A vehicle aftertreatment bracket diagnostic method, apparatus, device, and medium

Abstract

The application discloses a vehicle aftertreatment support diagnosis method, device, equipment and medium. The method comprises the following steps: obtaining a three-dimensional model of a current vehicle aftertreatment support, and generating a grid model according to the three-dimensional model; generating each sub-evaluation result according to the grid model; and generating a support diagnosis result according to each sub-evaluation result. The three-dimensional model of the vehicle aftertreatment support is obtained, the grid model is generated by performing grid division according to simulation requirements through the three-dimensional model, each sub-evaluation result can be determined by analyzing the grid model, wherein the sub-evaluation result comprises a modal structure result, a stiffness evaluation result and a strength evaluation result, and finally the support diagnosis result can be generated according to each sub-evaluation result, so that simulation and diagnosis of the aftertreatment support structure in the support design process are realized, the structure can be adjusted in time, the manpower and material resources are saved, the diagnosis efficiency is improved, the stiffness, the strength and the modal analysis of the support are comprehensively considered, and the diagnosis accuracy is improved.

Description

Technical Field

[0001] This invention relates to the field of bracket strength analysis, and more particularly to a method, apparatus, equipment and medium for diagnosing vehicle after-processor brackets. Background Technology

[0002] In order to improve the reliability of after-processors, the structure of after-processor assemblies is constantly changing in the industry, which leads to continuous changes in the structure of after-processor brackets. In addition, commercial vehicles are used in harsh road conditions, and the loads they are subjected to under certain harsh conditions are much higher than those of passenger cars, which places higher demands on the strength of the after-processor brackets.

[0003] In existing technologies, strength analysis can only be performed manually on the existing post-processor support structure. If an anomaly is diagnosed, the hardware structure needs to be changed and repeated diagnoses need to be performed to ensure that the support strength meets the requirements. It is impossible to adjust the post-processor support structure during the support design process, which consumes a lot of manpower and resources and results in low diagnostic efficiency. Summary of the Invention

[0004] This invention provides a diagnostic method, device, equipment, and medium for vehicle after-processor brackets, which comprehensively considers the influence of factors such as the shape and mass distribution of the after-processor under bracket load on the strength of the after-processor bracket, and performs structural strength analysis.

[0005] According to one aspect of the present invention, a method for diagnosing a vehicle after-processor bracket is provided, the method comprising:

[0006] Obtain the 3D model of the current vehicle's after-processor bracket, and generate a mesh model based on the 3D model;

[0007] Each sub-evaluation result is generated based on the mesh model. The sub-evaluation results include modal structure results, stiffness evaluation results, and strength evaluation results.

[0008] Stent diagnostic results are generated based on the results of each sub-evaluation.

[0009] Optionally, generating a mesh model from the 3D model includes: obtaining the target material number; matching the target material number in a pre-set material library to obtain the target intrinsic properties that match the target material number, wherein the material library includes the correspondence between material numbers and intrinsic properties; determining the components of interest and target connectors in the 3D model; obtaining the seed size and element type based on the target connectors and components of interest, wherein the seed size includes mesh density, and the element type includes continuum elements, shell elements, membrane elements, beam elements, rod elements, rigid body elements, connection elements, and infinite elements; and combining the target intrinsic properties, seed size, element type, target connectors, and components of interest to generate a mesh model.

[0010] Optionally, determining the components of interest and target connectors in the 3D model includes: obtaining the length of the target longitudinal beam, and obtaining the components of interest and their connection relationships based on the 3D model, wherein the connection relationships include connection lengths and connectors; and filtering each connection length according to the length of the target longitudinal beam to obtain target connectors that match the length of the target longitudinal beam.

[0011] Optionally, generate sub-evaluation results based on the mesh model, including: generating modal structure results based on the mesh model; applying an acceleration load in a specified direction to the mesh model to perform stiffness and strength calculations and generate stiffness and strength calculation results; extracting displacement from the stiffness and strength calculation results; determining the stiffness evaluation result as normal when the displacement is within a specified displacement range; extracting stress values ​​from the stiffness and strength calculation results and generating strength evaluation results based on the stress values.

[0012] Optionally, generating modal structure results based on the mesh model includes: obtaining contact pairs and boundary constraints; performing modal calculations on the mesh model based on the contact pairs and boundary constraints to generate a modal cloud map; determining whether the color value in the modal cloud map is greater than a preset color threshold; if so, determining the modal structure result as abnormal; otherwise, determining the modal structure result as normal.

[0013] Optionally, a strength evaluation result is generated based on the stress value, including: inputting the stress value into a preset algorithm to determine a safety factor; determining whether the safety factor is greater than a preset threshold; if so, determining the strength evaluation result as normal; otherwise, determining the strength evaluation result as abnormal.

[0014] Optionally, a stent diagnosis result is generated based on each sub-evaluation result, including: determining whether each sub-evaluation result contains abnormal results; if so, determining the stent diagnosis result as abnormal; otherwise, determining the stent diagnosis result as normal.

[0015] According to another aspect of the present invention, a vehicle after-processor bracket diagnostic device is provided, the device comprising:

[0016] The mesh model generation module is used to obtain the 3D model of the current vehicle's after-processor bracket and generate a mesh model based on the 3D model.

[0017] The sub-evaluation result generation module is used to generate various sub-evaluation results based on the mesh model. These sub-evaluation results include modal structure results, stiffness evaluation results, and strength evaluation results.

[0018] The stent diagnosis result generation module is used to generate stent diagnosis results based on the results of each sub-evaluation.

[0019] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0020] At least one processor; and

[0021] A memory communicatively connected to the at least one processor; wherein,

[0022] The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform a vehicle after-processor bracket diagnostic method according to any embodiment of the present invention.

[0023] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement a vehicle after-processor bracket diagnostic method according to any embodiment of the present invention.

[0024] The technical solution of this invention obtains a three-dimensional model of the vehicle after-processor bracket, and generates a mesh model by meshing the three-dimensional model according to simulation requirements. By analyzing the mesh model, the sub-evaluation results can be determined. The sub-evaluation results include modal structure results, stiffness evaluation results, and strength evaluation results. Finally, the bracket diagnosis results can be generated based on the sub-evaluation results. This realizes the simulation and diagnosis of the after-processor bracket structure during the bracket design process, which facilitates timely adjustment of the structure, saves manpower and material resources, and improves diagnostic efficiency. It comprehensively considers the bracket stiffness, strength, and modal analysis, thereby improving the accuracy of diagnosis.

[0025] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a flowchart of a vehicle after-processor bracket diagnostic method according to Embodiment 1 of the present invention;

[0028] Figure 2 This is a schematic diagram of the structure of a post-processor bracket according to Embodiment 1 of the present invention;

[0029] Figure 3 This is a flowchart of another vehicle after-processor bracket diagnostic method provided in Embodiment 1 of the present invention;

[0030] Figure 4 This is a flowchart of another vehicle after-processor bracket diagnostic method provided in Embodiment 2 of the present invention;

[0031] Figure 5 This is a schematic diagram of the structure of a vehicle after-processor bracket diagnostic device according to Embodiment 3 of the present invention;

[0032] Figure 6 This is a schematic diagram of the structure of an electronic device that implements a vehicle after-processor bracket diagnostic method according to an embodiment of the present invention. Detailed Implementation

[0033] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0034] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0035] Example 1

[0036] Figure 1 This is a flowchart of a vehicle after-processor bracket diagnostic method provided in Embodiment 1 of the present invention. This embodiment is applicable to situations where after-processor bracket strength analysis is performed on vehicles using after-processors. This method can be executed by a vehicle after-processor bracket diagnostic device, which can be implemented in hardware and / or software and can be configured in the vehicle controller. Figure 1 As shown, the method includes:

[0037] S110. Obtain the 3D model of the current vehicle's after-processor bracket, and generate a mesh model based on the 3D model.

[0038] The aftertreatment system is an integrated unit of the catalytic converter and engine exhaust muffler, located at the rear of the vehicle. It is used to treat exhaust pollutants and also functions as a muffler. The aftertreatment system bracket is a crucial component for mounting the aftertreatment system to the vehicle frame, and its structure significantly impacts the installation and operation of the aftertreatment system. Obtaining a 3D model of the current vehicle's aftertreatment system bracket includes obtaining 3D models of the aftertreatment system assembly bracket, the connecting frame longitudinal beams, the aftertreatment system assembly, and the bracket connecting bolts. The controller can then generate a mesh model based on the 3D model for subsequent bracket strength diagnostics. Figure 2 This invention provides a schematic diagram of the structure of a post-processor bracket. Figure 2 In the diagram, 1 represents the longitudinal beam section, 2 represents the after-processor assembly bracket, and 3 represents the after-processor assembly.

[0039] S120. Generate sub-evaluation results based on the mesh model, including modal structure results, stiffness evaluation results, and strength evaluation results.

[0040] Figure 3 This invention provides a flowchart of a vehicle after-processor bracket diagnostic method according to Embodiment 1. Step S120 mainly includes the following steps S121 to S124:

[0041] S121. Generate modal structure results based on the mesh model.

[0042] Optionally, generating modal structure results based on the mesh model includes: obtaining contact pairs and boundary constraints; performing modal calculations on the mesh model based on the contact pairs and boundary constraints to generate a modal cloud map; determining whether the color value in the modal cloud map is greater than a preset color threshold; if so, determining the modal structure result as abnormal; otherwise, determining the modal structure result as normal.

[0043] Specifically, contact pairs can be established in the contact areas of components, and constraints can be applied to the cut-off positions of the longitudinal beams. The controller can then obtain the set contact pairs and boundary constraints. Furthermore, the output mesh model can be a .inp format model file. After the model file is generated, modal calculations can be performed on the mesh model based on the contact pairs and boundary constraints. Modal calculation refers to the process of solving constrained modes, outputting the first 10 mode shapes to generate a modal contour map. Based on the modal contour map, it can be determined whether the post-processor support structure needs improvement. This can be judged by the color values ​​in the modal contour map. When the modal contour map is brightly colored, i.e., the color value is greater than the preset color threshold, it indicates a high risk of resonance in that area, and the support structure needs to be improved. In this case, the modal structure result will be determined as abnormal. Conversely, when the color value is not greater than the preset color threshold, it indicates no risk of resonance, and the post-processor support structure does not need to be improved. The modal structure result will be determined as normal.

[0044] S122. Apply an acceleration load in a specified direction to the mesh model to perform stiffness calculation and generate stiffness calculation results.

[0045] For example, stiffness and strength can be calculated by applying acceleration loads in specified directions to the assembly based on experimental data. The static load acceleration in each direction is the extreme value of the measured load spectrum, and the fatigue load is the equivalent average amplitude. After loading, the data is imported into ABAQUS software for solution calculation, and the stiffness and strength calculation results are obtained in .odb file format.

[0046] S123. Extract the displacement from the stiffness calculation results. When the displacement is within the specified displacement range, determine that the stiffness evaluation result is normal.

[0047] Specifically, displacement data can be read from the stiffness calculation results to evaluate the bracket stiffness. The evaluation criteria are determined based on the actual space and displacement requirements. When the displacement is within the specified range, the stiffness is deemed to meet the requirements, meaning the stiffness evaluation result is normal. When the displacement is outside the specified range, the stiffness is deemed to fail to meet the requirements, meaning the stiffness evaluation result is abnormal.

[0048] Furthermore, when the stiffness does not meet the requirements, a stiffness evaluation anomaly prompt can be generated based on the displacement. The controller will then issue an alarm in a specified manner based on the prompt information. The alarm is intended to alert the user, allowing them to promptly understand the abnormality in the stiffness evaluation result and enabling them to inspect and adjust the post-processor support structure to ensure the proper installation and operation of the subsequent post-processor. The specified methods include voice or image. Voice can be broadcast through a speaker connected to the controller; for example, the voice content could be: "Stiffness evaluation result abnormal." Images can be displayed through a user terminal connected to the controller to alert the user.

[0049] S124. Extract stress values ​​from the stiffness and strength calculation results, and generate strength evaluation results based on the stress values.

[0050] Optionally, a strength evaluation result is generated based on the stress value, including: inputting the stress value into a preset algorithm to determine a safety factor; determining whether the safety factor is greater than a preset threshold; if so, determining the strength evaluation result as normal; otherwise, determining the strength evaluation result as abnormal.

[0051] Specifically, stress values ​​can be extracted from the strength calculation results. These stress values ​​are then input into the FEMFAT software for safety factor calculation. The strength of the post-processor assembly support is evaluated based on the safety factor. The safety factor includes a static safety factor and a fatigue safety factor. When the safety factor is greater than a preset threshold, the support strength is considered good, meaning the strength evaluation result is normal. For example, the preset threshold can be 1. When the safety factor is less than or equal to 1, the support strength is considered poor, meaning the strength evaluation result is abnormal. It should be noted that the preset thresholds related to the safety factor evaluation are formed through accumulated experience. If accumulated experience data or evaluation standards are unavailable, strength evaluation can be performed based on the stress calculation results, with the evaluation standard being that the maximum stress value is less than the material's tensile strength limit.

[0052] S130. Generate stent diagnosis results based on the results of each sub-evaluation.

[0053] Optionally, a stent diagnosis result is generated based on each sub-evaluation result, including: determining whether each sub-evaluation result contains abnormal results; if so, determining the stent diagnosis result as abnormal; otherwise, determining the stent diagnosis result as normal.

[0054] Specifically, if any sub-evaluation result among the modal structure result, stiffness evaluation result, and strength evaluation result is abnormal, it indicates that the post-processor support structure does not meet the requirements, and the support diagnosis result is determined to be abnormal. Only when all sub-evaluation results are normal is the support diagnosis result determined to be normal, and no adjustment to the support structure is required.

[0055] The technical solution of this invention obtains a three-dimensional model of the vehicle after-processor bracket, and generates a mesh model by meshing the three-dimensional model according to simulation requirements. By analyzing the mesh model, the sub-evaluation results can be determined. The sub-evaluation results include modal structure results, stiffness evaluation results, and strength evaluation results. Finally, the bracket diagnosis results can be generated based on the sub-evaluation results. This realizes the simulation and diagnosis of the after-processor bracket structure during the bracket design process, which facilitates timely adjustment of the structure, saves manpower and material resources, and improves diagnostic efficiency. It comprehensively considers the bracket stiffness, strength, and modal analysis, thereby improving the accuracy of diagnosis.

[0056] Example 2

[0057] Figure 4 This is a flowchart of a vehicle after-processor bracket diagnostic method provided in Embodiment 2 of the present invention. This embodiment adds a specific process for generating a mesh model based on a 3D model, building upon Embodiment 1. The specific content of steps S260-S270 is largely the same as steps S120-S130 in Embodiment 1, and therefore will not be repeated in this embodiment. Figure 4 As shown, the method includes:

[0058] S210. Obtain the 3D model of the current vehicle's after-processor bracket.

[0059] S220. Obtain the target material number, and match it in the preset material library according to the target material number to obtain the target inherent attribute that matches the target material number. The material library includes the correspondence between material numbers and inherent attributes.

[0060] The material properties include the material's elastic modulus, Poisson's ratio, tensile strength, yield strength, and S / N curve. The controller can match the target material number entered by the user with a preset material library. The material library includes the correspondence between material numbers and inherent properties. For example, the target material number could be Q235, and the corresponding target inherent property can be matched in the material library using this target material number.

[0061] S230. Determine the focus components and target connectors of the 3D model.

[0062] Optionally, determining the components of interest and target connectors in the 3D model includes: obtaining the length of the target longitudinal beam, and obtaining the components of interest and their connection relationships based on the 3D model, wherein the connection relationships include connection lengths and connectors; and filtering each connection length according to the length of the target longitudinal beam to obtain target connectors that match the length of the target longitudinal beam.

[0063] Specifically, after obtaining the 3D model, it is necessary to identify the components of interest and target connectors. ANSA software can be used for geometric cleanup and model simplification, removing components with low relevance and other unnecessary structures in the model. During cleanup, connectors can be filtered according to their connection length, and structures with minimal impact on the calculation results can be simplified, i.e., parts that are far from the components of interest can be simplified.

[0064] S240. Obtain seed size and element type based on target connector and interest element, wherein seed size includes mesh density, and element type includes continuum element, shell element, thin film element, beam element, rod element, rigid body element, connection element and infinite element.

[0065] The element type is related to the user's analysis needs, and the seed size refers to the mesh density of each component in the mesh model.

[0066] S250 combines the target's inherent properties, seed size, element type, target connectors, and elements of interest to generate a mesh model.

[0067] It should be noted that the mesh model requirements include: the extracted chassis portion should be modeled using 2D elements, with element sizes defined based on the overall chassis dimensions. The standard is that the element sizes should accurately represent the chamfers, bends, and other features of the component. The afterprocessor assembly bracket should use a 3D second-order tetrahedral mesh. The mesh element sizes should also be defined based on the overall dimensions of the afterprocessor assembly bracket, ensuring that the element sizes accurately represent the chamfers, bends, and other features of the component. The quality of the mesh elements must meet the computational requirements; distorted elements such as excessively small elements or overly sharp angles are not permitted.

[0068] Specifically, each component (including components of interest and target connectors) needs to have its corresponding inherent properties set, and each component needs to be assigned a corresponding seed size and element type to generate a mesh model. Additionally, each component needs to have the correct density set to ensure that the total mass of the afterprocessor assembly matches the actual mass. For example, components such as the afterprocessor assembly bracket and frame can have their properties defined according to actual material properties. The afterprocessor assembly itself is not a component of interest in this calculation and is used as a load. Shell elements are used to simulate and determine the mass distribution of the afterprocessor assembly to ensure the total mass is correct.

[0069] S260. Generate sub-evaluation results based on the mesh model, including modal structure results, stiffness evaluation results, and strength evaluation results.

[0070] Optionally, generate sub-evaluation results based on the mesh model, including: generating modal structure results based on the mesh model; applying an acceleration load in a specified direction to the mesh model to perform stiffness and strength calculations and generate stiffness and strength calculation results; extracting displacement from the stiffness and strength calculation results; determining the stiffness evaluation result as normal when the displacement is within a specified displacement range; extracting stress values ​​from the stiffness and strength calculation results and generating strength evaluation results based on the stress values.

[0071] Optionally, generating modal structure results based on the mesh model includes: obtaining contact pairs and boundary constraints; performing modal calculations on the mesh model based on the contact pairs and boundary constraints to generate a modal cloud map; determining whether the color value in the modal cloud map is greater than a preset color threshold; if so, determining the modal structure result as abnormal; otherwise, determining the modal structure result as normal.

[0072] Optionally, a strength evaluation result is generated based on the stress value, including: inputting the stress value into a preset algorithm to determine a safety factor; determining whether the safety factor is greater than a preset threshold; if so, determining the strength evaluation result as normal; otherwise, determining the strength evaluation result as abnormal.

[0073] S270. Generate stent diagnosis results based on the results of each sub-evaluation.

[0074] Optionally, a stent diagnosis result is generated based on each sub-evaluation result, including: determining whether each sub-evaluation result contains abnormal results; if so, determining the stent diagnosis result as abnormal; otherwise, determining the stent diagnosis result as normal.

[0075] The technical solution of this invention obtains a three-dimensional model of the vehicle after-processor bracket, and generates a mesh model by meshing the three-dimensional model according to simulation requirements. By analyzing the mesh model, the sub-evaluation results can be determined. The sub-evaluation results include modal structure results, stiffness evaluation results, and strength evaluation results. Finally, the bracket diagnosis results can be generated based on the sub-evaluation results. This realizes the simulation and diagnosis of the after-processor bracket structure during the bracket design process, which facilitates timely adjustment of the structure, saves manpower and material resources, and improves diagnostic efficiency. It comprehensively considers the bracket stiffness, strength, and modal analysis, thereby improving the accuracy of diagnosis.

[0076] Example 3

[0077] Figure 5 This is a schematic diagram of a vehicle after-processor bracket diagnostic device provided in Embodiment 3 of the present invention. Figure 5 As shown, the device includes:

[0078] Mesh model generation module 310 is used to obtain the three-dimensional model of the current vehicle after-processor bracket and generate a mesh model based on the three-dimensional model;

[0079] The sub-evaluation result generation module 320 is used to generate various sub-evaluation results based on the mesh model. The sub-evaluation results include modal structure results, stiffness evaluation results, and strength evaluation results.

[0080] The stent diagnosis result generation module 330 is used to generate stent diagnosis results based on the results of each sub-evaluation.

[0081] Optionally, the mesh model generation module 310 specifically includes: a mesh model generation unit, used for: obtaining the target material number; matching the target material number in a pre-set material library to obtain the target intrinsic properties that match the target material number, wherein the material library includes the correspondence between material numbers and intrinsic properties; determining the components of interest and target connectors in the 3D model; obtaining the seed size and element type based on the target connectors and components of interest, wherein the seed size includes mesh density, and the element type includes continuum elements, shell elements, membrane elements, beam elements, rod elements, rigid body elements, connection elements, and infinite elements; and combining the target intrinsic properties, seed size, element type, target connectors, and components of interest to generate a mesh model.

[0082] Optionally, the mesh model generation unit specifically includes: a sub-unit for determining the components of interest and the target connectors, used to: obtain the length of the target longitudinal beam, and obtain the components of interest and their connection relationships based on the 3D model, wherein the connection relationships of the components of interest include connection lengths and connectors; and filter each connection length according to the length of the target longitudinal beam to obtain target connectors that match the length of the target longitudinal beam.

[0083] Optionally, the sub-evaluation result generation module 320 specifically includes: a modal structure result generation unit, used to generate modal structure results based on the mesh model; a stiffness calculation result generation unit, used to apply an acceleration load in a specified direction to the mesh model to perform stiffness calculation and generate stiffness calculation results; a stiffness evaluation result determination unit, used to extract displacement from the stiffness calculation results; when the displacement is within a specified displacement range, the stiffness evaluation result is determined to be normal; and a strength evaluation result generation unit, used to extract stress values ​​from the stiffness calculation results and generate strength evaluation results based on the stress values.

[0084] Optionally, the modal structure result generation unit is specifically used for: obtaining contact pairs and boundary constraints; performing modal calculations on the mesh model based on the contact pairs and boundary constraints to generate a modal cloud map; determining whether the color value in the modal cloud map is greater than a preset color threshold; if so, determining the modal structure result as abnormal; otherwise, determining the modal structure result as normal.

[0085] Optionally, the strength evaluation result generation unit is specifically used to: input the stress value into a preset algorithm to determine the safety factor; determine whether the safety factor is greater than a preset threshold; if so, determine the strength evaluation result as normal; otherwise, determine the strength evaluation result as abnormal.

[0086] Optionally, the stent diagnosis result generation module 330 is used to: determine whether each sub-evaluation result contains abnormal results; if so, determine that the stent diagnosis result is abnormal; otherwise, determine that the stent diagnosis result is normal.

[0087] The technical solution of this invention obtains a three-dimensional model of the vehicle after-processor bracket, and generates a mesh model by meshing the three-dimensional model according to simulation requirements. By analyzing the mesh model, the sub-evaluation results can be determined. The sub-evaluation results include modal structure results, stiffness evaluation results, and strength evaluation results. Finally, the bracket diagnosis results can be generated based on the sub-evaluation results. This realizes the simulation and diagnosis of the after-processor bracket structure during the bracket design process, which facilitates timely adjustment of the structure, saves manpower and material resources, and improves diagnostic efficiency. It comprehensively considers the bracket stiffness, strength, and modal analysis, thereby improving the accuracy of diagnosis.

[0088] The vehicle after-processor bracket diagnostic device provided in this embodiment of the invention can execute the vehicle after-processor bracket diagnostic method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0089] Example 4

[0090] Figure 6 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0091] like Figure 6 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0092] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0093] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as a vehicle after-processor bracket diagnostic method.

[0094] In some embodiments, a vehicle after-processor bracket diagnostic method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or mounted on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the vehicle after-processor bracket diagnostic method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform a vehicle after-processor bracket diagnostic method by any other suitable means (e.g., by means of firmware).

[0095] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0096] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0097] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0098] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0099] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0100] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0101] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0102] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A diagnostic method for a vehicle after-processor bracket, characterized in that, include: Obtain a 3D model of the current vehicle's after-processor bracket, and generate a mesh model based on the 3D model; Each sub-evaluation result is generated based on the mesh model, wherein the sub-evaluation results include modal structure results, stiffness evaluation results, and strength evaluation results; Generate stent diagnostic results based on the sub-evaluation results described above; The step of generating a mesh model based on the three-dimensional model includes: Obtain the target material number, and match it in a preset material library to obtain the target inherent attribute that matches the target material number. The material library includes the correspondence between material numbers and inherent attributes. Identify the elements of interest and target connectors in the 3D model; Seed size and element type are obtained based on the target connector and the element of interest, wherein the seed size includes mesh density, and the element type includes continuum element, shell element, thin film element, beam element, rod element, rigid body element, connecting element, and infinite element; The inherent properties of the target, the seed size, the cell type, the target connector, and the element of interest are combined to generate the mesh model; The step of determining the focus component and target connector of the 3D model includes: Obtain the length of the target longitudinal beam, and obtain the components of interest and their connection relationships based on the three-dimensional model, wherein the connection relationships of the components of interest include connection length and connecting components; The connection lengths are filtered according to the target longitudinal beam length to obtain target connectors that match the target longitudinal beam length.

2. The method according to claim 1, characterized in that, The generation of sub-evaluation results based on the grid model includes: Generate modal structure results based on the mesh model; An acceleration load in a specified direction is applied to the mesh model to perform stiffness calculation and generate stiffness calculation results; Extract the displacement from the stiffness calculation results; When the displacement is within the specified displacement range, the stiffness evaluation result is determined to be normal. Stress values ​​are extracted from the stiffness calculation results, and strength evaluation results are generated based on the stress values.

3. The method according to claim 2, characterized in that, The step of generating modal structure results based on the mesh model includes: Obtain contact pairs and boundary constraints; Modal calculations are performed on the mesh model based on the contact pairs and the boundary constraints to generate a modal cloud map. Determine whether the color value in the modal cloud map is greater than a preset color threshold. If so, determine that the modal structure result is abnormal. Otherwise, the modal structure result is determined to be normal.

4. The method according to claim 2, characterized in that, The step of generating a strength evaluation result based on the stress value includes: The stress value is input into a preset algorithm to determine the safety factor; Determine whether the safety factor is greater than a preset threshold; if so, determine that the strength evaluation result is normal. Otherwise, the intensity evaluation result is determined to be abnormal.

5. The method according to claim 1, characterized in that, The step of generating stent diagnostic results based on each of the sub-evaluation results includes: Determine whether each of the sub-evaluation results contains abnormal results; if so, determine that the stent diagnosis result is abnormal. Otherwise, the stent diagnosis result is determined to be normal.

6. A diagnostic device for a vehicle after-processor bracket, characterized in that, include: The mesh model generation module is used to obtain a three-dimensional model of the current vehicle after-processor bracket and generate a mesh model based on the three-dimensional model. The sub-evaluation result generation module is used to generate sub-evaluation results based on the mesh model, wherein the sub-evaluation results include modal structure results, stiffness evaluation results, and strength evaluation results; The stent diagnosis result generation module is used to generate stent diagnosis results based on the sub-evaluation results. The mesh model generation module specifically includes a mesh model generation unit, used for: obtaining a target material number; matching the target material number in a pre-set material library to obtain target intrinsic properties matching the target material number, wherein the material library includes the correspondence between material numbers and intrinsic properties; determining the components of interest and target connectors of the 3D model; obtaining seed size and element type based on the target connectors and components of interest, wherein the seed size includes mesh density, and the element type includes continuum elements, shell elements, membrane elements, beam elements, rod elements, rigid body elements, connection elements, and infinite elements; and combining the target intrinsic properties, seed size, element type, target connectors, and components of interest to generate the mesh model. The mesh model generation unit specifically includes a subunit for determining the components of interest and the target connectors, used to: obtain the length of the target longitudinal beam, and obtain the components of interest and their connection relationships based on the three-dimensional model, wherein the connection relationships of the components of interest include connection lengths and connectors; and filter each connection length according to the length of the target longitudinal beam to obtain target connectors that match the length of the target longitudinal beam.

7. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.

8. A computer storage medium, characterized in that, The computer storage medium stores computer instructions that are used to cause a processor to execute the method of any one of claims 1-5.

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