Airflow control method and system of purging device

Abstract

The invention provides an airflow control method and system of a purging device. The method comprises the following steps: determining a layout scheme of a purging device, and setting the purging device according to the layout scheme; collecting dust concentration data and dust distribution image data of different parts of the vehicle bottom and the vehicle side; according to the dust concentration data and the dust distribution image data, the smudginess degrees of different parts of the vehicle bottom and the vehicle side are determined; and the blowing direction and the blowing strength of the blowing airflow are adjusted according to the smudginess degrees of different areas of the vehicle bottom and the vehicle side. Through the method, the blowing direction and the blowing strength of the blowing airflow can be automatically adjusted according to the smudginess degrees of different areas of the vehicle bottom and the vehicle side, so that the blowing effect is ensured.

Description

Technical Field

[0001] This application relates to the field of rail transit equipment maintenance technology, and in particular to an airflow control method and system for a purging device. Background Technology

[0002] With continuous development, the scale and complexity of urban rail transit have greatly increased. The components of urban rail transit vehicles are highly complex, with a large scope of maintenance and a large number of small parts that are prone to being missed. In the current maintenance process, the work of trains entering the depot mainly relies on manual labor or single testing equipment, including train inspection and purging operations.

[0003] In automated purging operations, the airflow control method of the purging device has a significant impact on the purging effect. Therefore, it is urgent to provide an optimal airflow control method for the purging device. Summary of the Invention

[0004] In view of this, this application provides an airflow control method and system for a purging device, which aims to obtain the optimal arrangement of the purging device and to control the purging intensity and purging direction of the purging device in order to improve the purging effect of the purging device.

[0005] In a first aspect, this application provides an airflow control method for a purging device, comprising: Determine the layout scheme of the purging device, and set up the purging device according to the layout scheme; Collect dust concentration data and dust distribution image data from different parts of the vehicle underside and sides; Based on dust concentration data and dust distribution image data, the degree of dirtiness of different parts of the vehicle undercarriage and sides is determined; Adjust the blowing direction and intensity of the blowing airflow according to the degree of dirt in different areas of the vehicle's undercarriage and sides.

[0006] Optionally, the formula for adjusting the purging intensity of the purging airflow is as follows:

[0007] In the formula, This indicates the purging velocity of the purging airflow. The reference jet velocity representing the purging airflow. , , Indicates control parameters, Indicates the adjustment time. This indicates the degree of dirtiness in different areas of the car's undercarriage and sides. Indicates the bottom and sides of the vehicle. Thresholds for the degree of dirtiness in each area.

[0008] Optionally, the formula for adjusting the purging direction of the purging airflow is as follows:

[0009] In the formula, Indicates the direction of the purging airflow. Indicates the reference direction angle. Indicates the maximum adjustment angle. This indicates the degree of dirtiness in different areas of the car's undercarriage and sides. Indicates the bottom and sides of the vehicle. Threshold for the degree of dirtiness in each area This indicates the maximum permissible level of dirt in different areas of the vehicle's undercarriage and sides.

[0010] Optionally, the steps for determining the layout of the purging device include: A three-dimensional flow basin model was constructed, including key purging areas, nozzles, suction ports, and flexible shields, and the flow field control equations were determined. Based on the three-dimensional watershed model, the nozzle is simulated to determine the nozzle type, nozzle purging posture, and air compressor parameters. Based on the aforementioned three-dimensional flow domain model, the suction port is simulated to determine the arrangement of the suction port, the relative position of the suction port and the nozzle, and the negative pressure parameters. Based on the three-dimensional watershed model, the end shielding effect is simulated to determine the flexible shielding arrangement area. By integrating nozzle type, purging posture, air compressor parameters, dust inlet layout scheme, relative position of dust inlet and nozzle, negative pressure parameters, and flexible shielding arrangement area, a preliminary layout scheme is obtained. Based on the preliminary layout scheme, an overall flow field simulation is performed. The preliminary layout scheme is then fine-tuned based on the purging effect to obtain the final layout scheme of the purging device.

[0011] Optionally, the flow field governing equations include: a continuity equation, a momentum equation, and a turbulence model.

[0012] Optionally, based on the three-dimensional watershed model, the steps of performing simulation analysis on the nozzle to determine the nozzle type, nozzle purging posture, and air compressor parameters include: Based on the three-dimensional flow domain model, the flow field characteristics of different types of nozzles are analyzed, and suitable nozzle types are selected; wherein, the flow field characteristics of the nozzles include airflow concentration, velocity attenuation rate, penetration rate, and effective range. Several initial purging poses are formed. Based on the three-dimensional flow domain model, the airflow escape velocity, domain connectivity, and dust removal rate of the several initial purging poses are analyzed. The purging pose of the nozzle is determined from the several initial purging poses. Based on the aforementioned three-dimensional flow domain model, the air compressor parameters are determined through simulation according to the total air consumption of the nozzles, combined with the engineering redundancy coefficient and pipeline pressure loss.

[0013] Optionally, based on the three-dimensional watershed model, the steps of performing simulation analysis on the suction port to determine the arrangement scheme of the suction port, the relative position of the suction port and the nozzle, and the negative pressure parameters include: Based on the three-dimensional watershed model, the collection efficiency of the dust collection port at different locations is determined, and then the arrangement scheme of the dust collection port and the relative position of the dust collection port and the nozzle are determined. Several sets of initial negative pressure parameters are designed. Based on the three-dimensional flow domain model, simulation is performed according to the initial negative pressure parameters. The eddy current intensity, energy consumption, and collection efficiency are determined based on the simulation, and the negative pressure parameters of the dust suction port are determined.

[0014] Optionally, based on the three-dimensional watershed model, the step of simulating the end-shading effect and determining the flexible shielding arrangement area includes: Design different shielding heights and different material combinations. The initial arrangement scheme of the flexible shielding is simulated using the three-dimensional flow domain model. Based on the airflow escape rate obtained from the simulation, the arrangement scheme of the flexible shielding is determined.

[0015] Optionally, the feature is that it further includes: The simulation results were analyzed to form a structured system including layout and parameters; and a parameter fine-tuning mechanism based on different vehicle models and operating conditions was established based on the structured system.

[0016] Optionally, the steps of establishing a parameter fine-tuning mechanism based on different vehicle models and operating conditions according to the structured system include: Collect layout schemes for purging devices for different vehicle models to form a basic dataset; Based on the dataset, vehicle model correction factor and operating condition correction factor are defined; Based on the vehicle model correction factor and operating condition correction factor, parameter fine-tuning formulas are formed for different vehicle models and different operating conditions.

[0017] Secondly, this application provides an airflow control system for a purging device, comprising: The first determining module is used to determine the layout scheme of the purging device and set the purging device according to the layout scheme; The data acquisition module is used to collect dust concentration data and dust distribution image data from different parts of the vehicle underside and sides. The second determining module is used to determine the degree of dirt on different parts of the vehicle undercarriage and sides based on dust concentration data and dust distribution image data. The adjustment module is used to adjust the blowing direction and intensity of the blowing airflow according to the degree of dirt in different areas of the vehicle bottom and sides.

[0018] Thirdly, this application provides an electronic device including an airflow control system for the purging device as described above.

[0019] Fourthly, this application provides a computer-readable storage medium, characterized in that the computer-readable storage medium stores at least one piece of program code, which is executed by a processor to implement the airflow control method of the purging device as described in any of the preceding claims.

[0020] The beneficial effects of the technical solution provided in this application include: This application provides an airflow control method for a purging device. First, the method uses a three-dimensional flow domain model to simulate and analyze the layout of the nozzles, suction ports, and flexible shields in the purging device, thereby obtaining the optimal layout and the operating parameters of the nozzles and suction ports to improve the purging effect. Second, by adjusting the purging intensity and direction during the purging process, the purging effect is further enhanced, thus ensuring optimal purging performance. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0022] Figure 1 A schematic diagram of the nozzle of a purging device provided in an embodiment of this application; Figure 2 A schematic diagram of the suction port of a blowing device provided in an embodiment of this application; Figure 3 This is a flowchart of an airflow control method for a purging device provided in an embodiment of this application; Figure 4 A flowchart illustrating a method for optimizing the layout of a purging device according to an embodiment of this application; Figure 5 A flowchart of step S1012 in the layout optimization method of the purging device provided in an embodiment of this application; Figure 6 A flowchart of step S1013 in the layout optimization method of the purging device provided in an embodiment of this application; Figure 7A flowchart illustrating the airflow control method of a purging apparatus provided in another embodiment of this application; Figure 8 A structural block diagram of the airflow control system of a purging device provided in an embodiment of this application; Figure 9 This is a structural block diagram of an electronic device provided in an embodiment of this application.

[0023] The attached figures are labeled as follows: 11: First determination module; 12: Acquisition module; 13: Second determination module; 14: Adjustment module; 21: Processor; 22: Memory. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0025] Figure 1 This is a schematic diagram of the nozzle of a purging device provided in one embodiment of this application. See also... Figure 1 The diagram illustrates the undercarriage cleaning operation. Three nozzles, mounted on the end of a robotic arm, are located on the undercarriage and sides. This allows the arm to move to the area to be cleaned, even under complex undercarriage structures, and to deliver the airflow from approximately 25mm away from the surface to be cleaned. The airflow can be adjusted to a 90° or 45° position depending on the area being cleaned, thus achieving the best cleaning effect.

[0026] Figure 2 This is a schematic diagram of the suction port of a blowing device provided in one embodiment of this application. See also... Figure 2 The entire cleaning space is formed into a sealed area by the undercarriage inspection pit, the outer wall of the robot on the side of the vehicle, and the upper flexible shield at the end of the train axis. Three dust suction ports are arranged on the undercarriage and sides. The bottom dust suction port focuses on the dust falling in the cleaning area, while the side dust suction ports simultaneously capture the dust escaping from the side, thus achieving the best dust suction effect.

[0027] Figure 3 A flowchart illustrating the airflow control method of a purging apparatus according to an embodiment of this application. See also... Figure 3 ,include: S101. Determine the layout scheme of the purging device, and set up the purging device according to the layout scheme.

[0028] See Figure 4 In some examples, step S101 includes: S1011. Construct a three-dimensional flow basin model including key purging areas, nozzles, suction ports, and flexible shields, and determine the flow field control equations.

[0029] For the operation scenario of the fully automatic undercarriage cleaning device, CFD simulation software was selected to determine the flow field control equations based on the basic principles of fluid mechanics; a simplified three-dimensional flow domain model was constructed, including key cleaning parts, nozzles, suction ports, and flexible shields, and the mesh was densified in areas with drastic airflow changes; basic information was imported in combination with actual working conditions, and simulation assumptions and initial parameters, including ambient temperature and nozzle / suction port boundary types, were set to complete the basic model construction.

[0030] In some examples, step 1 uses the mainstream CFD simulation software ANSYS Fluent to determine the flow field control equations based on the basic principles of fluid mechanics (mass conservation, momentum conservation, and turbulent motion laws), including the continuity equation, momentum equation, and turbulence model, to ensure that the simulation closely matches the actual airflow motion characteristics.

[0031] In some examples, the continuity equation is formulated as follows:

[0032] In the formula, air density, For time, This is the velocity vector.

[0033] In some examples, the momentum equation is formulated as follows:

[0034] In the formula, For static pressure, For viscous stress tensor, This is the acceleration due to gravity.

[0035] In some examples, the turbulence model adopts Two-equation model, in which turbulent kinetic energy Equations and Turbulent Dissipation Rate The equations are as follows:

[0036]

[0037] In the formula, The molecular viscosity coefficient, The viscosity coefficient is the turbulent viscosity. , For Prandtl numbers, , It is an empirical constant. This is a turbulence generating term.

[0038] In some examples, when constructing the 3D flow domain model in step 1, it is necessary to construct it based on the actual structure of the vehicle underside, including key blowing areas such as axle end gaps and heat dissipation holes, as well as nozzles, dust inlets, and flexible shielding. Unstructured meshes are used for mesh generation, and the mesh is refined in areas with drastic airflow changes, such as the nozzle outlet and the area around the dust inlet, to improve simulation accuracy.

[0039] In some examples, when setting simulation assumptions in step 1, the boundary type specifically refers to the fluid motion constraints set according to the effects of different components in the flow field, including: (1) The nozzle boundary is set as the mass inlet, and the mass flow rate, airflow velocity direction and turbulence intensity need to be set. (2) The dust suction port boundary is set as the pressure outlet, and the static pressure value, recirculation turbulence intensity and recirculation temperature need to be set. (3) The flexible shield boundary is set as the wall boundary, and it is set to no slip, adiabatic conditions, and mass exchange is ignored. (4) The surface boundary of the vehicle bottom component is set as the wall boundary, and the roughness is set. (5) If the model has a symmetrical structure, the symmetry plane boundary can be set, and the normal velocity is set to 0.

[0040] S1012. Based on the three-dimensional flow domain model, the nozzle is simulated to determine the nozzle type, nozzle purging posture, and air compressor parameters.

[0041] See Figure 5 In some examples, step S1012 includes: S10121. Based on the three-dimensional flow domain model, analyze the flow field characteristics of different types of nozzles and select suitable nozzle types; wherein, the flow field characteristics of the nozzle include airflow concentration, velocity attenuation rate, penetration rate and effective range.

[0042] Specifically, for the jetting airflow, the flow field characteristics of different types of nozzles are compared first, and the appropriate type is selected based on the purging requirements of the vehicle bottom.

[0043] In some examples, when optimizing the nozzle type in step S10121, flow field simulations are performed on clustered and flat nozzles under the same input conditions to compare the concentration of airflow jets, velocity attenuation law and effective range, and the appropriate type is selected in combination with the airflow requirements of the complex structure under the vehicle.

[0044] In some examples, the specific implementation process of nozzle type filtering is as follows: First, set unified simulation input conditions, namely inlet pressure, purging distance, ambient temperature, and turbulence intensity. Then, select two typical nozzle types, clustered and flat, to build a three-dimensional model and define the airflow concentration. Velocity decay rate Penetration and effective range of action As evaluation indicators, the calculation formulas for each indicator are as follows:

[0045] In the formula: The average velocity within 3mm of the outlet center. The average velocity across the entire cross section at the exit. , These are the average velocities at the inlet and the surface to be purged, respectively. The number of airflow particles that can penetrate the gap at the shaft end, Total number of particles ejected, effective range For the area of ​​the surface to be purged with a velocity ≥15m / s, the comprehensive evaluation formula is established as follows:

[0046] The evaluation indicators of each nozzle are calculated by simulation and substituted into the formula to obtain a comprehensive score. Finally, the nozzle types that meet the comprehensive score requirements and satisfy the core requirements of penetration are selected.

[0047] S10122. Form several initial purging poses. Based on the three-dimensional flow domain model, analyze the airflow escape velocity, domain connectivity, and dust removal rate of the several initial purging poses. Determine the purging pose of the nozzle from the several initial purging poses.

[0048] Among them, by designing multiple sets of purging posture conditions, analyzing airflow escape and penetration, and determining the basic posture and adaptation scheme for special parts.

[0049] In some examples, the design of the purging posture conditions adopts an orthogonal experimental design method, selecting the "angle between the nozzle and the horizontal plane" as the experimental factor, setting five levels: 0°, 30°, 45°, 60°, and 90°. Each condition is simulated three times to eliminate random errors, and the airflow escape velocity is defined. Scope connectivity Dust removal rate As a monitoring indicator, the weighted scoring formula is established as follows:

[0050] In the formula: To determine the maximum escape velocity under each operating condition, a score is calculated for each condition using simulation. The optimal working condition is used as the basic pose for the normal area, and a special adaptive pose is selected for special parts such as the gap at the shaft end.

[0051] S10123. Based on the three-dimensional flow domain model, the air compressor parameters are determined by simulation according to the total air consumption of the nozzles and in combination with the engineering redundancy coefficient and pipeline pressure loss.

[0052] In some examples, the process of determining the air compressor parameters in step S10123 is as follows: First, calculate the air consumption of a single nozzle based on the flow rate formula. The formula is as follows:

[0053] In the formula: The flow coefficient is set to 0.9. The nozzle exit area, Due to work pressure, This refers to air density.

[0054] Then calculate the total gas consumption based on the number of nozzles working simultaneously, and combine this with the engineering redundancy factor. Determine the minimum air output of the air compressor, taking into account pipeline pressure loss. The rated working pressure is determined by the safety margin, and finally the parameters are optimized in combination with the requirements of equipment structure compactness to determine the final matching range of air compressor pressure and air output.

[0055] S1013. Based on the three-dimensional flow domain model, simulate the suction port to determine the arrangement of the suction port, the relative position of the suction port and the nozzle, and the negative pressure parameters.

[0056] Referring to Figure 6, in some examples, step S1013 includes: S10131. Based on the three-dimensional watershed model, determine the collection efficiency of the dust collection port at different locations, and then determine the arrangement scheme of the dust collection port and the relative position of the dust collection port and the nozzle.

[0057] Based on the airflow theory, the dust collection efficiency of the suction port at different positions is simulated to determine the principle of "combining primary and secondary" layout and the relative position of the nozzles.

[0058] In some examples, the process for determining the dust collection efficiency when optimizing the dust collection port layout in step S10131 is as follows: Firstly, it is based on the point-collection airflow theory. The core of this theory is that when the dust suction port is working, a negative pressure point is formed, and the surrounding airflow carrying dust converges towards the dust suction port. Its flow velocity distribution follows the formula:

[0059] In the formula: Distance from the vacuum nozzle airflow velocity at that location For dust suction flow, This is the straight-line distance between the monitoring point and the dust extraction port.

[0060] This formula provides a theoretical basis for the airflow motion law in simulation; subsequently, targeted simulation conditions are set to simulate actual working scenarios: The dust suction ports are flat, with the bottom port parallel to the ground and its width matching the width of the maintenance pit, suitable for capturing dust over a large area under the vehicle. The side suction ports are perpendicular to the ground and their height matches the height of the enclosed area under the vehicle, suitable for capturing dust and releasing it in the blowing area. The dust particles were matched to those found under actual vehicles. To comprehensively evaluate the collection capability at different distances, five distance gradients within the range of 100mm-500mm were selected, and the motion trajectory of each particle was tracked through simulation. Finally, the number of particles successfully captured by the suction port at each distance gradient was counted. Calculate the capture efficiency for each distance using the following formula:

[0061] This is used to determine the dust collection capabilities of different suction ports for different ranges of dust.

[0062] The "primary and secondary combination" layout and the principle of relative position with the nozzle in step S10131 are determined based on the above-mentioned collection efficiency simulation results. The specific steps are as follows: The first step is to define the attributes of the vacuuming area.

[0063] Based on the collection efficiency data of the suction ports at different locations and combined with practical experience, the bottom suction port is defined as the main suction core, which is used to directly capture the dust blown off by the nozzle, and the side suction ports are defined as secondary suction supplements, which are used to make up for the blind spots of the main suction area and capture the escaped low-speed dust.

[0064] The second step is to determine the relative horizontal distance from the nozzle.

[0065] The aim is to ensure that the dust blown off by the jet airflow can be efficiently captured by the suction port, avoiding blind spots in the capture or interference between the blowing and suction airflows. The principle is that the arrangement of the planar suction ports must cover the effective range of the jet airflow from the nozzles, and the capture ranges of the main and secondary suction ports should complement each other. In terms of details, the blowing and suction synergy effect at different distances is verified through CFD simulation. After fine-tuning and optimization, the final relative position parameters are determined to ensure a reasonable layout of "bottom main suction + side secondary suction".

[0066] S10132. Design several sets of initial negative pressure parameters, and perform simulation based on the three-dimensional flow domain model according to the initial negative pressure parameters. Determine the eddy current intensity, energy consumption and collection efficiency based on the simulation, and determine the negative pressure parameters of the dust suction port.

[0067] Design multiple negative pressure operating conditions, analyze flow field stability and energy consumption, and clarify the design logic of negative pressure parameters.

[0068] In some examples, when optimizing the vacuum suction negative pressure parameters in step S1032, the parameter design process is as follows: First, design 5 sets of working conditions within the negative pressure gradient range of 0.02MPa-0.1MPa, and monitor the eddy current intensity. Energy consumption and capture efficiency The three indicators are formulated as follows:

[0069]

[0070] In the formula: , , They are respectively , , The airflow velocity component in the axial direction, , , The coordinate axes of the spatial coordinate system, For vacuuming negative pressure, This refers to the suction flow rate.

[0071] Then set the optimization target threshold and take... , By minimizing W and comparing various operating conditions through simulation, a range of negative pressure parameters that meet the optimization objectives is selected.

[0072] S1014. Based on the three-dimensional watershed model, simulate the end-blocking effect to determine the flexible blocking arrangement area.

[0073] In some examples, when solving the problem of airflow escape at the axial end of the train in step S1014, the control effects of different shielding positions and methods are simulated to determine the arrangement area and design principles of flexible shielding.

[0074] In some examples, step S1014 includes: Design different shielding heights and different material combinations. The initial arrangement scheme of the flexible shielding is simulated using the three-dimensional flow domain model. Based on the airflow escape rate obtained from the simulation, the arrangement scheme of the flexible shielding is determined.

[0075] The specific implementation process of flexible shielding arrangement is as follows: Design different shielding heights and different material combinations. Group scheme, defining airflow escape rate ( This refers to the end-escape airflow rate. The evaluation index is based on the jet flow rate and the installation complexity coefficient (1-5 points, with 1 point being the simplest). The evaluation index of each scheme is calculated by simulation, and the scheme with low airflow escape rate and simple installation is selected as the optimal scheme. Then, the layout area and material of the flexible shield are determined.

[0076] S1015. Integrate nozzle type, purging posture, air compressor parameters, dust inlet layout scheme, relative position of dust inlet and nozzle, negative pressure parameters, and flexible shielding layout area to obtain a preliminary layout scheme. Perform overall flow field simulation based on the preliminary layout scheme, and fine-tune the preliminary layout scheme according to the purging effect to obtain the final layout scheme of the purging device.

[0077] In step S1015, by integrating the blowing and suction airflow organization (nozzles, suction port) with the flexible shielding model, the vehicle under structure is simplified as the core flow area, and the key planes to be monitored are determined; the overall flow field simulation is carried out to analyze the blowing and suction synergy effect; for problems such as airflow decoupling and local escape, the layout or parameters are finely adjusted, and the simulation is iterated until the closed-loop synergy of "blowing-suction" is achieved.

[0078] In some examples, step S1015 integrates the model by importing the subsystem models of the blowing system (including the selected nozzle type, determined pose, and working pressure), the dust collection system (including the primary and secondary layout and negative pressure parameters), and the flexible shield (including the optimal height and material) into the same computational domain using the multi-component assembly function of ANSYS Fluent. During the construction process, it is necessary to set the interaction boundary conditions of each subsystem (the nozzle outlet and the flow domain are mass exchange boundaries, and the flexible shield and the flow domain are momentum exchange boundaries), and simplify the non-critical structures of the vehicle bottom while retaining the core flow domain.

[0079] The process of determining and monitoring the critical plane is as follows: The nozzle purging plane, the horizontal plane of the dust suction port, and the surface plane of key components are selected as critical monitoring planes, and the airflow coverage is defined. Velocity uniformity Escape rate As a monitoring indicator, the formula is as follows:

[0080]

[0081]

[0082] In the formula: To monitor the area on a plane where the airflow velocity direction is directed towards the dust collection zone and has an effective velocity, To monitor the total area of ​​the plane, To monitor the standard deviation of airflow velocity on a plane, To monitor the average velocity of airflow on a plane, The area is defined as the region where the airflow velocity direction is away from the suction area and its size is higher than the escape velocity threshold; then, a threshold is set for the above indicators, and... , , The critical plane is monitored by comparing real-time data with thresholds.

[0083] In some examples, the specific method for correcting the parameters in step S1015 is as follows: (1) To address the airflow decoupling problem discovered in the simulation, the velocity difference in the decoupling region is first calculated. ,like If the problem is large, then the solution is to increase the vacuuming negative pressure or reduce the distance between the nozzle and the suction port; (2) For the problem of local escape, if If the error is too large, the solution is to increase the height of the flexible shield or the number of suction ports. After fine-tuning, the simulation is repeated, and the above correction process is repeated until all monitoring indicators meet the threshold requirements, with no more than 5 iterations.

[0084] See Figure 7 In another example, step S101 includes: S1011a. Construct a three-dimensional flow basin model including key purging areas, nozzles, suction ports, and flexible shields, and determine the flow field control equations.

[0085] See step S1011.

[0086] S1012a. Based on the three-dimensional flow domain model, the nozzle is simulated to determine the nozzle type, nozzle purging posture, and air compressor parameters.

[0087] See step S1012.

[0088] S1013a. Based on the three-dimensional flow domain model, the suction port is simulated to determine the arrangement of the suction port, the relative position of the suction port and the nozzle, and the negative pressure parameters.

[0089] See step S1013.

[0090] S1014a. Based on the three-dimensional watershed model, the end shielding effect is simulated to determine the flexible shielding arrangement area.

[0091] See step S1014.

[0092] S1015a. Integrating nozzle type, purging posture, air compressor parameters, dust inlet layout scheme, relative position of dust inlet and nozzle, negative pressure parameters, and flexible shielding layout area, a preliminary layout scheme is obtained. Based on the preliminary layout scheme, an overall flow field simulation is performed. The preliminary layout scheme is then fine-tuned based on the purging effect to obtain the final layout scheme of the purging device.

[0093] See step S1015.

[0094] S1016a. Organize the simulation results to form a structured system including layout and parameters; and establish a parameter fine-tuning mechanism based on different vehicle models and operating conditions according to the structured system.

[0095] In some examples, when outputting parameters in step S1016a, the optimization results are organized into a structured parameter system. The specific implementation process is as follows: The first step is to classify and integrate the parameters.

[0096] The key parameters after simulation optimization are classified and collected according to the four core modules of "jet blowing system - dust collection system - flexible shielding - air compressor", and the core parameter types under each module are clarified: (1) Jet blowing system parameters include nozzle type parameters, blowing posture parameters, jet blowing pressure parameters, etc. (2) Dust collection system parameters include dust collection port layout parameters, negative pressure adjustment parameters, etc. (3) Flexible shielding parameters include layout area parameters, structural size parameters, etc.; (4) Air compressor parameters include rated pressure parameters, air production parameters, etc.

[0097] The second step is to establish a parameter correlation model.

[0098] Based on simulation data mining, the intrinsic correlation relationships between various parameters are mined, and a parameter correlation table is constructed, using correlation coefficient symbols. Characterizes the strength of the correlation between parameters ( The range of values ​​is , The closer to 1, the stronger the correlation. Clarify the mapping logic between core parameters and derived parameters (such as the positive correlation between injection pressure parameters and air compressor pressure parameters).

[0099] The third step is to label the simulation verification information.

[0100] For each core parameter, a corresponding simulation verification effect index is matched, a "parameter-index" correspondence table is established, the simulation basis for the value range of each parameter is clarified, the basic working condition boundary conditions applicable to the parameter are marked, and finally a complete structured parameter manual covering "parameter type-relationship-value range-applicable boundary-effect index" is formed.

[0101] In some examples, when establishing the adaptation verification mechanism in step S1016a, the rationality of the parameters is verified from three dimensions: purging effect (dust removal rate, dust emission rate), economy (equipment cost, energy consumption), and feasibility (parameter engineering implementation range), and a parameter fine-tuning mechanism based on vehicle model and working condition differences is formed.

[0102] In some examples, establishing parameter fine-tuning mechanisms based on different vehicle models and operating conditions according to the structured system includes: The first step is to build the basic database.

[0103] The system collects core structural parameters such as the undercarriage space layout of different vehicle models, as well as key environmental parameters (including dust concentration distribution parameters, ambient temperature and humidity parameters, etc.) under different operating conditions, and establishes a basic parameter database covering multiple vehicle models and multiple operating conditions to provide data support for fine-tuning logic.

[0104] The second step is to define the correction factor and the fine-tuning formula.

[0105] Define vehicle model correction factors based on database data. (Different models correspond to different) Values ​​are selected to adapt to differences in vehicle underbody structure and operating condition correction factors. (Different operating conditions correspond to different) The value is used to adapt to differences in dust load. Regarding the core operating parameters (air compressor output) Negative pressure for dust collection Nozzle blowing speed The unified fine-tuning formula is established as follows:

[0106]

[0107]

[0108] In the formula: , , These are the baseline values ​​for air compressor output, dust suction negative pressure, and nozzle blowing speed under the baseline operating conditions.

[0109] The third step is physical testing and calibration.

[0110] Typical samples covering multiple vehicle models and operating conditions were selected from the database, and physical purging tests were conducted to obtain the optimal parameters. Parameters calculated with the fine-tuning formula The comparison was performed, and the parameter error was defined as follows:

[0111] In the formula: These are the core operating parameters to be calibrated, and the vehicle model correction factor is iteratively adjusted. With operating condition correction factor The value of the parameter is taken until the parameter error is reached. Meet the preset error threshold requirements, complete the calibration of the fine-tuning formula, and ensure the adaptation accuracy of the fine-tuning mechanism.

[0112] Based on the above overall framework and CFD simulation optimization method, this invention also provides engineering implementation suggestions, including specific spatial layout and parameter scheme selection recommendations, as follows: At the blow-blowing system level, the cluster nozzle has a significantly better blowing speed than the flat nozzle when the blowing distance is about 25mm, and it is also suitable for the complex structure of the vehicle underside, so the cluster nozzle is selected. According to the simulation results, the escape velocity of the airflow in the motor plane is the smallest under the radial 45° blowing posture, and the blowing area and the dust collection area are connected, resulting in the best dust collection effect. The 90° posture is more effective for difficult-to-blow areas. Therefore, the radial 45° posture is used for the conventional blowing area, and the radial 90° posture is suitable for difficult-to-blow areas such as the gap at the shaft end.

[0113] At the dust collection system level, the bottom suction port is used to capture dust in the blowing area, while the side suction ports are used to capture dust that escapes at a lower speed. This layout has been verified by simulation to avoid the problem of insufficient collection efficiency of a single suction port. A flexible shield should be added at the upper part of the train's axial end to solve the problem of airflow turbulence and end escape during blowing. The gas blocking rate of the flexible shield has no significant impact on the dust collection pattern, so there is no need to strictly control the flexible shield material.

[0114] When selecting air compressor parameters, the rated working pressure of the air compressor should be 1-2 bar higher than the actual operating pressure, and the total air production capacity should be multiplied by a coefficient based on the total air consumption. ( Taking 1.2 as an example, and considering the air consumption of the nozzle and the requirements for structural compactness, the working pressure of the air compressor is determined to be 0.8 MPa, and the air production capacity is 0.8-2.6 m³ / s. 3 / min.

[0115] At the control and implementation logic level of blow-and-suction coordination, the blowing and suction operations are started simultaneously, ensuring that dust is captured by the suction system as soon as it is blown off, preventing dust spread. During the blowing process, the cluster nozzles operate at a preset 45° or 90° position, and the air compressor maintains a working pressure of 0.8MPa and a suction power of 0.8-2.6m. 3 / min air production ensures stable airflow output from the nozzles; the bottom dust suction port focuses on the blowing area, while the side dust suction port simultaneously captures dust escaping from the sides, forming a "bottom + side" encirclement and capture; the flexible shield at the end of the train axis adopts a fixed installation method, which simplifies operation while ensuring the airflow escape control effect.

[0116] Once the layout of the purging device is determined, it is installed on the underside and sides of the vehicle. Then, the airflow organization method used by the purging device during purging is determined, thereby specifically adjusting the intensity and direction of the purging airflow based on the degree of dirt in different areas of the underside and sides of the vehicle.

[0117] It should be noted that the general layout and working process of the purging device of this application are as follows: Step 1: First, a relatively closed space is formed under the train by the outer wall of the purging structure and the flexible material to avoid dust diffusion and reduce the volume of the negative pressure space; Step 2: Second, a high-speed jet airflow is designed in the local area of ​​the structure where dust adheres, using air as the airflow medium, so that the dust attached to the train structure falls off and forms a dust airflow, which then diffuses into the entire closed space; Step 3: Finally, a dust suction airflow is designed in three directions at the bottom and sides of the closed space to provide power so that the air carrying dust in the closed space enters the dust collector through the dust suction hood. After being filtered in the dust collector, the dust in the air is collected and stored in the dust storage bin, and the filtered clean air is directly discharged.

[0118] The overall blowing and suction airflow is carried out simultaneously and confined to a relatively enclosed area under the vehicle. This allows the dust to be blown off and collected quickly and effectively. Firstly, it can effectively avoid air pollution caused by large-scale dust flying. Secondly, it can effectively avoid secondary pollution caused by dust re-adsorbing and falling onto the parts under the vehicle. This reduces the frequency of repeated blowing and cleaning and improves the efficiency of the blowing and cleaning operation.

[0119] S102. Collect dust concentration data and dust distribution image data of different parts of the vehicle underside and sides.

[0120] After the purging device is installed, it is used to purge the underside and sides of the vehicle. During purging, several sensors collect dust concentration data and dust distribution image data.

[0121] More specifically, dust concentration data can be collected using a dust concentration sensor, and dust distribution image data can be collected using a vision sensor. The number of sensors can be set to multiple.

[0122] S103, Based on dust concentration data Using image data of dust distribution, the degree of dirtiness in different parts of the vehicle's undercarriage and sides can be determined.

[0123] In some examples, step S103 includes: S1031. Convert the dust distribution image data into grayscale value quantization data.

[0124] Among them, grayscale value quantization data The equivalent dust concentration obtained through grayscale mapping is obtained as follows: First, the acquired color images are preprocessed by removing ambient light interference and image noise through Gaussian filtering. Then, the images are cropped according to the vehicle underbody components (such as the axle end gap area, the inverter heat dissipation hole area, etc.). The cropped color images are converted into grayscale images using a weighted average method. Subsequently, the average grayscale value of each component area is calculated. Finally, the following calibration experimental procedure is used to establish a precise mapping relationship between grayscale values ​​and dust concentration: The first step is to build a calibration test platform to simulate the working environment under the vehicle, fix the installation position of the vision sensor and the nozzle blowing parameters, and avoid interference from irrelevant variables.

[0125] The second step is to select a dust type consistent with the actual operation (the common dust under urban rail vehicles is a mixture of metal dust and ash, with a particle size of 10-100μm). A gradient dust concentration is generated in the calibration area through a dust generator. The concentration gradient is set to 5mg / m³, 10mg / m³, 15mg / m³, 20mg / m³, 25mg / m³, and 30mg / m³, covering the typical concentration range of 0-30mg / m³ in actual operation.

[0126] The third step involves simultaneously collecting the actual dust concentration value and the average grayscale value of the image captured by the visual sensor for each concentration gradient. Ten sets of data are collected for each gradient. After removing outliers, six valid sample pairs are obtained, described as follows:

[0127] in The average grayscale value. This corresponds to the actual dust concentration.

[0128] The fourth step is to establish a mapping model using data fitting methods. First, correlation analysis is used to determine the relationship between gray values ​​and dust concentration. If the correlation coefficient R² ≥ 0.95, a linear fitting model is used, and the mapping formula is:

[0129] If R² < 0.95, a quadratic polynomial fitting model is used, and the mapping formula is:

[0130] Based on the above sample pairs, the model parameters were solved using the least squares method. With experimental data showing R² = 0.97, the fitted linear mapping formula was obtained as follows:

[0131] The fifth step is to optimize the model through validation experiments. Select intermediate concentration values ​​that were not calibrated for testing, calculate the relative error between the mapped value and the true value. If the error is ≤ ±5%, the model is qualified. If the error exceeds the standard, supplement the sample pairs and refit until the accuracy requirements are met.

[0132] Finally, by substituting the average grayscale value of each component region into the validated mapping model, the grayscale value can be normalized to the same value as the model. Quantitative data of the same magnitude. The advantage of doing so is that it facilitates the integration of direct concentration data from dust concentration sensors and grayscale mapping equivalent data from vision sensors, reduces the error of a single sensor, and outputs accurate and reliable comprehensive dust concentration values, providing core data support for the precise adjustment of the jet airflow.

[0133] S1032. Use a weighted fusion algorithm to process dust concentration data. and grayscale value quantization data The data is then integrated to determine the degree of dirt on different parts of the vehicle's undercarriage and sides.

[0134] The fusion formula is as follows:

[0135] In the formula: , The weighting coefficients and Dynamically adjusted based on sensor accuracy, resulting in a uniform dust concentration area. , Dust accumulation area , Then, a threshold matrix for cleaning procedures of different undercarriage components is preset, expressed as follows:

[0136] Each element in the matrix Units and Consistent, both are mg / m 3 It is based on different components The system incorporates the structural characteristics, cleaning standards, and historical test data to preset critical dust concentration values. The intelligent control system integrates this data. Compared with the threshold matrix, if If this is detected, the area is determined to require enhanced cleaning, and an airflow adjustment command is generated.

[0137] S104. Adjust the blowing direction and intensity of the blowing airflow according to the degree of dirt in different areas of the vehicle bottom and sides.

[0138] In some examples, a PID control algorithm is used to achieve precise adjustment of the intensity and direction of the jet airflow, where the airflow intensity adjustment formula is as follows:

[0139] In the formula, This indicates the purging velocity of the purging airflow. The reference jet velocity representing the purging airflow. , , Indicates control parameters, Indicates the adjustment time. This indicates the degree of dirtiness in different areas of the car's undercarriage and sides. Indicates the bottom and sides of the vehicle. Thresholds for the degree of dirtiness in each area.

[0140] It should be noted that in this application, the degree of dirtiness is quantified by dust concentration value.

[0141] In some examples, the airflow direction adjustment formula is:

[0142] In the formula, Indicates the direction of the purging airflow. Indicates the reference orientation angle (default 45°). This indicates the maximum adjustment angle (±30°). This indicates the degree of dirtiness in different areas of the car's undercarriage and sides. Indicates the bottom and sides of the vehicle. Threshold for the degree of dirtiness in each area This indicates the maximum permissible level of dirt (maximum permissible dust concentration threshold) in different areas of the vehicle's undercarriage and sides.

[0143] By using the above control methods and formulas, the intensity and direction of the blowing airflow in the corresponding area are dynamically adjusted to ensure that the blowing airflow is accurately adapted to the cleaning needs of different parts and to improve the local dust blowing effect.

[0144] This application focuses on realizing variable-position blowing airflow and relying on this control function to implement the coordinated execution of intelligent control system and multi-level airflow adjustment: the blowing component is moved by displacement adjustment mechanism, so that the blowing airflow can flexibly switch the action area along the space under the vehicle, and dynamically adjust the action position of airflow for different structural parts such as shaft end gaps and inverter heat dissipation holes, so as to avoid the coverage blind spot formed by fixed position airflow.

[0145] Meanwhile, this variable position control function is deeply integrated with the intelligent control system and the multi-stage airflow adjustment device: when the intelligent control system monitors the dust distribution in a certain area through sensors and determines that the airflow intensity or spray direction needs to be adjusted, the displacement adjustment mechanism can accurately move the blowing component to the target area, and the multi-stage airflow adjustment device outputs matching parameters in sync, so that the variable position airflow can accurately carry the intelligent adjustment command, ensuring that different parts get the appropriate airflow effect and efficiently blow off the attached dust.

[0146] The intelligent control system can adjust the suction airflow parameters in a coordinated manner: when the sensor detects that the dust concentration in a certain area is high, while adjusting the blowing airflow parameters in that area, the negative pressure of the suction airflow in the corresponding area is increased simultaneously, so that the dust can be efficiently captured the moment it is blown off, further reducing secondary pollution, and avoiding the decrease in cleaning efficiency or energy waste caused by mismatch in airflow parameters.

[0147] Figure 8 This is a structural block diagram of the airflow control system of a purging device provided in one embodiment of this application. See also... Figure 8 ,include: The first determining module 11 is used to determine the layout scheme of the purging device and set the purging device according to the layout scheme; The acquisition module 12 is used to acquire dust concentration data and dust distribution image data of different parts of the vehicle underside and side; The second determining module 13 is used to determine the degree of dirt on different parts of the vehicle bottom and side based on dust concentration data and dust distribution image data. The adjustment module 14 is used to adjust the blowing direction and blowing intensity of the blowing airflow according to the degree of dirt in different areas of the vehicle bottom and sides.

[0148] Figure 9 This is a structural block diagram of an electronic device provided according to an embodiment of this application. See also... Figure 9 Electronic devices may include Figure 8The airflow control system of the purging device. Typically, the electronic equipment includes a processor 21 and a memory 22. The processor 21 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 21 may be implemented using at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), or PLA (Programmable Logic Array). The processor 21 may also include a main processor and a coprocessor. The main processor is used to process data in the wake-up state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor used to process data in the standby state. The memory 22 may include one or more computer-readable storage media, which may be non-transitory. The memory 22 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments, the non-transitory computer-readable storage medium in memory 22 is used to store at least one instruction, which is executed by processor 21 to implement the airflow control method of the purging device performed by an electronic device provided in the method embodiments of this application.

[0149] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for controlling the airflow of a purging device, characterized in that, include: Determine the layout scheme of the purging device, and set up the purging device according to the layout scheme; Collect dust concentration data and dust distribution image data from different parts of the vehicle underside and sides; Based on dust concentration data and dust distribution image data, the degree of dirtiness of different parts of the vehicle undercarriage and sides is determined; Adjust the blowing direction and intensity of the blowing airflow according to the degree of dirt in different areas of the vehicle's undercarriage and sides.

2. The airflow control method for the purging device according to claim 1, characterized in that, The formula for adjusting the purging intensity of the purging airflow is as follows: In the formula, This indicates the purging velocity of the purging airflow. The reference jet velocity representing the purging airflow. , , Indicates control parameters, Indicates the adjustment time. This indicates the degree of dirtiness in different areas of the car's undercarriage and sides. Indicates the bottom and sides of the vehicle. Thresholds for the degree of dirtiness in each area.

3. The airflow control method for the purging device according to claim 1, characterized in that, The formula for adjusting the purging direction of the purging airflow is as follows: In the formula, Indicates the direction of the purging airflow. Indicates the reference direction angle. Indicates the maximum adjustment angle. This indicates the degree of dirtiness in different areas of the car's undercarriage and sides. Indicates the bottom and sides of the vehicle. Threshold for the degree of dirtiness in each area This indicates the maximum permissible level of dirt in different areas of the vehicle's undercarriage and sides.

4. The airflow control method for the purging device according to any one of claims 1 to 3, characterized in that, The steps for determining the layout of the purging device include: A three-dimensional flow basin model was constructed, including key purging areas, nozzles, suction ports, and flexible shields, and the flow field control equations were determined. Based on the three-dimensional watershed model, the nozzle is simulated to determine the nozzle type, nozzle purging posture, and air compressor parameters. Based on the aforementioned three-dimensional flow domain model, the suction port is simulated to determine the arrangement of the suction port, the relative position of the suction port and the nozzle, and the negative pressure parameters. Based on the three-dimensional watershed model, the end shielding effect is simulated to determine the flexible shielding arrangement area. By integrating nozzle type, purging posture, air compressor parameters, dust inlet layout scheme, relative position of dust inlet and nozzle, negative pressure parameters, and flexible shielding arrangement area, a preliminary layout scheme is obtained. Based on the preliminary layout scheme, an overall flow field simulation is performed. The preliminary layout scheme is then fine-tuned based on the purging effect to obtain the final layout scheme of the purging device.

5. The airflow control method for the purging device according to claim 4, characterized in that, Based on the aforementioned three-dimensional flow domain model, the steps for performing simulation analysis on the nozzle to determine the nozzle type, nozzle purging posture, and air compressor parameters include: Based on the three-dimensional flow domain model, the flow field characteristics of different types of nozzles are analyzed, and suitable nozzle types are selected; wherein, the flow field characteristics of the nozzles include airflow concentration, velocity attenuation rate, penetration rate, and effective range. Several initial purging poses are formed. Based on the three-dimensional flow domain model, the airflow escape velocity, domain connectivity, and dust removal rate of the several initial purging poses are analyzed. The purging pose of the nozzle is determined from the several initial purging poses. Based on the aforementioned three-dimensional flow domain model, the air compressor parameters are determined through simulation according to the total air consumption of the nozzles, combined with the engineering redundancy coefficient and pipeline pressure loss.

6. The airflow control method for the purging device according to claim 4, characterized in that, Based on the aforementioned three-dimensional flow domain model, the steps for simulating and analyzing the suction port to determine its layout, the relative positions of the suction port and the nozzle, and the negative pressure parameters include: Based on the three-dimensional watershed model, the collection efficiency of the dust collection port at different locations is determined, and then the arrangement scheme of the dust collection port and the relative position of the dust collection port and the nozzle are determined. Several sets of initial negative pressure parameters are designed. Based on the three-dimensional flow domain model, simulation is performed according to the initial negative pressure parameters. The eddy current intensity, energy consumption, and collection efficiency are determined based on the simulation, and the negative pressure parameters of the dust suction port are determined.

7. The airflow control method for the purging device according to claim 4, characterized in that, Also includes: The simulation results were analyzed to form a structured system including layout and parameters; And based on the structured system, a parameter fine-tuning mechanism is established for different vehicle models and operating conditions.

8. An airflow control system for a purging device, characterized in that, include: The first determining module is used to determine the layout scheme of the purging device and set the purging device according to the layout scheme; The data acquisition module is used to collect dust concentration data and dust distribution image data from different parts of the vehicle underside and sides. The second determining module is used to determine the degree of dirt on different parts of the vehicle undercarriage and sides based on dust concentration data and dust distribution image data. The adjustment module is used to adjust the blowing direction and intensity of the blowing airflow according to the degree of dirt in different areas of the vehicle bottom and sides.

9. An electronic device, characterized in that, The airflow control system includes the purging device as described in claim 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one piece of program code, which is executed by a processor to implement the airflow control method of the purging apparatus as described in any one of claims 1 to 7.

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