A flow channel optimization design method and system suitable for a polishing machine dust hood

Abstract

The application discloses a kind of flow channel optimization design method and system suitable for polishing machine dust hood. Including the following steps: first, determine the polishing dust size and dust speed of polisher;Then, set the initial structure parameters of polishing machine dust hood and build the three-dimensional grid model of polishing machine dust hood, then combine the polishing dust size and dust speed, the structure parameters of polishing machine dust hood are optimized and solved, and the optimal structure parameters are obtained, so as to complete the flow channel optimization design of polishing machine dust hood. The flow channel of the polishing machine dust hood is optimized and designed in the application, so that the polishing machine has higher dust collection efficiency, can effectively ensure the health of workers, and improve the polishing quality.

Description

Technical Field

[0001] This invention belongs to the field of fluid simulation technology, specifically relating to a flow channel optimization design method and system suitable for dust collection hoods of grinding machines. Background Technology

[0002] The installation of power cable accessories often involves grinding and polishing the cable surface. This installation typically takes place in confined cable tunnels or cable joint wells where air circulation is less efficient than outdoors. The grinding and polishing process generates a large amount of dust, which permeates the surrounding air. This necessitates spending excessive time cleaning the working environment and can even negatively impact the quality of the grinding. Furthermore, even with protective gear, prolonged exposure to dust can significantly affect the health of workers. Therefore, efficient dust control is crucial for a healthy working environment.

[0003] For grinding machines, the dust collection rate of the dust collection hood can be improved by optimizing the flow channel parameters, thereby reducing the dust generated by the grinding machine. Therefore, it is necessary to propose a flow channel optimization design method suitable for grinding machine dust collection hoods. Summary of the Invention

[0004] In response to the problems and needs existing in the background technology, this invention proposes a flow channel optimization design method and system suitable for dust collection hoods of grinding machines.

[0005] The technical solution of the present invention is as follows:

[0006] In a first aspect, the present invention proposes a flow channel optimization design method suitable for dust collection hoods of grinding machines, the method comprising the following steps:

[0007] (1) Determine the size and dust generation rate of the grinding dust from the grinding machine;

[0008] (2) Set the initial structural parameters of the dust collection hood of the grinding machine and construct a three-dimensional mesh model of the dust collection hood of the grinding machine. Then, combine the size of the grinding dust and the dust generation speed to optimize the structural parameters of the dust collection hood of the grinding machine and obtain the optimal structural parameters, thereby completing the flow channel optimization design of the dust collection hood of the grinding machine.

[0009] Furthermore, in (2), the structural parameters of the dust collection hood of the grinding machine include one or more combinations of the flow channel depth d of the dust collection hood, the distance x between the two rotating drive shafts of the grinding machine belt, and the suction port angle a.

[0010] Furthermore, (2) includes:

[0011] The internal flow channel of the dust collection hood of the grinding machine is dynamically simulated using simulation software. After the simulation is completed, a velocity cloud map of the fluid domain of the dust collection hood is generated. The structural parameters of the dust collection hood are optimized based on the velocity cloud map until the preset conditions are met and the optimal structural parameters are obtained.

[0012] Secondly, this invention proposes a flow channel optimization design system suitable for dust collection hoods of grinding machines, the system comprising:

[0013] The grinding data acquisition unit is used to acquire the size and dust generation speed of the grinding dust from the grinding machine;

[0014] Mesh model building unit, used to build a three-dimensional mesh model of the dust collection hood of the grinding machine based on the structural parameters of the dust collection hood;

[0015] The simulation unit is used to dynamically simulate the internal flow channel of the dust collection hood of the grinding machine based on the three-dimensional mesh model of the dust collection hood, as well as the size and dust generation speed of the grinding dust.

[0016] The optimization unit is used to adjust the structural parameters of the dust collection hood of the grinding machine based on the velocity cloud map in the fluid domain after simulation, until the optimal structural parameters are obtained.

[0017] Thirdly, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described in the first aspect above.

[0018] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in the first aspect above.

[0019] Fifthly, the present invention provides a computer program product comprising a computer program / instruction which, when executed by a processor, implements the steps of the method described in the first aspect above.

[0020] The beneficial effects of this invention are as follows:

[0021] 1. The shape design of the dust collection hood should conform to the requirements of fluid dynamics as much as possible to reduce airflow resistance. This invention adopts a design scheme that fits closely to the belt sander so that the airflow flows along the direction of the sander belt, reducing air turbulence and improving dust collection efficiency. Through a reasonable shell shape, dust can be guided to concentrate and smoothly enter the dust inlet, reducing dust diffusion and overflow, thus achieving the initial structural design of the dust collection hood.

[0022] 2. The present invention uses a dust generation speed measuring device to measure the dust generation speed and directly obtain the dust generation speed.

[0023] 3. This invention uses fluid simulation to analyze the internal flow field of the initial structure, tracks the movement trajectory of dust, analyzes the simulation results, calculates the dust collection rate for different structural parameters, gradually optimizes each parameter, and finally obtains a dust collection hood structure model with a high dust collection rate. Attached Figure Description

[0024] Figure 1 This is a flowchart of the method of the present invention;

[0025] Figure 2 Flowchart for measuring the size of grinding dust;

[0026] Figure 3 A schematic diagram of a dust generation velocity measuring device;

[0027] Figure 4 A cross-sectional view of the 3D model of the dust collection hood of a high-voltage cable grinding machine;

[0028] Figure 5 A schematic diagram of the mesh generation for the fluid domain;

[0029] Figure 6 A side view of the 3D model of the dust collection hood of the cable polishing machine;

[0030] Figure 7 Name the boundary conditions of the dust collection hood and their corresponding locations. Detailed Implementation

[0031] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0032] like Figure 1 As shown, the flow channel optimization design method for dust collection hoods of grinding machines proposed in this invention includes the following steps:

[0033] (1) Determine the size and dust generation rate of the grinding dust from the grinding machine;

[0034] Specifically:

[0035] The size of the grinding dust from the grinder depends on the mesh size of the abrasive belt. After selecting the abrasive belt mesh size, the high-voltage cable is ground to obtain the dust diameter. The relationship between the abrasive belt mesh size and the dust size is tested using a camera imaging method. The specific process is as follows:

[0036] First, the cable insulation layer was flexibly polished using 40-mesh, 80-mesh, and 120-mesh abrasive belts in sequence. Black cardstock was placed beneath the polishing area to collect the dust generated during polishing. Simultaneously, a 3mm diameter control disc was placed on the collection paper as a reference for image scale. Based on camera imaging principles, a high-definition camera was used to capture images of the naturally distributed dust on the black collection paper. This effectively captures the actual size distribution of the dust, facilitating subsequent analysis. The experiment was divided into three groups based on the mesh size of the abrasive belts: 40-mesh, 80-mesh, and 120-mesh. To minimize random errors, 50 image acquisitions were performed for each group.

[0037] Next, each group of images is processed. For example... Figure 2 As shown, the image processing specifically includes: first, binarizing the image. Dust appears white in the binarized image. Ellipse fitting is performed on the white area to obtain the major and minor axis parameters of the dust, which are then used to estimate the equivalent circle diameter. This method more accurately reflects the true shape of the dust and reduces fitting errors, thereby improving the accuracy and reliability of the experimental results. Then, the major and minor axes of the fitted ellipse are output to an Excel spreadsheet, and the equivalent diameter is calculated using these axes. After removing the maximum value of the equivalent diameter (i.e., the diameter of the control circle), 6000 sample dust diameters are randomly selected. Other camera images are processed using the same method to ensure a consistent sample size. The pixel size of the 6000 dust diameters is distributed within 60 equidistant intervals of 0-30 pixels, thus obtaining the probability density distribution of dust diameter in each camera image. The results show that the dust pixel size appears most frequently around 5.25.

[0038] To aggregate and calculate data from each group of 50 imaging studies and ensure consistent scaling across all images, the samples need to be scaled. After selecting the pixel diameter of 6000 dust samples for each study, the scale of these 6000 dust samples is adjusted based on the ratio of the pixel size of the initial control circle to the pixel sizes of all other control circles. This step ensures the comparability of dust diameter data obtained at a uniform scale.

[0039] The probability density distributions of 40-mesh, 80-mesh, and 120-mesh abrasive belts in 10, 20, 30, 40, and 50 experiments were compared using the above method. The dust distribution pattern of abrasive belts with different mesh sizes under different grinding times was obtained. By calculating the error s before and after each additional 10 sets of data for different mesh sizes of abrasive belts, the following formula was obtained, where n represents the average of 10 times as 1 calculation.

[0040]

[0041] Where S is the average absolute error of the probability density values ​​of each particle size range relative to the previous calculation results after adding 10 sets of experimental data; This is the probability density value of the i-th particle size interval in the (n-1)-th calculation (i.e., the data accumulated in the previous calculation); This is the probability density value of the i-th particle size interval in the n-th calculation (i.e., the current accumulated n sets of data).

[0042] After calculating the error, it was found that the average error of the interval decreased after every 10 additional sets of data, indicating that the data had stabilized. Therefore, the results of 50 experiments have basically converged, and there is no need to continue adding dust distribution data from image acquisition.

[0043] Based on the dust distribution patterns of different mesh abrasive belts under different polishing cycles obtained above, the average pixel diameter of dust from polishing with 40-mesh, 80-mesh, and 120-mesh abrasive belts can be calculated using the following formula according to camera imaging principles:

[0044]

[0045] Where D is the actual diameter of the reference circle, which is constant at 3 mm; d r d is the pixel equivalent diameter of the first image of the reference circle; m d is the average pixel diameter of the dust particles; d is the actual average diameter of the dust particles.

[0046] The actual average diameter d of the dust can be calculated using the formula above. There is an inverse relationship between the actual diameter of the dust and the mesh size of the abrasive belt; that is, the larger the mesh size of the abrasive belt, the smaller the diameter of the dust produced. This indicates that the mesh size of the abrasive belt plays a crucial role in the grinding process, directly affecting the formation and size of the dust.

[0047] Dust rise velocity is a crucial basis for optimizing the flow channel design of the dust collection hood in high-voltage cable grinding machines. It refers to the speed of the airflow as dust particles are carried upwards to a certain height by the airflow, maintain that height, and oscillate back and forth. Therefore, measuring the dust rise velocity is significant for further improving the efficiency of the dust collection system and optimizing the flow channel design. It is the velocity of a single dust particle moving within a horizontal cross-section under the influence of airflow. It can be derived from the mathematical description of dust particle motion proposed by Haim Kalman. The expression is as follows:

[0048]

[0049] in, Archimedes numbers, The dust particle's velocity.

[0050] In one feasible implementation, the structural diagram of the dust generation rate measuring device is as follows: Figure 3 As shown, the dust velocity measuring device is divided into an inlet stabilization section, a test section, and an expansion section along the airflow direction. These sections are sealed together to form an integrated direct-flow wind tunnel structure. The inlet stabilization section is a 120mm × 120mm square channel with a hollow plate installed inside. The outlet end of the square channel connects to the inlet end of the test section. A contraction structure with a contraction ratio of 1.5 is installed from the inlet of the inlet of the stabilization section to the inlet of the test section to rectify the uneven airflow at the inlet into a uniform airflow, thereby reducing turbulence and thinning the boundary layer. The test section is a straight pipe with an 80mm × 80mm square cross-section and a length of 300mm. Measuring holes are opened on the upper wall of the test section for the probe of the anemometer to be inserted to measure the wind speed at the cross-section. The bottom wall of the test section is used to place the dust sample to be tested. The expansion section is connected to the outlet end of the test section, and its outlet cross-section is adapted to the inlet of a continuously variable speed fan to smoothly guide the airflow out of the test section and prevent separation, thereby reducing pressure loss.

[0051] Before testing, the insulation layer of the XLPE cable was first polished using sandpaper of the mesh size to be tested. A small black square of PLA (polylactic acid) material (10mm×10mm×1mm) was used as a collection carrier, placed below the polished area to collect naturally settling polishing dust, ensuring a uniform layer of dust on the square's surface. This square served as the sample for dust generation rate testing. During testing, the PLA square carrying the dust was placed in the center of the bottom wall of the test section. After closing the measuring hole in the test section, a continuously variable speed fan was started, and the wind speed was slowly and continuously increased from 0 m / s by adjusting the knob. The change in dust accumulation on the surface of the PLA square was continuously observed during the wind speed increase. When the dust began to gradually decrease, an anemometer probe was inserted into the test section through the measuring hole, with the direction mark on the probe facing the direction of the incoming flow, to record the current cross-sectional wind speed value in real time. When the amount of dust accumulated on the surface of the small square belt no longer decreases with increasing wind speed, the wind speed is stopped, and an image of the dust distribution on the surface of the small square belt is acquired. The dust distribution images before and after the fan is turned on are then binarized, and an ellipse fitting method is used to identify dust particles in the image and count the number of particles. The dust generation rate is calculated using the formula: the number of dust particles before the fan is turned on minus the number of particles remaining when the dust quantity no longer changes, divided by the number of particles before the fan is turned on. If the calculated dust generation rate reaches 90% or higher, the recorded wind speed is determined to be the dust generation rate corresponding to the current belt mesh size. If the dust generation rate is lower than 90%, the wind speed is slowly increased, and the above observation, recording, and calculation steps are repeated until the dust generation rate meets the requirements. The above test is repeated at least ten times under different belt mesh sizes, and the arithmetic mean of the dust generation rates obtained from each test is taken as the dust generation rate corresponding to that belt mesh size.

[0052] (2) Set the initial structural parameters of the dust collection hood for the grinding machine and construct a three-dimensional mesh model of the dust collection hood. Then, combine the size of the grinding dust and the dust generation speed to optimize the structural parameters of the dust collection hood and obtain the optimal structural parameters, thereby completing the flow channel optimization design of the dust collection hood. In the optimization solution, simulation software is used to dynamically simulate the internal flow channel of the dust collection hood. After the simulation, a velocity cloud map is generated in the fluid domain of the dust collection hood. The structural parameters of the dust collection hood are optimized according to the velocity cloud map until the preset conditions are met and the optimal structural parameters are obtained.

[0053] In one feasible implementation, the structural parameters of the dust collection hood of the grinder include one or more combinations of the following: the flow channel depth d of the dust collection hood, the distance x between the two rotating drive shafts of the grinder belt, and the suction port angle α. A schematic diagram of the structural parameters is shown below. Figure 4 and Figure 6 As shown.

[0054] Dust collection rate of the dust collection hood of the grinding machine The formula used to determine the dust collection capacity of a dust collection hood structure is as follows:

[0055]

[0056] Where escape represents the amount of dust captured by the pressure outlet, and number represents the total amount of incident dust.

[0057] In one feasible implementation, (2) specifically includes:

[0058] First, the air portion in the 3D model of the dust collection hood of the grinding machine is taken as the fluid domain of the 3D model of the dust collection hood.

[0059] The model is then meshed using the meshing component in simulation software to obtain a 3D mesh model of the dust collection hood of the grinding machine. Specifically, Fluent is preferred as the mesh solver, with 10mm tetrahedral mesh elements. Locally, 1mm and 0.1mm meshes are used for refinement to ensure a mesh skewness of less than 0.8. Figure 5 As shown, when all grid skewnesses are less than 0.8, the grid quality is considered good.

[0060] During the simulation, the general conditions and parameters of the physical model are set as follows:

[0061] The calculation type adopted is steady-state calculation. The working pressure is set to standard atmospheric pressure of 101325 Pa, the gravitational acceleration is 9.81 m / s², and the direction is along the negative Z-axis. The working density is 1.225 kg / m³. In the discrete phase model settings, the coupled calculation of the discrete phase and the continuous phase is enabled, with a coupling calculation interval of ten iterations. The Saffman lift and virtual mass force experienced by the XLPE dust moving in the airflow are considered simultaneously, with a virtual mass force coefficient of 0.5. The dust jet source type is a surface jet source. The incident surface is selected as the vertical plane at the tangent position of the abrasive belt and the cable insulation layer. The width of this incident surface is consistent with the width of the abrasive belt, which is 30 mm, and the length is 5 mm. The diameter of the incident dust particles is set according to the test results of the grinding dust size. The total number of incident dust particles is set as needed. The fluid medium is air, and the discrete phase particle material is cross-linked polyethylene.

[0062] The boundary conditions are set as follows:

[0063] The pressure inlet In is open to the atmosphere, and its gauge pressure is set to zero Pa. The pressure outlet Out has a gauge pressure set to -970 Pa. The boundary behavior of the discrete phase at both the inlet and outlet is set to escape. The boundary behavior of the discrete phase on the inner wall of the dust collection hood is set to reflection. The sand belt has a significant impact on the flow field inside the dust collection hood; therefore, the surface of the sand belt is divided into four moving walls, named the first moving wall, the second moving wall, the third moving wall, and the fourth moving wall, with corresponding wall angular velocities of V1, V2, V3, and V4, respectively. Figure 7 As shown in the diagram, the first moving wall moves along the negative X-axis at a speed of 10 meters per second; the second moving wall rotates clockwise at an angular velocity of 81.97 radians per second with the coordinate (0,131,0) as its center of rotation; the third moving wall rotates counterclockwise at an angular velocity of 308 radians per second with the coordinate (-80,0,0) as its center of rotation; and the fourth moving wall rotates counterclockwise at an angular velocity of 308 radians per second with the coordinate (80,0,0) as its center of rotation.

[0064] Since points smaller than the dust-raising velocity have no reference value for the air's ability to carry dust, the air velocity inside the dust collection hood must be greater than the dust-raising velocity.

[0065] The dust collection hood of the grinding machine in this invention contains both gas and solid phases within its flow channel, constituting a multiphase flow calculation. During the solution process, selectable solution methods include SIMPLE (a semi-implicit algorithm for pressure-coupled equations), SIMPLEC (a semi-implicit uniform algorithm for pressure-coupled equations), PISO (a pressure implicit splitting operator algorithm), and Coupled (a coupled solution algorithm). The number of iterations is set to 200 steps.

[0066] Simulation analysis can obtain simulation data for each parameter size. Based on the dust collection rate calculation method, the dust collection capacity of the dust collection hood under different geometric parameters can be obtained. This invention first conducts a single specific analysis and design of geometric parameters such as the flow channel depth d of the dust collection hood, the distance x between the two rotating drive shafts of the sander belt, and the suction port angle a, and then conducts a combined analysis of geometric parameters with larger dust collection rates.

[0067] The specific optimization steps are as follows:

[0068] The first step, due to the influence of grinding wheel thickness and portability, kept the axis spacing x and suction port angle a as initial values ​​and kept constant. The flow channel depth d was set within the range of 50mm to 70mm, and values ​​were taken in 5mm increments for simulation to obtain the trend of dust collection rate changing with the flow channel depth of the dust collection hood. The average velocity in the fluid domain corresponding to each flow channel depth value was calculated, and the d value corresponding to the highest average velocity was fixed as the optimal flow channel depth; the dust collection rate was highest when d=50mm. Comparison of velocity contour maps showed that the higher the dust collection rate, the larger the area of ​​the high-speed region.

[0069] The second step involves determining the center-to-center distance of the grinding wheels based on the length of the sanding belt. The channel depth *d* of the dust collection hood is then determined based on the trend of dust collection rate variation with the channel depth. Keeping the suction port angle *a* at its initial value and maintaining it constant, the optimal channel depth determined in the first step is used as a fixed value for *d*. The shaft spacing *x* is set within the range of 155mm to 185mm, incremented by 5mm, and simulations are performed to obtain the trend of dust collection rate variation with the distance *x* between the two outer arc centers of the dust collection hood. The average velocity corresponding to each *x* value is calculated, and the *x* value corresponding to the highest average velocity is fixed as the optimal shaft spacing. The dust collection rate is highest when *x* = 155mm. Comparison of velocity contour maps reveals that a higher dust collection rate results in a larger high-speed region.

[0070] The third step involves using the optimal channel depth determined in the first step and the optimal axis spacing determined in the second step as fixed values. The suction port angle 'a' is set to range from 0° to 90°, with values ​​incremented by 10° each time to simulate the trend of dust collection rate changing with the suction port angle. The average velocity corresponding to each 'a' value is calculated, and the 'a' value corresponding to the highest average velocity is determined as the optimal suction port angle. Comparison of velocity contour maps shows that when 'a' is 60°, the air velocity distribution is more uniform and the area of ​​the low-speed region is smaller.

[0071] Based on the optimization results of various geometric parameters of the dust collection hood of the high-voltage cable grinder, it can be found that when d=50mm, x=155mm, and a=60°, the dust collection hood enhances the flow field's ability to carry dust, thereby achieving efficient dust collection and improving the dust collection efficiency of the grinder's dust collection hood.

[0072] The average speed mentioned above is calculated based on the velocity contour map. The specific calculation steps are as follows:

[0073] 1) Read data: Read data from the Excel file corresponding to the speed cloud map and filter out the data that are greater than the dust generation speed.

[0074] 2) Use the actual coordinates of the input points as grid points: directly use the coordinates of the input data as grid points.

[0075] 3) Interpolate onto the grid: Use the griddata function to interpolate velocity values ​​at grid points.

[0076] 4) Calculate the volume of each small cube: Assuming that the distance between the input points is relatively uniform, take the average distance between adjacent points as the side length of each small cube.

[0077] 5) Calculate the total velocity: Weight the interpolated velocity values ​​by volume and calculate the total velocity.

[0078] 6) Calculate the total volume: Calculate the total volume of the entire mesh.

[0079] 7) Calculate the average speed: Divide the total speed by the total volume to get the average speed.

[0080] The present invention proposes a flow channel optimization design system for dust collection hoods of grinding machines, comprising:

[0081] The grinding data acquisition unit is used to acquire the size and dust generation speed of the grinding dust from the grinding machine;

[0082] Mesh model building unit, used to build a three-dimensional mesh model of the dust collection hood of the grinding machine based on the structural parameters of the dust collection hood;

[0083] The simulation unit is used to dynamically simulate the internal flow channel of the dust collection hood of the grinding machine based on the three-dimensional mesh model of the dust collection hood, as well as the size and dust generation speed of the grinding dust.

[0084] The optimization unit is used to adjust the structural parameters of the dust collection hood of the grinding machine based on the velocity cloud map in the fluid domain after simulation, until the optimal structural parameters are obtained.

[0085] The present invention proposes a computer device including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps of a flow channel optimization design method applicable to the dust collection hood of a grinding machine.

[0086] The present invention proposes a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of a flow channel optimization design method applicable to the dust collection hood of a grinding machine.

[0087] The present invention proposes a computer program product comprising a computer program / instruction which, when executed by a processor, implements the steps of a flow channel optimization design method applicable to a dust collection hood of a grinding machine.

[0088] The above embodiments are used to explain and illustrate the present invention, but not to limit the present invention. Any modifications and changes made to the present invention within the spirit and scope of the claims shall fall within the protection scope of the present invention.

Claims

1. A flow channel optimization design method suitable for dust collection hoods of grinding machines, characterized in that, Includes the following steps: (1) Determine the size and dust generation rate of the grinding dust from the grinding machine; (2) Set the initial structural parameters of the dust collection hood of the grinding machine and construct a three-dimensional mesh model of the dust collection hood of the grinding machine. Then, combine the size of the grinding dust and the dust generation speed to optimize the structural parameters of the dust collection hood of the grinding machine and obtain the optimal structural parameters, thereby completing the flow channel optimization design of the dust collection hood of the grinding machine.

2. The flow channel optimization design method for a dust collection hood of a grinding machine according to claim 1, characterized in that, In (2), the structural parameters of the dust collection hood of the grinding machine include the flow channel depth of the dust collection hood. d The distance between the two rotating drive shafts of the sander belt x and the angle of the suction port a One or more combinations thereof.

3. The flow channel optimization design method for a dust collection hood of a grinding machine according to claim 1, characterized in that, The (2) mentioned above includes: The internal flow channel of the dust collection hood of the grinding machine is dynamically simulated using simulation software. After the simulation is completed, a velocity cloud map of the fluid domain of the dust collection hood is generated. The structural parameters of the dust collection hood are optimized based on the velocity cloud map until the preset conditions are met and the optimal structural parameters are obtained.

4. A flow channel optimization design system suitable for dust collection hoods of grinding machines, characterized in that, include: The grinding data acquisition unit is used to acquire the size and dust generation speed of the grinding dust from the grinding machine; Mesh model building unit, used to build a three-dimensional mesh model of the dust collection hood of the grinding machine based on the structural parameters of the dust collection hood; The simulation unit is used to dynamically simulate the internal flow channel of the dust collection hood of the grinding machine based on the three-dimensional mesh model of the dust collection hood, as well as the size and dust generation speed of the grinding dust. The optimization unit is used to adjust the structural parameters of the dust collection hood of the grinding machine based on the velocity cloud map in the fluid domain after simulation, until the optimal structural parameters are obtained.

5. The flow channel optimization design system for a dust collection hood of a grinding machine as shown in claim 4, characterized in that, The structural parameters of the dust collection hood for the grinding machine include the flow channel depth of the dust collection hood. d The distance between the two rotating drive shafts of the sander belt x and the angle of the suction port a One or more combinations thereof.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the flow channel optimization design method for a dust collection hood of a grinding machine as described in claim 1.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the flow channel optimization design method for a dust collection hood of a grinding machine as described in claim 1.

8. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instruction is executed by the processor, it implements the steps of the flow channel optimization design method for a dust collection hood of a grinding machine as described in claim 1.

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