Pneumatic ash conveying intelligent control method and system based on intelligent pilot valve

Abstract

The invention discloses a pneumatic ash conveying intelligent control method and system based on an intelligent pilot valve, and relates to the technical field of intelligent control. According to the pneumatic ash conveying intelligent control method based on the intelligent pilot valve, when materials to be conveyed are conveyed in an ash conveying pipe, time sequence data are conveyed in real time, the time sequence data are pushed in real time, data analysis is conducted respectively, and a comprehensive conveying index of the ash conveying pipe at each time point and a pushing index of an air conveying pipe at each time point are obtained; performing comprehensive analysis to obtain a valve control index at each time point, and performing analysis to obtain a comprehensive valve control index change rate; according to the method, the comprehensive valve control index change rate and the preset comprehensive valve control index change rate interval are judged and analyzed, and the corresponding control measures are taken based on the judgment and analysis result, so that the change in the conveying process is mastered in real time, the dynamic optimization of the ash conveying process is realized, and the ash conveying efficiency is improved. And therefore, the conveying stability and the overall ash conveying efficiency are improved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent control technology, and in particular to an intelligent control method and system for pneumatic ash conveying based on an intelligent pilot valve. Background Art

[0002] In pneumatic conveying pipelines, the intelligent pilot valve is generally installed on the ash conveying pipeline. At the same time, an air pipe is installed along the ash conveying pipeline, and the intelligent pilot valve connects the conveying pipeline with the air pipe. When the medium is transported to a certain distance and reaches a full pipe state, the pilot valve installed on the pipeline will automatically detect the pressure in the ash conveying pipe. When the pressure setting value for the pilot valve to open is reached, the valve will automatically open to supplement the booster air source into the pipeline. The medium in the pipeline is pushed by the incoming air and automatically flows forward, thereby eliminating the pipe blockage phenomenon at the embolism point. After that, the pressure drops, the valve automatically closes, and the medium in the pipeline continues to move forward.

[0003] Prior art, such as a patent application with announcement number: CN117289608A, discloses an ash transportation optimization control method for a thermal power plant, including: laying a dedicated accompanying gas pipeline along the ash transportation pipeline, installing an intelligent concentration stabilizer at a preset distance on the ash transportation pipeline; calculating the real-time moisture content of the coal using the thermal balance principle of a direct-blowing 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 of the coal and the calorific value of the coal; calculating the real-time total ash content based on the ash content of the coal and the real-time coal feed of each coal mill; determining the pneumatic conveying ratio based on the real-time total ash content; and determining the ash transportation interval based on the pneumatic conveying ratio. The present invention solves the problem of high ash transportation cost and inability to optimize ash transportation frequency and ash transportation selection in the prior art.

[0004] Based on the above scheme, it is found that the limitations of the existing technology include at least the following problems: the existing technology lacks real-time adjustment of dynamic changes in actual operation. The parameters in the operation process may change at any time in actual production. The existing method is difficult to respond to these changes in time, resulting in the risk of instability in the pneumatic conveying system, such as ash plugs, poor material transportation, etc., which makes it difficult to cope with the real-time fluctuations in the state of the ash conveying pipeline, limiting its application in complex production environments. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides an intelligent control method and system for pneumatic ash conveying based on an intelligent pilot valve, which solves the problems that the prior art lacks real-time adjustment to dynamic changes in actual operation and is difficult to cope with real-time fluctuations in the state of the ash conveying pipeline, limiting its application in complex production environments.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: 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, the conveying timing data of the ash conveying pipe and the pushing timing data of the gas pipe are obtained in real time; the conveying timing data of the ash conveying pipe and the pushing timing data of the gas pipe are respectively analyzed to obtain the comprehensive conveying index of the ash conveying pipe at each time point and the pushing index of the gas 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; and 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 judged and analyzed with a preset comprehensive valve control index change rate interval, and corresponding control measures are taken for the intelligent pilot valve based on the judgment and analysis results.

[0007] Furthermore, the conveying timing data includes the conveying speed value, conveying flow 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, and the pushing timing data includes the gas density value, airflow turbulence value, gas moisture content value, airflow shear stress value, and gas vortex index of each gas transmission 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: Among them, FmK i is the valve control index of the intelligent pilot valve to be controlled at the i-th time point, SzH i is the comprehensive transport index of the ash conveying pipe at the i-th time point, α1 is the transport coefficient stored in the database, β1 is the transport adjustment coefficient stored in the database, TsZ i is the push index of the gas pipeline at the i-th time point, α2 is the push coefficient stored in the database, β2 is the push adjustment coefficient stored in the database, β3 is the interaction coefficient stored in the database, α1+α2=1, i=1, 2, 3, …, i0, i0 is the number of time points.

[0009] Furthermore, the specific steps to obtain the comprehensive conveying index of the ash conveying pipe at each time point are as follows: obtain the conveying speed reference value, conveying flow reference value and material density reference value of the ash conveying pipe, and conduct a comprehensive analysis based on the conveying speed value, conveying flow value and material density value of each ash conveying monitoring point at each time point to obtain the conveying stability index of the ash conveying pipe at each time point; and conduct a comprehensive analysis of 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 to obtain the conveying efficiency index of the ash conveying pipe at each time point; and conduct a comprehensive analysis of 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: standardize the material viscosity value, material agglomeration index and material specific surface area value of each ash conveying monitoring point of the ash conveying pipe at each time point to obtain the standardized material viscosity value, material agglomeration index and material specific surface area value of each ash conveying monitoring point of the ash conveying pipe at each time point; and comprehensively analyze the material viscosity value, material agglomeration index and material specific surface area value of each ash conveying monitoring point of the ash conveying pipe at each time point after the standardized processing to obtain the conveying efficiency index of the ash conveying pipe at each time point.

[0011] Furthermore, the specific formula for calculating the conveying stability index and comprehensive conveying index of the ash conveying pipe at each time point is as follows: Among them, SwD i is the transport stability index of the ash conveying pipe at the i-th time point, SdZ ij is the conveying speed value of the jth ash conveying monitoring point at the i-th time point of the ash conveying pipe, CsD is the conveying speed reference value of the ash conveying pipe, θ1 is the speed coefficient stored in the database, LsZ ij is the conveying flow value of the jth ash conveying monitoring point at the i-th time point of the ash conveying pipe, CsL is the conveying flow reference value of the ash conveying pipe, θ2 is the flow coefficient stored in the database, WmD ij is the material density value of the jth ash conveying monitoring point at the ith time point of the ash conveying pipe, CmD is the material density value of the ash conveying pipe, θ3 is the density coefficient stored in the database, SzH i is the comprehensive transport index of the ash conveying pipe at the i-th time point, η1 is the stability coefficient stored in the database, XsL i is the transport efficiency index of the ash conveying pipe at the i-th time point, η2 is the efficiency coefficient stored in the database, η1+η2=1, i=1,2,3,…,i0,i0 is the number of time points, j=1,2,3,…,j0,j0 is the number of ash conveying monitoring points, and e is a natural constant.

[0012] Furthermore, the specific steps for obtaining the push 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 vortex index of each gas transmission monitoring point at each time point of the gas pipeline to obtain the gas density reference value, airflow turbulence reference value, gas moisture content reference value, and airflow shear stress reference value at each time point of the gas pipeline; and compare the gas density reference value, airflow turbulence reference value, gas moisture content reference value, and airflow shear stress reference value at each time point of the gas pipeline with the gas density reference value, airflow turbulence reference value, gas moisture content reference value, and airflow shear stress reference value at each gas transmission monitoring point. The gas density values, airflow turbulence values, gas moisture content values, and airflow shear stress values ​​are analyzed for difference, and the gas density difference, airflow turbulence difference, gas moisture content difference, and airflow shear stress difference of each gas transmission monitoring point of the gas pipeline at each time point are obtained, and normalized in combination with the gas vortex index; based on the normalized gas density difference, airflow turbulence difference, gas moisture content difference, airflow shear stress difference, and gas vortex index of each gas transmission monitoring point of the gas pipeline at each time point, a comprehensive analysis is performed to obtain the push index of the gas 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: Among them, TsZ i is the pushing index of the gas pipeline at the i-th time point, QmD′ ia , QyL′ ia , QsH′ ia , QnL′ ia , QwL′ ia They are respectively the gas density difference, airflow turbulence difference, gas moisture content difference, airflow shear stress difference, and gas vortex index of the ath gas transmission monitoring point at the i-th time point of the gas pipeline after normalization. μ1, μ2, μ3, μ4, μ5, and μ6 are respectively the density coefficient, turbulence coefficient, gas moisture coefficient, shear stress coefficient, vortex coefficient, and interaction coefficient stored in the database. i=1, 2, 3, …, i0, where i0 is the number of time points. a=1, 2, 3, …, a0, where a0 is 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 comprehensive valve control index change rate of the intelligent pilot valve to be controlled is lower than the preset lower limit of the comprehensive valve control index change rate interval, take the first control measure; if the comprehensive valve control index change rate of the intelligent pilot valve to be controlled is within the preset comprehensive valve control index change rate interval, take the second control measure; if the comprehensive valve control index change rate of the intelligent pilot valve to be controlled is higher than the preset upper limit of the comprehensive valve control index change rate interval, take the third control measure.

[0015] A pneumatic ash conveying intelligent control system based on an intelligent pilot valve comprises: 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 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 respectively analyze the conveying timing data of the ash conveying pipe and the pushing timing data of the gas conveying pipe, obtain the comprehensive conveying index of the ash conveying pipe at each time point and the pushing index of the gas conveying pipe at each time point, and 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, 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 comprehensive valve control index change rate of the intelligent pilot valve to be controlled and a preset comprehensive valve control index change rate interval, 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 of pneumatic ash conveying based on the intelligent pilot valve collects the conveying timing data of the ash conveying pipeline and the pushing timing data of the air pipe in real time, and performs accurate dynamic analysis, so as to grasp the various changes in the conveying process in real time, adjust the conveying state according to the actual situation, and realize the dynamic optimization of the ash conveying process, thereby improving the conveying stability and overall ash conveying efficiency, thereby ensuring the long-term stable operation of the equipment, while reducing the downtime and related costs.

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

[0019] (3) The intelligent control method of pneumatic ash conveying based on the intelligent pilot valve can accurately control the working state of the valve by real-time collection and analysis of the timing data of conveying and pushing, so as to effectively avoid problems such as blockage during conveying, and can effectively reduce the power consumption and gas waste during pneumatic conveying, thereby improving the overall energy utilization efficiency, and then helping to achieve more environmentally friendly operations.

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

[0021] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0023] Figure 2 The present invention is a flowchart of the steps of obtaining the comprehensive conveying index of the ash conveying pipe at each time point in the intelligent control method of pneumatic ash conveying based on the intelligent pilot valve.

[0024] Figure 3 The present invention is a block diagram of an intelligent control system for pneumatic ash conveying based on an intelligent pilot valve. DETAILED DESCRIPTION

[0025] The overall idea of ​​the problem in the embodiment of this application is as follows:

[0026] When the material to be transported is transported 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 obtained in real time, and analyzed respectively to obtain the comprehensive conveying index of the ash conveying pipe at each time point 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, and then analysis is performed to obtain the comprehensive valve control index 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 judged and analyzed with the preset comprehensive valve control index change rate interval, and corresponding control measures are taken for the intelligent pilot valve based on the judgment and analysis results.

[0027] See also Figure 1, the embodiment of the present invention provides a technical solution: a pneumatic ash conveying intelligent control method based on an intelligent pilot valve, comprising 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 obtained in real time; the conveying timing data of the ash conveying pipe and the pushing timing data of the gas conveying pipe are respectively analyzed to obtain the comprehensive conveying index of the ash conveying pipe at each time point 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; and 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 judged and analyzed with a preset comprehensive valve control index change rate interval, 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: Among them, ZhB is the comprehensive valve control index change rate of the intelligent pilot valve to be controlled, FmK i+1 FmK is the valve control index of the intelligent pilot valve to be controlled at the i+1th time point, i is the valve control index of the intelligent pilot valve to be controlled at the i-th time point, i=1, 2, 3, ..., i0, where i0 is 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: Among them, FmK i is the valve control index of the intelligent pilot valve to be controlled at the i-th time point, SzH i is the comprehensive transport index of the ash conveying pipe at the i-th time point, α1 is the transport coefficient stored in the database, β1 is the transport adjustment coefficient stored in the database, TsZ i is the push index of the gas pipeline at the i-th time point, α2 is the push coefficient stored in the database, β2 is the push adjustment coefficient stored in the database, β3 is the interaction coefficient stored in the database, α1+α2=1, i=1, 2, 3, …, i0, i0 is the number of time points.

[0029] It needs to be explained that the β3*SzH in the formula i *TZ i The combined effect of the comprehensive conveying index of the ash conveying pipe at each time point and the pushing 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] α1 and α2 can be obtained through the following steps: read 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, perform mean analysis, perform sum analysis based on the mean analysis results to obtain the control sum value, and perform proportion analysis on the mean analysis results and the control sum value respectively, and use the proportion analysis results as the corresponding coefficients.

[0031] β1, β2, and β3 can be obtained through the following steps: first, obtain historical data and determine the initial influence weight of each variable on the valve control index through statistical regression analysis. Then, use the sensitivity analysis method to adjust the value range of the coefficient 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 algorithm) to ensure that the formula can accurately reflect the valve control of the actual intelligent pilot valve.

[0032] The specific implementation example of calculating the valve control index of the first time point of the intelligent pilot valve to be controlled is as follows, and the following data are available:

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

[0034] The push index of the gas pipeline at the first time point is approximately: 1.06.

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

[0036] The delivery 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 factor 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 of the valve control index at each time point of the intelligent pilot valve to be controlled, we can obtain:

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

[0042] The conveying timing data includes the conveying speed value, conveying flow 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 timing data includes the gas density value, airflow turbulence value, gas moisture content value, airflow shear stress value, and gas vortex index of each gas transmission monitoring point at each time point.

[0043] The conveying speed value is the speed value of the gas in the gas pipe and the material in the ash pipe combining together. It can be obtained through a flow rate sensor and is used to reflect the stability of conveying.

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

[0045] The material density value refers to the degree of compaction of the material and the compactness of the material composition. It can be obtained through a density sensor and is used to reflect the fluidity of the material.

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

[0047] The material agglomeration index is the degree of adhesion of material particles during the transportation process. The material temperature value and material humidity value are obtained, standardized, and weighted based on the standardized processing results to obtain the material agglomeration index. The material temperature value can be obtained through a temperature sensor, and the material humidity value can be obtained through a humidity sensor. The material agglomeration index is used to reflect the efficiency of transportation.

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

[0049] The airflow turbulence value is the degree of turbulence of the flowing gas, that is, the ratio of the velocity fluctuation value (that is, 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, and the velocity value of each point can be obtained through a thermal flow velocity sensor, which is used to reflect the stability of the gas.

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

[0051] The air flow shear stress value is a measure of the friction force inside the fluid, which can be obtained by a suspended force sensor and is used to reflect the fluidity of the gas.

[0052] The gas vortex index is the intensity and influence of the vortex in the gas flow. It is obtained by obtaining the flow rate, pressure and temperature values ​​of the ash conveying monitoring point, and standardized processing is performed. A weighted analysis is performed based on the standardized processing results. The weighted result is the gas vortex index, which is used to reflect the stability of the gas in the gas pipeline.

[0053] Specifically, Figure 2 As shown, the specific steps for obtaining the comprehensive conveying index of the ash conveying pipe at each time point are as follows: obtain the conveying speed reference value, conveying flow reference value, and material density reference value of the ash conveying pipe, and conduct a comprehensive analysis based on the conveying speed value, conveying flow value, and material density value of each ash conveying monitoring point at each time point to obtain the conveying stability index of the ash conveying pipe at each time point; and conduct a comprehensive analysis of 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 to obtain the conveying efficiency index of the ash conveying pipe at each time point; and conduct a comprehensive analysis of 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 formula for calculating the conveying stability index and comprehensive conveying index of the ash conveying pipe at each time point is as follows: Among them, SwD i is the transport stability index of the ash conveying pipe at the i-th time point, SdZ ij is the conveying speed value of the jth ash conveying monitoring point at the i-th time point of the ash conveying pipe, CsD is the conveying speed reference value of the ash conveying pipe, θ1 is the speed coefficient stored in the database, LsZ ij is the conveying flow value of the jth ash conveying monitoring point at the i-th time point of the ash conveying pipe, CsL is the conveying flow reference value of the ash conveying pipe, θ2 is the flow coefficient stored in the database, WmD ij is the material density value of the jth ash conveying monitoring point at the ith time point of the ash conveying pipe, CmD is the material density value of the ash conveying pipe, θ3 is the density coefficient stored in the database, SzH i is the comprehensive transport index of the ash conveying pipe at the i-th time point, η1 is the stability coefficient stored in the database, XsL i is the conveying efficiency index of the ash conveying pipe at the i-th time point, η2 is the efficiency coefficient stored in the database, η1+η2=1, i=1, 2, 3, …, i0, i0 is the number of time points, j=1, 2, 3, …, j0, j0 is the number of ash conveying monitoring points, e is a natural constant, and in this implementation example it takes a value of 2.71.

[0055] It should be explained that θ1, θ2, and θ3 can be obtained through the following steps: obtain the conveying speed value, conveying flow value, and material density reference value of each ash conveying monitoring point at each historical time point, conduct statistical regression analysis, and quantify the specific impact of each factor on the environmental correction, so as to fit the initial weight value. Secondly, use the sensitivity analysis method to adjust the value range of the corresponding coefficient to ensure the stability and rationality of the model, and based on the actual situation, correct and optimize the preliminary fitting coefficients to finally determine the corresponding coefficient values.

[0056] η1 and η2 can be obtained through the following steps: read the conveying stability index and conveying efficiency index of the ash conveying pipe at each time point (it should be noted here that the conveying stability index and conveying efficiency index are dimensionless values ​​and can be directly calculated), perform mean analysis, and perform sum analysis based on the mean analysis results to obtain the conveying sum value, perform proportion analysis on the mean analysis results and the conveying sum value, and use the proportion analysis results as the corresponding coefficients.

[0057] In this implementation scheme, by comprehensively considering multiple key factors such as conveying speed, flow rate, material density, material viscosity, agglomeration index, etc., the actual conveying status of the ash conveying pipe can be accurately reflected, so that the conveying process can be monitored and adjusted in real time in a dynamic environment, thereby ensuring the stability and efficiency of the conveying. Secondly, by calculating the conveying stability index in real time, the stability of the conveying process at each time point can be evaluated, and potential unstable factors can be discovered in time, which helps to prevent blockage or other failures in the ash conveying pipe, and adjust the conveying method in time, while ensuring continuous and stable operation.

[0058] By calculating the conveying efficiency index, this step can effectively evaluate the material conveying efficiency at each time point, including the fluidity, viscosity and agglomeration characteristics of the material. The optimization of the conveying efficiency index can reduce energy consumption, improve the accuracy and speed of material conveying, thereby reducing operating costs and improving the overall production efficiency of the system. The improvement of conveying efficiency means higher material conveying volume and lower energy consumption, which plays an important role in improving the productivity of the factory. Then, through regression analysis and sensitivity analysis of historical data, the impact of each influencing factor on the conveying process is quantified, so that the corresponding coefficients can be dynamically adjusted in actual operation, thereby ensuring the stability and rationality of the model, and can also be optimized in real time according to 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 the adaptability to different working conditions and further ensuring the smoothness and efficiency of the production process.

[0059] Specifically, the specific steps for obtaining the conveying efficiency index of the ash conveying pipe at each time point are as follows: standardize 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 (i.e., remove the unit) 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 comprehensively analyze 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 after the standardized processing 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: Among them, XsL i is the transport efficiency index of the ash conveying pipe at the i-th time point, WnD′ ij is the material viscosity value of the jth ash conveying monitoring point of the ash conveying pipe at the i-th time point after standardization, φ1 is the viscosity coefficient stored in the database, WtC′ ij is the material agglomeration index of the jth ash conveying monitoring point at the ith time point of the ash conveying pipe after standardization, φ2 is the agglomeration coefficient stored in the database, WcS′ ij is the material specific surface area value of the jth ash conveying monitoring point at the ith time point of the ash conveying pipe after standardized processing, φ3 is the sedimentation coefficient stored in the database, φ1+φ2+φ3=1, i=1, 2, 3, …, i0, i0 is the number of time points, j=1, 2, 3, …, j0, j0 is the number of ash conveying monitoring points.

[0061] It should be explained that φ1, φ2, and φ3 can be obtained through the following steps: read 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 standardized ash conveying pipe, perform mean analysis, and obtain the mean value of material viscosity, the mean value of material agglomeration degree, and the mean value of material sedimentation rate of the standardized ash conveying pipe, perform sum analysis to obtain the efficiency and value, and perform proportion analysis on the mean value of material viscosity, the mean value of material agglomeration degree, and the mean value of material sedimentation rate of the standardized ash conveying pipe respectively with the efficiency and value, and use the proportion analysis results as the corresponding coefficients.

[0062] In this implementation scheme, standardization is performed to eliminate the differences in units and dimensions of different material properties, so that various indicators can be compared and analyzed on the same scale, thereby improving the comparability of various data and avoiding calculation errors caused by different units, thereby making the final conveying efficiency index more accurate and reliable. Secondly, through a comprehensive analysis of multiple key factors such as material viscosity, agglomeration index and specific surface area, the conveying efficiency of the ash conveying pipe can be more comprehensively evaluated, so as to make a reasonable evaluation of the conveying efficiency under different working conditions, thereby helping the intelligent pilot valve to respond quickly under complex working conditions to ensure the maximization of the conveying efficiency. Finally, through mean analysis and proportion analysis, it is ensured that the conveying efficiency index can stably and accurately reflect the actual conveying effect under different operating conditions. Especially in a dynamic environment, the material properties during the conveying process will change. The proportion analysis can be used to adjust and optimize the conveying parameters according to the actual situation to further improve the conveying efficiency.

[0063] Specifically, the specific steps for obtaining the push 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 vortex index of each gas transmission monitoring point at each time point of the gas pipeline to obtain the gas density reference value, airflow turbulence reference value, gas moisture content reference value, and airflow shear stress reference value at each time point of the gas pipeline; and compare the gas density reference value, airflow turbulence reference value, gas moisture content reference value, and airflow shear stress reference value at each time point of the gas pipeline with the gas density reference value, airflow turbulence reference value, gas moisture content reference value, and airflow shear stress reference value of each gas transmission monitoring point. The difference analysis is performed on the values, airflow turbulence values, gas moisture content values, and airflow shear stress values ​​to obtain the gas density difference, airflow turbulence difference, gas moisture content difference, and airflow shear stress difference of each gas transmission monitoring point of the gas pipeline at each time point, and normalization is performed (i.e., unit removal) in combination with the gas vortex index; a comprehensive analysis is performed on the gas density difference, airflow turbulence difference, gas moisture content difference, airflow shear stress difference, and gas vortex index of each gas transmission monitoring point of the gas pipeline at each time point after the normalization to obtain the push index of the gas pipeline at each time point.

[0064] It is characterized in that the specific formula for calculating the push index of the gas pipeline at each time point is as follows: Among them, TsZ i is the pushing index of the gas pipeline at the i-th time point, QmD′ ia is the gas density difference of the a-th gas transmission monitoring point at the i-th time point in the gas transmission pipeline after normalization, QyL′ ia QsH′ is the normalized difference in airflow turbulence at the a-th gas transmission monitoring point at the i-th time point in the gas transmission pipeline. iais the gas moisture content difference of the a-th gas transmission monitoring point at the i-th time point in the gas transmission pipeline after normalization, QnL′ ia is the normalized shear stress difference of the a-th gas transmission monitoring point at the i-th time point in the gas transmission pipeline, QwL′ ia are the gas density difference, airflow turbulence difference, gas moisture content difference, airflow shear stress difference, and gas vortex index of the ath gas transmission monitoring point at the ith time point of the gas pipeline after normalization, μ1 is the density coefficient stored in the database, μ2 is the turbulence coefficient stored in the database, μ3 is the gas moisture coefficient stored in the database, μ4 is the shear stress coefficient stored in the database, μ5 is the vortex coefficient stored in the database, μ is the interaction coefficient stored in the database, i=1, 2, 3,…, i0, i0 is the number of time points, a=1, 2, 3,…, a0, a0 is the number of gas transmission monitoring points.

[0065] It needs to be explained that μ6*QmD′ in the formula ij *QyL′ ij *QsH′ ij *QnL′ ij *QwL′ ij It is used for the normalized gas density difference, airflow turbulence difference, gas moisture content difference, airflow shear stress difference, and gas vortex index superposition effect to prevent the push index from being too high or too low.

[0066] μ1, μ2, μ3, μ4, μ5, and μ6 can be obtained through the following steps: obtain the gas density value, airflow turbulence value, gas moisture content value, airflow shear stress value, gas vortex index, and interaction product (i.e., the product of gas density value, airflow turbulence value, gas moisture content value, airflow shear stress value, and gas vortex index) of each gas transmission monitoring point at each historical time point, perform statistical regression analysis, quantify the specific impact of each factor on the push index, and thus fit the initial weight value. Secondly, use the sensitivity analysis method to adjust the value range of the corresponding coefficient to ensure the stability and rationality of the model, and based on the actual situation, correct and optimize the preliminary fitting coefficients to finally determine the corresponding coefficient values.

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

[0068] Specifically, 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 comprehensive valve control index change rate of the intelligent pilot valve to be controlled is lower than the preset lower limit of the comprehensive valve control index change rate interval (i.e., the minimum value of the comprehensive valve control index change rate interval), then take the first control measure (i.e., increase the valve opening, and increase the airflow push amount to increase the delivery flow rate and prevent poor delivery or blockage); if the comprehensive valve control index change rate of the intelligent pilot valve to be controlled is within the preset comprehensive valve control index change rate interval, then take the second control measure (i.e., maintain the existing valve opening); if the comprehensive valve control index change rate of the intelligent pilot valve to be controlled is higher than the preset upper limit of the comprehensive valve control index change rate interval (i.e., the maximum value of the comprehensive valve control index change rate interval), then take the third control measure (i.e., reduce the valve opening, and reduce the airflow push amount 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 push volume in real time, it is possible to maintain stable operation under different working conditions, avoid problems such as unstable airflow, poor material flow or blockage, thereby ensuring the reliability of the conveying system and reducing the possibility of failure. Secondly, by accurately 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 intervals, the valve state is adaptively adjusted to avoid the lag of manual intervention, improve the response speed, and ensure rapid adaptation and adjustment under different environments and working conditions. By setting different control measures, it is possible to flexibly respond to different working conditions and meet different conveying needs, thereby enabling the intelligent pilot valve to adapt to changing working environments and material conveying requirements.

[0070] See also Figure 3 The embodiment of the present 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 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 timing data of the ash conveying pipe and the pushing timing data of the gas conveying pipe respectively, to obtain the comprehensive conveying index of the ash conveying pipe at each time point 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 and the preset comprehensive valve control index change rate interval, and 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 the conveying timing data of the ash conveying pipeline and the pushing timing data of the gas pipe in real time and conducting precise dynamic analysis, we can grasp the various changes in the conveying process in real time, adjust the conveying status according to the actual situation, and realize the dynamic optimization of the ash conveying process, thereby improving the conveying stability and overall ash conveying efficiency, thereby ensuring the long-term stable operation of the equipment, while reducing downtime and related costs.

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

[0074] By collecting and analyzing the timing data of delivery and pushing in real time, the working status of the valve can be accurately controlled, so as to effectively avoid problems such as blockage during delivery, and can effectively reduce the power consumption and gas waste during pneumatic conveying, thereby improving the overall energy utilization efficiency, and then helping to achieve more environmentally friendly operations.

[0075] By acquiring the conveying and pushing timing data of the ash conveying pipe and the gas conveying pipe in real time, and using the data analysis module to perform precise time point data processing, a rapid response to the intelligent pilot valve can be 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 shorter time. This can effectively reduce the risk of loss of control or reduced efficiency of the ash conveying pipe in the face of a rapidly changing conveying environment, thereby improving the real-time adaptability and accuracy of the conveying process.

[0076] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0077] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. An intelligent control method for pneumatic ash conveying based on an intelligent pilot valve, characterized in that: The following steps are involved: When the material to be transported is transported in the ash conveying pipe, the transport timing data of the ash conveying pipe and the push timing data of the gas conveying pipe are obtained in real time; The conveying time series data of the ash conveying pipe and the pushing time series data of the gas conveying pipe are analyzed respectively to obtain the comprehensive conveying index of the ash conveying pipe at each time point 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; A comprehensive analysis is performed 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 comprehensive valve control index change rate of the intelligent pilot valve to be controlled is judged and analyzed with respect to the preset comprehensive valve control index change rate interval, and corresponding control measures are taken for the intelligent pilot valve based on the judgment and analysis results.

2. The intelligent control method for pneumatic ash conveying based on an intelligent pilot valve according to claim 1 is characterized in that: The conveying timing data includes the conveying speed value, conveying flow 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, and the pushing timing data includes the gas density value, airflow turbulence value, gas moisture content value, airflow shear stress value, and gas vortex index of each gas transmission monitoring point at each time point.

3. The intelligent control method for pneumatic ash conveying based on intelligent pilot valve according to claim 1 is characterized in that: The specific formula for calculating the valve control index at each time point of the intelligent pilot valve to be controlled is as follows: Among them, FmK i is the valve control index of the intelligent pilot valve to be controlled at the i-th time point, SzH i is the comprehensive transport index of the ash conveying pipe at the i-th time point, α1 is the transport coefficient stored in the database, β1 is the transport adjustment coefficient stored in the database, TsZ i is the push index of the gas pipeline at the i-th time point, α2 is the push coefficient stored in the database, β2 is the push adjustment coefficient stored in the database, β3 is the interaction coefficient stored in the database, α1+α2=1, i=1,2,3,…,i0, i0 is the number of time points.

4. The intelligent control method for pneumatic ash conveying based on an intelligent pilot valve according to claim 2 is characterized in that: The specific steps to obtain the comprehensive transport index of the ash conveying pipe at each time point are as follows: Obtain the reference value of the conveying speed, conveying flow rate and material density of the ash conveying pipe, and conduct a comprehensive analysis based on the conveying speed value, conveying flow rate value and material density value of each ash conveying monitoring point at each time point to obtain the conveying stability index of the ash conveying pipe at each time point; A comprehensive analysis is performed on 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 to obtain the conveying efficiency index of the ash conveying pipe at each time point; A comprehensive analysis is conducted on the conveying stability index and conveying efficiency index of the ash conveying pipe at each time point to obtain a comprehensive conveying index of the ash conveying pipe at each time point.

5. The intelligent control method for pneumatic ash conveying based on intelligent pilot valve according to claim 4 is characterized in that: The specific steps to obtain the conveying efficiency index of the ash conveying pipe at each time point are as follows: Standardize 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 to obtain 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 after the standardized processing; A comprehensive analysis is performed on the material viscosity value, material agglomeration index and material specific surface area value of each ash conveying monitoring point of the standardized ash conveying pipe at each time point to obtain the conveying efficiency index of the ash conveying pipe at each time point.

6. The intelligent control method for pneumatic ash conveying based on intelligent pilot valve according to claim 4 is characterized in that: The specific formula for calculating the conveying stability index and comprehensive conveying index of the ash conveying pipe at each time point is as follows: Among them, SwD i is the transport stability index of the ash conveying pipe at the i-th time point, SdZ ij is the conveying speed value of the jth ash conveying monitoring point at the i-th time point of the ash conveying pipe, CsD is the conveying speed reference value of the ash conveying pipe, θ1 is the speed coefficient stored in the database, LsZ ij is the conveying flow value of the jth ash conveying monitoring point at the i-th time point of the ash conveying pipe, CsL is the conveying flow reference value of the ash conveying pipe, θ2 is the flow coefficient stored in the database, WmD ij is the material density value of the jth ash conveying monitoring point at the ith time point of the ash conveying pipe, CmD is the material density value of the ash conveying pipe, θ3 is the density coefficient stored in the database, SzH i is the comprehensive transport index of the ash conveying pipe at the i-th time point, η1 is the stability coefficient stored in the database, XsL i is the transport efficiency index of the ash conveying pipe at the i-th time point, η2 is the efficiency coefficient stored in the database, η1+η2=1, i=1, 2, 3, …, i0, i0 is the number of time points, j=1, 2, 3, …, j0, j0 is the number of ash conveying monitoring points, and e is a natural constant.

7. The intelligent control method for pneumatic ash conveying based on an intelligent pilot valve according to claim 2 is characterized in that: The specific steps to obtain the push 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 vortex index of each gas transmission monitoring point at each time point in the gas transmission pipeline to obtain the reference value of gas density, airflow turbulence reference value, gas moisture content reference value, and airflow shear stress reference value at each time point in the gas transmission pipeline; The gas density reference value, airflow turbulence reference value, gas moisture content reference value, and airflow shear stress reference value at each time point of the gas pipeline are subjected to difference analysis with the gas density value, airflow turbulence value, gas moisture content value, and airflow shear stress value of each gas transmission monitoring point, so as to obtain the gas density difference, airflow turbulence difference, gas moisture content difference, and airflow shear stress difference of each gas transmission monitoring point at each time point of the gas pipeline, and normalize them in combination with the gas vortex index; Based on the normalized gas density difference, airflow turbulence difference, gas moisture content difference, airflow shear stress difference and gas vortex index of each gas transmission monitoring point 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.

8. The intelligent control method for pneumatic ash conveying based on an intelligent pilot valve according to claim 7 is characterized in that: The specific formula for calculating the push index of the gas pipeline at each time point is as follows: Among them, TsZ i is the pushing index of the gas pipeline at the i-th time point, QmD′ ia , QyL′ ia , QsH′ ia , QnL′ ia , QwL′ ia They are respectively the gas density difference, airflow turbulence difference, gas moisture content difference, airflow shear stress difference, and gas vortex index of the ath gas transmission monitoring point at the i-th time point of the gas pipeline after normalization. μ1, μ2, μ3, μ4, μ5, and μ6 are respectively the density coefficient, turbulence coefficient, gas moisture coefficient, shear stress coefficient, vortex coefficient, and interaction coefficient stored in the database. i=1, 2, 3, …, i0, where i0 is the number of time points. a=1, 2, 3, …, a0, where a0 is the number of gas transmission monitoring points.

9. The intelligent control method for pneumatic ash conveying based on intelligent pilot valve according to claim 1 is 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 comprehensive valve control index change rate of the intelligent pilot valve to be controlled is lower than the preset comprehensive valve control index change rate interval lower limit, the first control measure is taken; If the comprehensive valve control index change rate of the intelligent pilot valve to be controlled is within the preset comprehensive valve control index change rate range, the second control measure is adopted; If the comprehensive valve control index change rate of the intelligent pilot valve to be controlled is higher than the preset comprehensive valve control index change rate interval upper limit, the third control measure is taken.

10. An intelligent control system for pneumatic ash conveying based on an intelligent pilot valve, applying the intelligent control method for pneumatic ash conveying based on an intelligent pilot valve according to any one of claims 1 to 9, characterized in that: include: Data acquisition module, data analysis module, comprehensive analysis module, control 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 analyze the conveying time series data of the ash conveying pipe and the pushing time series data of the gas conveying pipe respectively, obtain the comprehensive conveying index of the ash conveying pipe at each time point and the pushing index of the gas conveying pipe at each time point, and 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 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 and the preset comprehensive valve control index change rate interval, and take corresponding control measures for the intelligent pilot valve based on the judgment and analysis results.

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