A gas-solid two-phase one-way transient coupling optimization design method for the dust collection hood of an edge banding machine

Abstract

The present invention provides a gas-solid two-phase one-way transient coupling optimization design method for an edge banding machine dust hood. The method includes: firstly, testing the dust hood in an operating state to obtain data such as inlet and outlet air pressure, chip speed, shape and size, and chip removal rate; then establishing a CFD simulation model, performing simulation calculations, and outputting transient flow field information; then comparing the flow field simulation results with the test data to verify the reliability of the flow field simulation; then establishing a discrete element simulation model; then transmitting the transient flow field information to the discrete element analysis software Rocky to perform gas-solid one-way transient coupling simulation; then comparing the discrete element simulation results with the test data to verify the reliability of the particle simulation; finally, based on the simulation results, optimizing the dust hood and performing gas-solid simulation, and determining whether the design requirements are met based on the simulation results. The gas-solid one-way transient coupling simulation of the present invention has a short calculation time while ensuring accuracy, and the CFD and Rocky coupling interface is simple, convenient, and efficient.

Description

Technical Field

[0001] The invention relates to the technical field of wood processing, in particular to a gas-solid two-phase unidirectional transient coupling optimization design method for a dust collection hood of an edge banding machine. Background Art

[0002] The edgebanding process for furniture panels like medium-density fiberboard, blockboard, solid wood, particleboard, polymer door panels, and plywood generates a large amount of swarf and dust. Woodworking edgebanding machines are typically equipped with dust collection devices. However, existing dust hoods are ineffective at removing swarf, allowing a large amount of swarf and dust to escape during operation, leading to a large accumulation of swarf, which impacts the work environment and can easily cause equipment failure. This requires workers to regularly clean up the swarf, which is time-consuming and labor-intensive, significantly impacting work efficiency.

[0003] The current design of woodworking machinery dust hoods mainly relies on empirical methods and conventional CFD methods. The empirical method optimizes the dust hood through continuous experimentation, which has a long R&D cycle and high costs, and is not conducive to the rapid updating of products. Conventional CFD methods can only simulate the movement of spherical chip particles. For example, Chinese patent CN202010402660.8 discloses an optimization design method for the dust hood of an edge banding machine. It uses conventional CFD methods for optimization design. Although it can basically meet the optimization requirements, the actual chip particles present different shapes during the cutting process due to the thickness, width, material, and cutting speed of the edge banding. Therefore, conventional CFD methods cannot accurately simulate the movement of actual chip particles of different shapes, which is not conducive to the optimization of the dust hood.

[0004] Simulating realistic chip particle motion is typically accomplished through computational fluid dynamics coupled discrete element methods. Currently, unidirectional steady-state coupling and bidirectional transient coupling are commonly used. However, unidirectional steady-state coupling cannot simulate rotating structures or conditions requiring time considerations, while bidirectional transient coupling is computationally expensive and resource-intensive, resulting in low computational efficiency. Furthermore, the commonly used Fluent and EDEM discrete element coupling requires a separate, complex interface design and is difficult to operate. Summary of the Invention

[0005] The purpose of the present invention is to provide a dust hood gas-solid two-phase unidirectional transient coupling optimization design method that saves manpower and material resources, has a short R&D cycle, and has low calculation time cost. The dust hood optimized by this method has a high chip removal rate.

[0006] In order to achieve the above purpose, the technical solution adopted is as follows: a gas-solid two-phase unidirectional transient coupling optimization design method for the edge banding machine dust collection hood, characterized in that it includes the following steps.

[0007] S1, data acquisition: Test the existing dust hood to obtain the dust hood inlet and outlet air pressure, the initial velocity, direction, shape and size of the chip particles and the chip removal rate under working conditions.

[0008] S2, flow field simulation: Establish a CFD simulation model for the existing dust hood, set the outlet conditions of the simulation model based on the outlet air pressure obtained from the test; set the transient flow field information to be output in F2R file format, and simulate and calculate the dust hood flow field information; compare the flow field simulation results with the test data to verify the reliability of the flow field simulation.

[0009] The specific operations of setting the transient flow field information output and simulating the flow field information of the dust hood in step S2 include: (1) for Fluent-Rocky one-way transient coupling, by setting Record one-way transient data, start recording the flow field and mesh information of each time step and save them in F2R, dat, mesh files; (2) set the time step length and the number of time steps, and perform iterative calculations; (3) stop recording the flow field and mesh information again by Record one-way transient data.

[0010] S3, particle simulation: The chip particle simulation parameters are set according to the chip speed, direction, shape and size obtained from the test, and a discrete element simulation model is established. The F2R file containing the transient flow field information is passed to the discrete element analysis software Rocky for a one-way gas-solid transient coupling simulation to obtain the chip motion trajectory and the chip removal rate of the dust hood. This step can achieve one-way transient coupling between CFD and discrete element Rocky. The coupling interface is simple and easy to operate. The chip particle discrete element simulation results are compared with the test data to verify the reliability of the chip particle simulation.

[0011] The operations of setting chip particle simulation parameters and transmitting transient flow field data in step S3 specifically include: (1) importing the dust hood geometric model in the discrete element software Rocky: importing the cas file saved by Fluent, and removing the inlet and outlet wall parts of the dust hood model in Rocky; (2) recreating the chip particle inlet in Rocky: using the Circular inlet type, setting the particle inlet center coordinates, radius, alignment angle and incline angle according to the actual cutting position point; (3) setting the chip particle material properties; (4) setting the chip particle shape and size: using spherical polygon (sphero-polygon) and coal block (briquette) types to set chip particles of different shapes; (5) through continuous injection sets the incident flow rate, speed, direction, start time and end time of the chip particles; (6) Create a one-way transient coupling link between fluent and Rocky in Rocky, import the F2R file that records the flow field information into Rocky, and Rocky reads the flow field information and grid information of each time step at one time and reserves it for subsequent particle simulation.

[0012] S4, Optimization design: Based on the gas-solid two-phase one-way transient coupling simulation results, optimize the design of the dust hood; perform one-way transient simulation of the flow field and particle field on the optimized dust hood, and determine whether it meets the design requirements based on the simulation results.

[0013] Furthermore, the test in step S1 specifically includes: (1) using a wind pressure gauge to measure the pressure and wind speed at the inlet and outlet of the dust hood; (2) using a high-speed camera to shoot the movement process of the cutting particles, and obtaining the movement speed, direction and distribution state of the cutting particles through image processing technology; (3) obtaining the chip removal rate of the dust hood by weighing method; first, all the cutting particles on the edge banding machine are cleaned up; secondly, the edge banding machine is started to bandage a certain number of furniture boards; thirdly, the cutting particles sucked away by the dust hood outlet and other cutting particles that are not sucked away are collected separately; finally, the collected cutting particles are weighed separately, and the weight of the cutting particles sucked away divided by the weight of all cutting particles is the cutting removal rate.

[0014] Furthermore, the operation of setting the outlet condition of the simulation model in step S2 includes: (1) establishing a dust hood geometric model in the preprocessor, constructing a rotating domain and an external flow field static domain, dividing the flow field grid, and setting the interface between the rotating domain and the static domain as an interface; (2) setting a CFD model in the solver; wherein the SST K-ω turbulence model is adopted, the pressure-velocity coupling solution adopts the SIMPLEC algorithm, and a discrete format with second-order accuracy or above is adopted; a sliding grid is used to simulate the tool rotation motion; the outlet pressure boundary condition is the outlet pressure value obtained by the test in step S1, and the pressure at the inlet is atmospheric pressure.

[0015] Furthermore, the specific operations of obtaining the chip motion trajectory and the chip removal rate of the dust hood in step S3 include:

[0016] (1) Set the particle force model; the particle force model is as follows:

[0017]

[0018]

[0019] Where m p is the particle mass, g is the acceleration due to gravity, F c is the contact force on the particles, including the normal force and tangential force when particles contact each other and particles contact the wall; F f→p is the force exerted by the fluid on the particles; v p is the particle velocity; ω p is the particle angular velocity; J p is the particle moment of inertia; M c is the contact force torque, including the contact torque caused by the tangential contact force and rolling friction; M f→p is the torque of the fluid on the particle;

[0020] When the particle density is much greater than the fluid density, the lift and virtual mass force are ignored, and the force exerted by the fluid on the particle is mainly the pressure gradient force. and drag force F D ,therefore:

[0021]

[0022] in,

[0023]

[0024]

[0025] Where C D is the drag coefficient, and its value is:

[0026]

[0027]

[0028] A=exp(2.3288-6.4581φ+2.4486φ 2 )

[0029] B=0.0964+0.5565φ

[0030] C=exp(4.905-13.8944φ+18.4222φ 2 -10.2599φ 3 )

[0031] D=exp(1.4681-12.2584φ-20.7322φ 2 +15.8855φ 3 )

[0032] Particle sphericity

[0033] Where,

[0034] V p is the particle volume

[0035] is the local pressure gradient

[0036] u is the velocity vector of the fluid

[0037] A' is the projected area of ​​the particle in the flow direction

[0038] A sph is the surface area of ​​a spherical particle that is equal to the actual particle volume

[0039] A p is the actual surface area of ​​the particle

[0040] The torque model of the particle subjected to the fluid is:

[0041]

[0042]

[0043]

[0044]

[0045] (2) When the fluid is in a turbulent state, the particles are also affected by the turbulent diffusion force caused by the pulsating velocity. At this time:

[0046]

[0047] is the average velocity of the fluid, u′ is the pulsating velocity;

[0048] (3) Set the calculation time, output result step size, and iterate the calculation;

[0049] (4) The Rocky post-processor is used to display the particle distribution and calculate the dust removal rate of the dust hood.

[0050] The present invention achieves the following beneficial effects: by coupling CFD with Rocky, it implements a one-way transient gas-solid two-phase coupling simulation. This allows for the simulation of both the motion of real chip particles and time-sensitive operating conditions, while avoiding the high computational resource requirements and lengthy computation times associated with bidirectional coupling. The CFD-Rocky coupling eliminates the need for a separate coupling interface, resulting in a simple, convenient, and easy-to-use interface. This method accurately simulates the velocity and pressure fields within a hood, as well as the motion fields of chip particles of varying shapes. This method can guide hood optimization, reduce design costs, and shorten development cycles. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 The present invention is a flow chart of the gas-solid two-phase unidirectional transient coupling optimization design method for the edge banding machine dust collection hood.

[0052] Figure 2 Schematic diagram of particles with different shapes.

[0053] Figure 3 This is a structural diagram of the initial model of the dust hood.

[0054] Figure 4 This is the pressure cloud diagram of the middle section of the initial model of the dust collector during the simulation process.

[0055] Figure 5 Velocity vector diagram of the middle section of the initial model of the dust collector during the simulation process.

[0056] Figure 6 The distribution diagram of spherical chip particles in the single CFD simulation of the initial model of the dust collector.

[0057] Figure 7 This is the distribution diagram of block particles in the CFD-Rocky one-way transient coupling simulation of the initial model of the dust collector.

[0058] Figure 8 The distribution diagram of flake particles in the CFD-Rocky one-way transient coupling simulation of the initial model of the dust collector.

[0059] Figure 9 This is the strip particle distribution diagram of the CFD-Rocky one-way transient coupling simulation of the initial model of the dust collector.

[0060] Figure 10The distribution diagram of blocky particles after optimizing the dust collection hood using CFD-Rocky one-way transient coupling simulation.

[0061] Figure 11 The distribution diagram of flake particles after optimizing the dust collector hood using CFD-Rocky one-way transient coupling simulation.

[0062] Figure 12 Strip particle distribution diagram of the optimized dust collector hood after CFD-Rocky one-way transient coupling simulation.

[0063] Figure 13 The distribution diagram of block particles in the dust collector hood after secondary optimization using CFD-Rocky one-way transient coupling simulation.

[0064] Figure 14 The distribution diagram of flake particles in the dust collector hood after secondary optimization using CFD-Rocky one-way transient coupling simulation.

[0065] Figure 15 This is the strip particle distribution diagram of the dust collector hood CFD-Rocky one-way transient coupling simulation after secondary optimization.

[0066] Figure 16 This is a schematic diagram of the structure of the dust hood after the secondary optimization design in the present invention is completed.

[0067] Figure 17 for Figure 16 Schematic diagram of the decomposition.

[0068] In the figure: 1. Air inlet; 2. Air outlet; 3. Upper cover; 4. Lower cover; 5. Cutting tool; 6. Buckle; 7. Mounting ear; 8. Guide vane. DETAILED DESCRIPTION

[0069] In order to make the purpose, technical solutions and advantages of the implementation of the present invention clearer, the technical solutions in the implementation cases of the present invention will be described in more detail below with reference to the accompanying drawings in the implementation cases of the present invention.

[0070] like Figure 1 As shown, the present invention provides an optimization design method for gas-solid two-phase unidirectional transient coupling of an edge banding machine dust collection hood, comprising the following steps:

[0071] S1: Data acquisition.

[0072] The existing dust hood is tested under working conditions to obtain test data such as the inlet and outlet air pressure, the initial velocity, direction, shape and size of the cutting particles, and the chip removal rate. Specifically including:

[0073] (1) Use an anemometer to measure the pressure and wind speed at the inlet and outlet of the dust hood;

[0074] (2) Using a high-speed camera to shoot the movement of cutting chips, the movement speed, direction and distribution of chip particles are obtained through image processing technology;

[0075] (3) Obtain the chip removal rate of the dust hood by weighing. First, clean all the chips on the edge banding machine. Second, start the edge banding machine and perform edge banding on a certain number of furniture boards. Third, collect the chips sucked away by the dust hood outlet and the remaining chips. Finally, weigh the collected chips separately. The weight of the chips sucked away divided by the weight of all chips is the chip removal rate.

[0076] S2: Flow field simulation.

[0077] First, a CFD simulation model is built for the existing dust hood. The outlet conditions of the simulation model are set according to the outlet air pressure obtained from the test, and the flow field information of the dust hood is obtained through simulation calculation. Specifically,

[0078] (1) Establish the geometric model of the dust collection hood in the preprocessor, construct the rotating domain and the static domain of the external flow field, divide the flow field grid, and set the interface between the rotating domain and the static domain as the interface surface;

[0079] (2) Set up the CFD model in the solver. The SST K-ω turbulence model is used, the SIMPLEC algorithm is used for pressure-velocity coupling, and a discrete format with second-order accuracy or higher is used. A sliding grid is used to simulate the tool rotation motion. The outlet pressure boundary condition is the outlet pressure value obtained in step S1, and the inlet pressure is atmospheric pressure.

[0080] Secondly, set the transient flow field information to be output in F2R file format and simulate the flow field information of the dust collector hood, including:

[0081] (1) Through the Rocky coupling module embedded in Fluent, set Record one-way transient data to start recording the flow field and mesh information at each time step and save them in F2R, dat, and mesh files;

[0082] (2) Set the time step and the number of time steps and perform iterative calculations;

[0083] (3) Use Record one-way transient data again to stop recording flow field and grid information.

[0084] Finally, the flow field simulation results were compared with the test data to verify the reliability of the flow field simulation. CFD post-processing extracted the hood's velocity and pressure fields, as well as physical quantities such as pressure and velocity at the inlet, and compared them with the test data for verification. If the error between the simulated inlet pressure and velocity and the experimental measurements was within 10%, the simulation model was considered reliable and used for subsequent simulation studies.

[0085] S3: Particle simulation.

[0086] The chip particle simulation parameters are set according to the chip speed, direction, shape and size obtained from the test, and a discrete element simulation model is established, including:

[0087] (1) Import the dust hood geometry model into the discrete element software Rocky: import the cas file saved by Fluent, and remove the inlet and outlet wall parts of the dust hood model in Rocky.

[0088] (2) Recreate the chip particle inlet in Rocky: Use the Circular inlet type and set the particle inlet center coordinates, radius, alignment angle, and incline angle according to the actual cutting position.

[0089] (3) Setting the chip particle material properties, mainly the material density;

[0090] (4) Setting the shape and size of the chip particles. Use spherical polygons, briquettes, and other types to set the chip particles in different shapes, such as filaments, flakes, and granules.

[0091] For spherical polygon type (sphero-polygon), the particle shape is adjusted by the vertical aspect ratio, horizontal aspect ratio, and number of corners values, and the particle size is set by the sieve size.

[0092] For briquette type, adjust the particle shape through the vertical aspect ratio, horizontal aspect ratio, side angle, and number of corners values, and set the particle size through sieve size.

[0093] (5) Set the incident flow rate, speed, direction, start time and end time of the chip particles through continuous injection.

[0094] (6) Create a one-way transient coupling link between FLUENT and Rocky in Rocky, and import the F2R file that records the flow field information into Rocky. Rocky reads the flow field information and grid information of each time step at one time and reserves it for subsequent particle simulation.

[0095] Furthermore, the transient flow field information is transmitted to the discrete element particle analysis software Rocky for a one-way gas-solid transient coupling simulation to obtain the chip motion trajectory and the chip removal rate of the dust hood. The specific operations include:

[0096] (1) Set the chip particle force model as follows:

[0097]

[0098]

[0099] Where m p is the particle mass, g is the acceleration due to gravity, F c is the contact force on the particles, including the normal force and tangential force when particles contact each other and particles contact the wall; F f→p is the force exerted by the fluid on the particles; v p is the particle velocity; ω p is the particle angular velocity; J p is the particle moment of inertia; M c is the contact force torque, including the contact torque caused by the tangential contact force and rolling friction; M f→p is the torque of the fluid on the particle.

[0100] When the particle density is much greater than the fluid density, the lift and virtual mass force can be ignored, and the force exerted by the fluid on the particle is mainly the pressure gradient force. and drag force F D ,therefore

[0101]

[0102] in,

[0103]

[0104]

[0105] Where C D is the drag coefficient, and its value is:

[0106]

[0107]

[0108] A=exp(2.3288-6.4581φ+2.4486φ 2 )

[0109] B=0.0964+0.5565φ

[0110] C=exp(4.905-13.8944φ+18.4222φ 2 -10.2599φ 3 )

[0111] D=exp(1.4681-12.2584φ-20.7322φ 2 +15.8855φ 3 )

[0112] Particle sphericity

[0113] V p is the particle volume

[0114] is the local pressure gradient

[0115] u is the velocity vector of the fluid

[0116] A' is the projected area of ​​the particle in the flow direction

[0117] A sph is the surface area of ​​a spherical particle that is equal to the actual particle volume

[0118] A p is the actual surface area of ​​the particle

[0119] The torque model of the fluid acting on the particle is as follows:

[0120]

[0121]

[0122]

[0123]

[0124] (3) When the fluid is in a turbulent state, the particles are also affected by the turbulent diffusion force caused by the pulsating velocity. At this time:

[0125]

[0126] is the average velocity of the fluid, and u′ is the pulsating velocity.

[0127] (4) Set the calculation time, output result step size, and iterate the calculation.

[0128] (5) The Rocky post-processor is used to display the particle distribution and calculate the dust removal rate of the dust hood.

[0129] S4, optimized design.

[0130] (1) The chip particle discrete element simulation results were compared with the test data to verify the reliability of the chip particle simulation. When the error between the simulated chip removal rate and the experimentally measured chip removal rate was within 10%, the simulation model was considered to be correct and reliable, and this simulation model was used for subsequent simulation studies.

[0131] (2) Simulate the chip removal rate of dust hoods with different chip particle shapes and optimize the design of the dust hood based on the simulation results. By changing the chip particle parameters, several chip particles of different shapes and sizes are obtained, and the chip removal rate is simulated and calculated for each. The dust hood is optimized based on the comprehensive simulation results.

[0132] (3) Perform one-way transient simulation of the flow field and particle field of the optimized dust hood, and judge whether it meets the design requirements based on the simulation results.

[0133] Specifically, the optimization design of the initial model of the dust hood after the simulation results analysis of the present invention is mainly the optimization design of the air inlet and the inner channel of the initial model of the dust hood, which is as follows:

[0134] like Figure 3 As shown, the air inlet 1 of the initial model of the dust hood is an open structure, and the pressure cloud map obtained by simulation ( Figure 4 ) It can be seen that the average static pressure at the inlet of the initial model of the dust hood is about -417Pa, the negative pressure is small, and the adsorption capacity is weak. The pressure drop between the inlet and outlet of the dust hood reaches 1282Pa, and the pressure loss is large, which weakens the adsorption capacity of the air inlet for waste chips. The cutting particle distribution diagram at a certain moment obtained by simulation ( Figure 6-Figure 9 ) It can be seen that some cutting particles fly out of the chip removal hood along the tangent direction of the tool rotation direction and diffuse into the external space. For single CFD particle simulation, the chip removal rate obtained by post-processing statistics is between 65% and 67%, which is similar to the simulation results of block particles under Fluent-Rocky one-way transient coupling. For flake and strip particles, single CFD cannot be simulated, while the Fluent-Rocky one-way transient coupling simulation shows that the chip removal rate of the initial model of the dust collection hood for flake and strip particles is only about 49%-53%. The velocity vector diagram obtained by simulation ( Figure 5 ) It can be seen that before optimization, vortices were generated on the side walls and corners of the channel inside the dust hood, and the particles could not be discharged quickly here, affecting the chip removal effect.

[0135] Chinese patent CN202010402660.8 optimized the air inlet and inner channel of the dust hood and used a single CFD method to simulate spherical particles. The results showed that the dust removal rate of spherical particles after optimization was between 95% and 97%, but it did not simulate and verify the flake and strip particles. The optimized dust hood in Chinese patent CN202010402660.8 was simulated using the CFD-Rocky one-way transient coupling method. The results showed that ( Figure 10-12 ) The dust removal rate of the optimized dust hood for block particles is between 94% and 96%, which is similar to the single CFD method; the dust removal rate for flaky particles is between 74% and 79%; and the dust removal rate for strip particles is between 78% and 82%.

[0136] In summary, the dust hood optimized in the Chinese patent CN202010402660.8 is optimized again. According to the simulation results of the flaky and strip-shaped particles by CFD-Rocky one-way transient coupling, the speed of the flaky and strip-shaped particles decreases when they move to the edge of the outlet. Therefore, a guide vane is added to the lower cover of the inlet cavity. On the one hand, the particle speed can be gradually reduced, and on the other hand, the inlet speed of each sub-cavity is made larger, the adsorption capacity is enhanced, and the chip removal effect is improved. Preferably, the distance between the guide vane and the outer contour of the tool is 1 / 2 of the distance between the guide vane and the inner wall on the right side of the lower cover (the upper, lower, left, and right directions are all relative to the accompanying figure), the angle between the tangent line of the lower edge of the guide vane and the horizontal line of the lower edge of the air inlet is in the range of 15°-30°, and the angle between the tangent line of the upper edge of the guide vane and the horizontal line of the air inlet is in the range of 65°-90°. The dust hood after the second optimization was subjected to CFD-Rocky one-way transient coupling simulation, and the results show that ( Figure 13-15 ), the chip removal rate for block particles is between 98%-99%, the chip removal rate for flaky particles is between 90%-94%, and the chip removal rate for strip particles is between 93%-96%.

[0137] The optimized design method of the dust hood is used to optimize the existing dust hood, and the motion law of chips with different particle shapes can be simulated. At the same time, the design cycle is shortened and the design cost is saved. The structure of the optimized dust hood is as follows: Figure 16 、 17 As shown, it solves the problem that the existing dust hood cannot clean up the waste chips of the edge banding, can adapt to the working conditions of different chip particle shapes under different edge banding thicknesses, improves the adsorption capacity of the dust hood, reduces the pressure loss of the dust hood, greatly improves the chip removal rate of the dust hood body, and meets various design requirements.

[0138] The above content is intended only to illustrate the technical solution of the present invention and is not intended to limit the scope of protection of the invention. Simple modifications or equivalent substitutions of the technical solution of the present invention by persons of ordinary skill in the art do not depart from the spirit and scope of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. A gas-solid two-phase unidirectional transient coupling optimization design method for an edge banding machine dust collection hood, characterized in that: The steps include: S1, data acquisition: testing the existing dust hood to obtain the dust hood inlet and outlet air pressure, the initial velocity, direction, shape and size of the chip particles, and the chip removal rate under working conditions; S2, flow field simulation: establish a CFD simulation model for the existing dust hood, and set the outlet conditions of the simulation model based on the outlet air pressure obtained from the test; Set the transient flow field information to be output in F2R file format, simulate and calculate the flow field information of the dust collector; compare the flow field simulation results with the test data to verify the reliability of the flow field simulation; The specific operations for setting the transient flow field information to be output in F2R file format and simulating the flow field information of the dust collector include: 1) For Fluent-Rocky one-way transient coupling, set Record one-way transient data in Fluent to start recording the flow field and mesh information at each time step and save them in F2R, dat, and mesh files; 2) Set the time step and number of time steps and perform iterative calculations; 3) Use Record one-way transient data again to stop recording flow field and grid information; S3, particle simulation: The chip particle simulation parameters are set based on the chip speed, direction, shape and size obtained from the test, and a discrete element simulation model is established. The transient flow field information is transmitted to the discrete element analysis software Rocky to perform a gas-solid two-phase one-way transient coupling simulation to obtain the chip motion trajectory and the chip removal rate of the dust collection hood. The chip particle discrete element simulation results are compared with the test data to verify the reliability of the chip particle simulation. The operations of setting chip particle simulation parameters and transmitting transient flow field information include: 1) Import the dust hood geometry model into the discrete element software Rocky: import the cas file saved by Fluent, and remove the inlet and outlet walls of the dust hood model in Rocky; 2) Recreate the chip particle inlet in Rocky: Use the Circular inlet type and set the particle inlet center coordinates, radius, alignment angle, and tilt angle according to the actual cutting position; 3) Set the chip particle material properties; 4) Set the shape and size of the chip particles; use spherical polygons and coal block types to set chip particles of different shapes; 5) Set the incident flow rate, speed, direction, start time and end time of the chip particles through continuous injection; 6) Create a one-way transient coupling link between Fluent and Rocky in Rocky, import the F2R file that records the flow field information into Rocky, and Rocky will read the flow field information and grid information of each time step at one time and reserve it for subsequent particle simulation; S4, Optimization design: Based on the gas-solid two-phase one-way transient coupling simulation results, optimize the design of the dust hood; perform one-way transient simulation of the flow field and particle field on the optimized dust hood, and determine whether it meets the design requirements based on the simulation results.

2. The gas-solid two-phase one-way transient coupling optimization design method for the edge banding machine dust collection hood according to claim 1 is characterized in that: The test in step S1 specifically includes: 1) Use a wind pressure gauge to measure the pressure and wind speed at the inlet and outlet of the dust hood; 2) Use a high-speed camera to shoot the movement of cutting particles, and obtain the movement speed, direction and distribution of cutting particles through image processing technology; 3) Obtain the chip removal rate of the dust hood by weighing. First, clean all the chips from the edge banding machine. Second, start the edge banding machine and perform edge banding on a certain number of furniture panels. Third, collect the chips sucked away by the dust hood outlet and the remaining chips. Finally, weigh the collected chips separately. The chip removal rate is the weight of the chips sucked away divided by the weight of all the chips.

3. The gas-solid two-phase one-way transient coupling optimization design method for the edge banding machine dust collection hood according to claim 1 is characterized in that: The operation of setting the exit condition of the simulation model in step S2 includes: 1) Establish a geometric model of the dust collection hood in the preprocessor, construct the rotating domain and the static domain model of the external flow field, divide the flow field grid, and set the interface between the rotating domain and the static domain as the interface surface; 2) Set up a CFD model in the solver; use the SST K-ω turbulence model, the SIMPLEC algorithm for pressure-velocity coupling, and a discrete format with second-order accuracy or higher; use a sliding mesh to simulate the tool rotation; the outlet pressure boundary condition is the outlet pressure value obtained in step S1, and the inlet pressure is atmospheric pressure.

4. The method for optimizing the design of the dust collection hood of an edge banding machine according to any one of claims 1 to 3, characterized in that: The specific operations of obtaining the chip motion trajectory and the chip removal rate of the dust hood in step S3 include: 1) Set the particle force model; the particle force model is as follows: Where m p is the particle mass, g is the acceleration due to gravity, F c is the contact force on the particles, including the normal force and tangential force when particles contact each other and particles contact the wall; F f→p is the force exerted by the fluid on the particles; v p is the particle velocity; ω p is the particle angular velocity; J p is the particle moment of inertia; M c is the contact force torque, including the contact torque caused by the tangential contact force and rolling friction; M f→p is the torque of the fluid on the particle; When the particle density is much greater than the fluid density, the lift and virtual mass force are ignored, and the force exerted by the fluid on the particle is mainly the pressure gradient force. and drag force F D ,therefore: in, Where C D is the drag coefficient, and its value is: A=exp(2.3288-6.4581φ+2.4486φ 2 ) B=0.0964+0.5565φ C=exp(4.905-13.8944φ+18.4222φ 2 -10.2599φ 3 ) D=exp(1.4681-12.2584φ-20.7322φ 2 +15.8855f 3 ) Particle sphericity Where, V p is the particle volume, is the local pressure gradient, u is the velocity vector of the fluid, A′ is the projected area of ​​the particle in the flow direction, A sph is the surface area of ​​a spherical particle that is equal to the actual particle volume, A p is the actual surface area of ​​the particle, The torque model of the particle subjected to the fluid is: 2) When the fluid is in a turbulent state, the particles are also affected by the turbulent diffusion force caused by the pulsating velocity. At this time: is the average velocity of the fluid, u′ is the pulsating velocity; 3) Set the calculation time, output result step size, and iterative calculation; 4) The Rocky post-processor displays the particle distribution and calculates the dust removal rate of the dust hood.

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