An ash conveying control optimization system for power plants

Abstract

The present invention discloses a power plant ash conveying control optimization system, which relates to the field of ash conveying control technology. The power plant ash conveying control optimization system includes a data acquisition module for acquiring power plant ash conveying status data in real time and performing preprocessing, an efficiency analysis module for analyzing the preprocessed power plant ash conveying status data to obtain a power plant ash conveying efficiency correction index, a judgment analysis module for judging whether the power plant ash conveying efficiency correction index is within a preset correction interval, and a control adjustment module for analyzing the ash conveying adjustment flow rate value and ash conveying adjustment pressure value of the conveying gas in the power plant ash conveying pipeline and performing control adjustment when the power plant ash conveying efficiency correction index is lower than the preset correction interval lower limit. The present invention can accurately calculate the power plant ash conveying efficiency correction index by analyzing various key parameters in the ash conveying system. When the index is lower than the preset correction interval, the flow rate and pressure value of the conveying gas are automatically adjusted to ensure the conveying efficiency of the airflow and dust.

Description

Technical Field

[0001] The present invention relates to the technical field of ash conveying control, and in particular to an ash conveying control optimization system for a power plant. Background Art

[0002] The ash conveying system of a power plant uses compressed air to transport dust generated by boilers and electrostatic precipitators through pipes to an ash storage or transfer bin. This process plays a vital role in the daily operation of a power plant. However, traditional ash conveying systems often face problems such as energy waste, system instability, and equipment wear during operation, which affects the overall ash conveying efficiency and the operating costs of the power plant.

[0003] Traditional ash conveying control systems, lacking precise flow and pressure regulation mechanisms, typically require a large margin in compressed air supply. This is especially true during the conveying process, where the air flow rate and pressure don't always match the actual dust conveying requirements, leading to significant compressed air waste. Excessive compressed air, especially at low loads or when the dust load is light, not only increases energy consumption but also worsens wear on ash conveying pipes and equipment.

[0004] Factors such as the physical properties of dust, the stability of airflow, and the roughness of the inner surface of the pipe will all affect the conveying efficiency. The size, shape, and density of dust particles will determine their behavior in the airflow. If the flow rate is inappropriate, dust will easily settle in the pipe, causing blockage and conveying interruption. The conveying parameters in existing systems are usually set to fixed values, which are difficult to dynamically adjust according to the real-time dust characteristics and airflow status, resulting in dust deposition and system failure during the conveying process.

[0005] Traditional ash conveying systems have limitations in flow rate regulation. There is a lack of an effective coordination mechanism between the flow rate of the airflow and the adhesion of dust. Excessively high flow rates will cause pipe wear and increase the waste of compressed air; while too low flow rates will cause dust particles to settle in the pipes, affecting the conveying effect. Due to the lack of precise regulation of flow rate and airflow, the ash conveying system often finds it difficult to maintain optimal working conditions under different load conditions, reducing the efficiency of the entire conveying process.

[0006] The adjustment of traditional ash conveying control systems relies on manually set or preset control rules, and the system's automation and intelligence levels are low. Although some modern systems have begun to adopt sensors and feedback mechanisms, due to the lack of integrated comprehensive analysis and real-time optimization and adjustment functions, it is still difficult to accurately adjust the system according to actual working conditions and dust characteristics, which can easily lead to slow system response and difficulty in real-time adaptation to complex working conditions.

[0007] Therefore, in the existing technology, although the ash conveying system has a certain degree of automatic control capability, it is often difficult to achieve the best ash conveying efficiency and energy utilization efficiency due to the lack of precise control in the system in terms of airflow regulation, dust conveying stability, compressed air energy saving, etc.

[0008] The prior art, such as the invention patent application with announcement number: CN111596632B, discloses an ash conveying control optimization system for a coal-fired power plant. The system is based on the existing ash conveying control system of the coal-fired power plant, and collects the pressure in the compressed air pipeline in the ash conveying system through an analog input module and transmits it to the main controller; collects the operating status of each valve and motor in the ash conveying system through a digital input module and transmits it to the main controller; the main controller sets the initial working parameters and ash conveying cycle time of the ash conveying system on the basis of realizing ash conveying control by the original ash conveying control system, starts automatic ash conveying, and obtains the pressure in the compressed air pipeline, the unit load and the pressure residence time, and then calculates the new ash conveying cycle time of the ash conveying system, and generates a control instruction to transmit to the digital output module; the digital output module indirectly controls the motor and valve in the ash conveying system by controlling the action of the intermediate relay, thereby reducing the supply margin of compressed air, avoiding waste of compressed air, and realizing optimized control of ash conveying.

[0009] Based on the above scheme, it is found that the limitations of the existing technology include at least the following problems. First, the existing technical scheme mainly relies on the periodic and manual control of the compressed air system, and the degree of automation of the ash conveying process is low. In particular, when controlling the air supply margin of the air compressor, it is difficult to flexibly adjust in real time according to the changes in the dust conveying volume or airflow, which easily leads to excessive supply of compressed air, resulting in waste, and uneven airflow speed is prone to occur during the conveying process, which increases pipeline wear, thereby increasing the maintenance cost and downtime of the system, thereby affecting the overall economic benefits. Secondly, the control system in the existing technology is difficult to accurately adjust the flow and pressure according to the real-time ash conveying status data. Although the existing system can adjust the ash conveying cycle based on certain parameters, it does not take into account the comprehensive influence of multiple dynamic parameters such as the adhesion of the conveyed dust, dust stability and flow field efficiency. Therefore, in actual operation, it is easy to lead to low ash conveying efficiency under different conditions, especially when the airflow is unstable or the dust particles are heavy, making it difficult to ensure an efficient and continuous ash conveying process. Summary of the Invention

[0010] In view of the shortcomings of the existing technology, the present invention provides a power plant ash conveying control optimization system, which solves the problems of compressed air waste, unstable ash conveying flow rate, and difficulty in real-time adjustment of the system in the existing technology.

[0011] To achieve the above objectives, the present invention is implemented through the following technical solutions: a power plant ash conveying control optimization system, comprising: a data acquisition module, an efficiency analysis module, a judgment analysis module, and a control adjustment module; the data acquisition module is used to acquire the power plant ash conveying status data in real time and perform preprocessing; the efficiency analysis module is used to perform a comprehensive analysis on the preprocessed power plant ash conveying status data to obtain the power plant conveying dust adhesion index, the power plant conveying dust stability index, and the power plant flow field efficiency index, and perform a comprehensive analysis to obtain the power plant ash conveying efficiency correction index; the judgment analysis module is used to determine whether the power plant ash conveying efficiency correction index is within a preset correction interval; the control adjustment module is used to analyze the ash conveying adjustment flow rate value and ash conveying adjustment pressure value of the conveying gas in the power plant ash conveying pipeline when the power plant ash conveying efficiency correction index is lower than the preset lower limit of the correction interval, and perform control adjustment; wherein, the specific formula for calculating the power plant ash conveying efficiency correction index is as follows: ;in, is the power plant ash transport efficiency correction index, Delivering dust stability index to power plants, is the power plant flow field efficiency index, Delivering dust adhesion index to power plants, It is the dust density value of the ash conveying pipeline in the power plant.

[0012] Furthermore, the power plant ash transportation status data includes the pipeline surface roughness value, pipeline diameter value, conveying gas secondary flow value, conveying gas viscosity value, conveying gas flow rate value, and conveying dust density value of the power plant ash transportation pipeline.

[0013] Furthermore, the specific steps for obtaining the power plant dust transportation stability index are as follows: obtaining the dynamic morphological factor of the dust transported in the power plant ash conveying pipeline; reading the power plant dust transportation adhesion index, and combining the secondary flow value of the conveying gas in the power plant ash conveying pipeline, the conveying gas flow rate value, the conveying dust density value and the dynamic morphological factor of the dust transported in the power plant ash conveying pipeline for comprehensive analysis to obtain the power plant dust transportation stability index.

[0014] Furthermore, the specific formula for calculating the power plant dust transport stability index is as follows: ;in, Delivering dust stability index to power plants, The dynamic shape factor of dust transported in the ash conveying pipeline of the power plant, is the conveying gas velocity value of the power plant ash conveying pipeline, is the secondary flow rate of the conveying gas in the power plant ash conveying pipeline, is the dust density value of the power plant ash conveying pipeline, Delivering dust adhesion index to power plants.

[0015] Furthermore, the specific steps for obtaining the power plant flow field efficiency index are as follows: reading the transport gas viscosity value and the transport dust density value of the power plant ash conveying pipeline, and analyzing the transport gas kinematic viscosity value of the power plant ash conveying pipeline; reading the power plant transport dust adhesion index, and performing a comprehensive analysis based on the transport gas flow rate value, transport dust density value, and transport gas kinematic viscosity value of the power plant ash conveying pipeline to obtain the power plant flow field efficiency index.

[0016] Furthermore, the specific formula for calculating the power plant flow field efficiency index is as follows: ;in, is the power plant flow field efficiency index, is the conveying gas velocity value of the power plant ash conveying pipeline, is the kinematic viscosity of the gas transported in the power plant's ash transport pipeline. is the velocity viscosity influence coefficient stored in the database, Delivering dust adhesion index to power plants, It is the dust density value of the ash conveying pipeline in the power plant.

[0017] Furthermore, the specific steps for obtaining the power plant dust adhesion index are as follows: reading the pipe surface roughness value and pipe diameter value of the power plant ash conveying pipeline, and analyzing the power plant ash conveying pipeline adhesion influencing factor; combining the power plant ash conveying pipeline adhesion influencing factor with the power plant ash conveying pipeline secondary flow value and conveying gas viscosity value for comprehensive analysis to obtain the power plant dust adhesion index.

[0018] Furthermore, the specific formulas for calculating the adhesion influencing factor of the power plant ash conveying pipeline and the power plant conveying dust adhesion index are as follows: ;in, is the influencing factor of ash conveying pipeline adhesion in power plants, is the surface roughness value of the ash conveying pipeline in the power plant, is the pipeline surface roughness influence coefficient stored in the database, is the pipe surface roughness weight coefficient stored in the database, is the diameter of the ash conveying pipeline in the power plant, is the pipe diameter influence coefficient stored in the database, is the pipe diameter weight coefficient stored in the database, , Delivering dust adhesion index to power plants, is the secondary flow rate of the conveying gas in the power plant ash conveying pipeline, It is the viscosity of the transport gas in the ash conveying pipeline of the power plant.

[0019] Furthermore, the specific steps for analyzing the ash transport adjustment flow rate value and the ash transport adjustment pressure value of the conveying gas in the power plant ash conveying pipeline are as follows: read the power plant ash transport efficiency correction index, and conduct a comprehensive analysis based on the power plant dust transport adhesion index, the conveying dust density value of the power plant ash conveying pipeline, the secondary flow value of the conveying gas in the power plant ash conveying pipeline, and the conveying gas viscosity value to obtain the ash transport adjustment flow rate value of the conveying gas in the power plant ash conveying pipeline; conduct a comprehensive analysis based on the conveying gas viscosity value of the power plant ash conveying pipeline, the power plant ash transport efficiency correction index and the ash transport adjustment flow rate value of the conveying gas in the power plant ash conveying pipeline to obtain the ash transport adjustment pressure value of the conveying gas in the power plant ash conveying pipeline.

[0020] Furthermore, the specific formulas for calculating the ash delivery adjustment flow rate and ash delivery adjustment pressure of the transport gas in the power plant ash delivery pipeline are as follows: ;in, Adjust the flow rate value for the ash conveying gas in the ash conveying pipeline of the power plant, is the power plant ash transport efficiency correction index, Delivering dust adhesion index to power plants, is the dust density value of the power plant ash conveying pipeline, is the secondary flow rate of the conveying gas in the power plant ash conveying pipeline, is the viscosity of the transport gas in the power plant's ash transport pipeline, Adjust the pressure value for ash conveying of gas in ash conveying pipeline of power plant.

[0021] The present invention has the following beneficial effects:

[0022] (1) The power plant ash conveying control optimization system can accurately calculate the power plant ash conveying efficiency correction index by acquiring and analyzing various key parameters in the ash conveying system in real time, such as pipeline surface roughness, pipeline diameter, conveying gas flow rate and secondary flow rate, etc., combined with the conveying dust adhesion index, dust stability index and flow field efficiency index. When the index is lower than the preset correction range, the system automatically adjusts the conveying gas flow rate and pressure value to ensure the conveying efficiency of airflow and dust. Through this precise adjustment, excessive or insufficient airflow is avoided, energy waste is reduced, and system operation efficiency is improved. For example, when the dust adhesion is strong, the system will automatically reduce the flow rate to prevent dust from depositing in the pipeline, thereby improving the overall conveying efficiency and saving energy.

[0023] (2) The power plant's ash conveying control optimization system can flexibly adjust the compressed air supply according to the ash conveying status and dust characteristics by adjusting the ash conveying flow rate and pressure in real time. In the existing technology, since the system is difficult to accurately adjust the airflow, it is often necessary to maintain a large compressed air supply margin to ensure the smooth transportation of dust. The system avoids this excessive air supply phenomenon by calculating the correction index, reducing the waste of compressed air, thereby effectively reducing the energy consumption and operating costs of the power plant. In actual application, this energy-saving effect is particularly obvious in periods when the dust load is low or the airflow pressure demand is small, which can greatly reduce the overall operating costs of the power plant.

[0024] (3) The power plant's ash conveying control optimization system, during the ash conveying process, excessive air flow velocity and excessive pressure will not only lead to waste of compressed air, but may also cause excessive wear on pipelines and related equipment, increasing the frequency and cost of system maintenance. Through the precise control in this system, when it detects that the air flow velocity in the pipeline is too fast or the pressure is too high, the system will automatically adjust these parameters to prevent pipeline wear and equipment damage caused by excessive air flow. Specifically, the flow rate control can prevent excessive air flow from generating excessive friction on the ash conveying pipeline and equipment, reduce downtime and maintenance costs caused by wear, and thus extend the service life of the ash conveying system equipment.

[0025] 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

[0026] Figure 1 This is a block diagram of a power plant ash conveying control optimization system according to the present invention.

[0027] Figure 2 The present invention is a flowchart of the specific steps for obtaining the power plant flow field efficiency index in a power plant ash conveying control optimization system.

[0028] Figure 3 This is a flowchart of the specific steps for analyzing the ash conveying adjustment flow rate value and ash conveying adjustment pressure value of the conveying gas in the power plant ash conveying pipeline in a power plant ash conveying control optimization system of the present invention. DETAILED DESCRIPTION

[0029] The overall approach to the problems in the embodiments of this application is as follows:

[0030] The data acquisition module collects the power plant's ash conveying status data in real time, including key parameters such as pipeline surface roughness, pipeline diameter, conveying gas flow rate, gas viscosity, secondary flow rate and dust density. All data will be preprocessed to provide a basis for subsequent analysis. Next, in the efficiency analysis module, these preprocessed data are comprehensively analyzed to obtain the power plant's conveying dust adhesion index, dust stability index and flow field efficiency index. Then, these indices will be further combined to calculate the power plant's ash conveying efficiency correction index. Finally, the judgment analysis module will determine whether the power plant's ash conveying efficiency correction index is in the preset correction range. If it is lower than the lower limit, the control adjustment module will adjust the conveying gas flow rate and pressure value according to the comprehensive analysis results to optimize the ash conveying process and achieve efficient conveying.

[0031] See also Figure 1 The embodiment of the present invention provides a technical solution: a power plant ash conveying control optimization system, including: a data acquisition module, an efficiency analysis module, a judgment analysis module, and a control adjustment module; the data acquisition module is used to acquire the power plant ash conveying status data in real time and perform preprocessing; the efficiency analysis module is used to perform a comprehensive analysis on the preprocessed power plant ash conveying status data to obtain the power plant conveying dust adhesion index, the power plant conveying dust stability index, and the power plant flow field efficiency index (referring to the degree of influence of the flow field on airflow and dust conveying), and perform a comprehensive analysis to obtain the power plant ash conveying efficiency correction index; the judgment analysis module is used to judge whether the power plant ash conveying efficiency correction index is within a preset correction range; the control adjustment module is used to analyze the ash conveying adjustment flow rate value and ash conveying adjustment pressure value of the conveying gas in the power plant ash conveying pipeline when the power plant ash conveying efficiency correction index is lower than the preset correction range lower limit, and perform control adjustment.

[0032] The specific formula for calculating the power plant ash handling efficiency correction index is as follows: ;in, is the power plant ash transport efficiency correction index, Delivering dust stability index to power plants, is the power plant flow field efficiency index, The dust adhesion index of the power plant (i.e. the adhesion index between the dust and the ash conveying pipeline) It is the dust density value of the ash conveying pipeline in the power plant.

[0033] The power plant ash transportation status data includes the pipeline surface roughness value, pipeline diameter value, conveying gas secondary flow value, conveying gas viscosity value, conveying gas flow rate value, and conveying dust density value of the power plant ash transportation pipeline.

[0034] Among them, the surface roughness value of the ash conveying pipeline of the power plant can be obtained through actual measurement or using standardized pipeline surface roughness data. The measurement usually adopts laser scanning, surface roughness measuring instruments and other equipment, or refers to the pipeline specifications and material data provided by the pipeline manufacturer. It is an important factor affecting fluid flow. The rougher the inner wall of the pipeline will increase the friction resistance of the airflow, which is likely to cause airflow turbulence and affect the dust conveying efficiency. Lower roughness can reduce energy loss and dust deposition, thereby improving the conveying efficiency.

[0035] The diameter of the power plant's ash conveying pipeline can be obtained by consulting the pipeline's design drawings or directly measuring the pipeline's diameter. It directly affects the airflow velocity, pressure loss, and flow characteristics of the fluid. A larger pipeline diameter can reduce airflow resistance and increase airflow velocity, thereby helping dust to be transported more easily. However, the pipeline diameter also needs to be matched with other parameters (such as flow velocity, fluid density, etc.) to ensure optimal conveying efficiency.

[0036] The secondary flow rate of the conveying gas in the power plant's ash conveying pipeline can be measured and calculated through flow meters, pressure sensors and flow field simulation. By actually monitoring the changes in the airflow in the pipeline, especially the secondary flow patterns such as vortex and backflow, it reflects the vortex or irregular flow in the fluid, which will affect the stability of the airflow. A larger secondary flow rate can easily lead to airflow instability, thereby affecting the dust conveying effect. Controlling the secondary flow rate can help optimize the stability of the airflow, thereby improving the conveying efficiency.

[0037] The viscosity of the conveying gas in the power plant's ash conveying pipeline can be measured experimentally or found in fluid mechanics literature. For common gases (such as air, steam, etc.), standard physical constants and formulas can be used to calculate or find the viscosity value by considering the influence of temperature and pressure. It is a key parameter that describes the internal friction resistance of the airflow. Higher viscosity usually means greater flow resistance, which can easily affect the flow rate and conveying effect of the airflow. By measuring and controlling the viscosity of the conveying gas, the fluidity of the airflow can be optimized and the conveying efficiency can be improved.

[0038] The conveying gas velocity value of the power plant's ash conveying pipeline can be measured in real time using devices such as flow meters, pitot tubes, and hot-wire anemometers. In addition, the flow velocity can also be indirectly calculated through the relationship between the flow rate and the cross-sectional area of ​​the pipeline. It is a key factor affecting the airflow carrying dust particles. A higher flow velocity helps to better suspend and transport dust particles and prevent deposition; however, excessively high flow velocity can easily lead to unstable airflow and energy waste. Therefore, the flow velocity needs to be precisely controlled according to system requirements to ensure the best conveying effect.

[0039] The dust density value of the power plant ash conveying pipeline can be measured experimentally by dust samples (for example, using a densitometer) or estimated based on the composition and physical properties of the dust. Different types of dust have different densities and need to be measured or referenced based on actual conditions. It determines its sedimentation and suspension properties in the fluid. Higher density may cause dust to easily settle in the pipeline, affecting the conveying efficiency; while lower density makes it easier for dust to suspend in the airflow. Therefore, accurately understanding and controlling dust density is crucial to optimizing the conveying system.

[0040] Specifically, the specific steps for obtaining the power plant dust transportation stability index are as follows: obtain the dynamic morphological factor of the dust transported in the power plant ash transportation pipeline; read the power plant dust transportation adhesion index, and conduct a comprehensive analysis based on the secondary flow value of the transportation gas, the transportation gas flow rate value, the transportation dust density value and the dynamic morphological factor of the transportation dust in the power plant ash transportation pipeline to obtain the power plant dust transportation stability index.

[0041] The specific steps for obtaining the dynamic shape factor of dust transported in the ash conveying pipeline of the power plant are as follows:

[0042] First, determine the physical characteristics of the dust particles, including:

[0043] Particle size: This refers to the diameter of dust particles, usually described by particle size distribution. The size of dust particles has a significant impact on their movement in airflow;

[0044] Particle shape: The shape of dust particles affects their trajectory in the airflow. Non-spherical particles (i.e., irregularly shaped particles) often affect the stability and efficiency of the flow.

[0045] Particle density: The density of dust particles affects their suspension and transport in the fluid;

[0046] Secondly, analyze the characteristics of the conveying airflow (the flow state of the fluid, such as laminar flow or turbulent flow, will affect the movement of dust particles), including:

[0047] Flow rate: The speed of the air flow is an important factor affecting whether dust particles can be transported. When the flow rate is low, the particles are easy to settle; when the flow rate is high, the particles are easy to suspend;

[0048] Fluid viscosity: The viscosity of the fluid determines the stability of the airflow and its ability to carry dust;

[0049] Flow field stability: Secondary flows such as eddies and backflows in the flow field affect the stability of dust particles;

[0050] Then, consider the surface characteristics of the pipe, including the roughness of the inner wall of the pipe and the diameter of the pipe, which will also affect the movement of dust particles. A rougher inner wall of the pipe will increase the probability of dust deposition.

[0051] Finally, the dynamic shape factor (a parameter that comprehensively considers the physical properties of dust particles, flow field characteristics, and pipe surface characteristics, and affects the stability of dust particles in the fluid) is calculated by combining the above factors: ;in, The dynamic shape factor of dust transported in the ash conveying pipeline of the power plant, is the dust density value of the power plant ash conveying pipeline, is the conveying gas velocity value of the power plant ash conveying pipeline, is the secondary flow rate of the conveying gas in the power plant ash conveying pipeline, Delivering dust adhesion index to power plants.

[0052] The specific formula for calculating the power plant conveying dust stability index is as follows: ;in, Delivering dust stability index to power plants, The dynamic shape factor of dust transported in the ash conveying pipeline of the power plant, is the conveying gas velocity value of the power plant ash conveying pipeline, is the secondary flow rate of the conveying gas in the power plant ash conveying pipeline, is the dust density value of the power plant ash conveying pipeline, Delivering dust adhesion index to power plants.

[0053] In this implementation scheme, by obtaining the physical properties of dust particles (such as particle size, shape, and density) and analyzing the characteristics of the conveying airflow (such as flow rate, fluid viscosity, and flow field stability), this scheme can accurately evaluate whether the dust can remain stably suspended during the conveying process. The shape and density of dust particles directly affect their behavior in the airflow, and the flow rate and airflow viscosity determine whether the particles are deposited or transported. Therefore, comprehensive consideration of these factors helps to adjust the system parameters in real time to ensure that dust particles can pass through the ash conveying pipeline stably and evenly, avoiding dust deposition or blockage caused by unstable airflow, thereby optimizing ash conveying efficiency. By combining the flow field characteristics and the pipeline surface characteristics, the dynamic morphological factor can be calculated to comprehensively evaluate the stability of the airflow and the behavior of dust particles in the pipeline. For example, secondary flows such as vortices and backflows in the flow field will affect the suspension and transportation of dust, while the roughness and diameter of the inner wall of the pipeline will affect the probability of dust deposition. By accurately calculating these influencing factors, the system can more effectively optimize the flow rate and pressure of the conveying gas, reduce pipeline wear, blockage and energy waste, and improve the stability and efficiency of the system operation. This scheme uses real-time monitoring and analysis Dynamically adjusting the ash conveying system based on multiple parameters (such as dust adhesion index, flow rate, and flow field stability) not only improves the automation level of the ash conveying process but also enables intelligent control. The system can automatically adjust flow rate and pressure when dust particle stability decreases or airflow becomes unstable, avoiding the delay and inaccuracy of manual adjustment, thereby optimizing the ash conveying system's response time and operational efficiency. By reducing dust deposition and improving airflow stability, the system can effectively reduce wear on ash conveying pipes, reducing equipment repair frequency and maintenance costs. Precise dust particle conveying management avoids pipe wear and compressed air waste caused by excessive or unstable airflow, extending the service life of the ash conveying system. Pipeline and equipment maintenance reduces overall costs and system downtime, thereby improving power plant production efficiency. By precisely controlling the flow rate and pressure of the conveying gas, this solution effectively avoids excessive compressed air supply and reduces unnecessary energy waste. At the same time, the stable ash conveying process reduces dust deposition and improves the overall energy efficiency of the system. This not only helps reduce the power plant's energy costs, but also reduces environmental pollution and secondary pollution, improving the plant's environmental friendliness.

[0054] Specifically, if Figure 2 As shown in FIG, the specific steps for obtaining the power plant flow field efficiency index are as follows: reading the transport gas viscosity value and the transport dust density value of the power plant ash conveying pipeline, and analyzing the transport gas kinematic viscosity value of the power plant ash conveying pipeline (that is, transport gas kinematic viscosity value = transport gas viscosity value / transport dust density value); reading the power plant transport dust adhesion index, and performing a comprehensive analysis based on the transport gas flow rate value, transport dust density value, and transport gas kinematic viscosity value of the power plant ash conveying pipeline to obtain the power plant flow field efficiency index.

[0055] The specific formula for calculating the power plant flow field efficiency index is as follows: ;in, is the power plant flow field efficiency index, is the conveying gas velocity value of the power plant ash conveying pipeline, is the kinematic viscosity of the gas transported in the power plant's ash transport pipeline. is the velocity viscosity influence coefficient stored in the database, Delivering dust adhesion index to power plants, It is the dust density value of the ash conveying pipeline in the power plant.

[0056] It should be explained that the velocity viscosity influence coefficient stored in the database The specific steps for obtaining it are: obtaining it through a large amount of experimental data or fluid dynamics model deduction, and actually measuring the gas viscosity and flow rate data under different conditions (such as temperature, pressure and flow rate, etc.), and performing regression analysis or using computational fluid dynamics (CFD) simulation to obtain the empirical relationship or mathematical model between flow rate and viscosity. It is usually stored in a database and searched and applied according to different operating conditions (such as air flow temperature, pressure, pipeline characteristics, etc.). As an influence coefficient, it is used to quantitatively describe the comprehensive impact of flow velocity and gas viscosity on the flow of the ash conveying system. It helps to adjust the airflow state according to different operating conditions in actual operation and optimize the ash conveying efficiency.

[0057] In this implementation plan, through a comprehensive analysis of parameters such as gas viscosity, dust density, flow velocity, and gas kinematic viscosity in the power plant's ash conveying pipeline, this plan can accurately calculate the power plant's flow field efficiency index (FEI). This index comprehensively considers airflow stability, dust conveying smoothness, and flow resistance, thereby optimizing airflow distribution and dust conveying. Accurate flow field efficiency analysis can effectively avoid dust deposition or uneven conveying caused by unstable flow, ensure that dust is evenly distributed in the pipeline, and improve conveying efficiency. By obtaining the kinematic viscosity of the gas and combining it with the adhesion index of the conveyed dust, the stability of the airflow and the fluidity of the dust can be evaluated in real time during system operation. Kinematic viscosity is the flow resistance of the fluid. The relationship between the flow rate and dust density directly affects the conveying effect of airflow and dust. By calculating the flow field efficiency index, the system can adjust the flow rate and pressure of the conveying gas according to the actual operating conditions, reduce the energy waste and equipment wear caused by too fast or too slow airflow, and improve the overall conveying effect. By comprehensively analyzing factors such as flow rate, gas viscosity, and dust density, the airflow control is optimized to avoid the negative impact of too fast or too slow airflow on the ash conveying efficiency. The system can intelligently adjust the airflow state to meet the ash conveying needs while reducing the waste of compressed air. Especially when the dust load is light or the airflow requirement is low, unnecessary energy is avoided by dynamically adjusting the flow rate and pressure. Consumption, thus achieving energy-saving effects, using the flow rate viscosity influence coefficient stored in the database, the system can be adjusted intelligently according to different working conditions (such as air flow temperature, pressure, etc.). This real-time control based on big data and fluid dynamics models has greatly improved the automation level of the ash conveying system. Traditional manual adjustment methods may have delays and inaccuracies, while this solution ensures that the system always operates in the best state through real-time monitoring and adjustment, thereby improving overall efficiency and reliability. By optimizing the airflow and dust conveying process, it reduces pipe wear and equipment damage caused by unstable airflow or excessively high flow rate, making the system run more smoothly, reducing maintenance frequency and downtime, and through precise control The conveying conditions and the system's pressure and load requirements for the equipment are more reasonable, thereby reducing the incidence of equipment failures, extending the service life of ash conveying pipelines and related equipment, and reducing maintenance costs and equipment replacement frequency. Since factors such as air flow temperature, pressure and dust load will change at different times and operating conditions, traditional fixed parameter control methods are often unable to cope with such changes. By using the flow rate viscosity influence coefficient and combining it with real-time measurement data, this solution can dynamically adjust the conveying conditions to ensure that the system can operate stably under various operating conditions. This enables the power plant ash conveying system to better cope with changes in different loads, climatic conditions and other external factors, providing a more flexible control solution.

[0058] Specifically, the specific steps for obtaining the power plant dust adhesion index are as follows: read the pipe surface roughness value and pipe diameter value of the power plant ash conveying pipeline, and analyze the power plant ash conveying pipeline adhesion influencing factor; combine the power plant ash conveying pipeline adhesion influencing factor with the power plant ash conveying pipeline secondary flow value and conveying gas viscosity value for comprehensive analysis to obtain the power plant dust adhesion index.

[0059] The specific formulas for calculating the adhesion influencing factor of the power plant ash conveying pipeline and the power plant conveying dust adhesion index are as follows: ;in, is the influencing factor of ash conveying pipeline adhesion in power plants, is the surface roughness value of the ash conveying pipeline in the power plant, is the pipeline surface roughness influence coefficient stored in the database, is the pipe surface roughness weight coefficient stored in the database, is the diameter of the ash conveying pipeline in the power plant, is the pipe diameter influence coefficient stored in the database, is the pipe diameter weight coefficient stored in the database, , Delivering dust adhesion index to power plants, is the secondary flow rate of the conveying gas in the power plant ash conveying pipeline, It is the viscosity of the transport gas in the ash conveying pipeline of the power plant.

[0060] It should be explained that the pipeline surface roughness influence coefficient stored in the database The specific steps for obtaining are: usually obtained through a large amount of experimental data or numerical simulation, and the influence of pipelines with different roughness on fluid flow is measured experimentally, especially under different flow rates and different gas types, to obtain the influence of pipeline surface roughness on the friction and flow resistance generated by the airflow. Then, a mathematical relationship between roughness and flow resistance is established through regression analysis to obtain the influence coefficient, which reflects the contribution of pipeline surface roughness to flow resistance. The greater the roughness, the greater the resistance to the airflow. Through this coefficient, the influence of roughness on the flow characteristics of the ash conveying pipeline can be quantitatively evaluated in the model.

[0061] Pipe surface roughness weight coefficient stored in the database The specific steps for obtaining is: It is usually obtained through experiments or numerical simulation methods. In the experiment or simulation, by comparing the effects of pipes with different roughness on the airflow, the relative weight of the roughness effect is calculated. The acquisition of this coefficient usually involves multiple factors in the pipe flow, especially the effect of roughness on the transition of airflow flow states (such as laminar flow and turbulent flow). This coefficient is used to express the contribution of roughness to the airflow characteristics. When calculating the total flow resistance, the roughness weight coefficient is used to quantify the proportion of roughness in the total resistance.

[0062] Pipe diameter influence coefficient stored in the database The specific steps for obtaining is as follows: It is obtained through experiments and numerical simulations. By studying the flow characteristics of airflow in pipes of different diameters, especially data such as flow velocity and pressure loss, the relationship between pipe diameter and airflow resistance is established. This is usually determined by changing the pipe diameter and measuring the airflow changes. The influence coefficient represents the influence of pipe diameter on airflow flow. The larger the diameter, the smaller the flow resistance of the airflow. Therefore, this coefficient helps to quantify the influence of pipe diameter on the flow of conveyed gas.

[0063] Pipe diameter weight coefficients stored in the database The specific steps for obtaining are: by analyzing the performance data of pipeline systems with different diameters, and calculating the weight effect of airflow in pipelines with different diameters through experiments or simulations, the influence of pipeline diameter is obtained. This coefficient is used to represent the relative weight of pipeline diameter in the entire flow system. When calculating the total flow resistance of the pipeline, this weight coefficient can help the model more accurately reflect the influence of pipeline diameter on flow characteristics.

[0064] In this implementation plan, by comprehensively analyzing factors such as the surface roughness, pipe diameter, gas secondary flow rate and gas viscosity of the power plant ash conveying pipeline, the degree of adhesion between the dust in the conveying pipeline and the pipeline surface can be accurately evaluated. The calculation of the dust adhesion index is based on multiple influencing factors, including pipeline surface roughness, pipe diameter, secondary flow rate, etc. These factors work together to determine whether dust particles are easy to deposit on the inner wall of the pipeline, thereby affecting the efficiency of the entire conveying system. Through precise calculations, the system can dynamically optimize the flow rate and pressure, reduce dust deposition, and ensure the stable operation of the conveying system. The pipeline surface roughness and pipeline diameter influence coefficients stored in the database provide a quantitative tool for pipeline optimization. These coefficients are obtained through a large number of experiments or numerical simulations. , which can help us accurately quantify the impact of pipeline characteristics on airflow. For example, a rougher pipeline surface will increase the friction resistance of the airflow, resulting in energy waste and unstable airflow, while a larger pipeline diameter can reduce flow resistance and help the airflow transport dust more stably. By accurately obtaining these influence coefficients, the system can dynamically adjust the airflow parameters according to different pipeline conditions during operation, thereby optimizing the delivery efficiency. By combining multiple data such as pipeline surface roughness, pipeline diameter, flow rate, gas viscosity, etc., the system can accurately evaluate the airflow resistance and flow efficiency under different operating conditions. The pipeline surface roughness influence coefficient and the pipeline diameter influence coefficient help quantify the contribution of these factors to the flow. By adjusting the flow rate and pressure, excessive air supply and airflow are avoided. Unstable, thereby reducing energy waste and improving overall transportation efficiency. For example, when the pipeline surface is rough, the system will automatically adjust the airflow conditions to avoid excessive use of compressed air and reduce energy consumption during system operation. This solution uses the influence coefficients stored in the database based on experimental data and numerical simulation results to enable the system to automatically adjust operating parameters according to the pipeline and airflow status monitored in real time. This method is more accurate and intelligent than traditional manual adjustment and can respond to changes in different operating conditions in real time, such as temperature, pressure, dust load, etc. Through intelligent adjustment, the system can not only optimize energy use, but also improve the stable transportation effect of dust, avoid errors in manual adjustment, and improve the overall automation level. By reducing unnecessary compressed air and gas In the case of too fast flow, this solution helps reduce the pipe wear problem caused by excessively high air flow rate or unstable flow. The rougher pipe surface will increase the resistance of the air flow, resulting in unstable air flow and pipe wear. By optimizing these factors, it can effectively reduce pipe damage, extend the service life of the equipment, reduce maintenance frequency and downtime. By controlling the influence of factors such as pipe diameter and roughness, the system can significantly reduce the maintenance cost of the ash conveying system. The analysis and calculation of adhesion influencing factors can play an important role in the suspension state of dust particles and air flow stability. By avoiding the deposition of dust particles in the pipe, the continuity and stability of the system are ensured, and the failure shutdown caused by dust blockage is reduced. In addition, the system adjusts parameters in real time according to different working conditions.This enables the system to transport dust stably and effectively under different dust loads and airflow conditions, avoiding instability in the dust transport process.

[0065] Specifically, if Figure 3 As shown, the specific steps of analyzing the ash conveying adjusted flow rate value and ash conveying adjusted pressure value of the conveying gas in the power plant ash conveying pipeline are as follows: read the power plant ash conveying efficiency correction index, and conduct a comprehensive analysis based on the power plant dust conveying adhesion index, the conveying dust density value of the power plant ash conveying pipeline, the secondary flow value of the conveying gas in the power plant ash conveying pipeline, and the conveying gas viscosity value to obtain the ash conveying adjusted flow rate value of the conveying gas in the power plant ash conveying pipeline; conduct a comprehensive analysis based on the conveying gas viscosity value of the power plant ash conveying pipeline, the power plant ash conveying efficiency correction index, and the ash conveying adjusted flow rate value of the conveying gas in the power plant ash conveying pipeline to obtain the ash conveying adjusted pressure value of the conveying gas in the power plant ash conveying pipeline.

[0066] The specific formulas for calculating the ash delivery adjustment flow rate and ash delivery adjustment pressure of the transport gas in the power plant ash delivery pipeline are as follows: ;in, Adjust the flow rate value for the ash conveying gas in the ash conveying pipeline of the power plant, is the power plant ash transport efficiency correction index, Delivering dust adhesion index to power plants, is the dust density value of the power plant ash conveying pipeline, is the secondary flow rate of the conveying gas in the power plant ash conveying pipeline, is the viscosity of the transport gas in the power plant's ash transport pipeline, Adjust the pressure value for ash conveying of gas in ash conveying pipeline of power plant.

[0067] In this implementation plan, by comprehensively analyzing the power plant ash conveying efficiency correction index, dust adhesion index, dust density, secondary flow and gas viscosity, the flow rate and pressure of the conveying gas can be accurately calculated and dynamically adjusted, which can ensure that the airflow reaches the optimal speed and pressure during the conveying process, thereby improving the dust conveying efficiency, reducing the instability of the airflow and the deposition of dust. Accurate flow rate and pressure adjustment can ensure that dust particles will not be deposited due to slow airflow, nor will it cause pipe wear and compressed air waste due to fast airflow. By optimizing the flow rate and pressure, excessive compressed air and energy waste are avoided. Traditional ash conveying systems may need to maintain a higher flow rate and pressure to ensure ash Dust can be transported smoothly, but this often leads to excessive energy consumption and waste of compressed air. This solution achieves precise control of airflow through dynamic adjustment based on correction index and multiple parameters. It can flexibly adjust the flow rate and pressure of the conveying gas according to actual conditions, avoid unnecessary energy consumption, and reduce the operating costs of power plants. During the ash conveying process, the airflow conditions will change due to various factors (such as dust load, gas properties, pipeline characteristics, etc.). This solution obtains data in real time and analyzes it in combination with multiple factors. It can adaptively adjust the flow rate and pressure of the conveying gas to ensure that the system can operate stably under different working conditions. This intelligent control enables the system to adapt to various working conditions. Changes, such as fluctuations in dust load and changes in airflow pressure, ensure that the system continues to operate efficiently and stably. By precisely controlling flow rate and pressure, the system can avoid excessive wear and tear on pipes and equipment caused by excessive airflow or unstable flow. For example, excessive airflow may cause damage to the inner wall of the pipe, increasing maintenance frequency and replacement costs. By optimizing flow rate and pressure, this wear and tear can be reduced, the service life of the equipment can be extended, and reducing system failures and maintenance can also reduce the downtime of the power plant and improve overall production efficiency. This solution combines multiple real-time data analyses and can automatically adjust airflow parameters according to different operating conditions. The adjustment of traditional ash conveying systems usually relies on manual settings and fixed parameters. , which is easily affected by human factors and environmental changes. Through dynamic calculation and automatic adjustment, the system can accurately control the flow rate and pressure according to real-time operation data, improve the intelligence level of the ash conveying process, reduce human intervention, and ensure the accuracy and flexibility of operation. By calculating and adjusting parameters such as dust adhesion, dust stability and flow field efficiency index, this solution can ensure the stable suspension of dust particles and avoid the decrease in conveying efficiency due to dust deposition. The system can automatically adjust the speed and pressure of the airflow according to real-time feedback, so that the dust is always kept in the airflow, avoiding deposition and blockage problems, which is of great significance for ensuring the efficient operation of the system and reducing the failure rate.

[0068] When the power plant's ash conveying efficiency correction index is lower than the preset lower limit of the correction range, a specific implementation example of analyzing the ash conveying adjustment flow rate and ash conveying adjustment pressure of the conveying gas in the power plant's ash conveying pipeline is as follows. The following data is available:

[0069] Power plant ash handling efficiency correction index is: 0.85.

[0070] Power plant transmission dust adhesion index is: 0.6.

[0071] Dust density value of the ash conveying pipeline in the power plant 1.3g / cm 3 (ie 1300kg / m 3 ).

[0072] Secondary flow rate of conveying gas in power plant ash conveying pipeline : 0.15m 3 / s.

[0073] Viscosity of transported gas in power plant ash transport pipelines is: 0.02Pa·s.

[0074] Substituting the above data into the specific formulas for calculating the ash delivery adjustment flow rate and ash delivery adjustment pressure of the gas transporting pipeline in the power plant, we obtain:

[0075] The adjusted ash transport flow rate of the gas transporting in the power plant ash transport pipeline = (0.85*(1+(0.6 / 1300))) / (1+(0.15 / 0.02)) = (0.85*(1+0.0004615)) / 8.5 = 0.8503948 / 8.5≈0.10006m / s.

[0076] The ash conveying adjustment pressure value of the conveying gas in the ash conveying pipeline of the power plant = (0.02*0.10006) / 0.85=0.0020012 / 0.85≈0.00235Pa.

[0077] In this embodiment, after calculation, the ash conveying adjustment flow rate value of the conveying gas in the ash conveying pipeline of the power plant is 0.10006 m / s, and the ash conveying adjustment pressure value is 0.00235 Pa.

[0078] In summary, this application has at least the following effects:

[0079] By acquiring and analyzing various key parameters in the ash conveying system in real time, such as pipeline surface roughness, pipeline diameter, conveying gas flow rate and secondary flow, combined with the conveying dust adhesion index, dust stability index and flow field efficiency index, the power plant ash conveying efficiency correction index can be accurately calculated. When the index is lower than the preset correction range, the system automatically adjusts the flow rate and pressure of the conveying gas to ensure the conveying efficiency of airflow and dust. Through this precise adjustment, excessive or insufficient airflow is avoided, energy waste is reduced, and system operation efficiency is improved. For example, in the case of strong dust adhesion, the system will automatically reduce the flow rate to prevent dust from depositing in the pipeline, thereby improving overall conveying efficiency and saving energy.

[0080] By adjusting the ash conveying flow rate and pressure in real time, the system can flexibly adjust the compressed air supply according to the ash conveying status and dust characteristics. In the existing technology, since it is difficult for the system to accurately adjust the airflow, it is often necessary to maintain a large compressed air supply margin to ensure the smooth transportation of dust. The system avoids this excessive air supply phenomenon by calculating the correction index, reducing the waste of compressed air, thereby effectively reducing the energy consumption and operating costs of the power plant. In actual applications, this energy-saving effect is particularly evident in periods of low dust load or low airflow pressure demand, which can greatly reduce the overall operating costs of the power plant.

[0081] During the ash conveying process, excessive air flow velocity and excessive pressure will not only lead to waste of compressed air, but may also cause excessive wear on pipelines and related equipment, increasing the frequency and cost of system maintenance. Through the precise control in this system, when it detects that the air flow velocity in the pipeline is too fast or the pressure is too high, the system will automatically adjust these parameters to prevent pipeline wear and equipment damage caused by excessive airflow. Specifically, the control of flow rate can prevent excessive airflow from generating excessive friction on the ash conveying pipeline and equipment, reduce downtime and maintenance costs caused by wear, and thus extend the service life of the ash conveying system equipment.

[0082] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional 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.

[0083] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A power plant ash handling control optimization system, characterized in that: include: Data acquisition module, efficiency analysis module, judgment analysis module, control and adjustment module; The data acquisition module is used to acquire the power plant ash transport status data in real time and perform preprocessing; The efficiency analysis module is used to conduct a comprehensive analysis on the pre-processed power plant ash conveying status data to obtain the power plant conveying dust adhesion index, the power plant conveying dust stability index, and the power plant flow field efficiency index, and to conduct a comprehensive analysis to obtain the power plant ash conveying efficiency correction index; The judgment and analysis module is used to judge whether the power plant ash transport efficiency correction index is within a preset correction range; The control and adjustment module is used to analyze the ash conveying adjustment flow rate value and ash conveying adjustment pressure value of the conveying gas in the ash conveying pipeline of the power plant and perform control adjustments when the ash conveying efficiency correction index of the power plant is lower than the preset correction interval lower limit; The specific formula for calculating the power plant ash handling efficiency correction index is as follows: ； in, 、 、 、 、 The following are the power plant ash conveying efficiency correction index, power plant dust conveying stability index, power plant flow field efficiency index, power plant dust conveying adhesion index, and power plant ash conveying pipeline dust density value; The power plant ash conveying status data includes the surface roughness value, diameter value, secondary flow value of the conveying gas, viscosity value, flow rate value, and density value of the conveying dust. The specific steps to obtain the power plant conveying dust stability index are as follows: Obtain the dynamic shape factors of dust transported in the ash conveying pipeline of the power plant; The power plant dust adhesion index is read and combined with the secondary flow rate value of the conveying gas in the power plant ash conveying pipeline, the conveying gas flow rate value, the conveying dust density value and the dynamic morphological factor of the conveying dust in the power plant ash conveying pipeline for comprehensive analysis to obtain the power plant dust conveying stability index. The calculation formula is as follows: ； in, The dynamic shape factor of dust transported in the ash conveying pipeline of the power plant, 、 They are the conveying gas velocity value and the conveying gas secondary flow value of the power plant ash conveying pipeline, Deliver dust adhesion index to power plants; The specific steps to obtain the power plant flow field efficiency index are as follows: Read the transport gas viscosity and dust density of the power plant's ash transport pipeline, and analyze the kinematic viscosity of the transport gas in the power plant's ash transport pipeline; The power plant's dust adhesion index is read and combined with the conveying gas velocity value, conveying dust density value, and conveying gas kinematic viscosity value of the power plant's ash conveying pipeline for comprehensive analysis to obtain the power plant flow field efficiency index. The calculation formula is as follows: ； in, is the kinematic viscosity of the gas transported in the power plant's ash transport pipeline. is the velocity viscosity influence coefficient stored in the database; The specific steps to obtain the dust adhesion index of power plant transportation are as follows: Read the surface roughness and diameter of the power plant's ash conveying pipelines, and analyze the factors affecting adhesion of the power plant's ash conveying pipelines; The adhesion influencing factor of the power plant ash conveying pipeline is combined with the secondary flow rate value and the viscosity value of the conveying gas in the power plant ash conveying pipeline to obtain the power plant conveying dust adhesion index. The calculation formula is as follows: ； in, is the influencing factor of ash conveying pipeline adhesion in power plants, is the surface roughness value of the ash conveying pipeline in the power plant, 、 They are the pipeline surface roughness influence coefficient and pipeline surface roughness weight coefficient stored in the database, is the diameter of the ash conveying pipeline in the power plant, 、 They are the pipe diameter influence coefficient and pipe diameter weight coefficient stored in the database, , It is the viscosity of the transport gas in the ash conveying pipeline of the power plant.

2. The power plant ash handling control optimization system according to claim 1, characterized in that: The specific steps for analyzing the ash conveying adjustment flow rate and ash conveying adjustment pressure of the gas conveying pipeline in the power plant are as follows: Read the power plant ash conveying efficiency correction index, and conduct a comprehensive analysis based on the power plant dust adhesion index, the dust density value of the power plant ash conveying pipeline, the secondary flow value of the conveying gas in the power plant ash conveying pipeline, and the conveying gas viscosity value to obtain the ash conveying adjustment flow rate value of the conveying gas in the power plant ash conveying pipeline; The viscosity of the conveying gas in the power plant's ash conveying pipeline is comprehensively analyzed in combination with the power plant's ash conveying efficiency correction index and the ash conveying adjustment flow rate of the conveying gas in the power plant's ash conveying pipeline to obtain the ash conveying adjustment pressure value of the conveying gas in the power plant's ash conveying pipeline.

3. The power plant ash handling control optimization system according to claim 2, characterized in that: The specific formulas for calculating the ash delivery adjustment flow rate and ash delivery adjustment pressure of the transport gas in the power plant ash delivery pipeline are as follows: ； in, Adjust the flow rate value for the ash conveying gas in the ash conveying pipeline of the power plant, is the power plant ash transport efficiency correction index, Delivering dust adhesion index to power plants, 、 、 They are the dust density value, secondary flow value and viscosity value of the ash conveying pipeline in the power plant, Adjust the pressure value for ash conveying of gas in ash conveying pipeline of power plant.

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