material entering the kiln based on the particle shape data, particle size distribution data and chemical composition data.

[0024] In practice, the particle shape data, particle size distribution data, and chemical composition data of the raw materials entering the kiln are first obtained.

[0025] The particle shape data includes roughness, which characterizes the degree of microscopic unevenness of the particle surface, and particle edge angle, which characterizes the sharpness of the particle outline. Roughness and particle edge angle can be obtained by image acquisition and analysis of the raw material before it enters the kiln using an industrial vision inspection system. The specific image acquisition and analysis process is existing technology and will not be described in detail here.

[0026] The particle size distribution data includes the mass percentage of each particle size range formed after the raw material is screened into the kiln, and the particle size distribution sequence constructed from the upper and lower limits of each particle size range. The mass percentage characterizes the weight distribution of particles of different sizes in the total raw material, directly reflecting the uniformity of the raw material; the particle size distribution sequence describes the overall size distribution characteristics of the raw material.

[0027] The specific acquisition process is as follows: The raw material sample entering the kiln is sieved through multiple layers using a mechanical vibrating screen to obtain the minimum and maximum particle sizes, constituting the overall particle size distribution range. The mass of each layer is then measured. Based on the kiln type, process control requirements, and screen specifications, the overall particle size distribution range is divided into several continuous particle size intervals, such as less than 5 mm, 5 to 10 mm, 10 to 15 mm, and 15 to 20 mm. These intervals are then arranged in ascending order, each interval represented by a numerical pair consisting of its upper and lower limits. The numerical pairs of all intervals are sequentially combined to form a particle size distribution sequence. Simultaneously, the mass of each layer is divided by the total mass to obtain the mass percentage of each particle size interval.

[0028] The chemical composition data includes the purity of calcium oxide, characterizing the content of effective components in limestone; the content of magnesium oxide, characterizing the level of associated impurities; and the total amount of acidic oxide impurities, characterizing the sum of impurities such as silicon, aluminum, and iron. The chemical composition data can be obtained by analyzing the raw material powder sample entering the kiln using X-ray fluorescence spectrometry. The total amount of acidic oxide impurities is the sum of the mass percentages of silicon dioxide, aluminum oxide, and ferric oxide.

[0029] Based on this, the comprehensive quality coefficient is then calculated. Specifically, the particle surface friction coefficient is first obtained by multiplying the particle edge angle by the roughness. The difference between the particle surface friction coefficient and the preset ideal sphere friction coefficient is calculated, and the ratio of the absolute value of this difference to the preset ideal sphere friction coefficient is used as the particle shape influence factor. The larger the particle shape influence factor, the lower the porosity between particles and the higher the risk of airflow resistance.

[0030] The ideal spherical friction coefficient characterizes the minimum friction coefficient of a smooth, regular sphere under the same external conditions (such as particle material and particle size), serving as a benchmark under ideal conditions. The ideal spherical friction coefficient can be obtained by consulting tribology handbooks. For limestone, the ideal spherical friction coefficient is typically in the range of 0.3-0.4, and in this invention, it can be specifically taken as 0.35.

[0031] Then, the particle size range with the highest mass proportion in the particle size distribution sequence is taken as the main particle size range. The ratio of the difference between the upper and lower limits of the main particle size range to the center value of the main particle size range is calculated to obtain the particle size dispersion coefficient. The larger the particle size dispersion coefficient, the more uneven the particle size within the main particle size range.

[0032] Next, the purity of calcium oxide is divided by the total amount of acidic oxide impurities to obtain the chemical purity ratio. Then, the chemical purity ratio is divided by the sum of one and the magnesium oxide content to obtain the chemical purity ratio after impurity correction.

[0033] Subsequently, the chemical purity ratio after impurity correction was divided by the theoretical stoichiometric ratio of calcium carbonate decomposition, and the result was normalized to obtain a chemical activity index in the range of 0-1. The closer the chemical activity index is to 1, the easier the raw material is to decompose and the lower the heat required.

[0034] The theoretical stoichiometric ratio of calcium carbonate decomposition refers to the theoretical mass ratio of calcium oxide to carbon dioxide when pure calcium carbonate is completely decomposed. That is, 100 parts of calcium carbonate decompose to produce 56 parts of calcium oxide and 44 parts of carbon dioxide. The mass ratio of calcium oxide to carbon dioxide is 56 / 44, which is approximately 1.27.

[0035] Finally, the particle size dispersion coefficient, particle shape influence factor, and chemical activity index are multiplied together to obtain the comprehensive quality coefficient. The comprehensive quality coefficient is dimensionless; the higher the value, the better the comprehensive quality of the raw material entering the kiln, that is, the higher the chemical activity, the more concentrated the particle size distribution, and the more regular the particle shape.

[0036] Step S2: Input the comprehensive quality coefficient into the pre-constructed calcination parameter matching model, and output the target calcination parameter combination that matches the current raw material entering the kiln.

[0037] The construction process of the calcination parameter matching model is as follows: First, multiple calcination condition adjustment operation records from the kiln's historical operation records are collected. These records include the comprehensive quality coefficient of the raw materials fed into the kiln and the target calcination parameter combination used under that comprehensive quality coefficient, forming a dataset. It should be noted that those skilled in the art should understand that historical operation records should exclude data affected by external factors such as equipment malfunctions and operational errors.

[0038] The target calcination parameter combination includes the target combustion air volume, the target gas flow rate, and the target channel temperature. The combustion air volume determines the oxygen supply, the gas flow rate determines the total heat input, and the channel temperature reflects the heat exchange efficiency. The synergistic effect of these three factors directly determines the limestone decomposition rate and energy consumption level. In this invention, the target channel temperature refers to the kiln tail flue gas temperature, that is, the temperature of the flue gas when it enters the settling chamber or preheater from the rotary kiln.

[0039] Then, the dataset is divided into training and validation sets according to a set ratio. To optimize model performance and test its generalization ability, stratified sampling can be used to maintain the distribution of different comprehensive quality coefficient ranges in the training and validation sets consistent with the original dataset. Furthermore, cross-validation can be used to select the specific ratio that minimizes the mean squared error of the validation set as the final set ratio. In this invention, an 8:2 ratio can be used.

[0040] Next, using the comprehensive quality coefficients from the training set as input features and the corresponding target calcination parameter combinations as target variables, the regression prediction model is trained. The regression prediction model includes, but is not limited to, random forest regression models and multilayer perceptron models. This invention employs a random forest regression model. Optimization algorithms (such as gradient descent or its variants) are used to fit and solve the model parameters, minimizing the error between predicted and actual values, thereby constructing an initial calcination parameter matching model.

[0041] Subsequently, the target calcination parameter combination of the validation set is predicted through the initial calcination parameter matching model. The initial calcination parameter matching model is adjusted and optimized using mean squared error and coefficient of determination. For example, the number of decision trees, the maximum depth of the trees, or the minimum number of sample splits in the random forest regression model are adjusted until the performance index of the model on the validation set meets the preset requirements. The final calcination parameter matching model is then output.

[0042] The coefficient of determination represents the degree to which the model's predicted values ​​explain the variability of the actual values. The closer the value is to 1, the higher the goodness of fit of the model and the better the prediction accuracy.

[0043] Mean squared error (MSE) represents the average of the squares of the differences between the predicted and actual values. The smaller the value, the higher the accuracy of the model's prediction and the smaller the error.

[0044] Please see Figure 3 Step S3: Calculate the kiln leakage rate based on the real-time pressure difference between the kiln head and the kiln tail and the air volume entering the kiln during the calcination process; obtain the corrected combustion air volume based on the kiln leakage rate and the target combustion air volume.

[0045] Air leakage can occur during kiln operation, which can disrupt the air volume balance and pressure distribution inside the kiln. Therefore, it is necessary to estimate the air leakage in real time and correct the target combustion air volume.

[0046] In practice, the pressure at the kiln head and kiln tail ends is obtained in real time through a pressure transmitter, and the air volume entering the kiln is obtained in real time through a flow meter installed on the air supply duct.

[0047] When the kiln is in a cold state (completely stopped and the internal temperature has dropped to ambient temperature) and all orifice valves are closed, start the combustion blower. By adjusting the blower speed or valve opening, at least six different test air volumes are blown into the kiln, and the pressure difference between the kiln head and tail ends is recorded for each test air volume. At this time, there is no high-temperature airflow disturbance and no change in raw material resistance inside the kiln; the pressure difference is entirely generated by the air volume overcoming the kiln resistance, thus forming a corresponding record of pressure difference and air volume.

[0048] The number of test air volumes can be selected according to 30%, 50%, 70%, and 90% of the rated air volume; the rated air volume can be obtained from the parameters on the fan nameplate.

[0049] During kiln firing, the pressure difference between the kiln head and kiln tail is calculated in real time at each moment. If the real-time pressure difference is equal to a pressure difference in the corresponding record, the corresponding test air volume is directly taken as the theoretical kiln inlet air volume at that moment. If the real-time pressure difference is not equal to any pressure difference in the corresponding record, the theoretical kiln inlet air volume Q is calculated based on the corresponding record using the following formula: .

[0050] in, , These are the smaller and larger values ​​of the two pressure differences adjacent to the real-time pressure difference, respectively. , They are respectively , The corresponding test air volume; P is the real-time pressure difference.

[0051] Preferably, considering the difference between the pressure difference and air volume relationship obtained from the above cold-state test and the actual situation where there are raw materials in the kiln and the kiln is at a high temperature, a correction factor is introduced to correct the theoretical kiln inlet air volume obtained above. The formula for calculating the correction factor K is as follows: .

[0052] in, The current average temperature inside the kiln (°C); 273 represents the ambient temperature (°C) during cold testing; 273 is the conversion constant for converting Celsius to Kelvin. This refers to the gas density during cold testing. The current gas density can be obtained in real time using a gas density meter.

[0053] Multiply the theoretical kiln inlet air volume obtained above by the correction factor K to obtain the corrected theoretical kiln inlet air volume, which is used for subsequent calculation of kiln leakage rate, but does not represent the actual air volume required to be sent into the kiln for actual production.

[0054] Next, the difference between the theoretical kiln inlet air volume and the measured kiln inlet air volume at the corresponding moment is calculated. This difference is then divided by the theoretical kiln inlet air volume to obtain the instantaneous air leakage rate. The instantaneous air leakage rate represents the proportion of air loss caused by air leakage at the current moment to the theoretical required air volume.

[0055] Finally, considering that the air leakage rate may fluctuate over time, the arithmetic mean of the instantaneous air leakage rates at multiple consecutive moments is taken as the kiln air leakage rate under the current calcination conditions. If the number of instantaneous air leakage rates collected before the current moment is less than 10, the arithmetic mean of all existing instantaneous air leakage rates is taken; if it reaches or exceeds 10, the arithmetic mean of the instantaneous air leakage rates at the 10 moments before the current moment is taken.

[0056] It should be noted that the pressure difference between the kiln head and the kiln tail is actually the difference between the average pressure of the cross-section at the kiln head and the average pressure of the cross-section at the kiln tail. The average cross-sectional pressure is obtained by taking the arithmetic mean of the measurements taken from at least six circumferentially distributed pressure measuring points evenly arranged on the same circumference of the cross-section.

[0057] If the kiln diameter is greater than 4 meters, the number of pressure measuring points can be increased to 12; if the kiln diameter is less than 2 meters, the number of pressure measuring points can be reduced to 4; for other kiln diameter values, the current number of pressure measuring points should be maintained.

[0058] After obtaining the kiln leakage rate, the corrected combustion air volume is obtained by compensating the target combustion air volume based on it.

[0059] The specific process is as follows: Because the raw material state and temperature distribution differ in different sections, the impact of air leakage on the calcination process also varies. Therefore, pressure distribution data is first obtained by collecting pressure data at pressure detection points set at predetermined intervals along the length of the kiln, using the pressure at each detection point at the same moment. This data is then repeatedly collected to obtain real-time pressure changes at each detection point within the collection period.

[0060] It should be noted that the pressure detection points are on the same horizontal line as the kiln body; the number of pressure detection points can be determined based on the total length of the kiln body, ensuring that the set distance does not exceed one-tenth of the total length of the kiln body, specifically one-fifteenth of the total length of the kiln body.

[0061] Then, based on the real-time pressure change data, taking the pressure of the last pressure detection point at the kiln tail end as the benchmark, the pressure difference between the remaining pressure detection points and the benchmark is calculated in sequence, and arranged in order from the kiln head to the kiln tail to form a pressure drop sequence.

[0062] Subsequently, the pressure drop sequence is traversed, and the difference between any two adjacent values ​​in the pressure drop sequence is calculated and sorted in descending order to form a pressure difference set. The set of pressure difference sets is then searched for the three consecutive differences with the largest values. If multiple sets of three consecutive differences exist, all of which are the maximum and equal, the set that appears first in the direction from the kiln head to the kiln tail is selected as the target interval. If no multiple sets of three consecutive differences exist, the set with the largest value is directly selected as the target interval.

[0063] Next, the starting pressure detection point of the target interval is marked as the first boundary point, and the ending pressure detection point is marked as the second boundary point. The area from the kiln head end to the first boundary point is designated as the kiln head section, the area from the first boundary point to the second boundary point is designated as the kiln middle section, and the area from the second boundary point to the kiln tail end is designated as the kiln tail section.

[0064] Subsequently, the real-time pressure difference between adjacent pressure monitoring points is calculated and accumulated along the length of the kiln to obtain the total pressure drop. The total pressure drop is then divided by the product of the particle size dispersion coefficient and the particle shape influence factor to obtain the resistance response coefficient. A smaller resistance response coefficient indicates a stronger obstruction of the airflow by the raw material, resulting in a lower ventilation volume that can pass through under the same pressure drop.

[0065] The process of pre-setting resistance level division intervals is as follows: collect the resistance response coefficients of multiple different production batches and sort them in ascending order of value. Divide them into at least 3 division intervals using the equal frequency method. Each division interval corresponds to a resistance level, such as low resistance level, medium resistance level, and high resistance level. The low resistance level corresponds to the ordinal number 1, the medium resistance level corresponds to the ordinal number 2, and the high resistance level corresponds to the ordinal number 3.

[0066] The resistance level of the current material layer is determined based on the interval to which the resistance response coefficient falls; the smaller the resistance response coefficient, the higher the resistance level. If the resistance response coefficient does not fall into any interval, it is assigned to the nearest adjacent interval. For example, a value less than the lower limit of the smallest interval is assigned to a low resistance level.

[0067] Because air leakage tends to occur in different areas under different resistance levels—for example, at high resistance levels, air leakage is more likely to occur in sections with low resistance—the current air leakage rate of the kiln body is allocated to the kiln head section, kiln middle section, and kiln tail section according to the resistance level in order to accurately locate the main location of air leakage.

[0068] The specific allocation process is as follows: the product of particle size dispersion coefficient and particle shape influence factor is divided by the pressure difference between the kiln head end and the kiln tail end to obtain the initial resistance distribution coefficient. Then, the initial resistance distribution coefficient is multiplied by the ordinal number corresponding to the current resistance level to obtain the corrected resistance distribution coefficient, so as to match the trend that air leakage is more likely to occur in the kiln head side section under high resistance level.

[0069] Then, each real-time pressure difference value is divided by the pressure difference between the kiln head and the kiln tail to obtain the pressure difference ratio between each adjacent pressure detection point. The absolute value of the difference between each pressure difference ratio and the corrected resistance distribution coefficient is calculated, and the position between adjacent detection points corresponding to the pressure difference ratio with the smallest absolute value is selected as the resistance boundary point. The section from the resistance boundary point to the kiln head is designated as the kiln head side section, and the remaining section from the resistance boundary point to the kiln tail is designated as the kiln tail side section.

[0070] Next, the current kiln leakage rate is multiplied by the current inlet air volume to obtain the leakage volumetric flow rate. Assuming the total length of the kiln is L, the length of the kiln head section is L1, and the length of the kiln tail section is L2, then the leakage component allocated to the kiln head section is the leakage volumetric flow rate multiplied by L1 / L, and the leakage component allocated to the kiln tail section is the leakage volumetric flow rate multiplied by L2 / L.

[0071] The air leakage component in the kiln head side section is the sum of the air leakage components in the kiln head section and the kiln middle section, and is considered as a type of air leakage. The air leakage component in the kiln tail side section is the same as the air leakage component in the kiln tail section, and is considered as a type of air leakage.

[0072] Subsequently, the reciprocal of the chemical activity index of the raw material currently entering the kiln is used as the heat compensation coefficient. Considering that the air leakage component in the kiln head section corresponds to the air volume that leaks before passing through the material layer, while the air leakage component in the kiln tail section corresponds to the air volume that leaks after passing through the material layer, the heat carried by the leakage component has been partially utilized, and heat compensation needs to be performed based on the activity of the raw material; therefore, the first type of air leakage is fully included in the compensation, while the second type of air leakage needs to be multiplied by the heat compensation coefficient.

[0073] Finally, the product of the second-class leakage volume and the heat compensation coefficient is added to the first-class leakage volume to obtain the total compensated air volume. The target combustion air volume is then added to the total compensated air volume to obtain the corrected combustion air volume. The corrected combustion air volume represents the total air volume that should be fed into the kiln to meet the actual calcination requirements, after considering leakage losses and heat compensation.

[0074] Please see Figure 4 Step S4: Calculate the excess air coefficient for the current calcination condition based on the target combustion air volume, the first-class air leakage volume, and the target gas flow rate.

[0075] Specifically, coal gas component analysis data is obtained through online gas chromatography or offline sampling and analysis. The coal gas component analysis data includes the volume percentage of various combustible components in the coal gas.

[0076] For each combustible component, the amount of oxygen required for its combustion is calculated based on the corresponding combustion chemical reaction equation. The amount of oxygen required for all combustible components is added together to obtain the total amount of oxygen required for the complete combustion of a unit volume of gas.

[0077] For example, the combustion chemical reaction equation for carbon monoxide (CO) is 2CO + 2CO + 2CO. =2 Therefore, the amount of oxygen required for the complete combustion of a unit volume of CO is 0.5 volume. If the volume percentage of CO in the gas is V, then the amount of oxygen required for combustion is 0.5V.

[0078] Then, divide the total amount of oxygen required for the complete combustion of a unit volume of gas by the oxygen volume fraction in the air (0.21) to obtain the theoretical amount of air required for the complete combustion of a unit volume of gas. Multiply the chemical activity index by the theoretical air amount to obtain the actual theoretical air requirement per unit volume of gas. Multiply the current target gas flow rate by the actual theoretical air requirement to obtain the total theoretical air required for the complete combustion of the current gas flow rate.

[0079] Finally, the effective air volume participating in the calcination reaction is obtained by subtracting the first-order leakage from the target combustion air volume. The excess air coefficient is obtained by dividing the effective air volume by the theoretical total air volume. If the excess air coefficient is too small, it may lead to incomplete combustion, producing black smoke and heat loss; while if it is too large, it will increase the heat loss carried away by the flue gas and may reduce the flame temperature, affecting heat transfer.

[0080] Step S5: Based on the difference between the target channel temperature and the real-time channel temperature and the excess air coefficient, determine the adjustment direction of the target gas flow rate and generate the control command.

[0081] The process for determining the adjustment direction is as follows: Calculate the difference between the target channel temperature and the real-time channel temperature to obtain the temperature deviation. Multiply the current measured gas flow rate by the theoretical air volume per unit, and then compare this with the measured combustion air volume per unit volume of gas to obtain the baseline value. The measured combustion air volume can be obtained in real time through a flow meter installed on the air supply duct. The channel temperature can be obtained through a temperature transmitter installed inside the kiln. The measured gas flow rate can be obtained through a gas flow meter on the gas pipeline.

[0082] Then, the logic for determining the adjustment direction is executed: if the temperature deviation is not zero, then when the temperature deviation is positive, the adjustment direction is determined to be positive, that is, to increase the gas flow rate; while when the temperature deviation is negative, the adjustment direction is determined to be negative, that is, to decrease the gas flow rate.

[0083] If the temperature deviation is zero, then when the current excess air coefficient is greater than the reference value, it indicates that there is excess air, which may lead to a decrease in temperature or thermal efficiency. Therefore, the adjustment direction is determined to be reverse adjustment. When the current excess air coefficient is less than the reference value, it indicates that there is insufficient air and incomplete combustion. Therefore, the adjustment direction is determined to be forward adjustment. When the current excess air coefficient is equal to the reference value, the current gas flow rate is kept constant.

[0084] After determining the adjustment direction, within the preset single adjustment step range, when the absolute value of the temperature deviation is less than the preset deviation threshold (e.g., 5℃), the lower limit of the single adjustment step range is selected as the adjustment amount. When the absolute value of the temperature deviation is greater than or equal to the preset deviation threshold, the ratio of the absolute value of the temperature deviation to the preset deviation threshold is calculated, and this ratio is multiplied by the upper limit of the single adjustment step range as the adjustment amount, and the adjustment amount does not exceed the upper limit of the single adjustment step range.

[0085] If the determined adjustment direction is positive, the adjustment amount is positive; if the determined adjustment direction is negative, the adjustment amount is negative.

[0086] In this invention, the single adjustment step size range can be exemplarily taken as 5% of the rated gas flow rate. The rated gas flow rate can be obtained from the range of the gas flow meter or the design parameters of the gas supply pipeline. If the rated heat load of the kiln is greater than 100MW, then 10% of the rated gas flow rate is taken; if the rated heat load of the kiln is less than or equal to 100MW, then 2% of the rated gas flow rate is taken. For other rated heat load values ​​of the kiln, the current single adjustment step size range is maintained.

[0087] If the cumulative time for a channel temperature deviation exceeding 8°C exceeds 15 minutes within a continuous hour, the preset deviation threshold will be reduced to 3°C; if the cumulative time for a channel temperature deviation less than 3°C exceeds 30 minutes within a continuous hour, the preset deviation threshold will be increased to 8°C. Otherwise, the current preset deviation threshold will be maintained.

[0088] Next, the target gas flow rate is superimposed with the adjusted flow rate to obtain the adjusted gas flow rate. If the adjusted gas flow rate exceeds the maximum or minimum flow limit of the gas regulating valve, the corresponding limit value is used as the adjusted gas flow rate. If the adjusted gas flow rate does not exceed the maximum or minimum flow limit, the calculated adjusted gas flow rate is maintained. The maximum and minimum flow limits of the gas regulating valve can be obtained from the technical parameter table provided by the valve manufacturer.

[0089] Next, the difference between the adjusted gas flow rate and the current measured gas flow rate, as well as the difference between the corrected combustion air volume and the current measured combustion air volume, are calculated to obtain the adjustment deviations of the gas flow rate and the combustion air volume.

[0090] Subsequently, a proportional control algorithm is used to convert the adjustment deviation of the gas flow rate into a gas regulating valve opening adjustment command, and the adjustment deviation of the combustion air flow rate into a combustion fan speed adjustment command. The specific conversion process is existing technology and will not be elaborated here. The combined gas regulating valve opening adjustment command and combustion fan speed adjustment command constitute the control command issued to the field actuator to achieve coordinated adjustment of gas and air flow.

[0091] The control instructions include: target equipment identifier (e.g., gas regulating valve 001), operation type (e.g., opening degree adjustment), target adjustment value (e.g., opening degree 35%), and instruction execution time.

[0092] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product.

[0093] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0094] In addition, the functional modules in the various embodiments of the present invention can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0095] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

[0096] Finally, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for optimizing limestone calcination quality based on particle shape and size control, characterized in that, Includes the following steps: Calculate the comprehensive quality coefficient of the raw materials entering the kiln based on the particle shape data, particle size distribution data, and chemical composition data of the raw materials. The comprehensive quality coefficient is input into the pre-constructed calcination parameter matching model, and the target calcination parameter combination that matches the current raw material entering the kiln is output; the target calcination parameter combination includes the target combustion air volume, the target gas flow rate, and the target channel temperature; Based on the real-time pressure difference between the kiln head and the kiln tail and the air volume entering the kiln during the calcination process, the air leakage rate of the kiln body is calculated; the target combustion air volume is compensated based on the air leakage rate of the kiln body to obtain the corrected combustion air volume and determine a type of air leakage. Calculate the excess air coefficient for the current calcination condition based on the target combustion air volume, Class I air leakage volume, and target gas flow rate. Based on the difference between the target channel temperature and the real-time channel temperature and the excess air coefficient, the adjustment direction of the target gas flow rate is determined, and a control command is generated based on the adjusted gas flow rate and the corrected combustion air volume; the adjustment direction includes forward adjustment and reverse adjustment.

2. The method for optimizing limestone calcination quality based on particle shape and particle size control according to claim 1, characterized in that, Particle shape data includes roughness and particle edge angle; particle size distribution data includes the mass percentage of each particle size range formed after screening of the raw material entering the kiln, and the particle size distribution sequence constructed from the upper and lower limits of each particle size range; chemical composition data includes calcium oxide purity, magnesium oxide content, and total amount of acidic oxide impurities.

3. The method for optimizing limestone calcination quality based on particle shape and particle size control according to claim 2, characterized in that, The calculation process for the overall quality coefficient is as follows: The particle surface friction coefficient is obtained by multiplying the particle edge angle by the roughness; the deviation of the particle surface friction coefficient from the preset ideal sphere friction coefficient is calculated as the particle shape influence factor. The difference between the upper and lower limits of the particle size interval with the highest mass proportion in the particle size distribution sequence is calculated and compared with the center value of the particle size interval to obtain the particle size dispersion coefficient. First, divide the purity of calcium oxide by the total amount of acidic oxide impurities to obtain the chemical purity ratio. Then, divide the chemical purity ratio by the sum of one and the magnesium oxide content to obtain the chemical purity ratio after impurity correction. The chemical purity ratio after impurity correction is divided by the theoretical stoichiometric ratio of calcium carbonate decomposition, and the result is normalized to obtain the chemical activity index. The comprehensive quality coefficient is obtained by multiplying the particle size dispersion coefficient, particle shape influence factor, and chemical activity index.

4. The method for optimizing limestone calcination quality based on particle shape and particle size control according to claim 3, characterized in that, The calcination parameter matching model is constructed as follows: Collect multiple calcination condition adjustment operation records from the historical operation records of the kiln; the records include the comprehensive quality coefficient of the raw materials fed into the kiln and the corresponding target calcination parameter combinations, forming a dataset; The dataset is divided into a training set and a validation set according to a set ratio; the comprehensive quality coefficient in the training set is used as the input feature, the corresponding target calcination parameter combination is used as the target variable, the set regression prediction model is input for training, the optimization algorithm is used to fit and solve the model parameters, and the initial calcination parameter matching model is constructed. The target calcination parameter combination of the validation set is predicted by the initial calcination parameter matching model. The prediction results are used to adjust and optimize the initial calcination parameter matching model, and the final calcination parameter matching model is output.

5. The method for optimizing limestone calcination quality based on particle shape and particle size control according to claim 2, characterized in that, The calculation process for the kiln air leakage rate is as follows: When the kiln is in a cold state and all the valves of the holes are closed, multiple test air volumes with different flow rates are blown into the kiln, and the pressure difference between the kiln head and the kiln tail is recorded under each test air volume to form a corresponding record of pressure difference and air volume. During the kiln firing process, the pressure difference between the kiln head and the kiln tail is calculated in real time at each moment. Find the test air volume corresponding to the real-time pressure difference from the corresponding record, and use it as the theoretical kiln inlet air volume; Calculate the difference between the theoretical kiln inlet air volume and the measured kiln inlet air volume at the corresponding moment, and divide the difference by the theoretical kiln inlet air volume to obtain the instantaneous air leakage rate; The arithmetic mean of the instantaneous air leakage rate at multiple consecutive moments is taken as the kiln body air leakage rate.

6. The method for optimizing limestone calcination quality based on particle shape and particle size control according to claim 3, characterized in that, The process for obtaining the corrected combustion air volume and Class I air leakage volume is as follows: Based on the real-time pressure changes at each pressure detection point set along the length of the kiln body, the kiln body is divided into the kiln head section, the kiln middle section, and the kiln tail section. Based on the particle shape influence factor and particle size dispersion coefficient of the current raw material entering the kiln, determine the resistance level of the material layer to the airflow. Based on the resistance level, the current air leakage rate of the kiln body is allocated to the kiln head section, the kiln middle section and the kiln tail section to obtain their respective air leakage components. The sum of the air leakage components in the kiln head section and the kiln middle section is taken as the first type of air leakage, and the air leakage component in the kiln tail section is taken as the second type of air leakage. The reciprocal of the chemical activity index of the raw material currently fed into the kiln is used as the heat compensation coefficient. Multiply the Class II air leakage by the heat compensation coefficient and add it to the Class I air leakage to obtain the total compensated air volume; add the target combustion air volume to the total compensated air volume to obtain the corrected combustion air volume.

7. The method for optimizing limestone calcination quality based on particle shape and particle size control according to claim 6, characterized in that, The process of obtaining the air leakage component is as follows: Calculate and sum the real-time pressure difference between adjacent pressure detection points along the length of the kiln body to obtain the total pressure drop; Dividing the total pressure drop by the product of the particle size dispersion coefficient and the particle shape influence factor yields the resistance response coefficient. The resistance level of the current material layer is determined based on the value of the resistance response coefficient. The resistance distribution coefficient is obtained by dividing the product of the particle size dispersion coefficient and the particle shape influence factor by the pressure difference between the kiln head and the kiln tail. Divide each real-time pressure difference value by the pressure difference between the kiln head end and the kiln tail end to obtain the pressure difference ratio between each adjacent pressure detection point. Calculate the absolute value of the difference between each pressure difference ratio and the resistance distribution coefficient, and select the position between adjacent detection points corresponding to the pressure difference ratio with the smallest absolute value as the resistance boundary point; use the resistance boundary point as the boundary to divide the kiln body into the kiln head side section and the kiln tail side section. The current air leakage rate of the kiln body is allocated according to the length ratio of the kiln head side section and the kiln tail side section to obtain the air leakage components of the kiln head side section and the kiln tail side section, which are respectively regarded as Class I air leakage and Class II air leakage.

8. The method for optimizing limestone calcination quality based on particle shape and particle size control according to claim 6, characterized in that, The calculation process for the excess air coefficient is as follows: Calculate the theoretical amount of air required for the complete combustion of a unit volume of gas based on the volume percentage of combustible components in the gas composition analysis data. Multiply the chemical activity index by the theoretical air volume to obtain the actual theoretical air requirement per unit volume of gas. Multiply the current target gas flow rate by the actual theoretical air demand to obtain the total theoretical air required for the complete combustion of the current gas flow rate. Subtracting the first type of air leakage from the target combustion air volume yields the effective air volume that actually participates in the calcination reaction; the excess air coefficient is obtained by dividing the effective air volume by the theoretical total air volume.

9. The method for optimizing limestone calcination quality based on particle shape and particle size control according to claim 8, characterized in that, The process of determining the adjustment direction is as follows: The temperature deviation is obtained by calculating the difference between the target channel temperature and the real-time channel temperature. Multiply the current measured gas flow rate by the theoretical air volume, and then compare it with the current measured combustion air volume per unit volume of gas to obtain the baseline value. If the temperature deviation is not zero, the adjustment direction is determined to be positive when the temperature deviation is positive and negative when the temperature deviation is negative. If the temperature deviation is zero, the adjustment direction is determined to be reverse when the current excess air coefficient is greater than the reference value, forward when it is less than the reference value, and the current gas flow rate is kept constant when it is equal to the reference value.

10. The method for optimizing limestone calcination quality based on particle shape and particle size control according to claim 1, characterized in that, The process of generating control commands is as follows: Based on the determined adjustment direction, the adjustment amount is selected within the preset single adjustment step size range, and the target gas flow rate is superimposed with the adjustment amount to obtain the adjusted gas flow rate. The difference between the adjusted gas flow rate and the current measured gas flow rate, and the difference between the corrected combustion air volume and the current measured combustion air volume are calculated respectively to obtain the adjustment deviation of the gas flow rate and the combustion air volume. The adjustment deviations of gas flow rate and combustion air volume are respectively converted into gas regulating valve opening adjustment commands and combustion air fan speed adjustment commands; The combined instructions for adjusting the opening degree of the gas regulating valve and the instructions for adjusting the speed of the combustion fan constitute the control instructions.

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