A pneumatic ash conveying intelligent control method and system based on intelligent pilot valve

Abstract

This invention discloses an intelligent control method and system for pneumatic ash conveying based on an intelligent pilot valve, belonging to the field of intelligent control technology. This intelligent control method for pneumatic ash conveying, based on an intelligent pilot valve, records real-time conveying and pushing time-series data when the material to be conveyed is transported in the ash conveying pipe. The data is analyzed to obtain the comprehensive conveying index of the ash conveying pipe and the pushing index of the air conveying pipe at each time point. A comprehensive analysis is then performed to obtain the valve control index at each time point, and the change rate of the comprehensive valve control index is obtained. This invention judges and analyzes the change rate of the comprehensive valve control index against a preset range, and takes corresponding control measures based on the judgment and analysis results. This allows for real-time monitoring of changes during the conveying process, thereby achieving dynamic optimization of the ash conveying process and improving the stability and overall ash conveying efficiency.

Description

Technical Field

[0001] This invention relates to the field of intelligent control technology, specifically to an intelligent control method and system for pneumatic ash conveying based on an intelligent pilot valve. Background Technology

[0002] In pneumatic conveying pipelines, intelligent pilot valves are typically installed on ash conveying pipes, along with an air pipe. The intelligent pilot valve connects the conveying pipeline to the air pipe. When the medium reaches a certain distance and the pipe is full, the pilot valve automatically detects the pressure inside the ash conveying pipe. When the pressure reaches the set value for the pilot valve to open, the valve automatically opens to supply booster air to the pipeline. The medium inside the pipeline is propelled forward by the incoming air, thus eliminating blockage at the embolism point. Afterward, as the pressure decreases, the valve automatically closes, and the medium continues to move forward in the pipeline.

[0003] Existing technology, such as the patent application with publication number CN117289608A, discloses an optimized control method for ash conveying in thermal power plants, comprising: laying a dedicated gas-tracing pipeline along the ash conveying pipeline; installing intelligent concentration stabilizers at preset intervals on the ash conveying pipeline; calculating the real-time moisture content of the coal using the heat balance principle of a direct-fired coal mill; predicting the calorific value of the coal based on a BP neural network; calculating the ash content of the coal based on the real-time moisture content and the calorific value; calculating the real-time total ash content based on the ash content and the real-time coal feed rate of each coal mill; determining the pneumatic conveying ratio based on the real-time total ash content; and determining the ash conveying interval based on the pneumatic conveying ratio. This invention solves the problems of high ash conveying costs and the inability to optimize ash conveying frequency and selection in existing technologies.

[0004] Based on the above solutions, the limitations of existing technologies include at least the following problems: existing technologies lack real-time adjustments to dynamic changes during actual operation. Parameters during operation can change at any time in actual production, and existing methods cannot react to these changes in a timely manner. This leads to the risk of instability in pneumatic conveying systems, such as ash plugs and poor material conveying. Consequently, it is difficult to cope with real-time fluctuations in the status of ash conveying pipelines, limiting their application in complex production environments. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a pneumatic ash conveying intelligent control method and system based on an intelligent pilot valve. This solves the problems of existing technologies, such as the lack of real-time adjustment for dynamic changes during actual operation and the difficulty in coping with real-time fluctuations in the ash conveying pipeline status, which limits their application in complex production environments.

[0006] To achieve the above objectives, the present invention provides the following technical solution: an intelligent control method for pneumatic ash conveying based on an intelligent pilot valve, comprising the following steps: when the material to be conveyed is conveyed in the ash conveying pipe, real-time conveying timing data of the ash conveying pipe and pushing timing data of the gas conveying pipe are acquired; the conveying timing data of the ash conveying pipe and the pushing timing data of the gas conveying pipe are analyzed to obtain the comprehensive conveying index of the ash conveying pipe and the pushing index of the gas conveying pipe at each time point, and a comprehensive analysis is performed to obtain the valve control index of the intelligent pilot valve to be controlled at each time point; the valve control index of the intelligent pilot valve to be controlled at each time point is comprehensively analyzed to obtain the comprehensive valve control index change rate of the intelligent pilot valve to be controlled; the comprehensive valve control index change rate of the intelligent pilot valve to be controlled is compared with a preset comprehensive valve control index change rate range, and corresponding control measures are taken for the intelligent pilot valve based on the comparison results.

[0007] Furthermore, the conveying time sequence data includes the conveying speed value, conveying flow rate value, material density value, material viscosity value, material agglomeration index, and material specific surface area value of each ash conveying monitoring point at each time point. The pushing time sequence data includes the gas density value, airflow turbulence value, gas moisture content value, airflow shear stress value, and gas eddy index of each gas conveying monitoring point at each time point.

[0008] Furthermore, the specific formula for calculating the valve control index of the intelligent pilot valve to be controlled at each time point is as follows: ;in, The first intelligent pilot valve to be controlled Valve control index at a given time point The first ash conveying pipe The comprehensive transport index at each point in time. The transmission coefficients are stored in the database. The transport adjustment coefficients are stored in the database. For the first gas pipeline Push index at a specific time point The push coefficients are stored in the database. The push adjustment coefficients are stored in the database. The interaction coefficients are stored in the database. , , The number of time points.

[0009] Furthermore, the specific steps for obtaining the comprehensive conveying index of the ash conveying pipe at each time point are as follows: Obtain the reference values ​​for conveying speed, conveying flow rate, and material density of the ash conveying pipe, and combine these with the conveying speed, flow rate, and material density values ​​of each ash conveying monitoring point at each time point for comprehensive analysis to obtain the conveying stability index of the ash conveying pipe at each time point; further, comprehensively analyze the material viscosity, material agglomeration index, and material specific surface area values ​​of each ash conveying monitoring point at each time point to obtain the conveying efficiency index of the ash conveying pipe at each time point; and finally, comprehensively analyze the conveying stability index and conveying efficiency index of the ash conveying pipe at each time point to obtain the comprehensive conveying index of the ash conveying pipe at each time point.

[0010] Furthermore, the specific steps for obtaining the conveying efficiency index of the ash conveying pipe at each time point are as follows: The material viscosity value, material agglomeration index, and material specific surface area value of each ash conveying monitoring point at each time point of the ash conveying pipe are standardized to obtain the standardized material viscosity value, material agglomeration index, and material specific surface area value of each ash conveying monitoring point at each time point of the ash conveying pipe; and a comprehensive analysis is performed on the standardized material viscosity value, material agglomeration index, and material specific surface area value of each ash conveying monitoring point at each time point of the ash conveying pipe to obtain the conveying efficiency index of the ash conveying pipe at each time point.

[0011] Furthermore, the specific formulas for calculating the conveying stability index and comprehensive conveying index of the ash conveying pipe at each time point are as follows: ;in, The first ash conveying pipe The transport stability index at each point in time. The first ash conveying pipe The first time point The conveying speed value at each ash conveying monitoring point This is a reference value for the conveying speed of the ash conveying pipe. The speed coefficient stored in the database. The first ash conveying pipe The first time point The conveying flow rate value at each ash conveying monitoring point This is a reference value for the conveying flow rate of the ash conveying pipe. The traffic coefficients are stored in the database. The first ash conveying pipe The first time point Material density values ​​at each ash conveying monitoring point This represents the material density value in the ash conveying pipe. This refers to the density coefficient stored in the database. The stability coefficients are stored in the database. The first ash conveying pipe The transport efficiency index at a given time point. Efficiency coefficients stored in the database. , , The number of time points, , This represents the number of ash conveying monitoring points. It is a natural constant.

[0012] Furthermore, the specific steps for obtaining the delivery index of the gas pipeline at each time point are as follows: Perform mean analysis on the gas density value, airflow turbulence value, gas moisture content value, airflow shear stress value, and gas eddy index of each gas pipeline monitoring point at each time point to obtain reference values ​​for gas density, airflow turbulence, gas moisture content, and airflow shear stress at each time point of the gas pipeline; and then correlate these reference values ​​with those of each gas pipeline monitoring point. The gas density, airflow turbulence, gas moisture content, and airflow shear stress values ​​were analyzed to obtain the differences in gas density, airflow turbulence, gas moisture content, and airflow shear stress at each gas transmission monitoring point at each time point in the gas transmission pipeline. These differences were then normalized using the gas eddy index. Based on the normalized differences in gas density, airflow turbulence, gas moisture content, airflow shear stress, and gas eddy index at each gas transmission monitoring point at each time point in the gas transmission pipeline, a comprehensive analysis was performed to obtain the push index of the gas transmission pipeline at each time point.

[0013] Furthermore, the specific formula for calculating the push index of the gas pipeline at each time point is as follows: ;in, , , , , The following are the normalized gas transmission pipes, numbered sequentially. The first time point The differences in gas density, airflow turbulence, gas moisture content, airflow shear stress, and gas eddy index at each gas transmission monitoring point are as follows: , , , , , The parameters stored in the database are, in order: density coefficient, disorder coefficient, gas moisture content coefficient, shear stress coefficient, eddy current coefficient, and interaction coefficient. , The number of time points, , This represents the number of gas transmission monitoring points.

[0014] Furthermore, the specific steps for taking corresponding control measures for the intelligent pilot valve based on the judgment and analysis results are as follows: If the rate of change of the comprehensive valve control index of the intelligent pilot valve to be controlled is lower than the lower limit of the preset range of the rate of change of the comprehensive valve control index, then the first control measure is taken; if the rate of change of the comprehensive valve control index of the intelligent pilot valve to be controlled is within the preset range of the rate of change of the comprehensive valve control index, then the second control measure is taken; if the rate of change of the comprehensive valve control index of the intelligent pilot valve to be controlled is higher than the upper limit of the preset range of the rate of change of the comprehensive valve control index, then the third control measure is taken.

[0015] A pneumatic ash conveying intelligent control system based on an intelligent pilot valve includes: a data acquisition module, a data analysis module, a comprehensive analysis module, and a control judgment module. The data acquisition module is used to acquire real-time conveying time sequence data of the ash conveying pipe and the pushing time sequence data of the gas conveying pipe when the material to be conveyed is conveyed within the ash conveying pipe. The data analysis module is used to analyze the conveying time sequence data of the ash conveying pipe and the pushing time sequence data of the gas conveying pipe respectively, obtaining the comprehensive conveying index of the ash conveying pipe and the pushing index of the gas conveying pipe at each time point, and then performing comprehensive analysis to obtain the valve control index of the intelligent pilot valve to be controlled at each time point. The comprehensive analysis module is used to perform comprehensive analysis of the valve control index of the intelligent pilot valve to be controlled at each time point, obtaining the comprehensive valve control index change rate of the intelligent pilot valve to be controlled. The control judgment module is used to judge and analyze the comprehensive valve control index change rate of the intelligent pilot valve to be controlled against a preset comprehensive valve control index change rate range, and take corresponding control measures for the intelligent pilot valve based on the judgment and analysis results.

[0016] The present invention has the following beneficial effects:

[0017] (1) The intelligent control method for pneumatic ash conveying based on intelligent pilot valve collects the conveying time sequence data of the ash conveying pipeline and the pushing time sequence data of the gas conveying pipe in real time and performs precise dynamic analysis, thereby grasping various changes in the conveying process in real time, adjusting the conveying state according to the actual situation, and realizing dynamic optimization of the ash conveying process, thereby improving the stability of conveying and the overall ash conveying efficiency, and ensuring the stable operation of the equipment for a long time, while reducing downtime maintenance time and related costs.

[0018] (2) The intelligent control method for pneumatic ash conveying based on intelligent pilot valve calculates the rate of change of valve control index in real time and compares it with the preset rate of change range, thereby automatically adjusting the valve state, thereby reducing the possibility of human operation error and improving the system's adaptive capability. At the same time, it can automatically adapt to dynamic adjustment under different working conditions, thereby greatly improving control accuracy and flexibility, and thus reducing errors and delays.

[0019] (3) The intelligent control method for pneumatic ash conveying based on intelligent pilot valve can accurately control the working state of the valve by collecting and analyzing the timing data of conveying and pushing in real time, thereby effectively avoiding problems such as blockage in conveying, and effectively reducing power consumption and gas waste in the pneumatic conveying process, thereby improving the overall energy utilization efficiency and thus helping to achieve more environmentally friendly operation.

[0020] (4) The intelligent control system for pneumatic ash conveying based on the intelligent pilot valve acquires the conveying and pushing time sequence data of the ash conveying pipe and the gas conveying pipe in real time, and uses the data analysis module to perform precise time point data processing to achieve a rapid response to the intelligent pilot valve. The comprehensive analysis module further optimizes the calculation of the valve control index. By tracking the changing trend of the valve control index in real time, it can make accurate control decisions in a short time. In this way, it can effectively reduce the risk of loss of control or reduced efficiency of the ash conveying pipe when facing a rapidly changing conveying environment, thereby improving the real-time responsiveness and accuracy in the conveying process.

[0021] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0022] Figure 1 This is a flowchart of an intelligent control method for pneumatic ash conveying based on an intelligent pilot valve, according to the present invention.

[0023] Figure 2 This is a flowchart illustrating the steps involved in obtaining the comprehensive conveying index of the ash conveying pipe at each time point in the pneumatic ash conveying intelligent control method based on an intelligent pilot valve, as described in this invention.

[0024] Figure 3 This is a block diagram of an intelligent control system for pneumatic ash conveying based on an intelligent pilot valve, according to the present invention. Detailed Implementation

[0025] The problem addressed in this application's embodiments can be summarized as follows:

[0026] When the material to be conveyed is transported in the ash conveying pipe, the conveying time sequence data of the ash conveying pipe and the pushing time sequence data of the gas conveying pipe are acquired in real time and analyzed separately to obtain the comprehensive conveying index of the ash conveying pipe and the pushing index of the gas conveying pipe at each time point. Then, a comprehensive analysis is performed to obtain the valve control index of the intelligent pilot valve to be controlled at each time point. Then, the comprehensive valve control index change rate of the intelligent pilot valve to be controlled is analyzed to obtain the comprehensive valve control index change rate change rate of the intelligent pilot valve to be controlled. Finally, the comprehensive valve control index change rate of the intelligent pilot valve to be controlled is compared with the preset comprehensive valve control index change rate range, and corresponding control measures are taken for the intelligent pilot valve based on the judgment and analysis results.

[0027] Please see Figure 1 This invention provides a technical solution: an intelligent control method for pneumatic ash conveying based on an intelligent pilot valve, comprising the following steps: when the material to be conveyed is conveyed in the ash conveying pipe, real-time conveying time sequence data of the ash conveying pipe and pushing time sequence data of the gas conveying pipe are acquired; the conveying time sequence data of the ash conveying pipe and the pushing time sequence data of the gas conveying pipe are analyzed to obtain the comprehensive conveying index of the ash conveying pipe and the pushing index of the gas conveying pipe at each time point, and a comprehensive analysis is performed to obtain the valve control index of the intelligent pilot valve to be controlled at each time point; the valve control index of the intelligent pilot valve to be controlled at each time point is comprehensively analyzed to obtain the comprehensive valve control index change rate of the intelligent pilot valve to be controlled; the comprehensive valve control index change rate of the intelligent pilot valve to be controlled is compared with a preset comprehensive valve control index change rate interval for judgment and analysis, and corresponding control measures are taken for the intelligent pilot valve based on the judgment and analysis results; wherein, the specific formula for calculating the comprehensive valve control index change rate of the intelligent pilot valve to be controlled is as follows: ;in, The rate of change of the comprehensive valve control index of the intelligent pilot valve to be controlled. The first intelligent pilot valve to be controlled Valve control index at a given time point The first intelligent pilot valve to be controlled Valve control index at a given time point , The number of time points.

[0028] The specific formula for calculating the valve control index of the intelligent pilot valve to be controlled at each time point is as follows: ;in, The first intelligent pilot valve to be controlled Valve control index at a given time point The first ash conveying pipe The comprehensive transport index at each point in time. The transmission coefficients are stored in the database. The transport adjustment coefficients are stored in the database. For the first gas pipeline Push index at a specific time point The push coefficients are stored in the database. The push adjustment coefficients are stored in the database. The interaction coefficients are stored in the database. , , The number of time points.

[0029] It needs to be explained that in the formula... The combined effect of the comprehensive conveying index of the ash conveying pipe at each time point and the push index of the gas conveying pipe at each time point prevents the valve control index of the intelligent pilot valve to be controlled from being too high or too low at each time point.

[0030] , The following steps can be taken to obtain the control sum: read the comprehensive conveying index of the ash conveying pipe and the pushing index of the gas conveying pipe at each time point, perform mean analysis, perform summation analysis based on the mean analysis results to obtain the control sum, and perform proportion analysis between the mean analysis results and the control sum, and use the proportion analysis results as the corresponding coefficients.

[0031] , , The following steps can be taken: First, obtain historical data and determine the initial influence weights of each variable on the valve control index through statistical regression analysis. Then, use sensitivity analysis to adjust the range of coefficient values ​​to evaluate the stability and applicability of these parameters to the formula output. Next, further fit the weights through model optimization (such as machine learning algorithms) to ensure that the formula can accurately reflect the valve control of the actual intelligent pilot valve.

[0032] The following is a specific implementation example for calculating the valve control index of the intelligent pilot valve to be controlled at the first time point, with the following data available:

[0033] The comprehensive conveying index of the ash conveying pipe at the first time point is approximately 1.74.

[0034] The push index of the gas delivery tube at the first time point was approximately 1.06.

[0035] The transmission coefficient stored in the database is approximately 0.62.

[0036] The transport adjustment factor stored in the database is approximately 0.38.

[0037] The push coefficient stored in the database is approximately 0.36.

[0038] The push adjustment coefficient stored in the database is approximately 0.41.

[0039] The interaction coefficient stored in the database is approximately 0.64.

[0040] Substituting the above data into the specific formula for the valve control index at each time point of the intelligent pilot valve to be controlled, we obtain:

[0041] The valve control index of the intelligent pilot valve to be controlled at the first time point = (0.62 * 1.74) 0.36+0.38*1.06 0.41 ) / (0.64*1.74*1.06)≈0.97.

[0042] The conveying time sequence data includes the conveying speed, conveying flow rate, material density, material viscosity, material agglomeration index, and material specific surface area of ​​each ash conveying monitoring point at each time point. The push time sequence data includes the gas density, airflow turbulence, gas moisture content, airflow shear stress, and gas eddy index of each gas conveying monitoring point at each time point.

[0043] The conveying speed value is the speed at which the gas in the gas conveying pipe combines with the material in the ash conveying pipe. It can be obtained by a flow rate sensor and is used to reflect the stability of the conveying process.

[0044] The conveying flow rate is the total amount of gas and material passing through the conveying pipeline, which can be obtained by a mass flow meter and is used to reflect the material conveying capacity.

[0045] Material density is a measure of the degree of compaction and the tightness of the material composition. It can be obtained through a density sensor and is used to reflect the flowability of the material.

[0046] The viscosity value of a material is the flow resistance of the material in the ash conveying pipe. It can be obtained by a rotational viscometer and is used to reflect the efficiency of the conveying process.

[0047] The material agglomeration index is the degree to which material particles stick together during the conveying process. It is obtained by acquiring material temperature and humidity values, standardizing them, and then weighting the results based on the standardization. The material temperature value can be obtained by a temperature sensor, and the material humidity value can be obtained by a humidity sensor. The material agglomeration index is used to reflect the efficiency of the conveying process.

[0048] The specific surface area of ​​a material is the surface area of ​​the material at the ash conveying monitoring point. It can be measured by a specific surface area meter (which calculates the surface area based on BET theory and then outputs the calculation results), and the measurement results are uploaded to the database to reflect the flowability of the material particles.

[0049] The airflow turbulence value is the degree of turbulence of the flowing gas, which is the ratio of the velocity fluctuation value (i.e., the standard deviation of the velocity at each ash conveying monitoring point) to the average velocity. The airflow turbulence value = velocity fluctuation value / average velocity. The velocity value at each point can be obtained by a thermal flow velocity sensor, which is used to reflect the stability of the gas.

[0050] The moisture content of a gas is the proportion of water vapor contained in the gas, which can be obtained by a humidity sensor and is used to reflect the flowability of the gas.

[0051] The airflow shear stress value is a measure of the frictional force inside the fluid and can be obtained through a suspended force sensor, which is used to reflect the flowability of the gas.

[0052] The gas eddy index is the intensity and influence of eddies in gas flow. It is obtained by acquiring the flow velocity, pressure and temperature values ​​at the ash conveying monitoring point, standardizing them, and then performing a weighted analysis based on the standardization results. The weighted result is the gas eddy index, which is used to reflect the stability of the gas in the gas conveying pipe.

[0053] Specifically, such as Figure 2 As shown, the specific steps to obtain the comprehensive conveying index of the ash conveying pipe at each time point are as follows: Obtain the reference values ​​for conveying speed, flow rate, and material density of the ash conveying pipe, and combine these with the conveying speed, flow rate, and material density values ​​of each ash conveying monitoring point at each time point for comprehensive analysis to obtain the conveying stability index of the ash conveying pipe at each time point; further analyze the material viscosity, agglomeration index, and specific surface area of ​​the ash conveying pipe at each ash conveying monitoring point at each time point to obtain the conveying efficiency index of the ash conveying pipe at each time point; and finally, comprehensively analyze the conveying stability index and conveying efficiency index of the ash conveying pipe at each time point to obtain the comprehensive conveying index of the ash conveying pipe at each time point.

[0054] The specific formulas for calculating the conveying stability index and comprehensive conveying index of the ash conveying pipe at each time point are as follows: ;in, The first ash conveying pipe The transport stability index at each point in time. The first ash conveying pipe The first time point The conveying speed value at each ash conveying monitoring point This is a reference value for the conveying speed of the ash conveying pipe. The speed coefficient stored in the database. The first ash conveying pipe The first time point The conveying flow rate value at each ash conveying monitoring point This is a reference value for the conveying flow rate of the ash conveying pipe. The traffic coefficients are stored in the database. The first ash conveying pipe The first time point Material density values ​​at each ash conveying monitoring point This represents the material density value in the ash conveying pipe. This refers to the density coefficient stored in the database. The stability coefficients are stored in the database. The first ash conveying pipe The transport efficiency index at a given time point. Efficiency coefficients stored in the database. , , The number of time points, , This represents the number of ash conveying monitoring points. It is a natural constant, and in this implementation example, it takes the value 2.71.

[0055] It needs to be explained that, , , The following steps can be taken to obtain the following data: obtain the conveying speed, conveying flow rate, and material density reference value of each ash conveying monitoring point at each historical time point, perform statistical regression analysis to quantify the specific impact of each factor on environmental correction, and thus fit the initial weight values. Next, use sensitivity analysis to adjust the range of values ​​of the corresponding coefficients to ensure the stability and rationality of the model. Based on the actual situation, correct and optimize the initially fitted coefficients, and finally determine the corresponding coefficient values.

[0056] , The following steps can be taken to obtain the following: Read the conveying stability index and conveying efficiency index of the ash conveying pipe at each time point (it should be noted that the conveying stability index and conveying efficiency index are dimensionless values ​​and can be calculated directly), perform mean analysis, perform summation analysis based on the mean analysis results to obtain the conveying sum value, and perform ratio analysis between the mean analysis results and the conveying sum value, and use the ratio analysis results as the corresponding coefficients.

[0057] This implementation plan comprehensively considers multiple key factors such as conveying speed, flow rate, material density, material viscosity, and agglomeration index to accurately reflect the actual conveying status of the ash conveying pipe. This allows for real-time monitoring and adjustment of the conveying process in a dynamic environment, thereby ensuring maximum stability and efficiency of the conveying. Furthermore, by calculating the conveying stability index in real time, the stability of the conveying process at each point in time can be assessed, and potential unstable factors can be identified in a timely manner. This helps prevent blockages or other malfunctions in the ash conveying pipe and allows for timely adjustments to the conveying method, while ensuring continuous and stable operation.

[0058] By calculating the conveying efficiency index, this step effectively assesses the material conveying efficiency at each time point, including the material's flowability, viscosity, and agglomeration characteristics. Optimizing the conveying efficiency index reduces energy consumption and improves the accuracy and speed of material conveying, thereby reducing operating costs and increasing the overall production efficiency of the system. Increased conveying efficiency means higher material conveying capacity and lower energy consumption, which plays a crucial role in improving factory productivity. Next, through regression analysis and sensitivity analysis of historical data, the impact of each influencing factor on the conveying process is quantified, allowing for dynamic adjustment of corresponding coefficients during actual operation. This ensures the stability and rationality of the model and enables real-time optimization based on changes in the conveying environment. Finally, by dynamically calculating the comprehensive conveying index at each time point, the conveying status at each time point can be monitored and optimized in real time, thereby improving adaptability to different operating conditions and further ensuring the smoothness and efficiency of the production process.

[0059] Specifically, the steps to obtain the conveying efficiency index of the ash conveying pipe at each time point are as follows: The material viscosity value, material agglomeration index, and material specific surface area value of each ash conveying monitoring point at each time point of the ash conveying pipe are standardized (i.e., unit removal) to obtain the standardized material viscosity value, material agglomeration index, and material specific surface area value of each ash conveying monitoring point at each time point of the ash conveying pipe; and a comprehensive analysis is performed on the standardized material viscosity value, material agglomeration index, and material specific surface area value of each ash conveying monitoring point at each time point of the ash conveying pipe to obtain the conveying efficiency index of the ash conveying pipe at each time point.

[0060] The specific formula for calculating the conveying efficiency index of the ash conveying pipe at each time point is as follows: ;in, The first ash conveying pipe The transport efficiency index at a given time point. The first standardized ash conveying pipe The first time point Material viscosity values ​​at each ash conveying monitoring point The viscosity coefficient is stored in the database. The first standardized ash conveying pipe The first time point Material agglomeration index at each ash conveying monitoring point The clustering coefficient is stored in the database. The first standardized ash conveying pipe The first time point The specific surface area value of the material at each ash conveying monitoring point. The settlement coefficient is stored in the database. , , The number of time points, , This represents the number of ash conveying monitoring points.

[0061] It needs to be explained that, , , The following steps can be taken to obtain the following data: Read the material viscosity, material agglomeration index, and material specific surface area of ​​each monitoring point at each time point of the standardized ash conveying pipe, perform mean analysis to obtain the mean material viscosity, mean material agglomeration degree, and mean material settling rate of the standardized ash conveying pipe, perform summation analysis to obtain the efficiency sum value, and perform ratio analysis between the mean material viscosity, mean material agglomeration degree, and mean material settling rate of the standardized ash conveying pipe and the efficiency sum value, and use the ratio analysis results as the corresponding coefficients.

[0062] In this implementation plan, standardization eliminates differences in units and dimensions of different material properties, allowing for comparison and analysis of various indicators on the same scale. This improves the comparability of data and avoids calculation errors caused by different units, resulting in a more accurate and reliable conveying efficiency index. Secondly, comprehensive analysis of multiple key factors such as material viscosity, agglomeration index, and specific surface area allows for a more comprehensive evaluation of the conveying efficiency of the ash conveying pipe. This enables reasonable assessments of conveying efficiency under different operating conditions, helping the intelligent pilot valve to react quickly in complex situations and ensuring maximum conveying efficiency. Finally, mean analysis and proportion analysis ensure that the conveying efficiency index stably and accurately reflects the actual conveying effect under different operating conditions. Especially in dynamic environments, where material characteristics change during conveying, proportion analysis allows for adjustment and optimization of conveying parameters based on actual conditions, further improving conveying efficiency.

[0063] Specifically, the steps to obtain the delivery index of the gas pipeline at each time point are as follows: Perform mean analysis on the gas density, airflow turbulence, gas moisture content, airflow shear stress, and gas eddy index values ​​at each gas monitoring point at each time point of the gas pipeline to obtain reference values ​​for gas density, airflow turbulence, gas moisture content, and airflow shear stress at each time point of the gas pipeline; and then compare these reference values ​​with the gas density at each gas monitoring point. The gas density, airflow turbulence, gas moisture content, and airflow shear stress values ​​at each time point in the gas pipeline are analyzed by difference to obtain the differences in gas density, airflow turbulence, gas moisture content, and airflow shear stress at each gas pipeline monitoring point. These values ​​are then normalized (i.e., unit removal) in conjunction with the gas eddy index. Based on the normalized differences in gas density, airflow turbulence, gas moisture content, airflow shear stress, and gas eddy index at each time point in the gas pipeline, a comprehensive analysis is performed to obtain the push index of the gas pipeline at each time point.

[0064] The key feature is that the specific formula for calculating the push index of the gas pipeline at each time point is as follows: ;in, The first normalized gas pipeline The first time point Gas density difference at each gas transmission monitoring point The first normalized gas pipeline The first time point The difference in airflow turbulence at each gas transmission monitoring point The first normalized gas pipeline The first time point Difference in gas moisture content at each gas transmission monitoring point The first normalized gas pipeline The first time point The difference in airflow shear stress at each gas transmission monitoring point The first normalized gas pipeline The first time point The differences in gas density, airflow turbulence, gas moisture content, airflow shear stress, and gas eddy index at each gas transmission monitoring point are as follows: The density coefficients stored in the database. The disorder coefficients stored in the database This refers to the gas moisture coefficient stored in the database. The shear stress coefficient is stored in the database. The eddy current coefficients are stored in the database. The interaction coefficients are stored in the database. , The number of time points, , This represents the number of gas transmission monitoring points.

[0065] It needs to be explained that in the formula... The superposition effect of gas density difference, airflow turbulence difference, gas moisture content difference, airflow shear stress difference, and gas eddy index after normalization is used to prevent the push index from being too high or too low.

[0066] , , , , , The following steps can be taken to obtain the following data: gas density, airflow turbulence, gas moisture content, airflow shear stress, gas eddy index, and interaction product (i.e., the product of gas density, airflow turbulence, gas moisture content, airflow shear stress, and gas eddy index) for each gas transmission monitoring point at each historical time point. Statistical regression analysis is then performed to quantify the specific impact of each factor on the push index, thereby fitting initial weight values. Next, sensitivity analysis is used to adjust the range of corresponding coefficients to ensure the stability and rationality of the model. Based on the actual situation, the initially fitted coefficients are corrected and optimized, and finally, the corresponding coefficient values ​​are determined.

[0067] In this implementation scheme, by normalizing various parameters, the influence of different gas properties can be compared and analyzed under the same standard, thus avoiding data deviations caused by inconsistent dimensions and improving the accuracy and consistency of data processing. Secondly, through mean analysis, difference analysis, and comprehensive analysis of various gas characteristics, the pushing status of the gas pipeline at different time points can be comprehensively evaluated. Through multi-dimensional parameter cross-analysis, the complex dynamic characteristics of airflow are reflected, including flow instability and changes in the physical properties of gases, which helps to accurately identify changes in airflow state, thereby optimizing airflow distribution in the pneumatic conveying process and improving pushing efficiency. At the same time, through difference analysis, the deviation between each monitoring point and the reference value can be obtained in real time, and the control parameters of pneumatic conveying can be adjusted according to these deviations to ensure the stable and efficient operation of the pneumatic conveying system. Finally, through accurate pushing index calculation, energy consumption and airflow distribution in the pneumatic conveying process can be effectively predicted and optimized. While ensuring conveying efficiency, energy waste caused by excessively strong or slow airflow can be avoided, thereby improving energy utilization efficiency, reducing system operating costs, and improving overall resource utilization.

[0068] Specifically, the steps for taking corresponding control measures for the intelligent pilot valve based on the judgment and analysis results are as follows: If the rate of change of the comprehensive valve control index of the intelligent pilot valve to be controlled is lower than the lower limit of the preset comprehensive valve control index rate of change range (i.e., the minimum value of the comprehensive valve control index rate of change range), then the first control measure is taken (i.e., increasing the valve opening and increasing the airflow push to increase the conveying flow and prevent poor conveying or blockage); if the rate of change of the comprehensive valve control index of the intelligent pilot valve to be controlled is within the preset comprehensive valve control index rate of change range, then the second control measure is taken (i.e., maintaining the existing valve opening); if the rate of change of the comprehensive valve control index of the intelligent pilot valve to be controlled is higher than the upper limit of the preset comprehensive valve control index rate of change range (i.e., the maximum value of the comprehensive valve control index rate of change range), then the third control measure is taken (i.e., reducing the valve opening and reducing the airflow push to avoid energy waste, airflow instability or material loss caused by excessive airflow).

[0069] In this implementation scheme, by adjusting the valve opening and airflow rate in real time, stable operation can be maintained under different working conditions, avoiding problems such as unstable airflow, poor material flow, or blockage, thus ensuring the reliability of the conveying system and reducing the possibility of failure. Secondly, by precisely controlling the valve opening, excessive airflow and energy waste are avoided. At the same time, through automated control strategies, combined with real-time monitoring data and preset control ranges, the valve state is adaptively adjusted, thereby avoiding the lag of manual intervention, improving response speed, and ensuring rapid adaptation and adjustment under different environments and working conditions. By setting different control measures, it can flexibly respond to different working conditions and meet different conveying needs, thus enabling the intelligent pilot valve to adapt to changing working environments and material conveying requirements.

[0070] Please see Figure 3This invention provides a technical solution: an intelligent control system for pneumatic ash conveying based on an intelligent pilot valve, comprising: a data acquisition module, a data analysis module, a comprehensive analysis module, and a control judgment module; the data acquisition module is used to acquire in real time the conveying time sequence data of the ash conveying pipe and the pushing time sequence data of the gas conveying pipe when the material to be conveyed is conveyed in the ash conveying pipe; the data analysis module is used to perform data analysis on the conveying time sequence data of the ash conveying pipe and the pushing time sequence data of the gas conveying pipe respectively, to obtain the comprehensive conveying index of the ash conveying pipe and the pushing index of the gas conveying pipe at each time point, and to perform comprehensive analysis to obtain the valve control index of the intelligent pilot valve to be controlled at each time point; the comprehensive analysis module is used to perform comprehensive analysis on the valve control index of the intelligent pilot valve to be controlled at each time point, to obtain the comprehensive valve control index change rate of the intelligent pilot valve to be controlled; the control judgment module is used to judge and analyze the comprehensive valve control index change rate of the intelligent pilot valve to be controlled against a preset comprehensive valve control index change rate range, and to take corresponding control measures for the intelligent pilot valve based on the judgment and analysis results.

[0071] In summary, this application has at least the following effects:

[0072] By collecting real-time data on the conveying time of the ash conveying pipeline and the pushing time of the gas conveying pipeline, and performing precise dynamic analysis, the system can monitor various changes in the conveying process in real time. This allows for adjustments to the conveying status based on actual conditions, achieving dynamic optimization of the ash conveying process. Consequently, the system improves the stability of the conveying process and the overall ash conveying efficiency, ensuring long-term stable operation of the equipment while reducing downtime and maintenance time and related costs.

[0073] By calculating the rate of change of the valve control index in real time and comparing it with the preset rate of change range, the valve state is automatically adjusted, thereby reducing the possibility of human error and improving the system's adaptability. At the same time, it can automatically adapt to dynamic adjustments under different working conditions, thus greatly improving control accuracy and flexibility, and reducing errors and delays.

[0074] By collecting and analyzing the timing data of delivery and push in real time, the working status of the valve can be precisely controlled, thereby effectively avoiding problems such as blockage during delivery. It can also effectively reduce power consumption and gas waste in the pneumatic delivery process, thereby improving the overall energy utilization efficiency and helping to achieve more environmentally friendly operation.

[0075] By acquiring real-time data on the conveying and pushing of ash and gas pipes and using a data analysis module for precise time-point data processing, a rapid response to the intelligent pilot valve is achieved. The comprehensive analysis module further optimizes the calculation of the valve control index. By tracking the changing trend of the valve control index in real time, accurate control decisions can be made in a short period of time. This effectively reduces the risk of loss of control or reduced efficiency of the ash conveying pipe when facing rapidly changing conveying environments, thereby improving the real-time responsiveness and accuracy of the conveying process.

[0076] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0077] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A pneumatic ash conveying intelligent control method based on an intelligent pilot valve, characterized in that, Includes the following steps: When the material to be conveyed is conveyed in the ash conveying pipe, the conveying timing data of the ash conveying pipe and the pushing timing data of the gas conveying pipe are acquired in real time. The conveying time sequence data includes the conveying speed value, conveying flow rate value, material density value, material viscosity value, material agglomeration index, and material specific surface area value of each ash conveying monitoring point at each time point. The pushing time sequence data includes the gas density value, airflow turbulence value, gas moisture content value, airflow shear stress value, and gas eddy index of each gas conveying monitoring point at each time point. Data analysis was performed on the conveying time sequence data of the ash conveying pipe and the pushing time sequence data of the gas conveying pipe to obtain the comprehensive conveying index of the ash conveying pipe and the pushing index of the gas conveying pipe at each time point. A comprehensive analysis was then performed to obtain the valve control index of the intelligent pilot valve to be controlled at each time point. The specific steps to obtain the comprehensive conveying index of the ash conveying pipe at each time point are as follows: The reference values ​​for conveying speed, conveying flow rate, and material density of the ash conveying pipe are obtained. Combined with the conveying speed, conveying flow rate, and material density values ​​of each ash conveying monitoring point at each time point, a comprehensive analysis is conducted to obtain the conveying stability index of the ash conveying pipe at each time point. The material viscosity, agglomeration index, and specific surface area of ​​each ash conveying monitoring point at each time point of the ash conveying pipe are comprehensively analyzed to obtain the conveying efficiency index of the ash conveying pipe at each time point. Furthermore, a comprehensive analysis was conducted on the conveying stability index and conveying efficiency index of the ash conveying pipe at each time point to obtain the comprehensive conveying index of the ash conveying pipe at each time point; The specific formula for calculating the valve control index of the intelligent pilot valve to be controlled at each time point is as follows: ； in, The first intelligent pilot valve to be controlled Valve control index at a given time point The first ash conveying pipe The comprehensive transport index at each point in time. The transmission coefficients are stored in the database. The transport adjustment coefficients are stored in the database. For the first gas pipeline Push index at a specific time point The push coefficients are stored in the database. The push adjustment coefficients are stored in the database. The interaction coefficients are stored in the database. , , The number of time points; Furthermore, a comprehensive analysis of the valve control index at each time point of the intelligent pilot valve to be controlled is performed to obtain the comprehensive valve control index change rate of the intelligent pilot valve to be controlled. The rate of change of the comprehensive valve control index of the intelligent pilot valve to be controlled is compared with the preset range of the rate of change of the comprehensive valve control index, and corresponding control measures are taken for the intelligent pilot valve based on the results of the comparison and analysis.

2. The intelligent control method for pneumatic ash conveying based on an intelligent pilot valve according to claim 1, characterized in that, The specific steps to obtain the conveying efficiency index of the ash conveying pipe at each time point are as follows: The material viscosity value, material agglomeration index, and material specific surface area value of each ash conveying monitoring point at each time point of the ash conveying pipe are standardized to obtain the standardized material viscosity value, material agglomeration index, and material specific surface area value of each ash conveying monitoring point at each time point of the ash conveying pipe. The material viscosity, agglomeration index, and specific surface area of ​​the ash conveying pipe at each time point after standardization were comprehensively analyzed to obtain the conveying efficiency index of the ash conveying pipe at each time point.

3. The intelligent control method for pneumatic ash conveying based on an intelligent pilot valve according to claim 1, characterized in that, The specific formulas for calculating the conveying stability index and comprehensive conveying index of the ash conveying pipe at each time point are as follows: ; in, The first ash conveying pipe The transport stability index at each point in time. The first ash conveying pipe The first time point The conveying speed value at each ash conveying monitoring point This is a reference value for the conveying speed of the ash conveying pipe. The speed coefficient stored in the database. The first ash conveying pipe The first time point The conveying flow rate value at each ash conveying monitoring point This is a reference value for the conveying flow rate of the ash conveying pipe. The traffic coefficients are stored in the database. The first ash conveying pipe The first time point Material density values ​​at each ash conveying monitoring point This represents the material density value in the ash conveying pipe. This refers to the density coefficient stored in the database. The stability coefficients are stored in the database. The first ash conveying pipe The transport efficiency index at a given time point. Efficiency coefficients stored in the database. , , The number of time points, , This represents the number of ash conveying monitoring points. It is a natural constant.

4. The intelligent control method for pneumatic ash conveying based on an intelligent pilot valve according to claim 1, characterized in that, The specific steps to obtain the push index of the gas pipeline at each time point are as follows: The average values ​​of gas density, airflow turbulence, gas moisture content, airflow shear stress, and gas eddy index at each gas transmission monitoring point at each time point in the gas transmission pipeline were analyzed to obtain reference values ​​of gas density, airflow turbulence, gas moisture content, and airflow shear stress at each time point in the gas transmission pipeline. The reference values ​​of gas density, airflow turbulence, gas moisture content, and airflow shear stress at each time point in the gas pipeline were compared with the gas density, airflow turbulence, gas moisture content, and airflow shear stress values ​​at each gas transmission monitoring point. The differences in gas density, airflow turbulence, gas moisture content, and airflow shear stress at each gas transmission monitoring point at each time point in the gas pipeline were obtained and normalized by combining the gas eddy index. Based on the gas density difference, airflow turbulence difference, gas moisture content difference, airflow shear stress difference, and gas eddy index of each gas transmission monitoring point at each time point after normalization, a comprehensive analysis is performed to obtain the push index of the gas transmission pipeline at each time point.

5. The intelligent control method for pneumatic ash conveying based on an intelligent pilot valve according to claim 4, characterized in that, The specific formula for calculating the push index of the gas pipeline at each time point is as follows: ； in, , , , , The following are the normalized gas transmission pipes, numbered sequentially. The first time point The differences in gas density, airflow turbulence, gas moisture content, airflow shear stress, and gas eddy index at each gas transmission monitoring point are as follows: , , , , , The parameters stored in the database are, in order: density coefficient, disorder coefficient, gas moisture content coefficient, shear stress coefficient, eddy current coefficient, and interaction coefficient. , The number of time points, , This represents the number of gas transmission monitoring points.

6. The intelligent control method for pneumatic ash conveying based on an intelligent pilot valve according to claim 1, characterized in that, The specific steps for taking corresponding control measures for the intelligent pilot valve based on the judgment and analysis results are as follows: If the rate of change of the comprehensive valve control index of the intelligent pilot valve to be controlled is lower than the lower limit of the preset range of the rate of change of the comprehensive valve control index, then the first control measure shall be taken. If the rate of change of the comprehensive valve control index of the intelligent pilot valve to be controlled is within the preset range of the rate of change of the comprehensive valve control index, then the second control measure shall be adopted. If the rate of change of the comprehensive valve control index of the intelligent pilot valve to be controlled is higher than the upper limit of the preset range of the rate of change of the comprehensive valve control index, then a third control measure will be taken.

7. A pneumatic ash conveying intelligent control system based on an intelligent pilot valve, employing the pneumatic ash conveying intelligent control method based on an intelligent pilot valve as described in any one of claims 1-6, characterized in that, include: Data acquisition module, data analysis module, comprehensive analysis module, control and judgment module; The data acquisition module is used to acquire the conveying timing data of the ash conveying pipe and the pushing timing data of the gas conveying pipe in real time when the material to be conveyed is conveyed in the ash conveying pipe. The data analysis module is used to perform data analysis on the conveying time sequence data of the ash conveying pipe and the pushing time sequence data of the gas conveying pipe, respectively, to obtain the comprehensive conveying index of the ash conveying pipe and the pushing index of the gas conveying pipe at each time point, and to perform comprehensive analysis to obtain the valve control index of the intelligent pilot valve to be controlled at each time point. The comprehensive analysis module is used to comprehensively analyze the valve control index of the intelligent pilot valve to be controlled at each time point, and obtain the comprehensive valve control index change rate of the intelligent pilot valve to be controlled. The control judgment module is used to judge and analyze the change rate of the comprehensive valve control index of the intelligent pilot valve to be controlled and the preset range of the change rate of the comprehensive valve control index, and to take corresponding control measures for the intelligent pilot valve based on the judgment and analysis results.

Images