Method and system for diagnosing and optimizing blast furnace bag-type dust collector based on CFD (computational fluid dynamics) simulation

Abstract

The invention provides a CFD simulation-based blast furnace bag-type dust remover diagnosis and optimization method and system, and the diagnosis method comprises the following steps: S1, processing a three-dimensional CAD model of a blast furnace dust removal system to obtain a dust removal system model; s2, setting operation condition parameters according to actual conditions; s3, performing discrete grid processing to obtain a model after grid division; s4, a computational fluid mechanics model is constructed and solved, and result data obtained through calculation of the CFD method is obtained; and S5, extracting flow parameters of a specific position and a section, and analyzing to obtain an analysis result. According to the invention, a computational fluid mechanics analogue simulation technology is adopted, and the high-speed impact positions of airflow and dust in the bag-type dust collector are quickly and accurately simulated in a computer at low cost, so that designers can optimize the structure of the dust collector and reduce the abrasion of the dust collector, thereby prolonging the service life of the dust collector.

Description

Technical Field

[0001] The present invention relates to the field of environmental protection equipment and technology, and in particular to a diagnosis and optimization method and system for a blast furnace bag filter based on CFD simulation. Background Art

[0002] The blast furnace bag filter is a device for purifying blast furnace flue gas, mainly used to remove particulate matter and pollutants in the flue gas to protect the environment and improve production efficiency. Figure 2 As shown in the figure, its main components include pre-processor, middle box and internal structure. The pre-processor performs preliminary purification on the flue gas, and uses inertia and gravity to separate large particles and dust, which reduces the load on the subsequent filter bags, thereby improving the life of the filter bags and the filtering effect. The middle box is the key part connecting the pre-processor and the filter bag. It is equipped with guide plates and guide devices inside. After reasonable design and arrangement, the flue gas can be evenly distributed before entering the filter bag, improving the efficiency and life of the filter bag. The core of the internal structure is the filter bag, which is made of high-temperature wear-resistant materials to effectively filter tiny particles in the flue gas. The filter bag usually adopts a bag structure and has tiny pores on the surface. Through these pores, the flue gas can pass through, while retaining particles on the surface of the filter bag to achieve flue gas purification. In short, the pre-processor removes larger impurities first, the middle box ensures that the flue gas is evenly distributed, and the filter bag of the internal structure completes the final filtration of tiny particles.

[0003] At present, the design of blast furnace bag dust collectors mainly relies on engineering experience or standard experiments, and lacks in-depth analysis and application of internal airflow and dust particle flow mechanism. This makes it difficult to accurately know the cause of dust collector wear, and problems are often discovered only after the bag or shell is damaged, which not only causes economic losses, but also affects the safety of the dust collector and the overall operation of the blast furnace.

[0004] Computational Fluid Dynamics (CFD) is a simulation method that uses computers and numerical methods to solve the movement of fluids and fluid-solid mixtures. The CFD method can be used to simulate and model the flow field and particles inside the dust collector, simulate the movement speed, pressure, flow path, etc. of the airflow and particles in the dust collector, and consider the two flow characteristics in the dust collector during the design stage, identify the wear-prone locations, and optimize the structural design.

[0005] Through searching patent documents, it is found that the invention patent with publication number CN116362145A discloses a simple simulation analysis method for cartridge dust collector or bag dust collector, which includes: extracting a real single chamber model from the cartridge dust collector or bag dust collector, setting a guide plate structure for simulation, and obtaining a single chamber model A; simplifying the cartridge structure or bag structure in the single chamber model A to form a new filtering structure, and establishing a single chamber model B; simulating the single chamber model B, comparing the single chamber model A, and correcting the new filtering structure to obtain an equivalent filtering structure and an equivalent single chamber model C; using the single chamber model C to simulate the entire dust collector and optimize the dust collector guide structure. The patent experiment has high cost and long cycle, and it is impossible to predict the wear-prone position in advance, and there are safety hazards.

[0006] In summary, in response to the above-mentioned problems of the prior art, studying a diagnosis and optimization method and system for blast furnace bag dust collector based on CFD simulation has become a key task that needs to be solved urgently. Summary of the invention

[0007] In view of the defects in the prior art, the object of the present invention is to provide a blast furnace bag filter diagnosis and optimization method and system based on CFD simulation.

[0008] A blast furnace bag filter health status diagnosis method based on CFD simulation provided by the present invention comprises the following steps:

[0009] Step S1, processing the three-dimensional CAD model of the blast furnace dust removal system to obtain a dust removal system model containing a fluid region that can be used for CFD simulation calculation;

[0010] Step S2, setting operating parameters according to actual conditions;

[0011] Step S3, performing discretization grid processing on the fluid region of the dust removal system model to obtain a grid-divided model;

[0012] Step S4, based on the operating condition parameters and the meshed model, construct and solve a computational fluid dynamics model to obtain result data calculated by the CFD method;

[0013] Step S5, extracting the flow parameters of specific positions and cross sections from the result data obtained by the CFD method to visualize the flow state inside the dust collector, and analyzing to obtain the analysis results.

[0014] Preferably, in step S1, the three-dimensional CAD model of the blast furnace dust removal system includes: a preprocessor inlet, a dust outlet, a preprocessor internal baffle, a preprocessor, a middle box and a middle box outlet, and the three-dimensional CAD model of the blast furnace dust removal system is initially in the form of a solid shell.

[0015] Preferably, step S1 includes, for the three-dimensional CAD model of the blast furnace dust removal system, using the Boolean operation function in the CAD software, establishing a block larger than the model boundary, subtracting the outer shell of the dust removal system from the block, and then refining the remaining model.

[0016] Preferably, in step S2, the ambient temperature is set to 25 degrees and the air density is set to 1.2 kg / m 3 , dynamic viscosity is 959e-6N*s / m 2 , inlet flow rate is 140000m 3 / h, outlet pressure is 10Kpa.

[0017] Preferably, in step S3, the fluid region is spatially discretized by meshing software using a meshing method combining polyhedral boundaries with hexahedral cores to obtain a meshed model.

[0018] Preferably, step S4 includes the following sub-steps:

[0019] Step S4.1, reading the meshed model obtained in step S3;

[0020] Step S4.2, setting the time model to steady state;

[0021] Step S4.3, set the turbulence model to the ke standard turbulence model and the standrad wall function model;

[0022] Step S4.4, the physical property parameters adopt the ambient temperature, air density and dynamic viscosity set in step S2;

[0023] Step S4.5, the boundary conditions are set to the inlet flow rate and outlet pressure set in step S2;

[0024] Step S4.6, the regional condition is set to the porous medium model;

[0025] Step S4.7, setting calculation parameters, such as iteration step size and convergence condition;

[0026] Step S4.8, setting the number of computer CPU cores for parallel solving;

[0027] Step S4.9, setting data extraction to extract the inlet and outlet pressures at each iteration time step;

[0028] Step S4.10, execute calculation to obtain result data obtained by CFD method calculation including various flow parameter results of all discrete grid cells.

[0029] Preferably, the analysis steps of step S5 are as follows:

[0030] Step S5.1, according to the structure of the dust collector, the key areas are identified as the pre-processor and the dust removal chamber;

[0031] Step S5.2, based on the key areas, extract the flow parameters of the specific positions and cross-sections of the pre-processor and the flow parameters of the specific positions and cross-sections of the dust removal chamber, and visualize the flow state inside the dust collector;

[0032] Step S5.3, based on the flow parameters of the specific position and cross section of the pre-processor extracted in step S5.2, analyzing the unevenness of the velocity distribution, and determining whether the placement of the internal baffles of the pre-processor is unreasonable;

[0033] Step S5.4, based on the flow parameters of the specific position and cross section of the preprocessor extracted in step S5.2, determine a reasonable shell shape of the preprocessor and a placement position of the baffle;

[0034] Step S5.5, based on the flow parameters of the specific position and cross section of the dust removal chamber extracted in step S5.2, determine whether the airflow direction at the dust removal chamber inlet is correct; if the airflow direction is incorrect, improve the dust removal chamber inlet direction according to the analysis results, and optimize the placement of the guide plate;

[0035] Step S5.6, based on the flow parameters of the specific position and cross section of the dust removal chamber extracted in step S5.2, the vortex distribution is analyzed, the area with larger vortex is identified as an invalid area, and the corresponding redundant structure in the dust collector is removed.

[0036] The present invention also provides a blast furnace bag filter optimization method based on CFD simulation, comprising the following steps:

[0037] Step S1, processing the three-dimensional CAD model of the blast furnace dust removal system to obtain a dust removal system model containing a fluid region that can be used for CFD simulation calculation;

[0038] Step S2, setting operating parameters according to actual conditions;

[0039] Step S3, performing discretization grid processing on the fluid region of the dust removal system model to obtain a grid-divided model;

[0040] Step S4, based on the operating condition parameters and the meshed model, construct and solve a computational fluid dynamics model to obtain result data calculated by the CFD method;

[0041] Step S5, extracting flow parameters at specific positions and cross sections from the result data calculated by the CFD method, for visualizing the flow state inside the dust collector, and analyzing to obtain analysis results;

[0042] Step S6, optimizing the vulnerable structure based on the analysis results.

[0043] Preferably, step S6 comprises:

[0044] Based on the analysis results, when the analysis finds that the flow rate from the middle box to the cabin inlet gradually increases and the inflow distribution of each cabin is uneven, the flow distribution of each cabin is optimized by improving the structure of the middle box or adding guide plates; when it is calculated that the structure of the middle box flow channel, pre-treatment baffle and other structures account for more than 50% of the overall pressure drop and there are a large number of vortex areas, the shape of the relevant structures is optimized to greatly reduce the pressure drop; when the inlet velocity distribution of the bottom surface of the filter bag is uneven and the airflow impact is concentrated on the side close to the middle box, the shape and arrangement of the guide plate entering the filter bag are optimized to make the airflow distribution of the filter bag more uniform, thereby reducing the airflow impact of the filter bag near the box side; when it is diagnosed that the cloth bag near the box side is severely worn due to uneven distribution of airflow inlet from the filter bag and mainly concentrated on the side close to the box, and the unreasonable design of the guide plate, the shape of the guide plate is adjusted to a 90-degree arc plus two straight line segments, and the placement angle is changed from 30 degrees to the left to 30 degrees to the right. The center point of the arrangement position is basically the same but the height arrangement is more compact.

[0045] The present invention also provides a blast furnace bag filter optimization system based on CFD simulation, comprising:

[0046] Module M1 processes the three-dimensional CAD model of the blast furnace dust removal system to obtain a dust removal system model containing a fluid region that can be used for CFD simulation calculations;

[0047] Module M2, setting operating parameters according to actual conditions;

[0048] Module M3, discretizes the fluid area of ​​the dust removal system model into a grid to obtain a grid-divided model;

[0049] Module M4, based on the operating condition parameters and the meshed model, constructs and solves the computational fluid dynamics model to obtain the result data calculated by the CFD method;

[0050] Module M5, extracts the flow parameters of specific positions and cross sections from the result data obtained by CFD method calculation, which is used to visualize the flow state inside the dust collector and analyze the analysis results;

[0051] Module M6, optimizes vulnerable structures based on analysis results.

[0052] Compared with the prior art, the present invention has the following beneficial effects:

[0053] 1. We conducted in-depth research on dust collectors, involving CFD models and their calculation methods, and built a universal simulation model and process system. With this system, we can accurately locate vulnerable locations based on simulation results, and then carry out structural optimization work in a targeted manner. Through continuous iterations of design and simulation, we can effectively extend the service life of bag dust collectors while reducing their energy consumption.

[0054] 2. In the early design stage of blast furnace bag dust collectors, the present invention can effectively alleviate and solve the problems of dust collector wear and reduced service life caused by factors such as airflow, dust particle concentration and high-speed impact in a low-cost and accurate manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0056] Figure 1 Flow chart of a method for diagnosing the health status of a blast furnace bag filter based on CFD simulation in an embodiment of the present invention;

[0057] Figure 2 A diagram of a blast furnace bag filter in the background technology;

[0058] Figure 3 A three-dimensional preview diagram of a blast furnace dust removal system in an embodiment of the present invention;

[0059] Figure 4 is the preprocessor fluid calculation domain in the embodiment of the present invention;

[0060] Figure 5 is the dust removal cabin fluid calculation domain in the embodiment of the present invention;

[0061] Figure 6 is a middle side cross section of a pre-processor in an embodiment of the present invention;

[0062] Figure 7 It is the middle side cross section of the middle box body in the embodiment of the present invention;

[0063] Figure 8 is a top view of the middle section of the preprocessor in an embodiment of the present invention;

[0064] Fig. 9 is a preprocessor outlet speed cloud diagram in an embodiment of the present invention;

[0065] Fig.10 is a velocity vector diagram of the middle section of the box in the main dust collector in an embodiment of the present invention;

[0066] Fig.11 A cross-sectional vector diagram of a single dust removal chamber in an embodiment of the present invention;

[0067] Fig.12 This is a velocity distribution diagram of the bottom (inlet) cross section of the filter bag in the dust removal chamber in an embodiment of the present invention;

[0068] Fig.13 The figure is a structural diagram of an optimized guide plate according to an embodiment of the present invention.

[0069] Fig.14 A comparison diagram of the airflow direction of the optimized guide plate and the original guide plate according to an embodiment of the present invention, wherein the optimized guide plate (left) vs. the original guide plate (right);

[0070] Fig.15 This is a comparison diagram of the filter bag inlet velocity distribution of the optimized guide plate and the original guide plate according to an embodiment of the present invention, wherein the optimized guide plate (left) vs. the original guide plate (right). DETAILED DESCRIPTION

[0071] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0072] The present invention adopts computational fluid dynamics simulation technology to simulate the airflow and high-speed dust impact position in the bag filter in a computer at low cost, quickly and accurately, so that designers can optimize the structure of the filter, reduce the wear of the filter, and thus increase the service life of the filter.

[0073] Embodiment 1:

[0074] Figure 1 The present invention is a flowchart of a method for diagnosing the health status of a blast furnace bag filter based on CFD simulation in an embodiment of the present invention.

[0075] like Figure 1 As shown, the present invention proposes a blast furnace bag filter health status diagnosis method based on CFD simulation, comprising the following steps:

[0076] Step S1, processing the three-dimensional CAD model of the blast furnace dust removal system to obtain a dust removal system model containing a fluid region that can be used for CFD simulation calculations.

[0077] Figure 3 It is a three-dimensional preview diagram of the blast furnace dust removal system in an embodiment of the present invention.

[0078] like Figure 3As shown, in this embodiment, the three-dimensional CAD model of the blast furnace dust removal system includes: a preprocessor inlet 1, a dust outlet 2, a preprocessor internal baffle 3, a preprocessor 4, a middle box 5 and a middle box outlet 6, and the three-dimensional CAD model of the blast furnace dust removal system is initially in the form of a solid shell.

[0079] Since the calculation of the flow field requires a fluid area, the blast furnace dust removal system must be closed and the fluid area must be extracted to obtain the fluid calculation space required for CFD simulation.

[0080] Figure 4 is the preprocessor fluid calculation domain in the embodiment of the present invention; Figure 5 It is the dust removal cabin fluid calculation domain in the embodiment of the present invention.

[0081] In this embodiment, for the three-dimensional CAD model of the blast furnace dust removal system, the Boolean operation function of the CAD software is used to create a block larger than the model boundary, and the outer shell of the blast furnace dust removal system is subtracted from the block, and then the remaining model is refined, that is, the internal fluid domain of each part is retained, and the shell and the outer shell area are deleted. Figure 4 , 5 The dust collection system model shown contains the fluid regions that can be used for CFD simulation calculations.

[0082] The dust treatment sequence of the blast furnace dust removal system is: pre-processor 4, middle box 5 and middle box outlet 6.

[0083] Step S2, setting operating parameters according to actual conditions.

[0084] In order to accurately present the flow state of the dust collector during operation, it is necessary to set the operating conditions in the simulation process according to the actual situation, including the flow fluid characteristics (such as temperature, density) and the flow conditions at the boundary of the calculation domain (such as inlet mass flow rate, external pressure, etc.).

[0085] In this embodiment, the ambient temperature is set to 25 degrees and the air density is 1.2 kg / m 3 , dynamic viscosity is 959e-6N*s / m 2 , inlet flow rate is 140000m 3 / h, outlet pressure is 10Kpa.

[0086] During simulation, the corresponding calculation parameters are input into the software. Different parameters lead to different calculation results, and only one round of calculation is required, without the need to increase the number of rounds in equal proportions.

[0087] Step S3, performing discretization grid processing on the fluid region of the dust removal system model to obtain a grid-divided model.

[0088] In this implementation, computational fluid dynamics (CFD) methods use space and time discretization methods to solve flow problems.

[0089] Figure 6 is a middle side cross section of a pre-processor in an embodiment of the present invention; Figure 7 It is the middle side cross section of the middle box body in the embodiment of the present invention.

[0090] In this embodiment, the meshing software is used to spatially discretize the fluid region by using a meshing method combining a polyhedron boundary with a hexahedron core, and the following is obtained: Figure 6 The middle side section of the preprocessor shown and Figure 7 The model after meshing of the middle side section of the middle box is shown.

[0091] Step S4, based on the operating condition parameters and the meshed model, a computational fluid dynamics model is constructed and solved to obtain result data calculated by the CFD method.

[0092] Specifically, step S4 includes the following sub-steps:

[0093] Step S4.1, reading the meshed model obtained in step S3;

[0094] Step S4.2, setting the time model to steady state;

[0095] Step S4.3, set the turbulence model to the ke standard turbulence model and the standrad wall function model;

[0096] Step S4.4, the physical property parameters adopt the ambient temperature, air density and dynamic viscosity set in step S2;

[0097] Step S4.5, the boundary conditions are set to the inlet flow rate and outlet pressure set in step S2;

[0098] Step S4.6, the regional condition is set to the porous medium model;

[0099] Step S4.7, setting calculation parameters, such as iteration step size and convergence condition;

[0100] Step S4.8, setting the number of computer CPU cores for parallel solving;

[0101] Step S4.9, setting data extraction to extract the inlet and outlet pressures at each iteration time step;

[0102] Step S4.10, execute calculation to obtain result data obtained by CFD method calculation including various flow parameter results of all discrete grid cells.

[0103] Figure 8 It is a top view of the middle cross section of the pre-processor in the embodiment of the present invention.

[0104] The simulation result screenshot obtained in step S4 is as follows: Figure 8 shown.

[0105] Step S5, extracting the flow parameters of specific positions and cross sections from the result data obtained by the CFD method to visualize the flow state inside the dust collector, and analyzing to obtain the analysis results.

[0106] Specifically, the analysis steps of step S5 are as follows:

[0107] Step S5.1, according to the structure of the dust collector, the key areas are clearly defined as the pre-processor and the dust removal chamber.

[0108] Step S5.2, based on the key area, extract the preprocessor ( Figure 8 is a top view of the middle section of the preprocessor in an embodiment of the present invention; Fig. 9 is the pre-processor outlet velocity cloud diagram in the embodiment of the present invention) and the dust removal chamber ( Fig.10 is a velocity vector diagram of the middle section of the box in the main dust collector in an embodiment of the present invention; Fig.11 The flow parameters of a specific position and cross section of a single dust removal chamber (cross-sectional vector diagram) in an embodiment of the present invention are displayed, and the flow state inside the dust collector is visualized.

[0109] In this embodiment, step S5.2 is specifically as follows:

[0110] For the preprocessor exit speed distribution, such as Fig. 9 As shown in the figure, the velocity distribution is uneven due to the wind blocking by the baffle, and most of the flow is concentrated at the middle diagonal of the outlet (the outlet is the red frame area in the figure), and a vortex area is formed at the vertical corner in the lower left corner of the outlet, resulting in a low-speed flow area, which hinders normal flow.

[0111] Regarding the main dust collector box, such as Fig.10 As shown in the figure, the airflow flows from left to right, then downwards into each compartment, then flows out from the top of the compartment, and then passes through the middle box from left to right to the fan. As shown in the red box in the figure, the first compartment inlet of the middle box of the main dust collector is affected by the position, and the flow turning radius is small, making it difficult for air to turn and enter. In addition, as the position is arranged downstream (that is, to the right in the figure), the downstream compartment inlet flow rate gradually increases, which leads to uneven distribution of inflow in each compartment, and forms a recirculation area above the outlet flow channel, which limits the effective outflow of gas.

[0112] Step S5.3, based on the exit of the preprocessor extracted in step S5.2 (i.e. Fig. 9The flow parameters of the outlet section (shown by the preprocessor outlet velocity cloud diagram) and the presented velocity distribution are analyzed to analyze the unevenness of the velocity distribution and determine whether the placement of the internal baffles of the preprocessor is unreasonable.

[0113] Step S5.4, based on the extracted data in step S5.2 Figure 8 The velocity direction of the velocity vector in the top-down cross-section of the middle of the preprocessor determines the reasonable shell shape of the preprocessor and the placement position of the baffle.

[0114] Step S5.5, based on the speed direction of the speed vector diagram of the dust removal chamber extracted in step S5.2, determine whether the airflow direction at the dust removal chamber inlet is correct. If the airflow direction is incorrect, improve the dust removal chamber inlet direction based on the analysis results, and make corresponding adjustments and optimizations to the placement of the guide plate.

[0115] Fig.11 It is a cross-sectional vector diagram of a single dust removal chamber in an embodiment of the present invention.

[0116] like Fig.11 As shown in the figure, the flow of air in a single dust removal chamber: the airflow flows downward from the middle box into the two side chambers, and after entering the chamber, it impacts the guide plate, which blocks and guides the airflow. Among them, the second and third guide plates from the inside to the outside have obvious guiding effects. After being guided, the airflow is mainly divided into several parts: one part impacts the upper left with the second and third guide plates. One part impacts the wall downward and moves upward along the wall. Another part impacts the wall downward and swirls downward along the wall.

[0117] Fig.12 It is a velocity distribution diagram of the bottom (inlet) cross section of the filter bag in the dust removal chamber in an embodiment of the present invention.

[0118] like Fig.12 As shown, the filter bags near the inside are impacted by a larger amount of airflow, while the filter bags in the middle and outside are impacted by a smaller amount of airflow.

[0119] Step S5.6, based on the extracted data in step S5.2 Fig.10 The velocity vector diagram of the middle section of the box in the main dust collector is used to analyze the vortex distribution, identify the area with larger vortex as the invalid area, and remove the corresponding redundant structure in the dust collector.

[0120] Embodiment 2:

[0121] This embodiment provides a blast furnace bag filter optimization method based on CFD simulation, based on the blast furnace bag filter health status diagnosis method based on CFD simulation in the above embodiment 1, including the following steps:

[0122] Step S1, processing the three-dimensional CAD model of the blast furnace dust removal system to obtain a dust removal system model containing a fluid region that can be used for CFD simulation calculation;

[0123] Step S2, setting operating parameters according to actual conditions;

[0124] Step S3, performing discretization grid processing on the fluid region of the dust removal system model to obtain a grid-divided model;

[0125] Step S4, based on the operating condition parameters and the meshed model, construct and solve a computational fluid dynamics model to obtain result data calculated by the CFD method;

[0126] Step S5, extracting flow parameters at specific positions and cross sections from the result data calculated by the CFD method, for visualizing the flow state inside the dust collector, and analyzing to obtain analysis results;

[0127] Step S6, optimizing the vulnerable structure based on the analysis results.

[0128] The original blast furnace bag filter design was designed using empirical formulas, and did not find the location where the airflow impacted at high speed. However, the health status diagnosis method based on CFD simulation analysis can clearly see the location where the airflow impacted, and can be optimized based on this.

[0129] Specifically, based on the analysis results of step S5, when it is found that the flow rate from the middle box to the cabin inlet gradually increases and the inflow distribution of each cabin is uneven, the load of the rear cabin is obviously greater than that of the front cabin, and the service life is reduced compared to the general working conditions. By improving the middle box or adding guide plates, the flow distribution of each cabin is optimized, thereby reducing the unevenness of the flow distribution of each cabin.

[0130] When calculations show that the middle box flow channel and pre-treatment baffle structure account for more than 50% of the overall pressure drop and there are a large number of vortex areas, the shape of the relevant structures is optimized to reduce the pressure drop and reduce the fan energy consumption.

[0131] When the velocity distribution at the bottom inlet of the filter bag is uneven and the airflow impact is concentrated on the side close to the middle box body, the inner filter bag is more susceptible to impact and wear, and its life is reduced. By optimizing the shape and arrangement of the guide plate on the filter bag inlet, the airflow distribution on the filter bag inlet is made more uniform, thereby reducing the airflow impact on the filter bag near the box body and increasing the service life of the filter bag near the box body.

[0132] When it is diagnosed that the cloth bag near the box body is severely worn due to uneven airflow distribution at the filter bag inlet and mainly concentrated on the side near the box body, and due to unreasonable design of the guide plate, the guide plate is optimized.

[0133] According to actual cases, the deflector shape designed by experience originally had serious airflow impact near the box body, serious wear of the cloth bag near the box body, and high replacement frequency. The deflector designed originally mainly blocked the wind direction. The second and third deflectors facing the wind attracted a lot of wind, while causing the rest of the wind to deflect downward, resulting in too little air volume received by the subsequent deflectors.

[0134] Fig.13 The figure is a structural diagram of an optimized guide plate according to an embodiment of the present invention.

[0135] like Fig.13 As shown in the figure, the guide plate with optimized design is adjusted to a 90-degree arc plus two straight line segments, and the placement angle is changed from 30 degrees to the left to 30 degrees to the right. The center points of the guide plate are basically the same, but the height arrangement is more compact. This guides the wind to blow upward, reduces the flow separation caused by the large deflection angle of the wind direction, and reduces the influence of the inner guide plate on the subsequent outer guide plate receiving the air volume. The internal flow of the optimized guide plate is re-simulated, and it is clearly observed that the airflow distribution is more uniform, the pressure drop, airflow concentration and wear near the filter bag are reduced, the life of the bag filter is increased, and the energy consumption is reduced, achieving the optimization action based on the analysis results.

[0136] Fig.14 1 is a comparison diagram of the airflow direction of the optimized guide plate and the original guide plate according to an embodiment of the present invention, wherein the optimized guide plate (left) vs. the original guide plate (right).

[0137] like Fig.14 As shown in the figure, before optimization, the airflow is concentrated on the second and third guide plates, and the velocity distribution in the upper filter bag area is uneven. After optimization, the airflow is more evenly distributed in the first, third, fourth, and fifth plates, and the airflow distribution in the upper filter bag area is more even.

[0138] Fig.15 This is a comparison diagram of the filter bag inlet velocity distribution of the optimized guide plate and the original guide plate according to an embodiment of the present invention, wherein the optimized guide plate (left) vs. the original guide plate (right).

[0139] like Fig.15 As shown in the figure, after optimizing the guide plate, the velocity distribution at the filter bag inlet is more uniform than before optimization, the air flow velocity of the inner filter bag is reduced, the air flow concentration is reduced, and most of the air flow is dispersed in the outer area.

[0140] Embodiment 3:

[0141] This embodiment provides a blast furnace bag filter optimization system based on CFD simulation, based on the blast furnace bag filter optimization method based on CFD simulation shown in the above embodiment 2, including:

[0142] Module M1 processes the three-dimensional CAD model of the blast furnace dust removal system to obtain a dust removal system model containing a fluid region that can be used for CFD simulation calculations;

[0143] Module M2, setting operating parameters according to actual conditions;

[0144] Module M3, discretizes the fluid calculation area of ​​the dust removal system model into grids to obtain a grid-divided model;

[0145] Module M4, based on the operating condition parameters and the meshed model, calculates the fluid dynamics model and solves it to obtain the result data calculated by the CFD method;

[0146] Module M5, extracts the flow parameters of specific positions and cross sections from the result data obtained by CFD method calculation, which is used to visualize the flow state inside the dust collector and analyze the analysis results;

[0147] Module M6, optimizes vulnerable structures based on analysis results.

[0148] Those skilled in the art know that, in addition to realizing the system and its various devices, modules, and units provided by the present invention in a purely computer-readable program code, it is entirely possible to realize the same functions in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for realizing various functions can also be regarded as structures within the hardware component; the devices, modules, and units for realizing various functions can also be regarded as both software modules for realizing the method and structures within the hardware component.

[0149] In the description of the present application, it should be understood that the terms "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0150] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A blast furnace bag filter health status diagnosis method based on CFD simulation, characterized in that: The steps include: Step S1, processing the three-dimensional CAD model of the blast furnace dust removal system to obtain a dust removal system model containing a fluid region that can be used for CFD simulation calculation; Step S2, setting operating parameters according to actual conditions; Step S3, performing discretization grid processing on the fluid region of the dust removal system model to obtain a grid-divided model; Step S4, constructing and solving a computational fluid dynamics model based on the operating condition parameters and the meshed model to obtain result data calculated by a CFD method; Step S5, extracting flow parameters at specific positions and cross-sections from the result data calculated by the CFD method, for visualizing the flow state inside the dust collector, and analyzing to obtain analysis results.

2. The method for diagnosing the health status of a blast furnace bag filter based on CFD simulation according to claim 1 is characterized in that: In step S1, the three-dimensional CAD model of the blast furnace dust removal system includes: a preprocessor inlet, a dust outlet, a preprocessor internal baffle, a preprocessor, a middle box and a middle box outlet, and the three-dimensional CAD model of the blast furnace dust removal system is initially in the form of a solid shell.

3. The method for diagnosing the health status of a blast furnace bag filter based on CFD simulation according to claim 1 is characterized in that: The step S1 includes, for the three-dimensional CAD model of the blast furnace dust removal system, using the Boolean operation function in the CAD software, establishing a block larger than the model boundary, subtracting the outer shell of the dust removal system from the block, and then refining the remaining model.

4. The method for diagnosing the health status of a blast furnace bag filter based on CFD simulation according to claim 1 is characterized in that: In step S2, the ambient temperature is set to 25 degrees and the air density is set to 1.2 kg / m 3 , dynamic viscosity is 959e-6N*s / m 2 , inlet flow rate is 140000m 3 / h, outlet pressure is 10Kpa.

5. The method for diagnosing the health status of a blast furnace bag filter based on CFD simulation according to claim 1 is characterized in that: In the step S3, the fluid region is spatially discretized by meshing software using a meshing method combining polyhedral boundaries with hexahedral cores to obtain a meshed model.

6. The method for diagnosing the health status of a blast furnace bag filter based on CFD simulation according to claim 4 is characterized in that: The step S4 includes the following sub-steps: Step S4.1, reading the meshed model obtained in step S3; Step S4.2, setting the time model to steady state; Step S4.3, set the turbulence model to the ke standard turbulence model and the standrad wall function model; Step S4.4, the physical property parameters adopt the ambient temperature, air density and dynamic viscosity set in step S2; Step S4.5, the boundary conditions are set to the inlet flow rate and outlet pressure set in step S2; Step S4.6, the regional condition is set to the porous medium model; Step S4.7, setting calculation parameters, such as iteration step size and convergence condition; Step S4.8, setting the number of computer CPU cores for parallel solving; Step S4.9, setting data extraction to extract the inlet and outlet pressures at each iteration time step; Step S4.10, execute calculation to obtain result data obtained by CFD method calculation including various flow parameter results of all discrete grid cells.

7. The method for diagnosing the health status of a blast furnace bag filter based on CFD simulation according to claim 2 is characterized in that: The analysis steps of step S5 are as follows: Step S5.1, according to the structure of the dust collector, the key areas are identified as the pre-processor and the dust removal chamber; Step S5.2, based on the key area, extracting the flow parameters of the specific position and cross section of the pre-processor and the flow parameters of the specific position and cross section of the dust removal chamber, and visually displaying the flow state inside the dust collector; Step S5.3, based on the flow parameters of the specific position and cross section of the pre-processor extracted in step S5.2, analyzing the unevenness of the velocity distribution, and determining whether the placement of the internal baffles of the pre-processor is unreasonable; Step S5.4, based on the flow parameters of the specific position and cross section of the preprocessor extracted in step S5.2, determine a reasonable shell shape of the preprocessor and a placement position of the baffle; Step S5.5, based on the flow parameters of the specific position and cross section of the dust removal chamber extracted in step S5.2, determine whether the airflow direction at the dust removal chamber inlet is correct; if the airflow direction is incorrect, improve the dust removal chamber inlet direction according to the analysis results, and optimize the placement of the guide plate; Step S5.6, based on the flow parameters of the specific position and cross section of the dust removal chamber extracted in step S5.2, the vortex distribution is analyzed, the area with larger vortex is identified as an invalid area, and the corresponding redundant structure in the dust collector is removed.

8. A blast furnace bag filter optimization method based on CFD simulation, based on a blast furnace bag filter health status diagnosis method based on CFD simulation according to any one of claims 1 to 7, characterized in that: The steps include: Step S1, processing the three-dimensional CAD model of the blast furnace dust removal system to obtain a dust removal system model containing a fluid region that can be used for CFD simulation calculation; Step S2, setting operating parameters according to actual conditions; Step S3, performing discretization grid processing on the fluid region of the dust removal system model to obtain a grid-divided model; Step S4, constructing and solving a computational fluid dynamics model based on the operating condition parameters and the meshed model to obtain result data calculated by a CFD method; Step S5, extracting flow parameters at specific positions and cross sections from the result data calculated by the CFD method, for visualizing the flow state inside the dust collector, and analyzing to obtain analysis results; Step S6: optimizing the vulnerable structure based on the analysis result.

9. The blast furnace bag filter optimization method based on CFD simulation according to claim 8 is characterized in that: The step S6 comprises: Based on the analysis results, when it is found that the flow rate from the middle box to the cabin inlet gradually increases and the inflow distribution of each cabin is uneven, the flow distribution of each cabin is optimized by improving the structure of the middle box or adding guide plates; when it is calculated that the structure of the middle box flow channel, pretreatment baffle and other structures account for more than 50% of the overall pressure drop and there are a large number of vortex areas, the pressure drop is greatly reduced by optimizing the shape of the relevant structures; when the inlet velocity distribution of the bottom surface of the filter bag is uneven and the airflow impact is concentrated on the side close to the middle box, the airflow distribution of the filter bag is made more uniform by optimizing the shape and arrangement of the guide plate entering the filter bag, thereby reducing the airflow impact of the filter bag near the box side; when it is diagnosed that the cloth bag near the box side is severely worn due to uneven distribution of airflow at the filter bag inlet and mainly concentrated on the side close to the box, and due to unreasonable design of the guide plate, the shape of the guide plate is adjusted to a 90-degree arc plus two straight line segments, and the placement angle is changed from 30 degrees to the left to 30 degrees to the right. The center point of the arrangement position is basically the same but the height arrangement is more compact.

10. A blast furnace bag filter optimization system based on CFD simulation, characterized in that: include: Module M1 processes the three-dimensional CAD model of the blast furnace dust removal system to obtain a dust removal system model containing a fluid region that can be used for CFD simulation calculations; Module M2, setting operating parameters according to actual conditions; Module M3, discretizing the fluid region of the dust removal system model to obtain a meshed model; Module M4, based on the operating condition parameters and the meshed model, constructs and solves a computational fluid dynamics model to obtain result data calculated using a CFD method; Module M5, extracting flow parameters at specific positions and cross sections from the result data calculated by the CFD method, for visualizing the flow state inside the dust collector, and analyzing to obtain analysis results; Module M6, based on the analysis results, optimizes the vulnerable structure.

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