A method and system for optimizing analysis of cement clinker firing heat consumption

Abstract

The present application relates to the technical field of cement clinker sintering, and relates to a kind of cement clinker sintering heat consumption optimization analysis method and system.The present application collects the real-time working condition index and actual heat consumption value in the process of cement clinker sintering in real time, matches and analyzes it with the theoretical heat consumption benchmark and the benchmark range of theoretical working condition index output by heat consumption prediction model respectively, dynamically adjusts the preparation ratio of cement raw material based on the analysis result, realizes the accurate calculation and ratio balance of each raw material adjustment amount, improves the production stability and product qualification rate, simultaneously monitors the calcination state parameters of raw meal in the decomposing furnace and rotary kiln after ratio adjustment in real time, analyzes whether the oxygen content of flue gas at the outlet of decomposing furnace and the excess air coefficient of kiln head flue gas are within the optimal range, if it is out of the optimal range, dynamically controls the fuel supply amount and ventilation of decomposing furnace and the fuel supply amount and secondary air quantity of kiln head, so that the sintering heat consumption is continuously and stably at the optimal level.

Description

Technical Field

[0001] This invention relates to the field of cement clinker calcination technology, and to a method and system for optimizing the heat consumption of cement clinker calcination. Background Technology

[0002] Cement clinker calcination is a core step in the cement production process, and its heat consumption level directly affects the production cost, energy efficiency, and environmental benefits of cement production. With the increasing demands for energy conservation, emission reduction, and green, low-carbon development in the building materials industry, how to precisely optimize the heat consumption of cement clinker calcination and minimize energy consumption while ensuring clinker quality meets standards has become a critical issue that urgently needs to be addressed within the industry.

[0003] However, the existing technology has the following problems: 1. When the actual heat consumption is found to be higher than the theoretical value, the existing technology often uses fixed production experience to adjust the ratio without considering the sensitivity weight of different raw materials to changes in heat consumption and the optimization of the ratio balance. This results in the clinker quality not meeting the standards or the heat consumption increasing further after adjustment, affecting production stability.

[0004] 2. The linkage control between calcination state parameters and heat consumption is lacking. Existing technologies often only focus on adjusting the raw material ratio, ignoring the dynamic changes in calcination state parameters in the decomposition furnace and rotary kiln after the ratio is adjusted. If these parameters exceed the optimal range, it will lead to incomplete fuel combustion or increased heat loss. Even if the ratio is reasonable, it is difficult to achieve optimal heat consumption and precise control of heat consumption, which ultimately affects the overall optimization effect. Summary of the Invention

[0005] This invention aims to solve the problems of existing technologies and provides a method and system for optimizing the heat consumption of cement clinker during calcination. By constructing an accurate heat consumption prediction model, establishing a scientific proportioning adjustment mechanism, and realizing dynamic control of calcination parameters, the invention achieves full-process synergistic optimization of raw material proportioning and calcination state, ultimately reducing calcination heat consumption and improving energy utilization efficiency and product quality stability.

[0006] The technical solution adopted by the present invention to solve its technical problem is: The present invention provides a method for optimizing and analyzing the heat consumption of cement clinker calcination, including: S1, feeding the prepared cement raw materials into the calcining kiln in batches according to the set feeding amount, and collecting the real-time operating conditions and actual heat consumption values ​​during the cement clinker calcination process.

[0007] S2. Based on the preparation ratio of cement raw materials, the theoretical heat consumption benchmark and the benchmark range of theoretical working condition indicators are output through the heat consumption prediction model.

[0008] S3. Match the actual heat consumption value and real-time operating condition index with the theoretical heat consumption benchmark and the benchmark range of the theoretical operating condition index, respectively, and dynamically adjust the preparation ratio of cement raw materials based on the analysis results.

[0009] S4. Real-time monitoring of the calcination state parameters of the raw materials in the decomposition furnace and rotary kiln after adjusting the proportions, wherein the calcination state parameters include the oxygen content of the flue gas at the decomposition furnace outlet and the excess air coefficient of the flue gas at the kiln head.

[0010] S5. Based on the calcination state parameters, analyze whether the oxygen content of the flue gas at the decomposition furnace outlet and the excess air coefficient of the flue gas at the kiln head are within the optimal range. If they exceed the optimal range, dynamically control the fuel supply and ventilation of the decomposition furnace, as well as the fuel supply and secondary air volume at the kiln head.

[0011] The present invention also provides a system for optimizing and analyzing the heat consumption of cement clinker during calcination, including a calcination process monitoring module, a theoretical data acquisition module, a preparation ratio adjustment module, a calcination state parameter monitoring module, and a heat consumption correlation parameter optimization module.

[0012] The connections between the modules are as follows: the calcination process monitoring module is connected to the theoretical data acquisition module; the preparation ratio adjustment module is connected to both the theoretical data acquisition module and the calcination state parameter monitoring module; and the heat consumption correlation parameter optimization module is connected to the calcination state parameter monitoring module.

[0013] The calcination process monitoring module feeds the prepared cement raw materials into the calcining kiln in batches according to the set feeding amount, and collects real-time operating conditions and actual heat consumption values ​​during the cement clinker calcination process.

[0014] The theoretical data acquisition module, based on the preparation ratio of cement raw materials, outputs the theoretical heat consumption benchmark and the benchmark range of theoretical operating condition indicators through the heat consumption prediction model.

[0015] The preparation ratio adjustment module matches and analyzes the actual heat consumption value and real-time operating condition index with the theoretical heat consumption benchmark and the benchmark range of the theoretical operating condition index, and dynamically adjusts the preparation ratio of cement raw materials based on the analysis results.

[0016] The calcination state parameter monitoring module monitors the calcination state parameters of the raw materials in the decomposition furnace and rotary kiln in real time after the proportioning is adjusted. The calcination state parameters include the oxygen content of the flue gas at the decomposition furnace outlet and the excess air coefficient of the flue gas at the kiln head.

[0017] The heat consumption correlation parameter optimization module analyzes whether the oxygen content of the flue gas at the decomposition furnace outlet and the excess air coefficient of the flue gas at the kiln head are within the optimal range based on the calcination state parameters. If they exceed the optimal range, the module dynamically controls the fuel supply and ventilation of the decomposition furnace, as well as the fuel supply and secondary air volume at the kiln head.

[0018] Compared with the prior art, the present invention has the following beneficial effects: (1) The present invention constructs a heat consumption prediction model based on historical data of different historical firing records, and outputs the theoretical heat consumption benchmark and the benchmark range of theoretical working condition index by combining the preparation ratio of cement raw materials. This achieves accurate matching between theoretical data and raw material preparation ratio, provides a reliable basis for subsequent heat consumption optimization, effectively avoids blind optimization direction, and reduces ineffective energy consumption loss.

[0019] (2) This invention analyzes the actual heat consumption value and real-time operating conditions with the corresponding theoretical data, calculates the preliminary adjustment amount by combining the sensitivity weight of each cement raw material to heat consumption changes, and adjusts the proportion balance of cement raw materials based on the preliminary adjustment amount, so as to achieve accurate calculation and proportion balance of each raw material adjustment amount, reduce heat consumption while ensuring the quality of cement clinker meets the standards, and improve production stability and product qualification rate.

[0020] (3) This invention determines whether the oxygen content of the flue gas at the outlet of the decomposition furnace and the excess air coefficient of the flue gas at the kiln head are within the optimal range. When the optimal range is exceeded, the fuel supply and ventilation of the decomposition furnace and the fuel supply and secondary air volume at the kiln head are dynamically controlled to ensure full combustion and minimize heat loss in the calcination process after adjusting the proportions. This further consolidates the heat consumption optimization effect and keeps the calcination heat consumption stable at the optimal level. Attached Figure Description

[0021] 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.

[0022] Figure 1 This is a schematic diagram of the method steps of the present invention.

[0023] Figure 2 This is a schematic diagram of the calculation steps for the actual heat consumption value in this invention.

[0024] Figure 3 This is a schematic diagram of step S3 in the present invention.

[0025] Figure 4 This is a schematic diagram of the system module connections of the present invention. Detailed Implementation

[0026] 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.

[0027] 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.

[0028] 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.

[0029] Please see Figure 1 As shown, the present invention provides a method for optimizing the heat consumption of cement clinker calcination, including: S1, feeding the prepared cement raw materials into the calcining kiln in batches according to the set feeding amount, and collecting real-time operating conditions and actual heat consumption values ​​during the cement clinker calcination process.

[0030] Considering that the calcination of cement raw materials requires multiple continuous reaction stages, and the activity of calcium oxide produced by the decomposition of raw materials can only last for more than ten minutes, if all the raw materials are put into the calcination kiln at one time, it will not only cause uneven heating and insufficient reaction of the materials, but also cause some materials to miss the best calcination time, affecting the strength of cement in the later stage.

[0031] Based on this, the method for determining the set feed amount includes: based on the rated processing capacity of the calcining kiln and the specified range of material filling rate in the kiln, the product of the rated processing capacity and the maximum value of the range of material filling rate in the kiln is used as the set feed amount.

[0032] Furthermore, considering that the cement clinker calcination process is a continuous process of pre-treating raw materials before calcination to generate minerals that meet the strength requirements of cement, if there is a lack of real-time data collection on the operating conditions during this continuous process and reliance is placed solely on manual experience, the calcination state may become uncontrolled, directly affecting the stability of clinker quality.

[0033] It is also considered that the raw material decomposition rate in the operating condition index directly determines the sintering efficiency of the subsequent rotary kiln. If the raw material decomposition rate is insufficient, the raw material will be under-burned in the kiln, resulting in excessive free calcium oxide.

[0034] If the real-time calcination temperature deviates from the optimal temperature range for cement clinker burning, when the real-time calcination temperature exceeds the maximum value of the optimal temperature range, it will cause fuel waste. When the real-time calcination temperature is lower than the minimum value of the optimal temperature range, it will result in insufficient clinker burning strength in the later stages.

[0035] If the conveying rate does not match the processing capacity of the calcining kiln, it will cause material accumulation.

[0036] Based on this, in a preferred embodiment of the present invention, the real-time operating condition indicators and actual heat consumption values ​​are obtained as follows: First, the operating condition indicators are determined according to the pretreatment process of cement raw materials, wherein the operating condition indicators include raw material decomposition rate, real-time calcination temperature and conveying rate.

[0037] Secondly, corresponding online monitoring sensors are deployed in the pretreatment process to collect real-time operating indicators and obtain real-time operating indicators.

[0038] Finally, the total fuel consumption and clinker output of the pretreatment process are measured simultaneously, and the actual heat consumption is calculated by combining the energy balance principle.

[0039] In one specific embodiment, such as Figure 2 As shown, the calculation method for the actual heat consumption value is as follows: First, the total fuel consumption of the pretreatment process is calculated with the standard lower heating value of the corresponding fuel to obtain the fuel chemical energy. Combined with the physical energy brought in by the single set amount of cement raw material, the total input energy is obtained by summing.

[0040] Fuel chemical energy is the product of the total fuel consumption in the pretreatment process and the standard lower heating value of the corresponding fuel.

[0041] The formula for calculating the physical energy introduced by the single set release quantity is as follows: .

[0042] In the formula, The physical energy introduced for a single set of delivery quantities. Set the amount of cement raw material to be added at one time. The specific heat capacity of cement raw materials is determined based on the composition of the cement raw materials. This determination method is an existing technical means and will not be described in detail here. The temperature of cement raw materials entering the kiln is obtained through a raw material inlet temperature sensor.

[0043] The second step is to analyze the physical energy carried out by the clinker based on the clinker output and the real-time calcination temperature, and then add the energy lost due to heat dissipation at the kiln head to obtain the total output energy.

[0044] The formula for calculating the physical energy carried out by clinker is as follows: .

[0045] In the formula, To extract physical energy from clinker, This refers to clinker output. This refers to the specific heat capacity of clinker, obtained in the same way as the specific heat capacity of cement raw materials. This refers to the real-time calcination temperature.

[0046] The energy loss due to heat dissipation at the kiln head is calculated by multiplying the heat flux density monitoring with the surface area. The specific details are as follows: the kiln body is divided into monitoring sections at set length intervals along the axial direction. Multiple heat flux sensors are evenly distributed in each section along the circumference, and the heat flux sensors are in close contact with the outer surface of the kiln body insulation layer to ensure good thermal contact with the kiln body.

[0047] The heat flux density values ​​of each heat flux sensor are collected in real time. Combined with the surface area of ​​the cylinder of the corresponding monitoring section, the product of the heat flux density value and the surface area of ​​the cylinder is used as the heat dissipation loss of each monitoring section. The heat dissipation loss of all monitoring sections is accumulated to obtain the heat dissipation loss energy of the kiln head.

[0048] The third step is to analyze the deviation rate between the total input energy and the total output energy. If the deviation rate is less than the set deviation threshold, the ratio of fuel chemical energy to clinker output is taken as the actual heat consumption value. Otherwise, the energy loss due to heat dissipation at the kiln head is re-examined and the above operation is repeated until the actual heat consumption value is determined.

[0049] It should be noted that the standard lower heating value of different fuels is set by personnel in the fuel industry. For example, the standard lower heating value of pulverized coal is usually [missing information]. .

[0050] S2. Based on the preparation ratio of cement raw materials, the theoretical heat consumption benchmark and the benchmark range of theoretical working condition indicators are output through the heat consumption prediction model.

[0051] Considering the strong correlation between the proportion of raw cement meal preparation, operating conditions and heat consumption during the cement clinker firing process, and the different correlation patterns among different types of clinker, using cross-type data to train the model would lead to significant prediction bias. Therefore, it is necessary to accurately retrieve historical data from the cement production history database corresponding to different historical firing records of the same type of cement clinker to ensure data correlation.

[0052] Based on this, in this embodiment of the invention, the method for constructing the heat consumption prediction model is as follows: First, retrieve historical data of different historical firing records corresponding to the same type of cement clinker from the cement production history database, wherein the historical data includes raw material preparation ratio, historical operating condition indicators and historical heat consumption values.

[0053] Secondly, outlier removal and data standardization were performed on historical data to filter out the remaining historical firing records.

[0054] Next, using the raw material preparation ratios of some historical firing records in the historical firing record set as input features and the corresponding historical heat consumption values ​​as output labels, a quantitative mapping relationship between the raw material preparation ratios and heat consumption values ​​is established through regression analysis algorithms, and an initial heat consumption prediction model is constructed.

[0055] Finally, the remaining historical firing records are used to verify the accuracy of the initial heat loss prediction model. Once the accuracy verification is successful, the final heat loss prediction model is output.

[0056] Accuracy is defined as the percentage of samples where the deviation between the predicted heat loss value from the initial heat loss prediction model and the historical heat loss value is within the allowable heat loss range. Accuracy verification is considered successful when the accuracy exceeds a preset proportion corresponding to the total number of remaining historical firing records. For example, the preset proportion can be 0.8, and implementers can adjust the preset proportion themselves, but it should be less than 1 and not too small.

[0057] It should be noted that outlier removal and data standardization are existing technologies and will not be elaborated further.

[0058] Considering that cement clinker calcination is a process involving the linkage of raw material proportions, operating conditions, and heat consumption, even if the raw material proportions are reasonable, if the operating conditions exceed the reasonable range, it will still lead to an increase in heat consumption. Furthermore, different raw material proportions correspond to different ranges of operating conditions. If only a single operating condition threshold is set, it will result in a mismatch with the actual proportions.

[0059] Based on this, in a specific embodiment of the present invention, the output of the theoretical heat consumption benchmark and the benchmark range of the theoretical operating condition index specifically includes: inputting the preparation ratio of cement raw materials into the constructed heat consumption prediction model, and outputting the theoretical heat consumption benchmark.

[0060] Historical firing records were selected from the collection of historical firing records that had the same preparation ratio and theoretical heat consumption benchmark as cement raw materials.

[0061] The maximum and minimum values ​​of the operating conditions are selected from the historical operating conditions corresponding to the same historical firing records, and the benchmark range of the theoretical operating conditions is formed based on the maximum and minimum values ​​of the operating conditions.

[0062] This invention constructs a heat consumption prediction model based on historical data from different historical firing records. Combined with the preparation ratio of cement raw materials, it outputs a theoretical heat consumption benchmark and a benchmark range with theoretical operating conditions. This achieves a precise match between theoretical data and raw material preparation ratio, providing a reliable basis for subsequent heat consumption optimization, effectively avoiding blind optimization direction, and reducing ineffective energy consumption loss.

[0063] S3. Match the actual heat consumption value and real-time operating condition index with the theoretical heat consumption benchmark and the benchmark range of the theoretical operating condition index, respectively, and dynamically adjust the preparation ratio of cement raw materials based on the analysis results.

[0064] Preferably, such as Figure 3 As shown, the steps of S3 are as follows: S31, Match and compare the actual heat consumption value and real-time operating condition index with the theoretical heat consumption benchmark and the benchmark range of the theoretical operating condition index respectively.

[0065] S32. When the actual heat consumption value is lower than the theoretical heat consumption benchmark and the real-time operating condition index is within the benchmark range of the corresponding theoretical operating condition index, there is no need to adjust the preparation ratio of cement raw materials.

[0066] S33. Conversely, it is necessary to adjust the preparation ratio of cement raw materials to obtain the deviation value between the actual heat consumption value and the theoretical heat consumption benchmark.

[0067] S34. Based on the heat consumption deviation value and the set sensitivity weight of each cement raw material to heat consumption changes, the initial adjustment amount of each cement raw material is calculated by weighted allocation, and the proportion balance of cement raw materials is adjusted based on the initial adjustment amount.

[0068] It should be noted that the sensitivity weight of each cement raw material to changes in heat consumption is set as follows: a large amount of historical data of the same type of clinker is retrieved from the historical database, and the correlation between changes in the preparation ratio of cement raw materials and changes in heat consumption is analyzed. For example, linear regression is used to calculate the influence coefficient of changes in the content of each cement raw material on the heat consumption value, and the ratio of this coefficient to the sum of the influence coefficients of all changes in the content of cement raw materials on the heat consumption value is used as the sensitivity weight of each cement raw material.

[0069] In this embodiment of the invention, the adjustment of the proportion of cement raw materials based on the initial adjustment amount specifically includes: first, obtaining the initial amount of each cement raw material according to the preparation proportion of the cement raw materials.

[0070] Next, the initial content of each cement raw material is added to the corresponding preliminary adjustment amount to obtain the final content.

[0071] Finally, the final content of each cement raw material is compared with the total final content of all cement raw materials, and the ratio of each cement raw material is converted into the adjusted cement raw material ratio.

[0072] This invention analyzes and matches actual heat consumption values ​​and real-time operating conditions with corresponding theoretical data. It calculates preliminary adjustment amounts by combining the sensitivity weights of each cement raw material to changes in heat consumption. Based on these preliminary adjustment amounts, it balances the proportions of the cement raw materials, achieving accurate calculation and proportion balance of each raw material's adjustment amount. This reduces heat consumption while ensuring the quality of cement clinker meets standards, improving production stability and product qualification rate.

[0073] Considering that the calcium carbonate content and the proportion of silica-alumina raw materials in the raw meal will change after the cement raw meal raw material ratio is adjusted, which will affect the decomposition efficiency of the raw meal in the decomposition furnace and the sintering reaction in the rotary kiln, if only the cement raw meal raw material ratio is adjusted but the subsequent changes in calcination state are ignored, even if the ratio meets the theoretical optimal, the heat consumption may increase or the clinker quality may decrease due to the mismatch of calcination conditions.

[0074] Based on this, in this embodiment of the invention, S4, real-time monitoring of the calcination state parameters of the raw materials in the decomposition furnace and rotary kiln after adjusting the proportions, wherein the calcination state parameters include the oxygen content of the flue gas at the outlet of the decomposition furnace and the excess air coefficient of the flue gas at the kiln head.

[0075] Preferably, the specific implementation of step S4 is as follows: by installing zirconia oxygen sensors and flue gas analyzers in the outlet flue of the decomposition furnace and the kiln head flue respectively, the oxygen content of the raw material in the outlet flue gas of the decomposition furnace and the excess air coefficient of the kiln head flue gas after adjusting the proportion are collected in real time, providing real-time and accurate status input for subsequent dynamic control of parameters, ensuring that calcination abnormalities can be detected in time, and avoiding the problem of heat consumption increasing despite proportion adjustment.

[0076] Among them, the excess air coefficient of the kiln head flue gas is the core parameter of the combustion system, which is defined as the ratio of the actual air supply to the theoretical air required for combustion.

[0077] S5. Based on the calcination state parameters, analyze whether the oxygen content of the flue gas at the decomposition furnace outlet and the excess air coefficient of the flue gas at the kiln head are within the optimal range. If they exceed the optimal range, dynamically control the fuel supply and ventilation of the decomposition furnace, as well as the fuel supply and secondary air volume at the kiln head.

[0078] The optimal range is determined by retrieving historical firing records that meet the cement clinker firing quality standards from the cement production history database, selecting the historical firing record with the lowest heat consumption value, and taking it as the historical optimal firing record.

[0079] The oxygen content of the flue gas at the decomposer outlet and the excess air coefficient of the flue gas at the kiln head in the historical best firing records were statistically analyzed, and the numerical ranges corresponding to the oxygen content of the flue gas at the decomposer outlet and the excess air coefficient of the flue gas at the kiln head were taken as the corresponding optimal ranges.

[0080] In this embodiment of the invention, the dynamic control of the fuel supply and ventilation of the decomposition furnace and the fuel supply and secondary air volume of the kiln head specifically includes: First, obtaining the deviation value of the oxygen content of the flue gas at the outlet of the decomposition furnace from the corresponding optimal range and the deviation value of the excess air coefficient of the flue gas at the kiln head from the corresponding optimal range, which are respectively recorded as the oxygen content deviation and the excess air coefficient deviation.

[0081] Next, based on the preset ratio between oxygen content deviation and ventilation volume adjustment, the ventilation volume adjustment value is determined in conjunction with the oxygen content deviation. The adjustment value of fuel supply is calculated based on the adjustment ratio between the ventilation volume adjustment value and the initial ventilation volume. The fuel supply and ventilation volume of the decomposition furnace are dynamically controlled based on the ventilation volume adjustment value and the fuel supply adjustment value.

[0082] Then, based on the dynamic control method of fuel supply and ventilation of the decomposition furnace, the secondary air volume and fuel supply of the kiln head are also dynamically controlled.

[0083] It should be noted that the adjustment value of the fuel supply is calculated by comparing the adjusted ventilation volume with the initial ventilation volume to obtain the ventilation volume adjustment ratio. The ventilation volume adjustment ratio reflects the increase or decrease in ventilation volume. In order to match the change in oxygen content, the fuel supply is adjusted synchronously according to the ventilation volume adjustment ratio to maintain combustion balance.

[0084] The product of the ventilation volume adjustment ratio and the original fuel supply of the decomposer is used as the adjustment value for the fuel supply.

[0085] Considering that the change in oxygen content in the flue gas at the decomposer outlet is directly related to the ventilation volume, insufficient ventilation will lead to an oxygen content lower than the optimal range, while excessive ventilation will lead to an oxygen content higher than the optimal range. Therefore, the adjustment value is calculated based on the ratio between the oxygen content deviation and the ventilation volume adjustment, thereby ensuring the scientific nature of the adjustment ratio.

[0086] Based on this, the preset ratio between the oxygen content deviation and the ventilation volume adjustment is as follows: retrieve all historical calcination records from the cement production history database where the oxygen content of the flue gas at the decomposition furnace outlet exceeds the optimal range, and extract the oxygen content deviation, the initial ventilation volume value, and the adjusted ventilation volume from each record.

[0087] The initial ventilation volume value was compared with the adjusted ventilation volume to obtain the ventilation volume adjustment value for each record. Linear regression analysis was used to analyze the regression coefficient between the oxygen content deviation and the ventilation volume adjustment value. Based on the regression coefficient, an equation was constructed to establish the proportional relationship between the oxygen content deviation and the ventilation volume adjustment.

[0088] This invention determines whether the oxygen content of the flue gas at the decomposition furnace outlet and the excess air coefficient of the flue gas at the kiln head are within the optimal range. When they exceed the optimal range, it dynamically controls the fuel supply and ventilation of the decomposition furnace, as well as the fuel supply and secondary air volume at the kiln head. This ensures full combustion and minimizes heat loss during the calcination process after adjusting the proportions, further consolidating the heat consumption optimization effect and keeping the calcination heat consumption consistently stable at the optimal level.

[0089] like Figure 4 As shown, the present invention provides a system for optimizing and analyzing the heat consumption of cement clinker during calcination, including a calcination process monitoring module, a theoretical data acquisition module, a preparation ratio adjustment module, a calcination state parameter monitoring module, and a heat consumption correlation parameter optimization module.

[0090] The connections between the modules are as follows: the calcination process monitoring module is connected to the theoretical data acquisition module; the preparation ratio adjustment module is connected to both the theoretical data acquisition module and the calcination state parameter monitoring module; and the heat consumption correlation parameter optimization module is connected to the calcination state parameter monitoring module.

[0091] The calcination process monitoring module feeds the prepared cement raw materials into the calcining kiln in batches according to the set feeding amount, and collects real-time operating conditions and actual heat consumption values ​​during the cement clinker calcination process.

[0092] The theoretical data acquisition module, based on the preparation ratio of cement raw materials, outputs the theoretical heat consumption benchmark and the benchmark range of theoretical operating condition indicators through the heat consumption prediction model.

[0093] The preparation ratio adjustment module matches and analyzes the actual heat consumption value and real-time operating condition index with the theoretical heat consumption benchmark and the benchmark range of the theoretical operating condition index, and dynamically adjusts the preparation ratio of cement raw materials based on the analysis results.

[0094] The calcination state parameter monitoring module monitors the calcination state parameters of the raw materials in the decomposition furnace and rotary kiln in real time after the proportioning is adjusted. The calcination state parameters include the oxygen content of the flue gas at the decomposition furnace outlet and the excess air coefficient of the flue gas at the kiln head.

[0095] The heat consumption correlation parameter optimization module analyzes whether the oxygen content of the flue gas at the decomposition furnace outlet and the excess air coefficient of the flue gas at the kiln head are within the optimal range based on the calcination state parameters. If they exceed the optimal range, the module dynamically controls the fuel supply and ventilation of the decomposition furnace, as well as the fuel supply and secondary air volume at the kiln head.

[0096] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0097] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0098] 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 implementation should not be considered beyond the scope of this application.

[0099] In addition, the functional modules in the various embodiments of this application 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.

[0100] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0101] 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 the heat consumption of cement clinker during firing, characterized in that, include: S1. The prepared cement raw materials are fed into the calcining kiln in batches according to the set feeding amount, and the real-time operating conditions and actual heat consumption values ​​of the cement clinker are collected in real time during the calcination process. S2. Based on the preparation ratio of cement raw materials, the theoretical heat consumption benchmark and the benchmark range of theoretical working condition indicators are output through the heat consumption prediction model. The preparation ratio of cement raw materials is input into the constructed heat consumption prediction model, and the theoretical heat consumption benchmark is output. The historical firing records with the same preparation ratio and theoretical heat consumption benchmark as cement raw materials are selected from the historical firing record set. The maximum and minimum values ​​of the working condition index are selected from the historical working condition index corresponding to each historical firing record. The benchmark range of the theoretical working condition index is constructed based on the maximum and minimum values ​​of the working condition index. S3. Match the actual heat consumption value and real-time operating condition index with the theoretical heat consumption benchmark and the benchmark range of the theoretical operating condition index, respectively, and dynamically adjust the preparation ratio of cement raw materials based on the analysis results. The actual heat consumption value and real-time operating condition index are matched and compared with the theoretical heat consumption benchmark and the benchmark range of the theoretical operating condition index, respectively. When the actual heat consumption is lower than the theoretical heat consumption benchmark and the real-time operating condition index is within the benchmark range of the corresponding theoretical operating condition index, there is no need to adjust the preparation ratio of cement raw materials. Conversely, it is necessary to adjust the preparation ratio of cement raw materials to obtain the actual heat consumption value and the heat consumption deviation value between the theoretical heat consumption benchmark; based on the heat consumption deviation value and the set sensitivity weight of each cement raw material to heat consumption changes, the initial adjustment amount of each cement raw material is calculated by weighted allocation, and the ratio of cement raw materials is adjusted to balance based on the initial adjustment amount. S4. Real-time monitoring of the calcination state parameters of the raw materials in the decomposition furnace and rotary kiln after adjusting the proportions, wherein the calcination state parameters include the oxygen content of the flue gas at the outlet of the decomposition furnace and the excess air coefficient of the flue gas at the kiln head. S5. Based on the calcination state parameters, analyze whether the oxygen content of the flue gas at the decomposition furnace outlet and the excess air coefficient of the flue gas at the kiln head are within the optimal range. If they exceed the optimal range, dynamically control the fuel supply and ventilation of the decomposition furnace, as well as the fuel supply and secondary air volume at the kiln head.

2. The method for optimizing the calcination heat consumption of cement clinker according to claim 1, characterized in that: The real-time operating condition indicators and actual heat consumption values ​​are obtained as follows: The operating conditions are determined based on the pretreatment process of cement raw materials, including raw material decomposition rate, real-time calcination temperature and conveying rate. In the pretreatment process, corresponding online monitoring sensors are deployed to collect various operating conditions in real time and obtain real-time operating conditions. The total fuel consumption and clinker output of the pretreatment process are measured simultaneously, and the actual heat consumption is calculated by combining the energy balance principle.

3. The method for optimizing the heat consumption of cement clinker firing according to claim 2, characterized in that: The actual heat consumption value is calculated as follows: The total fuel consumption in the pretreatment process is calculated by combining the standard lower calorific value of the corresponding fuel to obtain the fuel chemical energy. This is then combined with the physical energy brought in by the single set amount of cement raw material, and the total input energy is obtained by summing them up. The physical energy carried out by the clinker is obtained by combining the clinker output and real-time calcination temperature, and the total output energy is obtained by adding the energy lost due to heat dissipation at the kiln head. The deviation rate of total input energy and total output energy is analyzed. If the deviation rate is less than the set deviation threshold, the ratio of fuel chemical energy to clinker output is taken as the actual heat consumption value.

4. The method for optimizing the heat consumption of cement clinker firing according to claim 1, characterized in that: The method for constructing the heat loss prediction model is as follows: Historical data of different historical calcination records corresponding to the same type of cement clinker were retrieved from the cement production history database. The historical data included raw material preparation ratio, historical operating condition indicators, and historical heat consumption values. Outlier removal and data standardization were performed on historical data to filter out the remaining historical burning records. Using the raw material preparation ratios from a portion of the historical firing records as input features and the corresponding historical heat consumption values ​​as output labels, an initial heat consumption prediction model is trained and constructed. The remaining historical firing records are used to verify the accuracy of the initial heat loss prediction model. Once the accuracy verification is successful, the final heat loss prediction model is output.

5. The method for optimizing the heat consumption of cement clinker firing according to claim 1, characterized in that: The optimal range is determined as follows: Retrieve historical firing records that meet the cement clinker firing quality standards from the cement production history database, and select the historical firing record with the lowest heat consumption value as the best historical firing record. The oxygen content of the flue gas at the decomposer outlet and the excess air coefficient of the flue gas at the kiln head in the historical best firing records were statistically analyzed, and the numerical ranges corresponding to the oxygen content of the flue gas at the decomposer outlet and the excess air coefficient of the flue gas at the kiln head were taken as the corresponding optimal ranges.

6. The method for optimizing the heat consumption of cement clinker firing according to claim 1, characterized in that: The dynamic control of the fuel supply and ventilation volume of the decomposition furnace, as well as the fuel supply and secondary air volume at the kiln head, specifically includes: Obtain the deviation values ​​of oxygen content in flue gas at the decomposer outlet from the corresponding optimal range and the deviation values ​​of excess air coefficient in flue gas at the kiln head from the corresponding optimal range, and record them as oxygen content deviation and excess air coefficient deviation, respectively. Based on the preset ratio between oxygen content deviation and ventilation volume adjustment, the ventilation volume adjustment value is determined in conjunction with the oxygen content deviation. The adjustment value of fuel supply is calculated based on the adjustment ratio between the ventilation volume adjustment value and the initial ventilation volume. The fuel supply and ventilation volume of the decomposition furnace are dynamically controlled based on the ventilation volume adjustment value and the fuel supply adjustment value. Similarly, based on the dynamic control of fuel supply and ventilation in the decomposition furnace, the secondary air volume and fuel supply at the kiln head are also dynamically controlled.

7. The method for optimizing the calcination heat consumption of cement clinker according to claim 6, characterized in that: The preset ratio between the oxygen content deviation and the ventilation volume adjustment is as follows: Retrieve all historical calcination records from the cement production history database that show the oxygen content in the flue gas at the decomposer outlet exceeding the optimal range, and extract the oxygen content deviation, initial ventilation volume, and adjusted ventilation volume from each record; The initial ventilation volume value was compared with the adjusted ventilation volume to obtain the ventilation volume adjustment value for each record. Linear regression analysis was used to analyze the regression coefficient between the oxygen content deviation and the ventilation volume adjustment value. Based on the regression coefficient, an equation was constructed to establish the proportional relationship between the oxygen content deviation and the ventilation volume adjustment.

8. A system for optimizing and analyzing the calcination heat consumption of cement clinker, used to execute the steps in the method for optimizing and analyzing the calcination heat consumption of cement clinker according to any one of claims 1-7, characterized in that, include: The calcination process monitoring module feeds the prepared cement raw materials into the calcining kiln in batches according to the set feeding amount, and collects the real-time operating conditions and actual heat consumption values ​​of the cement clinker during the calcination process. The theoretical data acquisition module, based on the preparation ratio of cement raw materials, outputs the theoretical heat consumption benchmark and the benchmark range of theoretical working condition indicators through the heat consumption prediction model. The preparation ratio adjustment module matches and analyzes the actual heat consumption value and real-time operating condition index with the theoretical heat consumption benchmark and the benchmark range of the theoretical operating condition index, and dynamically adjusts the preparation ratio of cement raw materials based on the analysis results. The calcination state parameter monitoring module monitors the calcination state parameters of the raw materials in the decomposition furnace and rotary kiln after the proportioning is adjusted in real time. The calcination state parameters include the oxygen content of the flue gas at the outlet of the decomposition furnace and the excess air coefficient of the flue gas at the kiln head. The heat consumption correlation parameter optimization module analyzes whether the oxygen content of the flue gas at the decomposition furnace outlet and the excess air coefficient of the flue gas at the kiln head are within the optimal range based on the calcination state parameters. If they exceed the optimal range, the module dynamically controls the fuel supply and ventilation of the decomposition furnace, as well as the fuel supply and secondary air volume at the kiln head.

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