Method and system for quickly checking abnormal sound risk of body in white

Abstract

The invention belongs to the technical field of body-in-white design, and particularly relates to a body-in-white abnormal sound risk rapid inspection method and system.The body-in-white abnormal sound risk rapid inspection method comprises the steps that a body-in-white finite element model is obtained, and the model at least comprises metal plate data and welding spot data; on the basis of the sheet metal data, screening out a grid surface with a gap value between a sheet metal unit and an adjacent sheet metal unit smaller than a preset gap value, and marking the grid surface as a to-be-analyzed surface; on the basis of the welding spot data, a surrounding ball with the welding spot center as the circle center and the preset diameter is created for each welding spot; performing Boolean subtraction operation on the to-be-analyzed surface and the surrounding ball, and screening out a metal plate surface which is not covered by the surrounding ball; deleting the sheet metal surface with the area smaller than a preset area, and outputting a potential abnormal sound risk area; and re-importing the potential abnormal sound risk area into the body-in-white finite element model, and displaying a target risk area by adjusting visual parameters. According to the invention, the vehicle body abnormal sound problem can be rapidly identified.

Description

Technical Field

[0001] The present invention belongs to the technical field of body-in-white design, and in particular relates to a method and system for quickly inspecting the risk of abnormal noise in a body-in-white. Background Art

[0002] Abnormal vehicle noise is a frequent customer complaint during vehicle use. Its causes are complex and involve all vehicle components. Body-in-white (BIW) noise is a major source of this noise, and after-sales repairs are difficult and costly, significantly impacting customer satisfaction. Therefore, identifying and thoroughly addressing BIW noise before full vehicle production is crucial.

[0003] Generally, the inspection method for abnormal noise of the body in white is divided into two stages according to the vehicle development stage: data inspection and test development. The data inspection stage is to conduct design verification based on some empirical criteria for the data of the body in white sheet metal design, welding point layout, gluing layout, etc. during the body data design stage. The work is relatively complicated and the inspection cycle is long. The test development stage is a series of test development work based on engineering prototypes and trial production prototypes, including whole vehicle road tests, whole vehicle bench tests, and subsystem-level bench tests (body in white, doors and other subsystems, etc.). The development of abnormal noise tests is intuitive, but the search for the source of the abnormal noise often requires a lot of effort, and the manpower and resource investment is large. Therefore, it is particularly important to be able to accurately and quickly identify potential risk sources of abnormal noise in the body in white during the body data design stage. Summary of the Invention

[0004] In view of the above-mentioned shortcomings of the prior art, an object of the present invention is to provide a method and system for quickly checking the risk of abnormal noise of a body-in-white (BIW), which can quickly identify abnormal noise problems of the body-in-white (BIW).

[0005] To achieve the above objectives, the present invention adopts the following technical solutions.

[0006] A first aspect of the present invention provides a method for quickly checking the risk of abnormal noise of a body-in-white (BIW), comprising: Obtaining a finite element model of a body-in-white, wherein the model at least includes sheet metal data and welding point data; Based on the sheet metal data, mesh surfaces having a gap value between sheet metal units and adjacent sheet metal unit surfaces that is less than a preset gap value are screened out and marked as surfaces to be analyzed; Creating, based on the solder point data, for each solder point, a bounding sphere with a center of the solder point as the center and a preset diameter; Perform a Boolean subtraction operation on the surface to be analyzed and the enclosing sphere to filter out the sheet metal surface not covered by the enclosing sphere; Delete sheet metal surfaces with an area smaller than the preset area and output potential noise risk areas; The potential abnormal noise risk area is re-imported into the body-in-white finite element model, and the target risk area is displayed by adjusting the visualization parameters.

[0007] As an embodiment of the present invention, the file format of the body-in-white finite element model is .nas, .bdf or a finite element analysis compatible format.

[0008] As an embodiment of the present invention, the surface to be analyzed is marked by independent naming or labeling.

[0009] As an embodiment of the present invention, the preset diameter of the surrounding sphere is set to match the design experience value of the welding point spacing.

[0010] As an embodiment of the present invention, the Boolean subtraction operation is used to calculate the geometric difference between the surface to be analyzed and the set of bounding spheres.

[0011] As an embodiment of the present invention, the visualization parameter includes at least one of color and transparency.

[0012] As an embodiment of the present invention, the model further includes structural adhesive data and fixed point data; the target risk area is manually composite-verified using the structural adhesive data and the fixed point data.

[0013] As an embodiment of the present invention, after the target risk area is displayed by adjusting the visualization parameters, the solder joint arrangement optimization or the glue coating path correction is guided based on the visualization result of the target risk area.

[0014] A second aspect of the present invention provides a rapid inspection system for abnormal noise risk of a body-in-white (BIW), comprising: A model acquisition module is used to obtain a finite element model of the body-in-white, wherein the model includes at least sheet metal data and weld point data; a gap analysis module is used to screen out mesh surfaces where the gap between sheet metal units and adjacent sheet metal unit surfaces is less than a preset gap value based on the sheet metal data, and mark them as surfaces to be analyzed; A solder point enclosing module, which creates an enclosing sphere for each solder point based on the solder point data, with the solder point center as the circle center and a preset diameter; The Boolean operation module performs a Boolean subtraction operation on the surface to be analyzed and the enclosing sphere to filter out the sheet metal surfaces not covered by the enclosing sphere; the broken surface filtering module deletes the sheet metal surfaces with an area smaller than a preset area and outputs the potential abnormal noise risk area; The visualization module re-imports the potential abnormal noise risk area into the body-in-white finite element model and displays the target risk area by adjusting the visualization parameters.

[0015] The third aspect of the present invention provides an electronic device, comprising: at least one processor; and at least one memory communicatively connected to the processor, wherein: the memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to execute the steps of the method described in the first aspect of the present invention.

[0016] A fourth aspect of the present invention provides a readable storage medium storing a computer program, which is used by a processor to execute the steps of the method described in the first aspect of the present invention.

[0017] In summary, compared to existing technologies, this invention achieves automated localization of abnormal noise risk areas by combining sheet metal gap screening, weld point bounding sphere construction, Boolean subtraction operations, and small-area surface filtering within the finite element model of the body-in-white (BIW). Based on geometric operations and parameterized thresholds, it effectively eliminates misjudgments caused by mesh noise or weld point overlap, significantly improving risk detection efficiency. By spatially aligning the screening results with the original model and dynamically adjusting visualization parameters, target risk areas are intuitively identified, addressing the technical shortcomings of traditional manual inspections, which rely on experience, are time-consuming, and prone to missed detections. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0019] Figure 1 The figure is a flow chart of a method for quickly checking abnormal noise risk of a body-in-white according to a specific embodiment of the present invention.

[0020] Figure 2 This is a diagram of a body-in-white model before screening according to a specific embodiment of the present invention.

[0021] Figure 3 This is a schematic diagram of a unit surface after screening according to a specific embodiment of the present invention with a gap less than 0.5 mm.

[0022] Figure 4 This is a solder joint data diagram according to a specific embodiment of the present invention.

[0023] Figure 5 A specific embodiment of the present invention is based on Figure 4 The bounding sphere data graph generated from the solder joint data graph shown.

[0024] Figure 6 This is a schematic diagram of a target risk area according to a specific embodiment of the present invention.

[0025] Figure 7 The block diagram of a rapid inspection system for abnormal noise risk of a body-in-white according to a specific embodiment of the present invention is shown.

[0026] Figure 8 FIG. 1 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of this application. In addition, it should be understood that the specific embodiments described herein are only used to illustrate and explain the present application and are not used to limit the present application.

[0028] It should be noted that the order of description of the following embodiments does not limit the preferred order of the embodiments of the present application. In addition, in the following embodiments, the description of each embodiment has its own focus. For parts not described in detail in one embodiment, please refer to the relevant description of other embodiments.

[0029] The body in white (BIW) is a core structural component in the automotive manufacturing process. It refers to the unpainted body frame assembly formed by sheet metal parts welded, bonded with structural adhesives, and bolted together. Its structural strength and connection reliability directly determine vehicle safety, NVH (noise, vibration, and harshness) performance, and the risk level of abnormal noise. BIW design must strike a balance between lightweight and rigidity. However, due to inaccurate control of sheet metal overlap gaps, improper weld point distribution, or defects in structural adhesive coating, unexpected contact between sheet metal parts caused by vibration during driving can easily occur, resulting in abnormal noise.

[0030] Traditional body-in-white (BIW) noise detection relies on prototype road tests and manual audio inspections, which have the following defects: (1) Physical prototypes need to be produced, which is costly and time-consuming; (2) Manual audio inspections are highly subjective and difficult to quantify and locate the source of the noise; (3) Risks cannot be predicted during the design phase, and subsequent rectifications lead to a surge in development costs.

[0031] like Figure 1 As shown, the first aspect of the present invention provides a method for quickly checking the risk of abnormal noise of a body-in-white, including the following steps.

[0032] Step S100: obtaining a finite element model of a body-in-white, wherein the model at least includes sheet metal data, welding point data, structural adhesive data, and fixing point data.

[0033] Specifically, such as Figure 2As shown, the finite element model of the body in white can be established through computer-aided engineering (CAE), which includes all the sheet metal data, welding point data, structural adhesive data and fixing point data of the body in white. Through the finite element network, it can discretize the sheet metal surface shape and connection relationship to simulate the structural mechanical behavior of the body.

[0034] Step S200: Filtering out mesh surfaces whose gap values ​​between sheet metal units and adjacent sheet metal unit surfaces are smaller than a preset gap value based on the sheet metal data, and marking them as surfaces to be analyzed.

[0035] Specifically, such as Figure 3 As shown in the figure, when a vehicle vibrates, a small gap between adjacent sheet metal units can easily cause collision noise. Therefore, by marking the surface to be analyzed, it is possible to preliminarily locate areas at risk of vibration contact and identify defects in advance. The preset gap value can be set based on the vibration amplitude and material deformation threshold. For example, the present invention sets the preset gap value to 4mm. In principle, the preset gap value is not described in specific numbers and can be determined based on engineering experience.

[0036] For example, those skilled in the art can screen out units with adjacent sheet metal gaps less than 0.5 mm based on specific practice, reflect them in the finite element model, and make a simple conversion of the unit thickness, that is, the gap between two adjacent unit surfaces in the finite element model is -0.5*(unit surface 1 thickness + unit surface 2 thickness) ≤ 0.5 mm.

[0037] Step S300: creating a bounding sphere with a preset diameter and a center of the solder point as the center of each solder point based on the solder point data.

[0038] Specifically, such as Figure 4 and Figure 5 As shown, the enclosing sphere is a three-dimensional spherical geometric body generated with the center of the weld as the center of the circle. Its spatial range is controlled by a preset diameter, which represents the constraint coverage area design of the weld on the surrounding sheet metal parts. The function of the enclosing sphere is to mark the effective influence range of the weld. By visually defining the weld-related area with a spherical space, the weld protection capability is quantified.

[0039] Specifically, the preset diameter of the surrounding sphere is an adjustable parameter. In the present invention, the preset diameter is adjusted to 65 mm, which matches the empirical value of the welding point spacing design.

[0040] Step S400: performing a Boolean subtraction operation on the surface to be analyzed and the enclosing sphere to filter out the sheet metal surfaces not covered by the enclosing sphere.

[0041] Specifically, the Boolean subtraction operation is used to calculate the geometric difference between the surface to be analyzed and the set of bounding spheres. Boolean subtraction is a geometric operation defined as subtracting the overlapping portion of the second geometric object (the bounding sphere) from the first geometric object (the surface to be analyzed). This is expressed as: Resulting surface = Surface to be analyzed - (Surface to be analyzed ∩ Bounding Sphere). The remaining portion of the sheet metal surface after the Boolean subtraction operation is the local area not contained by any bounding sphere.

[0042] Step S500: Delete the sheet metal surfaces with an area smaller than a preset area and output the potential abnormal noise risk area.

[0043] Specifically, the preset area is an adjustable parameter. In the present invention, the preset area is set to 20mm 2 , which is used as a technical parameter to balance the analysis accuracy and calculation efficiency. By deleting small broken surfaces smaller than the preset area, invalid interference can be eliminated to ensure that the output abnormal sound risk area has engineering analysis value. Specifically, the preset area is 20mm 2 The reason is that the broken surface smaller than 20mm2 is usually considered to be an interference-ineffective surface or an area that is unlikely to produce abnormal noise, which can reduce the workload of subsequent inspections.

[0044] Step S600: re-importing the potential abnormal noise risk area into the body-in-white finite element model, and displaying the target risk area by adjusting visualization parameters.

[0045] like Figure 6 Specifically, by loading the potential abnormal noise risk area into the original body-in-white finite element model and keeping the model spatially aligned with the risk data, the risk sheet metal area can be highlighted in the finite element model, that is, the spatial coordinate set of the target risk area. Figure 6 In the figure, the red part represents the abnormal noise risk surface obtained by the final treatment.

[0046] Here, the present invention realizes the automatic location of abnormal noise risk areas by combining sheet metal gap screening, weld point enclosing sphere construction, Boolean subtraction operation and small area surface filtering steps in the body-in-white finite element model. Based on geometric operations and parameterized thresholds (gap < preset gap value such as 4mm, enclosing sphere diameter is preset diameter such as 65mm, area ≥ preset area such as 20mm 2 ), effectively eliminating misjudgments caused by grid noise or solder joint coverage, and significantly improving risk detection efficiency; by spatially aligning the screening results with the original model and dynamically adjusting the visualization parameters, the target risk area is intuitively identified, solving the technical defects of traditional manual inspection that relies on experience, is time-consuming and prone to missed inspections.

[0047] In one embodiment of the present invention, the file format of the body-in-white finite element model is .nas, .bdf or a finite element analysis compatible format.

[0048] In one embodiment of the present invention, the visualization parameter includes at least one of color and transparency.

[0049] Specifically, the color parameter is used to distinguish the RGB value or preset color code of the risk area from the non-risk area, such as red represents the risk surface, and the transparency parameter is used to display the transparency value of the level, such as the transparency of the non-risk area is set to 50%.

[0050] In one embodiment of the present invention, the target risk area is manually verified using structural adhesive data and fixed point data.

[0051] Here, by combining risk area data with multi-source design data such as structural adhesives and fixing points for composite verification, a dual analysis mechanism of "geometric screening-physical association" is formed to ensure the engineering interpretability of risk judgment; in addition, the present invention can also be combined with dynamic parameter optimization, such as adaptive adjustment of the enclosing sphere size of the weld type and generation of risk heat maps, to provide a data-driven decision-making basis for weld point arrangement and glue coating path, shorten the white body design verification cycle, and avoid rework costs caused by abnormal noise problems in the later stage.

[0052] like Figure 7 As shown, the second aspect of the present invention provides a rapid inspection system for abnormal noise risk of a body-in-white, comprising: The model acquisition module 71 is used to obtain a finite element model of the body-in-white, which includes at least sheet metal data and weld point data. The gap analysis module 72 is used to screen out mesh surfaces 73 where the gap between sheet metal units and adjacent sheet metal units is less than a preset gap value based on the sheet metal data, and mark them as surfaces to be analyzed. A solder point enclosing module 74 is configured to create an enclosing sphere for each solder point based on the solder point data, with the center of the solder point as the center and the diameter being a preset diameter; A Boolean operation module 75 performs a Boolean subtraction operation on the surface to be analyzed and the enclosing sphere to filter out the sheet metal surface not covered by the enclosing sphere; The broken surface filtering module 76 deletes sheet metal surfaces with an area smaller than a preset area and outputs potential abnormal noise risk areas; The visualization module re-imports the potential abnormal noise risk area into the body-in-white finite element model and displays the target risk area by adjusting the visualization parameters.

[0053] Based on the same idea as the method in the above embodiment, the system provided by the present invention can implement the method in the above embodiment. For the convenience of explanation, the structural diagram of the system embodiment only shows the parts related to the embodiment of the present invention. Those skilled in the art can understand that the illustrated structure does not constitute a limitation on the system, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0054] like Figure 8 As shown, the third aspect of the present invention provides an electronic device, including: At least one processor; and at least one memory communicatively connected to the processor, wherein: the memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to execute the steps of the method described in any one of the above embodiments.

[0055] A fourth aspect of the present invention discloses a readable storage medium storing a computer program, which is used by a processor to execute the steps of the method described in any one of the above embodiments.

[0056] Computer-readable storage media may include: any entity or device capable of carrying a computer program, recording media, USB flash drives, mobile hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), and software distribution media. A computer program includes computer program code. The computer program code may be in source code form, object code form, an executable file, or some intermediate form. Computer-readable storage media may include: any entity or device capable of carrying a computer program code, recording media, USB flash drives, mobile hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), and software distribution media.

[0057] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention pertain.

[0058] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, apparatus or device (such as a computer-based system, a system including a processing module, or other system that can fetch instructions from an instruction execution system, apparatus or device and execute instructions), or used in conjunction with such instruction execution systems, apparatuses or devices.

[0059] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A rapid inspection method for abnormal noise risk of a body-in-white, characterized by: include: Obtaining a finite element model of a body-in-white, wherein the model at least includes sheet metal data and welding point data; Based on the sheet metal data, mesh surfaces having a gap value between sheet metal units and adjacent sheet metal unit surfaces that is less than a preset gap value are screened out and marked as surfaces to be analyzed; Creating, based on the solder point data, for each solder point, a bounding sphere with a center of the solder point as the center and a preset diameter; Perform a Boolean subtraction operation on the surface to be analyzed and the enclosing sphere to filter out the sheet metal surface not covered by the enclosing sphere; Delete sheet metal surfaces with an area smaller than the preset area and output potential noise risk areas; The potential abnormal noise risk area is re-imported into the body-in-white finite element model, and the target risk area is displayed by adjusting the visualization parameters.

2. The rapid inspection method for abnormal noise risk of a body-in-white according to claim 1 is characterized in that: The file format of the body-in-white finite element model is .nas, .bdf or a finite element analysis compatible format.

3. The rapid inspection method for abnormal noise risk of a body-in-white according to claim 1 is characterized in that: The surface to be analyzed is marked by independent naming or labeling.

4. The rapid inspection method for abnormal noise risk of a body-in-white according to claim 1 is characterized in that: The Boolean subtraction operation is used to calculate the geometric difference between the surface to be analyzed and the bounding sphere set.

5. The rapid inspection method for abnormal noise risk of a body-in-white according to claim 1 is characterized in that: The visualization parameter includes at least one of color and transparency.

6. The rapid inspection method for abnormal noise risk of a body-in-white according to claim 1 is characterized in that: The model also includes structural adhesive data and fixed point data; the target risk area is manually composite-verified using the structural adhesive data and fixed point data.

7. The rapid inspection method for abnormal noise risk of a body-in-white according to claim 1 is characterized in that: After the target risk area is displayed by adjusting the visualization parameters, the solder joint arrangement optimization or glue coating path correction is guided based on the visualization result of the target risk area.

8. A rapid inspection system for abnormal noise risk of a body in white, characterized by: include: A model acquisition module, used to acquire a finite element model of a body-in-white, wherein the model at least includes sheet metal data and welding point data; A gap analysis module, based on the sheet metal data, screens out mesh surfaces where the gap between sheet metal units and adjacent sheet metal unit surfaces is less than a preset gap value, and marks them as surfaces to be analyzed; A solder point enclosing module, which creates an enclosing sphere for each solder point based on the solder point data, with the solder point center as the circle center and a preset diameter; A Boolean operation module performs a Boolean subtraction operation on the surface to be analyzed and the enclosing sphere to filter out the sheet metal surface not covered by the enclosing sphere; The broken surface filtering module deletes sheet metal surfaces with an area smaller than a preset area and outputs potential abnormal noise risk areas; The visualization module re-imports the potential abnormal noise risk area into the body-in-white finite element model and displays the target risk area by adjusting the visualization parameters.

9. An electronic device, characterized in that: include: at least one processor; and at least one memory communicatively connected to the processor, wherein: the memory stores program instructions executable by the processor, and the processor calls the program instructions to execute the steps of the rapid inspection method for the risk of abnormal noise of the white body as described in any one of claims 1-7.

10. A readable storage medium storing a computer program, characterized in that: The computer program is used by a processor to execute the steps of the method for quickly checking the risk of abnormal noise of a body-in-white according to any one of claims 1 to 7.

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