Holographic three-dimensional visualization method in coal-fired boiler and related equipment

Abstract

The invention discloses a holographic three-dimensional visualization method in a coal-fired boiler and related equipment, relates to the field of coal-fired boiler optimization guidance, and mainly aims to solve the problem of low efficiency of a traditional coal-fired boiler detection means. The method comprises the following steps: acquiring real-time dynamic data based on a distributed control system of the coal-fired boiler; inputting the real-time dynamic data into a CFD-AI model to obtain model data; and inputting the model data into a holographic three-dimensional visualization system so as to render a flowing combustion image in the coal-fired boiler. The method is used for the holographic three-dimensional visualization process in the coal-fired boiler.

Description

Technical Field

[0001] The present invention relates to the field of optimization guidance for coal-fired boilers, and particularly to a method for holographic three-dimensional visualization inside a coal-fired boiler and related equipment. Background Art

[0002] In the current field of energy utilization, as an important heat energy conversion device, the efficiency and environmental protection performance of coal-fired boilers have always been the focus of research. For coal-fired power plants, achieving real-time monitoring of the internal state of coal-fired boilers is the key to ensuring efficient and safe operation. Traditional monitoring methods often rely on limited sensor data and empirical judgments, which are not only inefficient but also difficult to comprehensively grasp the complex flow and combustion states inside the boiler. Summary of the Invention

[0003] In view of the above problems, the present invention provides a method for holographic three-dimensional visualization inside a coal-fired boiler and related equipment, mainly aiming to solve the problem of low efficiency of the detection means of traditional coal-fired boilers.

[0004] To solve the above-mentioned at least one technical problem, in a first aspect, the present invention provides a method for holographic three-dimensional visualization inside a coal-fired boiler, the method comprising:

[0005] Obtaining real-time dynamic data based on the distributed control system of the coal-fired boiler;

[0006] Inputting the real-time dynamic data into a CFD-AI model to obtain model data;

[0007] Inputting the model data into a holographic three-dimensional visualization system to render the flow combustion images inside the coal-fired boiler.

[0008] Optionally, the above method further comprises:

[0009] Cleaning and processing the historical data of the coal-fired boiler to obtain a set of typical working conditions;

[0010] Establishing a digital model of the coal-fired boiler based on the design parameters of the coal-fired boiler;

[0011] Inputting the set of typical working conditions into the digital model of the coal-fired boiler to determine the simulation results corresponding to different typical working conditions;

[0012] Performing deep learning training on the simulation results to determine the CFD-AI model.

[0013] Optionally, the establishing a digital model of the coal-fired boiler based on the design parameters includes:

[0014] Establishing a physical model of the coal-fired boiler based on the design parameters;

[0015] Mesh the physical model of the coal-fired boiler to establish a boiler mathematical model.

[0016] Optionally, meshing the physical model of the coal-fired boiler to establish a boiler mathematical model includes:

[0017] Establish the boiler mathematical model based on the basic conservation equations, turbulence model, discrete phase model, gas-phase combustion model, char oxidation model, devolatilization model, and radiation model.

[0018] In a second aspect, an embodiment of the present invention further provides a holographic three-dimensional visualization device inside a coal-fired boiler, including:

[0019] An acquisition unit for acquiring real-time dynamic data based on the distributed control system of the coal-fired boiler;

[0020] An input unit for inputting the real-time dynamic data into a CFD-AI model to obtain model data;

[0021] A rendering unit for inputting the model data into a holographic three-dimensional visualization system to render the flow combustion image inside the coal-fired boiler.

[0022] To achieve the above object, according to a third aspect of the present invention, there is provided a computer-readable storage medium, the computer-readable storage medium including a stored program, wherein when the above program is executed by a processor, the steps of the above holographic three-dimensional visualization method inside the coal-fired boiler are implemented.

[0023] To achieve the above object, according to a fourth aspect of the present invention, there is provided an electronic device, including at least one processor and at least one memory connected to the processor; wherein the above processor is used to call the program instructions in the above memory to execute the steps of the above holographic three-dimensional visualization method inside the coal-fired boiler.

[0024] With the above technical solutions, the method and related equipment for in-furnace holographic three-dimensional visualization of a coal-fired boiler provided by the present invention can address the problem of low efficiency in the detection means of traditional coal-fired boilers. The present invention can intuitively display the complex structure and flow state inside the boiler in the form of three-dimensional images, providing an intuitive monitoring interface for operators. It can not only help operators better understand the operating state of the boiler but also assist in fault diagnosis and performance analysis. By grasping the real-time information of each parameter in the three-dimensional field inside the boiler, operators can intuitively observe key parameters such as the temperature distribution, pressure change, air flow velocity, and direction inside the furnace. This intuitive three-dimensional view makes monitoring and analysis more efficient, helping to promptly detect and troubleshoot abnormal states, such as local overheating and incomplete fuel combustion. The visualization of real-time monitoring data can also help operators quickly make decisions, adjust combustion parameters and operating strategies, thereby enabling the boiler to reach the optimal operating state, improving energy utilization efficiency, and reducing environmental pollution. The application of the above holographic three-dimensional visualization technology not only improves the accuracy and response speed of monitoring but also greatly reduces the complexity of operation, enabling non-professional operators to understand the operating state of the boiler through intuitive images, thus enhancing the user-friendliness and operating safety of the entire system. In case of an emergency, this technology can provide strong support for rapid response and accident handling, ensuring the safe and stable operation of the boiler.

[0025] Correspondingly, the in-furnace holographic three-dimensional visualization device, equipment, and computer-readable storage medium provided by the embodiments of the present invention also have the above technical effects.

[0026] The above description is only an overview of the technical solutions of the present invention. In order to be able to more clearly understand the technical means of the present invention, it can be implemented in accordance with the content of the description. And in order to make the above and other purposes, features, and advantages of the present invention more obvious and understandable, the following specifically describes the embodiments of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] By reading the detailed description of the preferred embodiments below, various other advantages and benefits will become clear to those of ordinary skill in the art. The drawings are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present invention. Moreover, throughout the drawings, the same reference numerals are used to represent the same components. In the drawings:

[0028] Figure 1 shows a schematic flow chart of a method for in-furnace holographic three-dimensional visualization of a coal-fired boiler provided by an embodiment of the present invention;

[0029] Figure 2 shows a schematic flow chart of another method for in-furnace holographic three-dimensional visualization of a coal-fired boiler provided by an embodiment of the present invention;

[0030] Figure 3 Shows a schematic structural diagram of a CFD-AI model visualization platform provided by an embodiment of the present invention;

[0031] Figure 4 Shows a schematic block diagram of the composition of a holographic three-dimensional visualization device inside a coal-fired boiler provided by an embodiment of the present invention;

[0032] Figure 5 Shows a schematic block diagram of the composition of a holographic three-dimensional visualization electronic device inside a coal-fired boiler provided by an embodiment of the present invention. Detailed implementation manners

[0033] The exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present invention can be more thoroughly understood and the scope of the present invention can be fully conveyed to those skilled in the art.

[0034] To solve the problem of low efficiency of the detection means of traditional coal-fired boilers, an embodiment of the present invention provides a method for holographic three-dimensional visualization inside a coal-fired boiler, as Figure 1 shown, the method includes:

[0035] S101. Obtain real-time dynamic data based on the distributed control system of the coal-fired boiler;

[0036] Exemplarily, this application obtains real-time dynamic data information from the distributed control system (DCS, Distributed Control System) of the physical coal-fired boiler.

[0037] S102. Input the real-time dynamic data into the CFD-AI model to obtain model data;

[0038] Input the obtained real-time dynamic data into the CFD-AI model for in-depth analysis and calculation, obtain the data required for three-dimensional rendering by the holographic three-dimensional visualization system and some key information inside the furnace, and obtain the furnace fault diagnosis information and optimization guidance opinions.

[0039] Integrate parameters such as the boiler operation period, operation load, coal used, operation status of each layer of coal mills, total air volume, primary air volume of each layer of burners, secondary air volume of each layer of burners, coal feeding amount of each layer of burners, air temperature of each layer of burners, and wall temperature, etc., to obtain a large number of different working conditions, and each working condition includes the above parameters.

[0040] Select the operating conditions with relatively small changes in the boiler operating load within a continuous time period as the stable judgment conditions, and approximately process the operating load into load conditions such as BMCR, 100% THA, 95% THA, 90% THA, 85% THA... 45% THA, 40% THA, etc. Analyze the operation of the coal mills under different conditions, sort out several coal mill operation modes with higher frequencies under each approximate operating load, and screen out a large number of typical conditions based on this load-coal mill operation combination mode to construct a typical condition set. Each typical condition contains a unique load-coal mill operation combination mode.

[0041] In one embodiment, the above method further includes:

[0042] Clean the historical data of the coal-fired boiler to obtain a typical condition set;

[0043] Establish a digital model of the coal-fired boiler based on the design parameters of the coal-fired boiler;

[0044] Input the typical condition set into the digital model of the coal-fired boiler to determine the simulation results corresponding to different typical conditions;

[0045] Perform deep learning training on the simulation results to determine the CFD-AI model.

[0046] The above solution cleans and processes the historical data, organizes the processed historical data into a large number of different conditions, and screens out thousands of typical conditions from them to construct a typical condition set; establishes a physical model of the coal-fired boiler according to the design parameter data, and establishes a mathematical model (CFD model) of the coal-fired boiler on the basis of the boiler physical model; inputs the thousands of selected typical conditions into the CFD model for calculation to obtain the simulation results corresponding to the typical conditions; performs deep learning training on the CFD simulation results to obtain a CFD-AI model that can replace the original CFD model.

[0047] Based on the above solution, parameters such as the boiler operation period, operation load, used medium, operation of each layer of coal mills, total air volume, primary air volume of each layer of burners, secondary air volume of each layer of burners, coal feeding amount of each layer of burners, air temperature of each layer of burners, and wall temperature are integrated to obtain a large number of different conditions, and each condition contains the above parameters.

[0048] Select the operating conditions with relatively small changes in the boiler operating load within consecutive time periods as the stable judgment conditions, and approximately process the operating load as load conditions such as BMCR, 100% THA, 95% THA, 90% THA, 85% THA... 45% THA, 40% THA, etc. Analyze the operation of the coal mills under different conditions, sort out several coal mill operation modes with higher frequencies under each approximate operating load, and screen out a large number of typical conditions based on this load - coal mill operation combination mode to construct a typical condition set. Each typical condition contains a unique load - coal mill operation combination mode.

[0049] This application uses parameters such as the boiler operation period, operating load, coal type used, operation of each layer of coal mills, total air volume, primary air volume of each layer of burners, secondary air volume of each layer of burners, coal feeding amount of each layer of burners, air temperature of each layer of burners, and wall temperature as the input conditions of the AI model, extracts parameters such as three-dimensional field temperature, wall temperature, wall heat flux, vector velocity, oxygen concentration, carbon dioxide concentration, and carbon monoxide concentration in the CFD simulation results as the output results to be predicted by the AI model, and constructs a training set and a test set.

[0050] Use POD modal decomposition to decompose the parameters into spatial parameters and time coefficients, assign different sensitivity coefficients to each parameter according to expert experience, train the AI model through the multi-layer perceptron algorithm + long short-term memory recursive algorithm, and verify it through the test set. Finally, obtain a CFD-AI model that can replace the original CFD model.

[0051] Specifically, the above historical data includes: load, coal quality, total air volume, powder amount of each layer of burners, air volume of each layer of burners, air temperature of each layer of burners, wall temperature; it also includes the system pipeline instrument flow chart (PID, Process & Instrumentation Drawing) diagram, system heat balance diagram, system control logic diagram, characteristic curves of steam-water and air-smoke valves, burner diagram, and heating surface calculation table; the on-site data includes: the information table corresponding to the DCS measurement point number and measurement point name, historical operation data, and test reports during performance tests such as major repairs.

[0052] Specifically, this application extracts parameters such as the boiler operation period, operating load, coal type used, operation of each layer of coal mills, total air volume, primary air volume of each layer of burners, secondary air volume of each layer of burners, coal feeding amount of each layer of burners, air temperature of each layer of burners, and wall temperature from the acquired real-time dynamic data and inputs them into the CFD-AI model to calculate key information in the furnace such as three-dimensional field temperature, wall temperature, wall heat flux, vector velocity, oxygen concentration, carbon dioxide concentration, and carbon monoxide concentration.

[0053] Perform post-processing calculations on the above key information in the furnace to obtain the following parameters:

[0054] (1) Flame center position:

[0055] Perform weighted calculation on the temperature field data in the furnace area to obtain the flame center coordinates:

[0056]

[0057] Where S is the set of all points in the furnace area, x i , y i , z i are the coordinates of the i-th point, and T i is the temperature of the i-th point.

[0058] (2) Flue gas temperature deviation:

[0059] Divide the platen superheater area into two equal left and right areas (L and R), and calculate the average temperature of the two areas respectively:

[0060]

[0061]

[0062] Where n L , n R are the numbers of temperature data points in the left and right areas of the platen superheater respectively.

[0063] Then the flue gas temperature deviation ΔT is: ΔT = T L -T R

[0064] (3) Over-temperature area:

[0065] By comparing the wall temperature of a certain area of the boiler with the allowable temperature of the steel used in this area, it can be judged whether the wall of this area is over-temperature, and thus the over-temperature area can be calculated.

[0066] The above information such as the flame center position, flue gas temperature deviation, and over-temperature area obtained by analyzing the key information in the furnace such as the three-dimensional field temperature, wall temperature, wall heat flux, vector velocity, oxygen concentration, carbon dioxide concentration, and carbon monoxide concentration in the boiler and post-processing can be used to judge the over-temperature and uneven combustion conditions of the boiler, predict the fouling and slagging conditions of the boiler, and obtain the furnace fault diagnosis information and optimization guidance opinions.

[0067] In one embodiment, establishing a digital model of a coal-fired boiler based on the design parameters includes:

[0068] Establish a physical model of the coal-fired boiler based on the design parameters;

[0069] Perform mesh division on the physical model of the coal-fired boiler to establish a boiler mathematical model.

[0070] Specifically, the design parameter data includes: the finalized boiler instruction manual, design drawings, summary table of thermal calculations or summary table of performance data, steam-water flow description, flue gas, air and steam-water resistance tables for each section of the heating surface under various conditions, and DCS sensor measuring point layout position diagram.

[0071] In this application, 3D modeling of the boiler physical model is carried out using modeling software such as Solidworks.

[0072] In one embodiment, the mesh generation of the physical model of the coal-fired boiler to establish a boiler mathematical model includes:

[0073] The boiler mathematical model is established based on the basic conservation equations, turbulence model, discrete phase model, gas-phase combustion model, char oxidation model, devolatilization model, and radiation model.

[0074] Using software such as Ansys Fluent to carry out mesh generation on the boiler physical model and establish a boiler mathematical model. Specifically:

[0075] (1) Basic conservation equations:

[0076] Momentum equation:

[0077]

[0078] Continuity equation:

[0079]

[0080] Where σ ij = pδ ij - τ ij ,

[0081] Energy equation:

[0082]

[0083] Among them, Φ is the part of mechanical energy converted into heat energy under viscous action; is the energy change amount caused by heat conduction; S h is other energy source terms.

[0084] (2) Turbulence model:

[0085] The realizable k-ε model is selected as the turbulence model, where:

[0086] k equation:

[0087] ε equation:

[0088] Among them:

[0089]

[0090] η = Sk / ε

[0091] S = (2S ij S ij ) 1 / 2

[0092] All the constant values appearing in the formula are determined by the RNG equation, and the specific values are shown in the following table:

[0093]

[0094] (3) Discrete phase model:

[0095] The random trajectory model is used to simulate the motion of discrete phases in the flow field in the Lagrangian coordinate system. The particle random trajectory model of pulverized coal is:

[0096]

[0097] Where m p is the particle mass, A p is the particle surface area, g k is the gravitational acceleration. u' ig is the pulsating velocity of the gas phase in a certain direction, is the average velocity of the gas phase in a certain direction, u ip is the magnitude of the velocity component of the discrete phase in this direction. C D is the drag coefficient, ρ g is the density.

[0098] (4) Gas phase combustion model:

[0099] The transport equation of substances is:

[0100]

[0101] Where R i is the net production rate of chemical reactions, S i is the additional rate caused by discrete phases and other source phases; in the laminar flow case, the calculation method of the diffusion flux is:

[0102] J i = -ρD i,m ▽Y i

[0103] Where D im is the diffusion coefficient of substances in the mixture. In the turbulent flow case, the above formula is corrected to:

[0104]

[0105] The pulverized coal combustion process is simulated using the Finite-rate / eddy-dissipation model, which combines two main combustion models: the Finite-Rate Chemistry model and the Eddy Dissipation (ED) model.

[0106] In the Finite-Rate model, the chemical reaction source term of substance i is obtained by summing up the calculations of N R chemical reaction sources:

[0107]

[0108] where R i,r is the generation rate of substance i in reaction r, M w,i is the molecular weight of substance i, and N r is the total number of substances in reaction r. The generation rate of substance i in reaction r is as follows:

[0109]

[0110] where Γ represents the total influence of the medium on the reaction rate, v i ” ,r , v' i,r are the stoichiometric coefficients of product i and reactant i in reaction r, k i,r , b i,r are the forward and reverse reaction rate constants of reaction r, C j,r is the molar concentration of substance j in reaction r, and η' j,r is the rate exponent of substance j in the forward and reverse reactions of reaction r.

[0111] In the Eddy Dissipation model, the generation rate R i,r of substance i is determined by the smaller value of the following two equations:

[0112]

[0113] where Y p , Y R are the mass fractions of the product and the reactant, respectively. In the above two equations, the chemical reaction rate is controlled by the large eddy mixing time scale k / ε. Therefore, in the Finite-rate / eddy-dissipation model, the chemical reaction source term is:

[0114] R i,r =min[R i,1 , min(R i,r,2 , R i,r,3 )]

[0115] (5) Coal char oxidation model

[0116] The improved coal surface reaction mechanism is adopted to simulate the coal char oxidation process. The specific model parameters are shown in the following table

[0117] as follows:

[0118]

[0119]

[0120] (6) Devolatilization model

[0121] The chemical percolation devolatilization (CPD) model is used as the devolatilization model for coal during the simulation process. The specific parameters are as follows:

[0122] Y = c1 + c2*C + c3*C^2 + c4*H + c5*H^2 + c6*O + c7*O^2 + c8*VM + c9*VM^2

[0123] where,

[0124] C = Weight Percent Carbon (daf)

[0125] H = Weight Percent Hydrogen (daf)

[0126] N = Weight Percent Nitrogen (daf)

[0127] O = Weight Percent Oxygen (daf)

[0128] VM = ASTM Volatile Matter (daf)

[0129] The value-taking method of the parameters in the formula is:

[0130]

[0131]

[0132] where, Mdel is the percentage of volatile matter mass loss, MW is the cluster molecular weight, Po is the initial porosity, and sigma + 1 is the coal surface tension.

[0133] (7) Radiation model

[0134] The intensity of radiative heat transfer varies in different regions of the furnace, which is the result of the combined effects of gas and particles through absorption, emission, and scattering, as follows:

[0135]

[0136] where α is the absorption coefficient, and σ s is the emission coefficient, and σ is the dissipation constant (5.669×10 -8 W / m 2 ·K 4 ).

[0137] It should be noted that the chemical mechanism involved in the text is based on the improved WD-1 chemical reaction mechanism, and the specific chemical reaction parameters are shown in the following table:

[0138]

[0139] S103. Input the model data into the holographic three-dimensional visualization system to render the flow combustion image inside the coal-fired boiler furnace.

[0140] By outputting the data calculated by the CFD-AI model to the holographic three-dimensional visualization system, this system performs precise three-dimensional rendering based on real-time dynamic data, generates holographic three-dimensional images inside the boiler, and displays these images and key information inside the furnace on the front-end user interface. So that the operator can intuitively observe and understand the complex flow and combustion process inside the boiler through the holographic three-dimensional images and key information inside the furnace displayed on the front-end user interface, and can optimize and adjust the physical boiler system according to the in-furnace fault diagnosis information, optimization guidance, as well as his own experience and actual production conditions.

[0141] With the above technical solutions, for the problem of low efficiency of the detection means of traditional coal-fired boilers, the holographic three-dimensional visualization method and related equipment for the inside of the coal-fired boiler furnace provided by the present invention can intuitively display the complex structure and flow state inside the boiler in the form of three-dimensional images, providing an intuitive monitoring interface for the operator. It can not only help the operator better understand the operating state of the boiler, but also assist in fault diagnosis and performance analysis. By mastering the real-time information of each parameter in the three-dimensional field inside the boiler furnace, the operator can intuitively observe key parameters such as the temperature distribution, pressure change, air flow velocity and direction inside the furnace. This intuitive three-dimensional view makes monitoring and analysis more efficient, and helps to detect and troubleshoot abnormal states in a timely manner, such as local overheating, incomplete fuel combustion and other problems.

[0142] In addition, the visualization of real-time monitoring data can also help operators make decisions quickly, adjust combustion parameters and operation strategies, so that the boiler reaches the optimal operation state, improves energy utilization efficiency, and reduces environmental pollution. The application of the above holographic three-dimensional visualization technology not only improves the accuracy and response speed of monitoring, but also greatly reduces the complexity of operation, enabling non-professional operators to understand the operation state of the boiler through intuitive images, thus improving the user-friendliness and operation safety of the entire system. In case of emergency, this technology can provide strong support for rapid response and accident handling, ensuring the safe and stable operation of the boiler.

[0143] Furthermore, as an implementation of the above Figure 1 shown method, an embodiment of the present invention also provides a holographic three-dimensional visualization device inside a coal-fired boiler for implementing the above Figure 1 shown method. The device embodiment corresponds to the foregoing method embodiment. For ease of reading, the details of the foregoing method embodiment will not be repeated one by one in this device embodiment, but it should be clear that the device in this embodiment can correspondingly implement all the contents of the foregoing method embodiment. As Figure 4 shown, the device includes: an acquisition unit 21, an input unit 22, and a rendering unit 23, where

[0144] The acquisition unit 21 is used to acquire real-time dynamic data based on the distributed control system of the coal-fired boiler;

[0145] The input unit 22 is used to input the real-time dynamic data into the CFD-AI model to obtain model data;

[0146] The rendering unit 23 is used to input the model data into the holographic three-dimensional visualization system to render the flowing combustion image inside the coal-fired boiler.

[0147] The processor contains a kernel, and the kernel retrieves the corresponding program unit from the memory. One or more kernels can be set, and by adjusting the kernel parameters, a holographic three-dimensional visualization method inside a coal-fired boiler can be realized, which can solve the problem of low efficiency of traditional detection means for coal-fired boilers.

[0148] An embodiment of the present invention provides a computer-readable storage medium. The above computer-readable storage medium includes a stored program, and when the program is executed by a processor, the holographic three-dimensional visualization method inside the coal-fired boiler is realized.

[0149] An embodiment of the present invention provides a processor, and the processor is used to run a program. When the program runs, the holographic three-dimensional visualization method inside the coal-fired boiler is executed.

[0150] An embodiment of the present invention provides an electronic device, which includes at least one processor and at least one memory connected to the processor; wherein, the processor is configured to call program instructions in the memory to execute the in-furnace holographic three-dimensional visualization method for a coal-fired boiler as described above.

[0151] An embodiment of the present invention provides an electronic device 30, as Figure 5 shown, the electronic device includes at least one processor 301, at least one memory 302 connected to the processor, and a bus 303; wherein, the processor 301 and the memory 302 communicate with each other through the bus 303; the processor 301 is configured to call program instructions in the memory to execute the in-furnace holographic three-dimensional visualization method for a coal-fired boiler as described above.

[0152] The intelligent electronic device herein may be a PC, a PAD, a mobile phone, etc.

[0153] The present application also provides a computer program product, which is suitable for executing a program initialized with the steps of the in-furnace holographic three-dimensional visualization method for a coal-fired boiler when executed on a process management electronic device.

[0154] It should be noted that in the above embodiments, the descriptions of each embodiment have their own emphases. For parts not described in detail in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0155] Those skilled in the art should understand that the embodiments of the present application may be provided as a method, a system, or a computer program product. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0156] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, and the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in one Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0157] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a particular manner, such that the instructions stored in the computer-readable memory produce a manufacture including an instruction device that implements the functions specified in one or more of the processes and / or boxes Figure 1 one or more of the processes and / or boxes Figure 1 specified in one or more of the boxes or processes.

[0158] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operational steps are performed on the computer or other programmable device to produce a computer-implemented process, thereby providing steps for implementing the functions specified in one or more of the processes and / or boxes Figure 1 one or more of the processes and / or boxes Figure 1 specified in one or more of the boxes or processes.

[0159] The embodiments of the present application also provide a computer program product, which includes computer software instructions that, when running on a processing device, cause the processing device to execute the processes for controlling the memory as in Figure 1 the corresponding embodiments.

[0160] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, they implement all or part of the processes or functions according to the embodiments of the present application. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (such as coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can store or a data storage device such as a server or data center that includes one or more integrated available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a DVD), or a semiconductor medium (such as a solid state disk (SSD)).

[0161] Those skilled in the art can clearly understand that, for the sake of convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0162] In several embodiments provided in the present application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces, and the indirect couplings or communication connections of devices or units can be in electrical, mechanical, or other forms.

[0163] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place, or can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0164] In addition, in each embodiment of the present application, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0165] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in each embodiment of the present application. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0166] The above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of each embodiment of the present application.

Claims

1. A 3D holographic visualization method for a coal-fired boiler, characterized in that: include: Obtain real-time dynamic data based on the distributed control system of coal-fired boilers; Inputting the real-time dynamic data into the CFD-AI model to obtain model data; The model data is input into a holographic three-dimensional visualization system to render the flow combustion image in the coal-fired boiler furnace.

2. The method according to claim 1, characterized in that Also includes: Clean the historical data of coal-fired boilers to obtain a set of typical operating conditions; Establishing a digital model of the coal-fired boiler based on the design parameters of the coal-fired boiler; Inputting the typical operating condition set into the digital model of the coal-fired boiler to determine simulation results corresponding to different typical operating conditions; Deep learning training is performed on the simulation results to determine the CFD-AI model.

3. The method according to claim 2, characterized in that The method of establishing a digital model of a coal-fired boiler based on the design parameters comprises: Establishing a physical model of the coal-fired boiler based on the design parameters; The physical model of the coal-fired boiler is meshed to establish a mathematical model of the boiler.

4. The method according to claim 3, characterized in that The step of meshing the physical model of the coal-fired boiler to establish a mathematical model of the boiler includes: The mathematical model of the boiler is established based on basic conservation equations, turbulence model, discrete phase model, gas phase combustion model, coal char oxidation model, devolatilization model and radiation model.

5. A 3D holographic visualization device for coal-fired boiler furnace, characterized in that: Also includes: An acquisition unit, used for acquiring real-time dynamic data based on a distributed control system of a coal-fired boiler; An input unit, used for inputting the real-time dynamic data into the CFD-AI model to obtain model data; The rendering unit is used to input the model data into a holographic three-dimensional visualization system to render the flow combustion image in the coal-fired boiler furnace.

6. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed by a processor, the steps of the holographic three-dimensional visualization method for the interior of a coal-fired boiler as claimed in any one of claims 1 to 4 are implemented.

7. An electronic device, characterized in that: The electronic device includes at least one processor and at least one memory connected to the processor; wherein the processor is used to call program instructions in the memory to execute the steps of the holographic three-dimensional visualization method for the interior of a coal-fired boiler as described in any one of claims 1 to 4.

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