Control method and system for volatile kiln fuel supply

Abstract

The application provides a control method and system for volatile kiln fuel supply, and belongs to the technical field of industrial control. Firstly, real-time working condition data and historical working condition data of the volatile kiln are acquired, working condition trend prediction processing is performed based on the real-time working condition data and the historical working condition data, a working condition trend prediction result is obtained, a fuel supply plan library is constructed according to the working condition trend prediction result, a deviation between a current working condition and the prediction result is monitored in real time, a target supply adjustment strategy is matched and dynamically adapted from the fuel supply plan library, an execution scheme is obtained, the execution scheme is sent to a fuel supply system for execution, and feedback data is collected to update the plan library, so that the fuel supply of the volatile kiln can be intelligently and accurately controlled, the production efficiency and product quality are improved, and the cost is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of industrial control, in particular to a control method and system for volatile kiln fuel supply. BACKGROUND

[0002] In the field of industrial production, volatile kiln as an important thermal equipment is widely used in metallurgy, chemical industry and other industries. The accurate control of its fuel supply plays a key role in ensuring product quality, improving production efficiency and reducing energy consumption.

[0003] The traditional volatile kiln fuel supply control method mainly relies on manual experience and fixed control mode. In the manual experience control mode, the operator needs to adjust the fuel supply amount according to his subjective judgment of the volatile kiln working condition. However, due to the difference in experience level of different operators, and the manual judgment is easily affected by subjective factors, it is difficult to ensure the accuracy and stability of fuel supply. The fixed control mode is to supply fuel according to the pre-set parameters, which cannot be flexibly adjusted according to the dynamic changes of the actual working condition of the volatile kiln. In the production process, the working condition of the volatile kiln will change constantly due to the influence of many factors such as material composition, feeding speed, environmental temperature, etc. The fixed control mode cannot respond to these changes in time, which is easy to cause excessive or insufficient fuel supply. Excessive fuel supply will cause energy waste, increase production cost, and may also cause high temperature in the kiln, affecting the service life of the equipment and the quality of the product; insufficient fuel supply will cause insufficient reaction of the material in the kiln, reducing the production efficiency and product quality. SUMMARY

[0004] In view of the above-mentioned problems, in combination with the first aspect of the present application, the embodiments of the present application provide a control method for volatile kiln fuel supply, which comprises:

[0005] Obtaining volatile kiln real-time working condition data and volatile kiln historical working condition data, the volatile kiln real-time working condition data containing real-time reaction state information in the kiln and real-time processing progress information of the material, the volatile kiln historical working condition data containing fuel supply adjustment records and working condition change result information under different working conditions;

[0006] Performing working condition trend prediction processing based on the volatile kiln real-time working condition data and the volatile kiln historical working condition data, identifying the potential change direction and potential change period of the kiln working condition, and obtaining the working condition trend prediction result;

[0007] According to the working condition trend prediction result, a fuel supply plan library is constructed, the fuel supply plan library containing fuel supply adjustment strategies corresponding to different prediction trends, and each fuel supply adjustment strategy being associated with corresponding working condition adaptation conditions;

[0008] monitoring a deviation between the current working condition data of the volatile kiln and the working condition trend prediction result in real time, matching a target supply adjustment strategy from the fuel supply preplan library according to the deviation, and dynamically adapting the target supply adjustment strategy to obtain a fuel supply execution scheme;

[0009] sending the fuel supply execution scheme to a fuel supply system for execution, collecting kiln working condition feedback data after execution, and updating the fuel supply adjustment strategy and working condition adaptation condition in the fuel supply preplan library by using the kiln working condition feedback data.

[0010] In another aspect, the embodiment of the present application also provides a control system for fuel supply of a volatile kiln, which comprises a processor and a machine readable storage medium, the machine readable storage medium is connected with the processor, the machine readable storage medium is used for storing programs, instructions or codes, and the processor is used for executing the programs, instructions or codes in the machine readable storage medium to realize the above-mentioned method.

[0011] Based on the above aspects, the embodiment of the present application can recognize the potential change direction and potential change period of the kiln working condition by acquiring the volatile kiln real-time working condition data containing real-time reaction state information and real-time material processing progress information in the kiln, and the volatile kiln historical working condition data containing fuel supply adjustment records and working condition change result information under different working conditions, constructing a fuel supply preplan library according to the working condition trend prediction result, monitoring the deviation between the current working condition data and the prediction result in real time, matching a target supply adjustment strategy from the fuel supply preplan library according to the deviation, and dynamically adapting the target supply adjustment strategy to obtain a fuel supply execution scheme, which realizes the precise control and dynamic adjustment of the fuel supply, can timely respond to the working condition change, sends the fuel supply execution scheme to the fuel supply system for execution, collects the kiln working condition feedback data after execution, and updates the strategy and condition in the preplan library, continuously optimizes the fuel supply control effect, effectively improves the production efficiency and product quality of the volatile kiln, and reduces the energy consumption and production cost. BRIEF DESCRIPTION OF DRAWINGS

[0012] Figure 1 is an execution flow diagram of the control method for fuel supply of a volatile kiln provided by the embodiment of the present application.

[0013] Figure 2 is a schematic diagram of exemplary hardware and software components of the control system for fuel supply of a volatile kiln provided by the embodiment of the present application. DETAILED DESCRIPTION

[0014] The present application will be described in detail below with reference to the accompanying drawings, Figure 1is a flowchart of a control method for volatile kiln fuel supply provided by an embodiment of the present application. The control method for volatile kiln fuel supply will be described in detail below.

[0015] Step S110: Obtain volatile kiln real-time working condition data and volatile kiln historical working condition data. The volatile kiln real-time working condition data includes real-time reaction state information in the kiln and real-time processing progress information of the material. The volatile kiln historical working condition data includes fuel supply adjustment records and working condition change result information under different working conditions.

[0016] In this embodiment, the fuel supply control of the volatile kiln in the mineral roasting process is taken as the application scenario. Various monitoring devices are deployed on the kiln body, the feeding system, the discharging system, and the fuel supply system of the volatile kiln to collect data. The real-time reaction state information in the kiln is obtained by temperature sensor groups arranged uniformly along the length direction of the kiln body, an infrared thermal imager installed on the kiln top, a gas analyzer on the flue gas pipeline at the kiln tail, and a pressure sensor in the kiln. The temperature sensor groups collect temperature distribution data at different cross sections in the kiln, the infrared thermal imager captures temperature field images of the material surface in the kiln, the gas analyzer detects the volume fractions of oxygen, carbon monoxide, sulfur dioxide, and other gases in the flue gas, and the pressure sensor records the changes of static pressure and dynamic pressure in the kiln. The real-time processing progress information of the material is collected by a weighing sensor of the feeding belt, a material level meter in the kiln, a particle size detector at the discharging port, and a conveying speed sensor. The weighing sensor records the feeding amount per unit time, the level meter monitors the accumulation height of the material in the kiln, the particle size detector analyzes the particle size distribution of the discharged material, and the conveying speed sensor obtains the moving speed of the material in the kiln.

[0017] The volatile kiln historical working condition data is extracted from the database of the production management system and covers complete data of multiple production cycles in the past. The fuel supply adjustment records include fuel flow adjustment values, the opening number and angle settings of the fuel injection nozzles, the flow and pressure adjustment parameters of the combustion air, and fuel type switching records in different time periods. The working condition change result information corresponds to each adjustment record and includes the change curves of the temperatures in each region in the kiln after adjustment, the change data of the flue gas composition, the composition analysis results of the material after roasting, the fuel consumption data of the unit product, and the stability indicators of the equipment operation, etc.

[0018] During data collection, industrial-grade data acquisition modules are used for real-time operating condition data, supporting multiple signal types, with sampling frequencies set according to parameter characteristics. Slowly changing parameters such as temperature and pressure have longer sampling intervals, while rapidly changing parameters such as gas composition and material flow have shorter sampling intervals. Real-time data is transmitted to the data processing center via optical fiber, using encryption protocols to prevent data leakage or tampering. Historical operating condition data is stored in a redundant disk array, with regular backups and checks to ensure data integrity. At the same time, a data access management system is established, with sensitive data related to process parameters being divided into different access levels, with only authorized personnel allowed to query and modify the data.

[0019] Step S120: Based on the real-time operating condition data of the volatilization kiln and the historical operating condition data of the volatilization kiln, a trend prediction process is performed to identify the potential change direction and potential change period of the kiln operating conditions, and a trend prediction result is obtained.

[0020] After obtaining real-time and historical operating condition data, a series of processing steps such as data integration, feature extraction, and historical correlation analysis are performed to predict the future trend of kiln operating conditions based on the dynamic changes of real-time data and the experience rules of historical data.

[0021] Step S121: The real-time operating condition data of the volatilization kiln and the historical operating condition data of the volatilization kiln are integrated to obtain a standardized operating condition data set.

[0022] First, the real-time operating condition data and historical operating condition data of the volatilization kiln are preprocessed. The time format of the data is unified, and the timestamp of the real-time data and the recording time of the historical data are unified to the same format and the same time unit. The physical units of the data are standardized, such as temperature units in Celsius, pressure units in kilopascals, and flow units in cubic meters per hour. For abnormal jump values in real-time data, the Ljaparadze criterion is used to identify and remove them, and linear interpolation is used to fill in the data gaps. For missing data segments in historical data due to equipment failure, trend completion is performed based on complete data under similar operating conditions at the same time.

[0023] Then, the two types of data are integrated according to their attribute categories. Temperature, pressure, gas composition, and other data reflecting the reaction state in the kiln are classified into a reaction state data set, and feed quantity, material level, particle size, and conveying speed, and other data reflecting the material processing progress are classified into a material progress data set. The data in each data set is arranged in chronological order, and each data record contains data collection time, parameter name, parameter value, and data quality identifier. The data quality identifier is used to distinguish the reliability of the data, such as normally collected data, interpolated data, and manually corrected data.

[0024] Step S122: Extract the change characteristics of the volatile kiln real-time working condition data from the regularized working condition data set, and the change characteristics include the continuous change trajectory of the kiln reaction state and the rate change characteristics of the material processing progress.

[0025] The real-time working condition data of the recent period is filtered from the regularized working condition data set, and the time sequence feature extraction method is used to extract the change characteristics. For the continuous change trajectory of the kiln reaction state, the following methods are used: time series analysis is performed on the measurement values of the temperature sensors at different positions, the temperature change amount of each temperature sensor at consecutive time points is calculated, and the change slope of the temperature with time is obtained; the concentration data of each gas component detected by the gas analyzer is smoothed to remove high-frequency noise, and the trend item of the concentration change is extracted to obtain the change curve of the gas component; the measurement data of the pressure sensor is subjected to frequency spectrum analysis, and the main frequency component and amplitude change law of the pressure fluctuation are extracted. These temperature, gas and pressure change characteristics are combined to form the continuous change trajectory of the kiln reaction state, which can reflect the dynamic change of the reaction intensity in the kiln.

[0026] For the rate change characteristics of the material processing progress, the following methods are used: according to the measurement data of the feeding belt weighing sensor, the change rate of the feeding amount per unit time is calculated to obtain the change characteristics of the feeding rate; the filling rate change rate of the material in the kiln is calculated by combining the measurement data of the kiln level meter and the material conveying speed; the data of the discharge port particle size detector is statistically analyzed to calculate the change rate of the proportion of materials of different particle size ranges with time. These feeding, level and particle size rate change characteristics are integrated to form the rate change characteristics of the material processing progress, which can reflect the efficiency change trend of the material processing in the kiln.

[0027] Step S123: Associate the historical change segments similar to the change characteristics of the volatile kiln real-time working condition data in the volatile kiln historical working condition data, and extract the subsequent working condition change direction and subsequent working condition change period corresponding to the historical change segments.

[0028] Step S1231: Filter the historical data segments containing complete working condition change processes from the volatile kiln historical working condition data, and each historical data segment contains a change characteristic stage and a subsequent change stage.

[0029] Traverse the historical working condition data of the volatile kiln, and screen out historical data segments with complete working condition change cycles. Each historical data segment needs to include the complete process from the appearance of the change characteristics of the working condition, through the development and continuation of the characteristics, to the new stable state of the working condition or the turning point. The change characteristic stage refers to the stage in the historical data similar to the current real-time working condition change characteristics in trend, amplitude and frequency, for example, a stage in a historical segment where the temperature in the kiln presents a continuous upward trend, and the upward rate is similar to the current real-time data. The subsequent change stage is the development stage of the working condition after the characteristic stage, covering the entire process from the end of the characteristic stage to the stable or turning point. Each historical data segment is labeled with the start time, duration, key parameter change range of the change characteristic stage, and the time span and parameter change rule of the subsequent change stage.

[0030] Step S1232: Compare the change characteristics of the real-time working condition data of the volatile kiln with the change characteristic stages of each historical data segment, and calculate the feature similarity between the change characteristics and the change characteristic stages of each historical data segment.

[0031] Compare the current extracted real-time working condition change characteristics with the features of each historical data segment change characteristic stage in multiple dimensions. For the continuous change trajectory of the kiln reaction state, compare the consistency of temperature change trend (such as all rising, falling or stable), the closeness of temperature change rate, the shape similarity of gas composition change curve, the matching degree of pressure fluctuation frequency, etc. For the rate change characteristics of material handling progress, compare the consistency of feeding rate change direction, the similarity of material level change rate, the closeness of particle size change rate, etc.

[0032] In the comparison process, set the corresponding similarity calculation method for each feature dimension. For example, the consistency of temperature change trend is judged by comparing the direction of the trend vector, and the direction is the same, then the similarity of this dimension is high; the closeness of temperature change rate is measured by calculating the relative proportion of the rate difference, and the smaller the proportion, the higher the similarity. The similarity scores of each dimension are weighted and summed according to the preset weights to obtain the overall feature similarity. The setting of the weight is based on the importance of each feature dimension to the working condition change, for example, the weight of the temperature change feature is higher than that of the pressure fluctuation feature.

[0033] Step S1233: Screen out historical data segments with feature similarity higher than the similarity threshold, and select the screened historical data segments as candidate historical change segments.

[0034] According to the statistical analysis result of historical data, a feature similarity threshold is set. The determination of the feature similarity threshold comprehensively considers the distribution of similar feature segments in historical working conditions, ensuring that the selected historical segments have a high enough similarity with the current real-time changing features. The feature similarity of each historical data segment calculated is compared with the threshold, and the historical data segments with a feature similarity higher than the threshold are selected as candidate historical change segments, which enter the subsequent analysis process.

[0035] Step S1234: Extract the working condition change direction in the subsequent change stage of each candidate historical change segment, determine the key working condition parameter type associated with the working condition change direction, and record the change range of each key working condition parameter in the change direction.

[0036] The subsequent change stage of each candidate historical change segment is analyzed in detail to determine the working condition change direction. The working condition change direction includes reaction intensity enhancement in the kiln, reaction intensity weakening, reaction state remaining stable, and reaction abnormal fluctuation. For example, if the temperature continues to rise and the reaction gas concentration increases in the subsequent change stage, it is determined that the working condition change direction is reaction intensity enhancement; if the temperature gradually decreases and the proportion of unreacted components in the gas increases, it is determined that the working condition change direction is reaction intensity weakening.

[0037] The key working condition parameter type associated with each working condition change direction is determined. The key parameters associated with reaction intensity enhancement usually include kiln high-temperature zone temperature, reaction characteristic gas concentration, and material conversion rate; the key parameters associated with reaction intensity weakening include low-temperature zone temperature proportion, unreacted gas concentration, and material residence time; and the key parameters associated with reaction abnormal fluctuation include temperature fluctuation amplitude, pressure mutation frequency, and gas component fluctuation range.

[0038] The change range of each key working condition parameter in the change direction is recorded respectively. For example, for the change direction of reaction intensity enhancement, the target range of high-temperature zone temperature rising from the initial range and the target proportion of characteristic gas concentration increasing from the initial proportion are recorded; for the change direction of reaction intensity weakening, the target proportion of low-temperature zone temperature proportion rising from the initial proportion and the target concentration of unreacted gas concentration rising from the initial concentration are recorded. These change ranges are determined based on the actual measured values of the subsequent change stage of the historical data segment, and reflect the typical change interval of the parameters under similar change characteristics.

[0039] Step S1235: Extract the time length of the subsequent change stage of each candidate historical change segment, and determine the change period required for the key working condition parameters to reach a stable state according to the time length.

[0040] After analyzing the time series data of the subsequent change stage of each candidate historical change segment, the length of time experienced from the end of the change characteristic stage to the key working condition parameter reaching a steady state is determined. The steady state refers to a state in which the change rate of the key working condition parameter is reduced to below a preset stable threshold, and the parameter value fluctuates within a small range. For example, if the temperature in the subsequent change stage of a certain historical segment experiences a certain time from the end of the characteristic stage to the fluctuation amplitude being less than the stable threshold, then the time is the length of the subsequent change stage of the segment.

[0041] According to this length of time, in combination with the change rate of the key parameter in the historical segment and the change dynamics of the parameter in the current real-time working condition, the change period required for the key working condition parameter to reach a steady state under the current working condition is determined. The change period includes a starting period in which the parameter starts to change significantly, an acceleration period in which the change rate is fastest, a deceleration period in which the change rate gradually slows down, and a stable period in which the steady state is reached. For example, if the length of the subsequent change stage of the historical segment is short and the current real-time parameter change rate is fast, then the predicted change period to reach the steady state is correspondingly short; otherwise, it is long.

[0042] Step S1236: Record the corresponding working condition change direction, associated key working condition parameter type and its change range, change period for the key parameter to reach a steady state under the change direction, and characteristic similarity of each candidate historical change segment, to form a candidate historical information list.

[0043] The analysis results of each candidate historical change segment are recorded in a structured manner to form a candidate historical information list. Each record in the candidate historical information list includes the following contents: a specific description of the working condition change direction, such as “reaction intensity enhancement” and “reaction intensity weakening”; the associated key working condition parameter type, such as “high temperature zone temperature” and “characteristic gas concentration”; the specific change range of each key parameter under the change direction, represented in the form of parameter interval; the change period required for the key parameter to reach a steady state, including the time range of the starting period, the acceleration period, the deceleration period, and the stable period; and the characteristic similarity value of the historical segment and the current real-time change characteristic. Through the candidate historical information list, the key information of each candidate historical segment can be clearly displayed.

[0044] Step S1237: Perform deduplication processing on the working condition change direction and change period in the candidate historical information list, and retain the historical information with the highest characteristic similarity as the core reference information.

[0045] Step S1237-1: Classify the working condition change direction in the candidate historical information list, and group the historical information with the same or similar working condition change direction into the same direction group.

[0046] The change direction descriptions of each record in the candidate historical information list are compared one by one, and classified according to the core features of the change direction. For example, "slight increase in reaction intensity", "moderate increase in reaction intensity" and "significant increase in reaction intensity" are classified into the "reaction intensity increase" direction group; "slight decrease in reaction intensity" and "significant decrease in reaction intensity" are classified into the "reaction intensity decrease" direction group; and "local temperature fluctuation" and "slight pressure oscillation" are classified into the "stable fluctuation" direction group. Each direction group is provided with a unique identifier, and the number of historical information included in the group and the feature similarity of each information are recorded.

[0047] Step S1237-2: In each direction group, the first change period of the key process parameters reaching stability in the change direction of each historical information record is counted, and the average change period reaching stability in the same process change direction is calculated.

[0048] The change period (i.e., the first change period) of the key process parameters reaching stability of all historical information records in each direction group is extracted, including the start time, duration and other parameters. The first change period in the same direction group is statistically analyzed, and the average value of each period parameter is calculated to obtain the average change period reaching stability of the direction group. For example, there are three historical information in a certain direction group, and the duration of the first change period is a plurality of time length data, and the arithmetic mean value is calculated as the average duration of the group, and the average deviation value of the start time is calculated.

[0049] Step S1237-3: The feature similarity of each historical information in the same direction group is compared, and the historical information with the highest feature similarity is selected, and the second change period of the key process parameters reaching stability in the change direction of the historical information record is extracted.

[0050] In each direction group, the feature similarity values of each historical information are compared, and the historical information with the highest feature similarity is found. If there are multiple historical information with the same feature similarity and the highest feature similarity, the detailed matching degree of these information and the current real-time process characteristics is further compared, and the historical information with higher matching degree is selected as the high similarity candidate of the group. The change period (i.e., the second change period) of the key process parameters reaching stability of the high similarity candidate record is extracted, including the specific start time, the duration of each stage and other detailed information.

[0051] Step S1237-4: If the second change period deviates from the average change period reaching stability of the direction group by less than a set deviation, the historical information is directly selected as the representative information of the direction group.

[0052] The deviation value of the second change period from the average stable change period of the same direction group is calculated, and the deviation calculation includes the initial time deviation and the duration deviation. A deviation threshold is set, which is determined based on the statistical fluctuation range of historical data. If the calculated deviation value is less than the set deviation threshold, it indicates that the change period of the high similarity candidate is consistent with the average level of the same direction group, and the stability is high. The historical information is directly determined as the representative information of the direction group.

[0053] Step S1237-5: If the deviation of the second change period from the average stable change period of the same direction group is not less than the set deviation, the recorded stable change period of the key working condition parameter in the change direction of the historical information is corrected in combination with the average stable change period, to obtain a corrected stable change period. The historical information containing the corrected stable change period is taken as the representative information of the direction group.

[0054] When the deviation of the second change period from the average stable change period reaches or exceeds the set deviation threshold, the change period needs to be corrected. The correction method is to take the average stable change period as the reference, and to make a weighted adjustment in combination with the change trend of the second change period. For example, if the duration of the second change period is much longer than the average value, the duration is corrected to the weighted value of the average value and the second duration. The weight is set according to the feature similarity. The higher the feature similarity, the greater the weight of the second duration. The corrected stable change period is replaced by the original second change period to form the corrected historical information, which is taken as the representative information of the direction group.

[0055] Step S1237-6: From the representative information of each direction group, the representative information with the highest feature similarity is selected again as the core reference information.

[0056] The representative information of all direction groups is collected, and their feature similarity values are compared. The representative information with the highest feature similarity is selected as the core reference information. If there are multiple representative information with the same highest feature similarity, the fitting degree of their corresponding working condition change direction and the overall trend of the current real-time working condition is compared, and the representative information with the highest fitting degree is selected as the final core reference information.

[0057] Step S124: The change characteristics of the volatile kiln real-time working condition data and the similarity of the historical change segment are analyzed to determine the reference weight of the historical change segment to the current working condition.

[0058] The reference weight of each candidate historical change segment is determined according to the numerical size of the feature similarity. The higher the feature similarity of a historical segment, the more similar the change feature of the historical segment to the current real-time working condition, the greater the reference value for the current trend prediction, and thus a higher reference weight is given. The lower the feature similarity of a historical segment, the smaller the reference value, and thus a lower reference weight is given.

[0059] The calculation of the reference weight adopts a normalization processing mode, that is, the feature similarity value of each historical segment is divided by the sum of the feature similarity of all candidate historical segments, to obtain the relative weight of each historical segment. For example, if the feature similarity of a certain candidate historical segment is a certain numerical value, and the sum of the feature similarity of all candidate segments is another numerical value, then the reference weight of the segment is the ratio of the two. Through the above mode, the sum of the reference weights of all candidate historical segments is ensured to be the overall proportion, so that the reference values of different historical segments are reasonably distinguished.

[0060] Step S125: Based on the reference weight, the subsequent working condition information corresponding to the plurality of historical change segments is fused to generate a preliminary result of the potential change direction and the potential change period of the kiln working condition.

[0061] According to the reference weight of each candidate historical change segment, the corresponding subsequent working condition information is weighted and fused. For the potential change direction of the kiln working condition, the weight proportion of the change direction predicted by each candidate historical segment in the fusion is counted, and the change direction with the highest weight proportion is taken as the main candidate of the potential change direction. If there are multiple change directions with similar weight proportions, the overall stability of the current real-time working condition is combined for judgment, and the change direction consistent with the overall trend of the real-time working condition is preferentially selected.

[0062] For the change range of the key working condition parameter, the parameter change range of each candidate historical segment is weighted and integrated according to the reference weight. For example, if the change range of a certain parameter in two candidate segments is interval A and interval B respectively, and the corresponding reference weights are weight 1 and weight 2 respectively, then the integrated change range is the comprehensive interval of interval A according to weight 1 proportion and interval B according to weight 2 proportion. For the potential change period, the change period of each candidate segment is also weighted and calculated according to the reference weight to obtain the comprehensive start period, acceleration period, deceleration period and stable period.

[0063] Through the above fusion process, a preliminary result of the potential change direction and the potential change period of the kiln working condition is generated, which integrates the experience information of multiple similar historical segments.

[0064] Step S126: The preliminary result of the potential change direction and the potential change period is corrected in combination with the latest change dynamics of the volatile kiln real-time working condition data to obtain a final working condition trend prediction result.

[0065] The latest change trend of the real-time working condition data of the volatile kiln is obtained, that is, the real-time data newly collected after the preliminary result is generated. The change characteristics of these latest data are analyzed to determine whether they continue the previous change trend or whether new change signs appear. For example, if the rising rate of the latest temperature data is faster than the preliminary prediction, it indicates that the trend of increasing reaction intensity is more obvious; if the latest gas composition data appears abnormal fluctuations, it may indicate that the working condition change direction has changed.

[0066] The potential change direction is corrected according to the latest change trend. If the latest data supports the change direction of the preliminary prediction, the direction is maintained unchanged; if the latest data shows that the change direction deviates from the preliminary prediction, the description of the change direction is adjusted, or the uncertainty of the change direction is increased. The correction of the potential change period includes adjusting the time range of each period according to the change rate of the latest data. If the change rate is accelerated, the time to reach the stable state is shortened; if the change rate is slowed down, the corresponding time range is extended.

[0067] At the same time, the correction is combined with the interference factors in the real-time data, such as eliminating the influence of abnormal data caused by temporary sensor failure on the prediction result, or considering the delayed influence of external environmental changes (such as fluctuation of feed composition) on working condition changes. Through the above correction process, the final working condition trend prediction result is obtained, which includes the main potential change direction of the kiln working condition, the related key parameter change range, the specific period of each change stage, and the reliability identification of the prediction result.

[0068] Step S130: constructing a fuel supply plan library according to the working condition trend prediction result, the fuel supply plan library containing fuel supply adjustment strategies corresponding to different prediction trends, and each fuel supply adjustment strategy being associated with a corresponding working condition adaptation condition.

[0069] Based on the working condition trend prediction result, a plan library containing multiple fuel supply adjustment strategies is established through the steps of scene classification, strategy construction, condition association, and library structure design.

[0070] Step S131: classifying the potential change direction in the working condition trend prediction result to divide different working condition change scenes, each working condition change scene corresponding to a type of potential change direction.

[0071] The potential change direction in the working condition trend prediction result is analyzed in detail, and different working condition change scenarios are classified according to the nature, intensity and influence range of the change direction. For example, “reaction intensity enhancement and fast rate” and “reaction intensity enhancement and slow rate” are classified as reaction enhancement scenarios; “reaction intensity weakening and material retention” and “reaction intensity weakening and gas composition anomaly” are classified as reaction weakening scenarios; “reaction state is basically stable but local temperature fluctuates” is classified as a stable fluctuation scenario; and “reaction appears abnormal fluctuation and parameters exceed the range” is classified as an abnormal risk scenario. Each working condition change scenario has a clear feature description, including the core change direction, the change mode of the key parameters and the potential impact on the kiln reaction and material handling. For example, the core features of the reaction enhancement scenario are that the kiln temperature shows an overall upward trend, the reaction generated gas concentration increases, and the material handling rate accelerates; the core features of the reaction weakening scenario are that the temperature decreases, the unreacted material ratio increases, and the processing efficiency decreases; the core features of the stable fluctuation scenario are that the main parameters fluctuate within the normal range with small amplitude and no obvious overall trend; and the core features of the abnormal risk scenario are that the key parameters exceed the normal threshold and the fluctuation frequency and amplitude increase significantly. Through the above classification method, the complex working condition change trend is converted into a scenario category that is easy to manage.

[0072] Step S132: For each working condition change scenario, an adaptive fuel supply adjustment strategy is constructed, which includes the adjustment direction of the fuel supply amount and the adjustment method of the fuel supply rhythm.

[0073] Step S1321: Analyze the change of the kiln reaction demand for fuel under each working condition change scenario. If the working condition change scenario shows that the reaction intensity is enhanced, the adjustment direction of the fuel supply amount is determined to be increased; if the working condition change scenario shows that the reaction intensity is weakened, the adjustment direction of the fuel supply amount is determined to be decreased.

[0074] The core features of each working condition change scenario are analyzed, focusing on the change trend of the key parameters related to the reaction intensity. When the reaction intensity enhancement features such as continuous rise of kiln temperature, increase of reaction characteristic gas concentration and improvement of material conversion rate are obvious in the scenario, it is judged that the kiln reaction needs more heat support, so the adjustment direction of the fuel supply amount is determined to be increased. When the reaction intensity weakening features such as temperature drop, increase of unreacted component ratio and decrease of material processing efficiency appear in the scenario, it is judged that the reaction needs less heat, so the adjustment direction of the fuel supply amount is determined to be decreased. For stable fluctuation scenarios, according to the fluctuation amplitude and frequency, it is determined whether to maintain the current level of fuel supply amount or make small adjustments.

[0075] Step S1322: According to the change rate of the working condition change scene, determine the adjustment mode of the fuel supply rhythm, if the change rate of the working condition change scene meets the first rate interval, adjust the fuel supply rhythm to fast step type; if the change rate of the working condition change scene meets the second rate interval, adjust the fuel supply rhythm to slow gradual type, the minimum value of the first rate interval is greater than the maximum value of the second rate interval.

[0076] By calculating the change rate of the key parameters in the working condition change scene (such as the temperature change amount per unit time, the gas composition change rate, etc.), determine its belonging rate interval. The first rate interval corresponds to the scene of fast parameter change, at this time, the fast step type adjustment rhythm needs to be adopted, that is, multiple adjustments are made according to the preset step amplitude and interval time, for example, the fuel supply amount is increased once every short interval time, and the adjustment amplitude is large each time. The second rate interval corresponds to the scene of slow parameter change, the slow gradual type adjustment rhythm is adopted, that is, the fuel supply amount is adjusted continuously with small amplitude, and the adjustment interval time is long, so that the fuel supply amount changes smoothly. The division threshold of the rate interval is determined based on the correlation analysis of the parameter change rate and the adjustment effect in the historical data.

[0077] Step S1323: Combined with the duration of the working condition change scene, set the duration cycle of the fuel supply adjustment, so that the duration cycle of the fuel supply adjustment covers the complete duration of the working condition change.

[0078] According to the potential change duration of the scene in the working condition trend prediction result, determine the complete duration of the working condition change, including the whole process of parameter starting change, accelerating change, decelerating change and stable. The duration cycle of the fuel supply adjustment is set to be no less than the complete duration, so as to ensure that the adjustment process can cover the whole stage of the working condition change. For example, if the complete duration of the working condition change is a certain duration, the duration cycle of the fuel supply adjustment is set to be the same or slightly longer, and the time proportion of each adjustment stage is reasonably allocated in the cycle.

[0079] Step S1324: Label the key adaptation conditions corresponding to each fuel supply adjustment strategy, the key adaptation conditions include the initial parameters of the working condition change and the change rate threshold of the working condition change.

[0080] Label the key adaptation conditions for each constructed fuel supply adjustment strategy, as the judgment basis for the application of the strategy. The initial parameters of the working condition change include the basic parameters such as the initial temperature range in the kiln, the initial proportion of the gas composition, and the material feeding amount, which clearly define the initial working condition range of the strategy. The change rate threshold of the working condition change includes the minimum rate threshold and the maximum rate threshold, only when the working condition change rate is within the threshold range, the strategy is applicable. For example, the adaptation condition of the adjustment strategy of a certain reaction enhancement scene is labeled as "initial temperature is in a certain range, and the temperature change rate is within the first rate interval".

[0081] Step S1325: Simulate and verify the constructed fuel supply adjustment strategy, apply the fuel supply adjustment strategy to similar historical working condition scenarios, and observe the simulation working condition change results after application.

[0082] Select a historical segment similar to the current working condition change scenario from the historical working condition data, and apply the constructed fuel supply adjustment strategy to the virtual simulation environment corresponding to the historical segment. During the simulation process, set the fuel supply parameters according to the adjustment direction, rhythm, and cycle of the strategy, and real-time calculate the simulated parameters such as kiln temperature, gas composition, and material processing progress, to generate simulation working condition change results. The simulation verification uses a dynamic simulation model, which is constructed based on the heat transfer, mass transfer, and reaction kinetics characteristics of the volatile kiln, and can reflect the influence law of fuel supply change on the kiln working condition.

[0083] Step S1326: If the working condition change in the simulation working condition change results meets the expected stable target, determine that the fuel supply adjustment strategy is effective; if the working condition change in the simulation working condition change results does not meet the expected stable target, adjust the adjustment direction of the fuel supply amount or the adjustment mode of the fuel supply rhythm, re-perform simulation verification, and associate the verified fuel supply adjustment strategy with the corresponding working condition change scenario to form a basic pre-plan unit.

[0084] Compare the simulation working condition change results with the expected stable target, which includes stabilizing the kiln temperature in the target range, meeting the reaction gas composition, and meeting the material processing efficiency requirements. If all parameters in the simulation results can meet the expected target, and the fluctuation amplitude is within the allowable range, it is determined that the fuel supply adjustment strategy is effective. If the simulation results do not meet the expected target, for example, the temperature exceeds the target range or the stable time is too long, analyze the reasons and adjust the strategy, such as changing the adjustment amplitude of the fuel supply amount, adjusting the step interval or gradual rate of the adjustment rhythm, etc., and re-perform simulation verification after adjustment. Store the finally verified adjustment strategy in association with the corresponding working condition change scenario and adaptation conditions to form a basic pre-plan unit.

[0085] Step S133: Label each fuel supply adjustment strategy with the corresponding working condition adaptation condition, which includes the working condition change amplitude and working condition change rate range applicable to the fuel supply adjustment strategy.

[0086] To ensure that the fuel supply adjustment strategy can accurately adapt to the corresponding working condition change scene, the working condition adaptation condition is explicitly marked for each strategy. For the adjustment strategy of "reaction intensity enhancement and fast rate" in the reaction enhancement scene, the working condition adaptation condition is that the rising amplitude of the high-temperature zone temperature in the kiln per unit time exceeds the set amplitude threshold, and the growth rate of the reaction characteristic gas concentration exceeds the rate threshold, and the rising amplitude of the material handling rate is in a higher range.

[0087] For the adjustment strategy of "reaction intensity enhancement and slow rate", the working condition adaptation condition is that the rising amplitude of the kiln temperature is lower than the above-mentioned amplitude threshold, the growth rate of the reaction characteristic gas concentration is lower than the rate threshold, and the material handling rate changes relatively smoothly.

[0088] The adjustment strategy of "reaction intensity weakening and material retention" in the reaction weakening scene, the working condition adaptation condition includes: the descending amplitude of the average temperature in the kiln exceeds the set threshold, the residence time of the material in the kiln is extended by more than the specified time, and the proportion of unreacted material rises to a certain proportion. The working condition adaptation condition of the adjustment strategy of "reaction intensity weakening and abnormal gas composition" is that the descending amplitude of the kiln temperature reaches the set value, the concentration of unreacted components in the flue gas exceeds the normal range, and the fluctuation frequency of the gas composition increases.

[0089] The working condition adaptation condition of the fuel supply adjustment strategy of the stable fluctuation scene is that the main temperature parameters in the kiln fluctuate within the normal working range, the fluctuation amplitude is less than the fluctuation threshold, and the fluctuation frequency is at a low level, and the material handling progress is stable within the planned range.

[0090] The working condition adaptation condition of the adjustment strategy of "mild parameter out-of-range degree" in the abnormal risk scene is that the proportion of key parameters exceeding the normal range is lower than the out-of-range threshold, the parameter fluctuation amplitude is small, and there is no continuous deterioration trend. The working condition adaptation condition of the adjustment strategy of "severe parameter out-of-range degree" is that the proportion of key parameters exceeding the normal range is higher than the out-of-range threshold, the parameter fluctuation amplitude is large, and there is a continuous deterioration trend, and abnormal signals appear in the equipment operation.

[0091] Step S134: The working condition change scene, the corresponding fuel supply adjustment strategy and the corresponding working condition adaptation condition are associated and stored to form a basic preplan unit.

[0092] Each working condition change scene is bound to its corresponding fuel supply adjustment strategy and working condition adaptation condition to construct a basic preplan unit. Each basic preplan unit contains scene identification, scene feature description, fuel supply amount adjustment direction description, fuel supply rhythm adjustment mode details, and working condition adaptation condition parameter range. For example, the basic preplan unit of the “fast enhancement scene” in the reaction enhancement scene, the scene identification is “FY-ZQ-KS”, the scene feature description is “rapid temperature rise in the kiln and rapid increase in reaction gas concentration”, the fuel supply amount adjustment direction is “ladder type decrease”, the fuel supply rhythm adjustment mode is “decrease the fuel supply by a certain percentage every interval”, and the working condition adaptation condition parameter range includes the temperature rise range and the gas concentration growth rate range.

[0093] These information are stored together through a structured data format, each basic preplan unit has a unique identifier, facilitating subsequent retrieval and calling. At the same time, data association index is established during storage, so that scenes, strategies and conditions can be associated and queried with each other, for example, the corresponding adjustment strategy and adaptation condition can be quickly found through the scene identification, and the applicable scene range can be reversely queried through the adjustment strategy.

[0094] Step S135: classifying and arranging the basic preplan units, dividing the preplan modules according to the types of working condition change scenes, and each preplan module containing a plurality of basic preplan units of the same type of scene.

[0095] According to the types of working condition change scenes, the basic preplan units are classified and integrated to form different preplan modules. All basic preplan units of the reaction enhancement scene are classified into the “reaction enhancement preplan module”, which contains basic preplan units of different sub-scenes such as “fast enhancement” and “slow enhancement”. The basic preplan units of the reaction weakening scene are classified into the “reaction weakening preplan module”, which contains preplan units of sub-scenes such as “material retention type weakening” and “gas anomaly type weakening”. The basic preplan units of the stable fluctuation scene form the “stable fluctuation preplan module”, and the basic preplan units of the abnormal risk scene form the “abnormal risk preplan module”.

[0096] Each preplan module has module name, module description, and a list of contained basic preplan units. The module description details the working condition type and the overall adjustment principle applicable to the module, for example, “the reaction enhancement preplan module is applicable to various scenes where the reaction intensity in the kiln shows an upward trend, and the overall adjustment principle is to suppress the rapid enhancement of the reaction and maintain the stable reaction”. Through the above classification and arrangement, the structure of the fuel supply preplan library is more clear, and it is convenient to quickly locate the corresponding preplan module and basic preplan unit according to the actual working condition.

[0097] Step S136: integrate all the pre-plan modules, establish an indexing mechanism for quickly locating the corresponding pre-plan module and basic pre-plan unit according to the working condition trend prediction result, and form a fuel supply pre-plan library.

[0098] Each pre-plan module is integrated into a unified database to build a complete fuel supply pre-plan library. To achieve quick retrieval and calling of the pre-plan, a multi-dimensional indexing mechanism is established. The indexing mechanism includes scene feature indexing, parameter range indexing, adjustment strategy type indexing, etc. The scene feature indexing is established according to the core feature words of the working condition change scene, for example, the related basic pre-plan unit in the reaction enhancement pre-plan module can be retrieved through keywords such as "reaction enhancement" and "temperature rise". The parameter range indexing is established based on the parameter range in the working condition adaptation condition. When the change amplitude and rate of the real-time working condition parameters are input, the applicable basic pre-plan unit can be matched through this index. The adjustment strategy type indexing is established according to the adjustment direction of the fuel supply amount and the adjustment mode of the supply rhythm, which facilitates quick searching of the corresponding pre-plan according to the required adjustment strategy type.

[0099] The indexing mechanism adopts a tree structure design, with the first-level index being the pre-plan module type, the second-level index being the scene sub-type, and the third-level index being the basic pre-plan unit. At the same time, an index updating mechanism is established. When a basic pre-plan unit is added or modified in the pre-plan library, the indexing mechanism is automatically updated to ensure the consistency of the index and the pre-plan content. Through the integration of pre-plan modules and the establishment of an indexing mechanism, a functional fuel supply pre-plan library is formed, which can quickly and accurately match the appropriate fuel supply adjustment strategy according to the working condition trend prediction result.

[0100] Step S140: real-time monitoring of the deviation of the current working condition data of the volatile kiln from the working condition trend prediction result, matching of the target supply adjustment strategy from the fuel supply pre-plan library according to the deviation, and dynamic adaptation of the target supply adjustment strategy to obtain a fuel supply execution scheme.

[0101] By real-time monitoring of the deviation of the current working condition from the prediction result, the fuel supply strategy is dynamically adjusted to ensure that the fuel supply scheme is adapted to the actual working condition.

[0102] Step S141: real-time collection of the current working condition data of the volatile kiln according to the preset working condition deviation monitoring period, the current working condition data of the volatile kiln including real-time data of the kiln reaction state and real-time data of the material processing progress.

[0103] A fixed operating condition deviation monitoring period is set, and the length of the period is determined according to the rate of change of the operating condition and the system response time. For example, for a scene with a fast reaction, the monitoring period is short, and for a stable scene, the monitoring period is long. In each monitoring period, the current operating condition data of the volatile kiln is collected in real time by the data acquisition device. The real-time data of the kiln reaction state includes the latest measurement value of each area temperature sensor, the real-time gas composition data detected by the gas analyzer, the current pressure value of the pressure sensor, etc. The real-time data of the material handling progress includes the current feeding amount of the feeding belt, the real-time material level height of the kiln level meter, the latest particle size analysis result of the discharge port particle size detector, the current value of the material conveying speed, etc. The collected data is transmitted to the data processing module in real time.

[0104] Step S142: Compare the current operating condition data of the volatile kiln with the corresponding predicted data in the operating condition trend prediction result, calculate the deviation degree between the current operating condition data of the volatile kiln and the corresponding predicted data, and the deviation degree includes the deviation of the data change amplitude and the deviation of the data change rate.

[0105] The current collected kiln reaction state real-time data is compared with the predicted data at the corresponding time point in the operating condition trend prediction result. For the temperature parameter, the difference between the current measurement value of each temperature sensor and the predicted temperature value is calculated to obtain the deviation of the temperature change amplitude; the difference between the actual change rate of the current temperature in unit time and the predicted change rate is calculated to obtain the deviation of the temperature change rate. For the gas composition parameter, the difference between the current volume fraction of each gas component and the predicted volume fraction is calculated as a proportion of the predicted volume fraction, which is the deviation of the gas composition change amplitude; the difference between the actual value and the predicted value of the gas composition change rate is calculated as the deviation of the change rate.

[0106] For the material handling progress data, the deviation degree of the feeding amount is calculated by the difference between the current feeding amount and the predicted feeding amount and the difference ratio; the deviation degree of the material level height is calculated by the height difference and the change rate difference between the current material level and the predicted material level; the deviation degree of the particle size distribution is obtained by the difference between the actual value and the predicted value of the proportion of the material in different particle size ranges; the deviation degree of the conveying speed is calculated by the difference between the actual speed and the predicted speed and the difference between the speed change rate.

[0107] The change amplitude deviation and the change rate deviation of all parameters are integrated, and the overall deviation degree is obtained by weighted summation. The weight is set according to the importance of each parameter to the operating condition, for example, the weight of the temperature parameter is higher than that of the particle size parameter.

[0108] Step S143: Determine the deviation level according to the deviation degree. If the deviation degree is within the preset allowable range, the deviation level is low deviation; if the deviation degree exceeds the preset allowable range, the deviation level is high deviation.

[0109] The preset allowable range of the deviation degree is set according to the range of normal fluctuation in the historical working condition data, while referring to the accuracy range required by the process. When the comprehensive value of the overall deviation degree is less than or equal to the upper limit value of the allowable range, it is determined that the deviation level is low deviation, indicating that the current working condition is basically consistent with the prediction result, and the working condition change trend is within the expected range. When the comprehensive value of the overall deviation degree is greater than the upper limit value of the allowable range, it is determined that the deviation level is high deviation, indicating that there is a significant difference between the current working condition and the prediction result, and the working condition change trend deviates from the expectation, and more flexible matching and adjustment of the fuel supply adjustment strategy is required.

[0110] Step S144: When the deviation level is low deviation, the basic plan unit directly corresponding to the working condition trend prediction result is matched from the fuel supply plan library, and the fuel supply adjustment strategy in the basic plan unit is extracted as the initial target strategy.

[0111] In the case of low deviation, the current working condition is basically consistent with the prediction result, so the search is directly performed in the fuel supply plan library according to the working condition trend prediction result. Through the indexing mechanism of the plan library, the plan module directly corresponding to the working condition change scene in the prediction result is found, and then the basic plan unit adapted to the working condition change amplitude and change rate range in the prediction is matched from the module. For example, if the prediction result is a "slow enhancement" scene in the reaction enhancement type scene, and the deviation level is low deviation, the basic plan unit corresponding to the "slow enhancement" is extracted from the reaction enhancement plan module.

[0112] The fuel supply amount adjustment direction and the fuel supply rhythm adjustment mode in the basic plan unit are extracted as the initial target strategy. The initial target strategy retains the core adjustment logic in the original plan, such as the parameters of the fuel supply amount reduction ratio and the adjustment interval time.

[0113] Step S145: When the deviation level is high deviation, the basic plan unit similar to the current working condition data change characteristics of the volatile kiln is screened from the fuel supply plan library, and the initial target strategy is obtained by weighted fusion of the fuel supply adjustment strategies of multiple similar basic plan units.

[0114] In the case of high deviation, the actual change characteristics of the current working condition need to be considered more comprehensively, and multiple similar basic plan units are screened from the plan library for fusion.

[0115] Step S1451: The core characteristic parameters in the current working condition data change characteristics of the volatile kiln are extracted, including the kiln reaction state change rate and the material processing progress deviation value.

[0116] The core characteristic parameters that have the greatest impact on fuel supply adjustment are screened from the change characteristics of the current working condition data. The change rate of the reaction state in the kiln includes the actual rising or falling rate of the temperature in the high-temperature zone, the change rate of the concentration of the reaction characteristic gas, the frequency of pressure fluctuation, and the like; the material handling progress deviation value includes the deviation proportion of the feeding amount, the deviation value of the material level height, the deviation rate of the conveying speed, the statistical value of the particle size distribution deviation, and the like.

[0117] Step S1452: According to the core characteristic parameters, search in the fuel supply plan library, screen out the basic plan units whose working condition adaptation conditions contain the range of the core characteristic parameters, and take the screened basic plan units as the to-be-fused plan units.

[0118] By using the parameter range index of the plan library, the current values of the core characteristic parameters are input, and the basic plan units whose parameter ranges of the working condition adaptation conditions contain the values of the core characteristic parameters are searched in the plan library. For example, if the temperature rising rate in the high-temperature zone is a certain value in the current core characteristic parameters, all the basic plan units whose temperature rising rate ranges contain the value in the adaptation conditions are searched. The searched basic plan units are preliminarily screened, and the obviously irrelevant units are removed, for example, the plan units whose scene types are completely opposite to the change direction of the current working condition, and the remaining units are reserved as the to-be-fused plan units.

[0119] Step S1453: Calculate the matching degrees of the working condition adaptation conditions of each to-be-fused plan unit and the core characteristic parameters, and the higher the matching degree, the greater the weight coefficient corresponding to the to-be-fused plan unit.

[0120] For each to-be-fused plan unit, the matching degrees of the working condition adaptation conditions and the current core characteristic parameters are calculated. For the numerical value type parameters, the closeness of the core characteristic parameter value to the center value of the adaptation condition parameter range is calculated, and the closer to the center value, the higher the matching degree; for the range type parameters, the proportion of the core characteristic parameter value falling within the adaptation condition parameter range is calculated, and the higher the proportion, the higher the matching degree. The matching degrees of the core characteristic parameters are weighted and summed according to the preset weight to obtain the overall matching degree of each to-be-fused plan unit. The weight coefficient is determined according to the overall matching degree, the weight coefficient of the to-be-fused plan unit with the highest matching degree is the largest, the weight coefficients of the remaining units are sequentially decreased according to the relative sizes of the matching degrees, and the sum of the weight coefficients of all the to-be-fused plan units is the overall proportion.

[0121] Step S1454: Extract the fuel supply amount adjustment direction vector and the fuel supply amount adjustment amplitude in each to-be-fused plan unit, and perform weighted calculation according to the weight coefficients corresponding to the to-be-fused plan units to obtain the fused fuel supply amount adjustment direction vector and the fused fuel supply amount adjustment amplitude.

[0122] The direction vector of the fuel supply amount adjustment in the to-be-fused plan unit includes direction identifiers such as increase, decrease, and maintenance, and adjustment priority in each direction. The direction vector is converted into a numerical representation, for example, increase is a positive direction value, decrease is a negative direction value, and maintenance is a zero value. The direction vector values of the to-be-fused plan units are weighted and summed according to the weight coefficients to obtain a fused direction vector value, and the positive or negative of the value determines the direction of the fused fuel supply amount adjustment.

[0123] For the fuel supply amount adjustment range, the adjustment range parameters such as adjustment proportion or adjustment amount in each to-be-fused plan unit are extracted. The adjustment range parameters are weighted and calculated according to the weight coefficients to obtain a fused fuel supply amount adjustment range, which integrates the adjustment experience of multiple similar plan units.

[0124] Step S1455: Extract the fuel supply rhythm adjustment mode in each to-be-fused plan unit, count the frequency of each fuel supply rhythm adjustment mode in the to-be-fused plan unit, and select the fuel supply rhythm adjustment mode with the highest frequency and the largest matching degree weighting value as the fused fuel supply rhythm adjustment mode.

[0125] The fuel supply rhythm adjustment mode in the to-be-fused plan unit includes types such as stepwise, gradual, fine-tuning, and pulsed. The number of occurrences of each adjustment mode in the to-be-fused plan unit is counted to obtain the frequency of occurrence. At the same time, the matching degree weighting sum of all to-be-fused plan units corresponding to each adjustment mode is calculated, that is, the sum of the matching degrees of each unit multiplied by its weight coefficient. The adjustment mode with the highest frequency of occurrence is selected, and if there are multiple adjustment modes with the same frequency of occurrence, the adjustment mode with the largest matching degree weighting value is selected as the fused fuel supply rhythm adjustment mode.

[0126] Step S1456: Integrate the fused fuel supply amount adjustment direction vector, the fused fuel supply amount adjustment range, and the fused fuel supply rhythm adjustment mode to form a preliminary fused strategy.

[0127] The fused fuel supply amount adjustment direction vector, adjustment range, and fuel supply rhythm adjustment mode are integrated to determine the direction of fuel supply amount adjustment, the specific size of the adjustment range, and the rhythm of the adjustment. For example, the fused strategy can be "the direction of fuel supply amount adjustment is decrease, the adjustment range is a certain proportion, and the supply rhythm is stepwise decrease". The preliminary fused strategy needs to ensure that the contents are logically consistent, and the adjustment direction matches the adjustment range and rhythm.

[0128] Step S1457: detecting the coordination between the fuel supply amount and the fuel supply rhythm in the preliminary fusion strategy, if there is a contradiction between the fuel supply amount and the fuel supply rhythm, the adjustment mode of the fuel supply rhythm of the pre-fusion plan unit with the highest matching degree is prioritized to correct, and an initial target strategy is obtained.

[0129] The coordination between the fuel supply amount and the fuel supply rhythm in the preliminary fusion strategy is detected, mainly from the consistency of the adjustment direction and the adaptability of the adjustment amplitude and rhythm. The consistency of the adjustment direction is to judge whether the adjustment direction (increase or decrease) of the fuel supply amount and the adjustment mode (fast step type, slow progressive type, etc.) of the fuel supply rhythm conform to the conventional control logic. For example, when the adjustment direction of the fuel supply amount is significantly increased, if the supply rhythm adopts slow progressive type, it may cause the reaction intensity to lag behind, and at this time it is determined that there is a contradiction in the direction. The adaptability of the adjustment amplitude and the rhythm is to analyze whether the size of the adjustment amplitude and the speed of the rhythm match, for example, when the adjustment amplitude is large, if the fast step type rhythm is adopted, it may cause the kiln working condition to fluctuate violently, and when the adjustment amplitude is small, if the slow progressive type rhythm is adopted, it may cause the adjustment efficiency to be too low, which are all determined as the adaptability contradiction between the amplitude and the rhythm.

[0130] If it is found that there is a coordination contradiction, the pre-plan unit with the highest matching degree is selected from the pre-plan units to be fused, and the rhythm parameters in the preliminary fusion strategy are corrected based on the fuel supply rhythm adjustment mode of the unit. For example, if the supply amount in the preliminary fusion strategy needs to be significantly increased but the rhythm is slow progressive type, and the pre-plan unit with the highest matching degree adopts fast step type rhythm, then the rhythm of the preliminary fusion strategy is corrected to fast step type, and the step interval and the amplitude proportion of each adjustment are adjusted accordingly to ensure that the corrected rhythm can adapt to the adjustment demand of the supply amount. If no coordination contradiction is found, the preliminary fusion strategy is directly determined as the initial target strategy, which integrates the advantages of multiple similar pre-plan units and can better adapt to the working condition demand under high deviation.

[0131] Step S150: sending the fuel supply execution scheme to the fuel supply system for execution, while collecting the kiln working condition feedback data after execution, and updating the fuel supply adjustment strategy and working condition adaptation condition in the fuel supply pre-plan library using the kiln working condition feedback data.

[0132] After determining the fuel supply execution scheme, it is converted into executable control instructions and sent to the fuel supply system, and a closed-loop feedback mechanism is established to continuously optimize the strategies and conditions in the pre-plan library through working condition feedback data.

[0133] Step S151: Convert the fuel supply execution scheme into executable supply control instructions and send them to the fuel supply system, so that after the fuel supply system executes the supply control instructions, it collects feedback data of the kiln working condition according to the set feedback data collection period, and the feedback data of the kiln working condition includes the reaction state change data after execution and the material processing progress change data after execution.

[0134] The parameters in the fuel supply execution scheme, such as the fuel supply amount adjustment direction, adjustment amplitude, supply rhythm, etc., are converted into supply control instructions recognizable by the fuel supply system. The instruction format needs to comply with the communication protocol specification of the system, including instruction type identification, execution start time, adjustment parameter sequence, execution period, etc. For example, for the step adjustment strategy, the control instruction needs to clearly indicate the time node of each step adjustment, the adjusted fuel flow value or the adjustment amplitude ratio.

[0135] The supply control instructions are sent to the controller of the fuel supply system through the industrial bus. After receiving the instructions, the controller drives the fuel pump, regulating valve and other execution mechanisms to operate according to the instruction parameters. At the same time, a feedback data collection period is set, which is determined according to the response speed of the working condition change. For parameters sensitive to reaction (such as kiln temperature, gas composition), a shorter collection period is used, and for parameters that change slowly (such as material conversion rate), a longer collection period is used. Through the sensors and metering devices deployed in the kiln, the kiln reaction state change data after execution is collected periodically, including real-time monitoring values of temperature in each region, composition change curve of reaction generated gas, fluctuation of kiln pressure, etc.; the material processing progress change data after execution is collected, including the change of material moving speed in the kiln, the distribution change of discharge particle size, the balance state of feeding and discharging, etc., and these feedback data are transmitted to the data processing center in real time.

[0136] Step S152: Compare the expected working condition change corresponding to the fuel supply execution scheme with the actual working condition change in the feedback data of the kiln working condition, and calculate the degree of fit between the expected working condition change and the actual working condition change.

[0137] Extract the expected working condition change indicators from the fuel supply execution scheme. These indicators are set based on historical data and theoretical analysis, including expected temperature change range, gas composition optimization target, material processing efficiency improvement amplitude, etc. Compare the expected working condition change indicators with the actual working condition change data in the kiln working condition feedback data item by item. The comparison content covers the consistency of parameter change trend, the closeness of change amplitude, the time deviation of reaching stable state, etc.

[0138] The degree of coincidence of the expected working condition change and the actual working condition change is calculated, and a multi-dimensional weighted scoring method is adopted. For each comparison parameter, a corresponding weight is set, and the weight size is determined according to the importance of the parameter to the working condition in the kiln, for example, the weight of the temperature parameter is higher than that of the pressure parameter. For each parameter, the deviation ratio of the actual change value and the expected change value is calculated, and the coincidence score of the parameter is determined according to the deviation ratio. The smaller the deviation ratio, the higher the score. The coincidence scores of all parameters are weighted and summed according to the weights to obtain the overall coincidence value, which reflects the degree of coincidence between the actual effect of the fuel supply execution scheme and the expected target.

[0139] Step S153: If the coincidence degree is higher than the preset coincidence threshold, it is determined that the fuel supply adjustment strategy corresponding to the fuel supply execution scheme is effective, the matching relationship between the fuel supply adjustment strategy and the current working condition is recorded, and the matching relationship is supplemented to the basic plan unit corresponding to the fuel supply plan library.

[0140] When the calculated coincidence degree is higher than the preset coincidence threshold, it indicates that the fuel supply execution scheme can effectively guide the working condition in the kiln to develop in the expected direction, and the corresponding fuel supply adjustment strategy is suitable for the current working condition. At this time, the specific content of the fuel supply adjustment strategy is recorded in detail, including the adjustment direction, the adjustment amplitude, the rhythm parameter, etc., and the key parameters of the current working condition, such as the initial reaction temperature, the material characteristics, the feed amount, etc., are recorded, and the matching relationship between the two is determined.

[0141] The recorded matching relationship is supplemented to the corresponding basic plan unit in the fuel supply plan library, and the applicable cases of the basic plan unit are enriched. The supplemented content includes the time stamp of the matching success, the working condition description, the strategy execution effect data (such as the coincidence degree value), etc., so that the basic plan unit can accumulate more effective application examples and improve the matching accuracy in subsequent similar working conditions. At the same time, the index of the supplemented basic plan unit is updated to ensure that the association relationship between the basic plan unit and the corresponding working condition can be quickly identified during the retrieval of the plan library.

[0142] Step S154: If the coincidence degree is lower than the preset coincidence threshold, the reasons for the deviation between the expected working condition change and the actual working condition change are analyzed, which include the deviation of the fuel supply amount and the deviation of the fuel supply rhythm.

[0143] For example, when the coincidence degree is lower than the preset coincidence threshold, the deviation reasons need to be analyzed in depth from the two dimensions of fuel supply amount and fuel supply rhythm, and the problem source is located by comparing the actual parameters and the expected parameters.

[0144] Step S1541: If the deviated working condition parameter is the kiln reaction intensity, the corresponding expected fuel supply amount parameter in the fuel supply execution scheme is extracted, and the actual fuel supply amount parameter in the fuel supply system execution process is collected.

[0145] When the kiln reaction intensity deviates from the expected value, the expected fuel supply amount parameter in the fuel supply execution scheme for the reaction stage is first determined, including the fuel injection amount per unit time, the fuel distribution ratio of different combustion stages, etc. At the same time, the actual fuel supply amount data in the execution process is collected through the flow meter, pressure sensor and other devices of the fuel supply system, including the real-time fuel flow curve, the cumulative supply amount and the actual fuel distribution of each combustion stage.

[0146] Step S1542: The actual fuel supply amount parameter and the expected fuel supply amount parameter are compared in value. If the actual fuel supply amount parameter is less than the expected fuel supply amount parameter, and the actual kiln reaction intensity value is less than the expected kiln reaction intensity value, it is determined that the deviation is caused by the fuel supply amount setting deviation.

[0147] The actual fuel supply amount parameter and the expected fuel supply amount parameter collected are compared item by item, and the difference and the relative deviation ratio are calculated. When the actual fuel supply amount continuously falls below the expected fuel supply amount, and the corresponding actual kiln reaction intensity (such as temperature, reaction gas concentration, etc.) is also lower than the expected reaction intensity, it is indicated that the fuel supply amount cannot meet the reaction demand, and thus it is determined that the deviation is caused by the fuel supply amount setting deviation.

[0148] Step S1543: If the actual fuel supply amount parameter is greater than the expected fuel supply amount parameter, and the actual kiln reaction intensity value is greater than the expected kiln reaction intensity value, it is determined that the deviation is caused by the fuel supply amount setting deviation.

[0149] If the actual fuel supply amount continuously exceeds the expected fuel supply amount, and the actual kiln reaction intensity exceeds the expected reaction intensity, the temperature is too high, the reaction is too intense, etc., it is indicated that the fuel supply amount exceeds the reasonable demand range, and thus it is also determined that the deviation is caused by the fuel supply amount setting deviation.

[0150] Step S1544: If the deviated working condition parameter is the working condition stabilization time, the corresponding expected fuel supply rhythm parameter in the fuel supply execution scheme is extracted, which includes the time interval of fuel supply adjustment and the adjustment amplitude change frequency.

[0151] When the condition stable time (i.e. the time from the start of the fuel supply adjustment to the time when the kiln condition reaches a stable state) deviates, the expected fuel supply rhythm parameters set in the fuel supply execution scheme are extracted. These parameters include the time interval of the fuel supply amount adjustment (such as how often the supply amount adjustment is performed), the adjustment amplitude change frequency (such as whether the adjustment amplitude changes uniformly or in steps), and the adjustment sequence arrangement in different stages.

[0152] Step S1545: The actual fuel supply rhythm parameters in the fuel supply system execution process are collected, and the time interval in the actual fuel supply rhythm parameters is compared with the time interval in the expected fuel supply rhythm parameters, and the actual adjustment amplitude change frequency is compared with the expected adjustment amplitude change frequency.

[0153] The actual fuel supply rhythm parameters are collected through the control log and sensor records of the fuel supply system, including the actual adjustment operation time interval, the adjustment amplitude change of each adjustment, and the fluctuation of the adjustment frequency. The actual time interval is calculated by difference from the expected time interval to analyze the influence of the time deviation on the condition stability; the actual adjustment amplitude change frequency is compared with the expected frequency to judge the matching degree of the adjustment rhythm.

[0154] Step S1546: If the actual time interval is greater than the expected time interval, the actual adjustment amplitude change frequency is less than the expected adjustment amplitude change frequency, and the actual condition stable time value is greater than the expected condition stable time value, it is determined that the deviation reason is the fuel supply rhythm setting deviation.

[0155] When the actual adjustment time interval is longer than expected, the adjustment amplitude change frequency is lower than expected, and the kiln condition needs a longer time to reach a stable state, and the actual stable time exceeds the expected stable time, it indicates that the fuel supply rhythm is too slow and cannot adapt to the condition change demand in time, and thus it is determined that the deviation reason is the fuel supply rhythm setting deviation.

[0156] Step S1547: If the actual time interval is less than the expected time interval, the actual adjustment amplitude change frequency is greater than the expected adjustment amplitude change frequency, and the actual condition stable time value is less than the expected condition stable time value, and the kiln condition feedback data records the condition fluctuation phenomenon, it is determined that the deviation reason is the fuel supply rhythm setting deviation.

[0157] If the actual adjustment time interval is too short and the adjustment amplitude changes too frequently, the kiln condition fluctuates frequently in a short time, although the actual stable time is shorter than expected, but the condition fluctuation is obvious (such as frequent temperature and pressure oscillation), at this time it indicates that the fuel supply rhythm is too fast, causing the condition to be unstable, and similarly it is determined that the deviation reason is the fuel supply rhythm setting deviation.

[0158] Step S1548: Extract the actual value and the expected value of the existing deviation working condition parameter, calculate the difference between the actual value and the expected value, and then calculate the proportion of the difference in the expected value, to determine the severity of the deviation through the proportion.

[0159] For the existing deviation working condition parameters (such as reaction intensity, stabilization time, etc.), the actual value and the expected value are extracted respectively, and the absolute difference between the two values is calculated. Then the absolute difference is divided by the expected value to obtain the relative deviation proportion. According to the size of the relative deviation proportion, the severity of the deviation is divided into levels, such as slight deviation for smaller proportion and serious deviation for larger proportion.

[0160] Step S1549: Record the reasons for the deviation, the existing deviation working condition parameters, the comparison data between the actual and expected parameters, and the severity of the deviation, and arrange them into a deviation analysis report according to the preset format.

[0161] The deviation reasons (fuel supply amount deviation or rhythm deviation) analyzed, the corresponding working condition parameter types, the detailed comparison data (including difference, proportion) between the actual and expected parameters, and the severity of the deviation level and other information are recorded in a structured manner. According to the preset report format, the time of deviation occurrence, the involved process steps, the data source and the analysis process are clearly presented to form a complete deviation analysis report.

[0162] Step S155: According to the reasons for the deviation, correct the corresponding fuel supply adjustment strategy, adjust the fuel supply amount or fuel supply rhythm parameters in the fuel supply adjustment strategy, and correct the working condition adaptation conditions associated with the fuel supply adjustment strategy. Update the corrected fuel supply adjustment strategy and the corrected working condition adaptation conditions to the fuel supply plan library.

[0163] According to the deviation reasons determined by analysis, the fuel supply adjustment strategy is corrected. If the deviation reason is the deviation of fuel supply amount setting, according to the difference proportion between the actual reaction intensity and the expected value, the adjustment amplitude of the supply amount is adjusted, for example, when the reaction intensity is insufficient, the supply amount adjustment amplitude is increased by a certain proportion, and the upper and lower limit constraints of the supply amount are corrected to ensure that the adjusted supply amount is within the safe operation range of the equipment. If the deviation reason is the deviation of fuel supply rhythm setting, the step interval or gradual rate in the rhythm parameter is adjusted, for example, when the stabilization time is too long, the adjustment interval is shortened or the initial adjustment amplitude proportion is increased, so that the working condition can reach the stable state faster.

[0164] While revising the fuel supply adjustment strategy, the working condition adaptation condition associated with the strategy is re-evaluated. The difference between the current working condition and the original adaptation condition is analyzed, and the parameter range in the adaptation condition is adjusted. For example, if the original adaptation condition does not consider the influence of material humidity on the reaction, resulting in poor strategy effect, the limited range of material humidity is added in the revised adaptation condition. The revised fuel supply adjustment strategy and working condition adaptation condition are updated to the corresponding basic plan unit of the fuel supply plan library, replacing the original strategy content, and the revision reason, parameter comparison before and after revision, and effect evaluation after revision are recorded to ensure that the strategy in the plan library can continuously adapt to the changes in actual working conditions.

[0165] Step S156: The usage frequency and fit degree of each basic plan unit in a preset time period are counted, the basic plan unit with extremely low usage frequency and continuously low fit degree below a preset fit threshold is deleted, and the storage structure of the fuel supply plan library is optimized.

[0166] A preset time period, such as a production cycle, is set, the usage times of each basic plan unit in the fuel supply plan library in the preset time period are counted, the usage frequency is calculated, and the usage frequency is the ratio of the usage times to the total calling times. At the same time, the fit degree value of each basic plan unit after each use is counted, and the average fit degree and the change trend of the fit degree are calculated.

[0167] The basic plan unit with extremely low usage frequency and continuously low average fit degree below a preset fit threshold is marked. These units are usually applicable to special or rare working conditions, and the actual effect is poor. Continuing to retain these units will increase the redundancy of the plan library and affect the retrieval efficiency. After review and confirmation by technical personnel, these marked basic plan units are deleted from the plan library, and the deletion reason, deletion time and related parameters are recorded.

[0168] The storage structure of the plan library is optimized, the remaining basic plan units are sorted according to the usage frequency and fit degree, the units with high frequency and high fit degree are placed in the priority retrieval position, and the efficiency of plan matching is improved. At the same time, the index system of the plan library is reorganized, new retrieval keywords such as the revised working condition adaptation condition parameters are supplemented, and the structure of the plan library is more clear and the retrieval is more accurate.

[0169] Figure 2 A schematic diagram of exemplary hardware and software components of a control system 100 for volatile kiln fuel supply is shown, which can implement the idea of the present application. For example, the processor 120 can be used in the control system 100 for volatile kiln fuel supply, and used to execute the functions in the present application.

[0170] For example, the control system 100 for volatile kiln fuel supply can include a network port 110 connected to a network, one or more processors 120 for executing program instructions, a communication bus 130, and different forms of storage media 140, such as a disk, a ROM, or a RAM, or any combination thereof. Illustratively, the control system 100 for volatile kiln fuel supply can also include program instructions stored in a ROM, a RAM, or other types of non-transitory storage media, or any combination thereof. The methods of the present application can be implemented in accordance with these program instructions. The control system 100 for volatile kiln fuel supply also includes an I / O interface 150 between the computer and other input / output devices.

[0171] In addition, the embodiments of the present application further provide a readable storage medium, wherein computer executable instructions are preset in the readable storage medium, and when a processor executes the computer executable instructions, the control method for volatile kiln fuel supply is realized.

[0172] It should be noted that, in order to simplify the expression of the present application and to help the understanding of one or more embodiments of the present application, in the foregoing description of the embodiments of the present application, various features are sometimes incorporated into one embodiment, drawing or description thereof.

Claims

1. A control method for a volatile kiln fuel supply, characterized by, The method comprises: acquiring volatile kiln real-time working condition data and volatile kiln historical working condition data, wherein the volatile kiln real-time working condition data comprises real-time reaction state information and real-time material processing progress information in the kiln, and the volatile kiln historical working condition data comprises fuel supply adjustment records and working condition change result information under different working conditions; performing working condition trend prediction processing based on the volatile kiln real-time working condition data and the volatile kiln historical working condition data, identifying potential change direction and potential change period of the working condition in the kiln, and obtaining working condition trend prediction results; constructing a fuel supply plan library according to the working condition trend prediction results, wherein the fuel supply plan library comprises fuel supply adjustment strategies corresponding to different prediction trends, and each fuel supply adjustment strategy is associated with corresponding working condition adaptation conditions; real-time monitoring deviation of volatile kiln current working condition data and the working condition trend prediction results, matching a target supply adjustment strategy from the fuel supply plan library according to the deviation, and dynamically adapting the target supply adjustment strategy to obtain a fuel supply execution scheme; sending the fuel supply execution scheme to a fuel supply system for execution, collecting kiln working condition feedback data after execution, and updating fuel supply adjustment strategies and working condition adaptation conditions in the fuel supply plan library by using the kiln working condition feedback data; the sending the fuel supply execution scheme to a fuel supply system for execution, collecting kiln working condition feedback data after execution, and updating fuel supply adjustment strategies and working condition adaptation conditions in the fuel supply plan library by using the kiln working condition feedback data comprises: converting the fuel supply execution scheme into executable supply control instructions and sending them to the fuel supply system, so that the fuel supply system collects feedback data of the kiln working condition according to a set feedback data collection period after executing the supply control instructions, wherein the feedback data of the kiln working condition comprises post-execution kiln reaction state change data and post-execution material processing progress change data; comparing expected working condition changes corresponding to the fuel supply execution scheme with actual working condition changes in the feedback data of the kiln working condition, and calculating the fit degree of the expected working condition changes and the actual working condition changes; if the fit degree is higher than a preset fit threshold, it is determined that the fuel supply adjustment strategy corresponding to the fuel supply execution scheme is effective, the matching relationship between the fuel supply adjustment strategy and the current working condition is recorded, and the matching relationship is supplemented to a basic plan unit corresponding to the fuel supply plan library; if the fit degree is lower than the preset fit threshold, reasons for the deviation between the expected working condition changes and the actual working condition changes are analyzed, wherein the reasons for the deviation comprise fuel supply amount setting deviation and fuel supply rhythm setting deviation; according to the reasons for the deviation, the corresponding fuel supply adjustment strategy is corrected, the fuel supply amount or the fuel supply rhythm parameter in the fuel supply adjustment strategy is adjusted, the working condition adaptation conditions associated with the fuel supply adjustment strategy are corrected, and the corrected fuel supply adjustment strategy and the corrected working condition adaptation conditions are updated to the fuel supply plan library; The usage frequency and the fit degree of each basic plan unit in a preset time period are counted, a basic plan unit with a very low usage frequency and a fit degree continuously lower than a preset fit threshold is deleted, and a storage structure of the fuel supply plan library is optimized.

2. The control method for volatile kiln fuel supply according to claim 1, characterized by, The real-time working condition data of the volatile kiln and the historical working condition data of the volatile kiln are integrated to obtain a regularized working condition data set. The change characteristics of the real-time working condition data of the volatile kiln are extracted from the regularized working condition data set, and the change characteristics include a continuous change trajectory of a reaction state in the kiln and a rate change characteristic of a material processing progress. The historical change segments similar to the change characteristics of the real-time working condition data of the volatile kiln are associated in the historical working condition data of the volatile kiln, and the subsequent working condition change direction and the subsequent working condition change period corresponding to the historical change segments are extracted. The similarity degree of the change characteristics of the real-time working condition data of the volatile kiln and the historical change segments is analyzed to determine the reference weight of the historical change segments on the current working condition. Based on the reference weight, the subsequent working condition information corresponding to multiple historical change segments is fused to generate a preliminary result of the potential change direction and the potential change period of the working condition in the kiln. The preliminary result of the potential change direction and the potential change period is corrected in combination with the latest change dynamics of the real-time working condition data of the volatile kiln to obtain a final working condition trend prediction result. The historical data segments containing complete working condition change processes are screened from the historical working condition data of the volatile kiln, each historical data segment contains a change characteristic stage and a subsequent change stage.

3. The control method for volatile kiln fuel supply according to claim 2, characterized in that, The change characteristics of the real-time working condition data of the volatile kiln are compared with the change characteristic stages of each historical data segment to calculate the feature similarity of the change characteristics and the change characteristic stages of each historical data segment. The historical data segments with a feature similarity higher than a similarity threshold are screened out, and the screened historical data segments are taken as candidate historical change segments. The working condition change direction in the subsequent change stage of each candidate historical change segment is extracted, the key working condition parameter types associated with the working condition change direction are determined, and the change ranges of each key working condition parameter in the change direction are recorded respectively. The time length of the subsequent change stage of each candidate historical change segment is extracted, and the change period required for the key working condition parameters to reach a stable state is determined according to the time length. The working condition change direction corresponding to each candidate historical change segment, the associated key working condition parameter types and the change ranges thereof, the change period required for the key parameters to reach a stable state in the change direction, and the feature similarity are recorded to form a candidate historical information list. ​ ​ The working condition change direction and change period in the candidate historical information list are de-duplicated, and the historical information with the highest feature similarity is retained as core reference information.

4. The control method for volatile kiln fuel supply according to claim 3, characterized in that, The working condition change direction and change period in the candidate historical information list are de-duplicated, The historical information with the highest feature similarity is retained as core reference information, including: The working condition change directions in the candidate historical information list are classified, and the historical information with the same or similar working condition change direction is classified into the same direction group; In each direction group, the first change period in which the key working condition parameters reach stability in the change direction of each historical information record is counted, and the average change period to reach stability in the same working condition change direction is calculated; The feature similarities of the historical information in the same direction group are compared, the historical information with the highest feature similarity is screened out, and the second change period in which the key working condition parameters reach stability in the change direction of the historical information record is extracted; If the second change period deviates from the average change period to reach stability of the direction group by less than a set deviation, the historical information is directly taken as the representative information of the direction group; If the second change period deviates from the average change period to reach stability of the direction group by not less than a set deviation, the change period in which the key working condition parameters reach stability in the change direction of the historical information record is corrected in combination with the average change period to reach stability, to obtain a corrected change period to reach stability, and the historical information containing the corrected change period to reach stability is taken as the representative information of the direction group; From the representative information of each direction group, the representative information with the highest feature similarity is again screened out, and the representative information is taken as the core reference information.

5. The control method for volatile kiln fuel supply according to claim 1, characterized by, The fuel supply plan library is constructed according to the working condition trend prediction result, including: The potential change directions in the working condition trend prediction result are classified, and different working condition change scenes are divided, each working condition change scene corresponding to a type of potential change direction; For each working condition change scene, an adaptive fuel supply adjustment strategy is constructed, and the fuel supply adjustment strategy contains the adjustment direction of the fuel supply amount and the adjustment mode of the fuel supply rhythm; For each fuel supply adjustment strategy, a corresponding working condition adaptation condition is labeled, and the working condition adaptation condition contains the working condition change amplitude and the working condition change rate range applicable to the fuel supply adjustment strategy; The working condition change scene, the corresponding fuel supply adjustment strategy and the corresponding working condition adaptation condition are associated and stored to form a basic plan unit; The basic plan unit is classified and arranged, and a plan module is divided according to the type of working condition change scene, and each plan module contains a plurality of basic plan units of the same type of scene; All plan modules are integrated, an index mechanism is established, the index mechanism is used to quickly locate the corresponding plan module and basic plan unit according to the working condition trend prediction result, and a fuel supply plan library is formed.

6. The control method for volatile kiln fuel supply according to claim 5, characterized in that, The adaptive fuel supply adjustment strategy is constructed for each working condition change scene, including: The change in the demand for fuel by the reaction in the kiln under each working condition change scenario is analyzed. If the working condition change scenario shows that the reaction intensity is enhanced, the adjustment direction of the fuel supply amount is determined to be increased. If the working condition change scenario shows that the reaction intensity is weakened, the adjustment direction of the fuel supply amount is determined to be reduced. According to the change rate of the working condition change scenario, the adjustment mode of the fuel supply rhythm is determined. If the change rate of the working condition change scenario meets a first rate interval, the fuel supply rhythm is adjusted to be a fast step type. If the change rate of the working condition change scenario meets a second rate interval, the fuel supply rhythm is adjusted to be a slow gradual type. The minimum value of the first rate interval is greater than the maximum value of the second rate interval. In combination with the duration of the working condition change scenario, the duration of the fuel supply adjustment is set so as to cover the complete duration of the working condition change. The key adaptation conditions corresponding to each fuel supply adjustment strategy are labeled. The key adaptation conditions include initial parameters of the working condition change and a change rate threshold of the working condition change. The constructed fuel supply adjustment strategy is simulated and verified. The fuel supply adjustment strategy is applied to a similar historical working condition scenario, and the simulation working condition change result after the application is observed. If the working condition change in the simulation working condition change result meets the expected stable target, it is determined that the fuel supply adjustment strategy is effective. If the working condition change in the simulation working condition change result does not meet the expected stable target, the adjustment direction of the fuel supply amount or the adjustment mode of the fuel supply rhythm is adjusted, the simulation verification is re-performed, and the fuel supply adjustment strategy verified effectively is associated with the corresponding working condition change scenario to form a basic plan unit.

7. The control method for volatile kiln fuel supply according to claim 1, characterized by, The deviation of the real-time monitoring of the current working condition data of the volatile kiln from the working condition trend prediction result is monitored in real time. According to the deviation, a target supply adjustment strategy is matched from the fuel supply plan library, and the target supply adjustment strategy is dynamically adapted to obtain a fuel supply execution scheme, including: Real-time current working condition data of the volatile kiln is collected according to a preset working condition deviation monitoring period. The current working condition data of the volatile kiln includes real-time data of a kiln reaction state and real-time data of a material processing progress. The current working condition data of the volatile kiln is compared with corresponding prediction data in the working condition trend prediction result, and the deviation degree between the current working condition data of the volatile kiln and the corresponding prediction data is calculated. The deviation degree includes a deviation of a data change amplitude and a deviation of a data change rate. According to the deviation degree, a deviation level is determined. If the deviation degree is within a preset allowable range, the deviation level is low deviation. If the deviation degree exceeds the preset allowable range, the deviation level is high deviation. When the deviation level is low deviation, a basic plan unit directly corresponding to the working condition trend prediction result is matched from the fuel supply plan library, and a fuel supply adjustment strategy in the basic plan unit is extracted as an initial target strategy. When the deviation level is high deviation, a basic plan unit similar to the change characteristic of the current working condition data of the volatile kiln is selected from the fuel supply plan library, and an initial target strategy is obtained by weighted fusion of the fuel supply adjustment strategies of multiple similar basic plan units; The fuel supply rhythm in the initial target strategy is adjusted in combination with the real-time data of the material processing progress in the current working condition data of the volatile kiln, and the fuel supply amount in the initial target strategy is adjusted in combination with the real-time data of the reaction state in the kiln in the current working condition data of the volatile kiln, to form a fuel supply execution scheme.

8. The control method for a kiln fuel supply for volatilization according to claim 7, characterized by, The method comprises the following steps: Extract the core characteristic parameters in the change characteristic of the current working condition data of the volatile kiln, wherein the core characteristic parameters include the reaction state change rate in the kiln and the material processing progress deviation value; According to the core characteristic parameters, the working condition adaptation condition of the basic plan unit is selected from the fuel supply plan library, and the selected basic plan unit is used as a to-be-fused plan unit; The matching degree of the working condition adaptation condition of each to-be-fused plan unit and the core characteristic parameters is calculated, and the higher the matching degree, the greater the weight coefficient corresponding to the to-be-fused plan unit; The fuel supply amount adjustment direction vector and the fuel supply amount adjustment amplitude in each to-be-fused plan unit are extracted, and the fuel supply amount adjustment direction vector and the fuel supply amount adjustment amplitude after fusion are obtained by weighted calculation according to the weight coefficients corresponding to the to-be-fused plan units; The fuel supply rhythm adjustment mode in each to-be-fused plan unit is extracted, the appearance frequency of each fuel supply rhythm adjustment mode in the to-be-fused plan unit is counted, and the fuel supply rhythm adjustment mode with the highest appearance frequency and the largest matching degree weighted value is selected as the fuel supply rhythm adjustment mode after fusion; The fuel supply amount adjustment direction vector after fusion, the fuel supply amount adjustment amplitude after fusion, and the fuel supply rhythm adjustment mode after fusion are integrated to form a preliminary fusion strategy; The coordination of the fuel supply amount and the fuel supply rhythm in the preliminary fusion strategy is detected, and if there is a contradiction between the fuel supply amount and the fuel supply rhythm, the fuel supply rhythm adjustment mode of the to-be-fused plan unit with the highest matching degree is preferentially modified to obtain an initial target strategy.

9. A control system for a kiln fuel supply, characterised in that, The processor and the memory are connected, the memory is used to store programs, instructions or codes, and the processor is used to execute the programs, instructions or codes in the memory to realize the control method for fuel supply of the volatile kiln in any one of claims 1-8.

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