Automobile part installation deformation analysis method and device and electronic equipment

Abstract

The embodiment of the invention provides an automobile part installation deformation analysis method and device and electronic equipment, relates to the technical field of automobile manufacturing, and can comprehensively master multidirectional visual information of parts and assemblies by obtaining point cloud data of single parts and the assemblies before assembly. The method comprises the following steps: firstly, acquiring point cloud data, then carrying out alignment measurement on the point cloud data in a virtual environment to generate visual image data, then locking an installation deformation area from the image data, thus accurately measuring and quantifying installation deformation factors, and finally outputting part mold repair information according to the quantified installation deformation factors. According to the method, after the point cloud of the single part before installation and the point cloud of the assembly after installation are aligned, the interference values of the installation part and the installed part in the installation deformation area and the back face of the part can be quantitatively and visually output, then accurate part rectification guidance can be provided, and the cost of assembly deformation analysis and part mold repairing is remarkably reduced.

Description

[Technical field]

[0001] The embodiments of the present application relate to the field of automobile manufacturing technology, and in particular to a method, device and electronic equipment for analyzing the installation deformation of automobile parts. [Background technology]

[0002] At present, the analysis of the deformation problem of the installation of vehicle size matching parts mainly adopts the following steps: the installation single part and the installed single part are measured on their respective inspection fixtures, and the dimensional measurement data of the matching surface of each single part on the inspection fixture are recorded. Then, the installation single part and the installed single part are assembled together, and the clearance and fitting interference data of the matching positions between each single part in the assembly are recorded. The above dimensional measurement data and the assembly data are matched and compared, and the modification instructions of the parts are issued manually according to experience. After modification, the new part repeats the above steps until the assembly size matching problem is solved.

[0003] The above analysis schemes mainly have disadvantages such as high cost, low comparison and judgment accuracy, and reliance on manual experience. [Summary of the invention]

[0004] The embodiments of the present application propose an automobile part installation deformation analysis method, device and electronic equipment, which relate to the field of automobile manufacturing technology and can realize the analysis of component installation deformation and rectification guidance at low cost and high precision.

[0005] In a first aspect, an embodiment of the present application provides a method for analyzing deformation of automobile parts during installation, the method comprising:

[0006] At least obtain first point cloud data of the installation single part and second point cloud data of the assembly after the installation single part and the installed single part are assembled;

[0007] Aligning the first point cloud data with the second point cloud data;

[0008] Generate visual image data based on the alignment results, and determine the installation deformation area according to the image data;

[0009] Using the installation deformation area, determine and quantify the installation deformation factor;

[0010] Output part mold modification information according to the quantified installation deformation factor.

[0011] In at least one possible implementation manner, aligning the first point cloud data with the second point cloud data includes:

[0012] The first point cloud data is used as a target object and the second point cloud data is used as a reference object;

[0013] The outer surfaces of the non-matching areas of the mounting single part and the mounted single part are selected as the alignment area, and the target object is frontally aligned with the reference object using the fitting method.

[0014] In at least one possible implementation manner, determining the installation deformation area according to the image data includes:

[0015] Pre-set several color levels corresponding to the degree of deformation of parts;

[0016] Using the front alignment result of the installed single part and the assembly, and combining it with the color scale, a data color map is generated;

[0017] According to the different color areas presented in the data color map, the target area where the installation deformation occurs is determined.

[0018] In at least one possible implementation, determining and quantifying the installation deformation factor includes:

[0019] Based on the installation deformation area, constructing cross-sectional data of the first point cloud data and the second point cloud data;

[0020] The intrusion value of the first point cloud data relative to the second point cloud data is determined in the cross-sectional data.

[0021] In at least one possible implementation manner, the point cloud data acquisition method includes: using a visual measurement device to scan the point cloud data of at least the front and back sides of a single part and an assembly in a free state.

[0022] In at least one possible implementation, the point cloud data acquisition method specifically includes: acquiring continuous point cloud data of all surface features on both the front and back sides of a single part and an assembly.

[0023] The technical role of this solution can be referenced as follows: By obtaining the point cloud data of a single part before assembly and the point cloud data of the assembly after assembly, the multi-directional visual information of the parts and assemblies can be fully and visually grasped. Then, the point cloud data of the installed single part and the assembly are aligned and measured in a virtual environment, which can significantly save the related costs of the development, production, and maintenance of the inspection tools of the traditional analysis method. After that, visual image data is generated based on the alignment results, and the installation deformation area is determined from it. The installation deformation factor can be measured and quantified through the installation deformation area, and finally the part mold repair information is output according to the quantified installation deformation factor. That is, after the point cloud of the single part before installation and the assembly after installation is aligned, the interference data between the installed part and the installed part in the installation deformation area and the back of the part can be quantitatively measured, and then accurate part rectification data can be provided, thereby significantly reducing the cost of repeated part mold repair.

[0024] In a second aspect, an embodiment of the present application provides a device for analyzing deformation of automobile parts installation, the device comprising:

[0025] A point cloud data acquisition module, used for acquiring at least first point cloud data of an installed single part and second point cloud data of an assembly after the installed single part and the installed single part are assembled;

[0026] A point cloud data alignment module, used to align the first point cloud data with the second point cloud data;

[0027] A deformation area visualization module is used to generate visualized image data based on the alignment result, and determine the installation deformation area according to the image data;

[0028] A deformation factor quantification determination module is used to determine and quantify the installation deformation factor using the installation deformation area;

[0029] The mold repair information output module is used to output the part mold repair information according to the quantified installation deformation factor.

[0030] In at least one possible implementation, the deformation factor quantification measurement module is specifically used to: construct cross-sectional data of the first point cloud data and the second point cloud data based on the installation deformation area; and measure the intrusion value of the first point cloud data relative to the second point cloud data in the cross-sectional data.

[0031] In a third aspect, an embodiment of the present application provides an electronic device, comprising: one or more processors, a memory, and one or more computer programs, wherein the memory may adopt a non-volatile storage medium, wherein the one or more computer programs are stored in the memory, and the one or more computer programs include instructions, and when the instructions are executed by the device, the electronic device performs the method as described in the first aspect or any possible implementation manner of the first aspect.

[0032] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer-readable storage medium is run on a computer, the computer executes the method as described in the first aspect or any possible implementation of the first aspect.

[0033] It should be understood that the second to fourth aspects of the embodiments of the present application are consistent with the technical solutions of the first aspect of the embodiments of the present application, and the beneficial effects achieved by each aspect and the corresponding feasible implementation methods are similar and will not be repeated here.

Brief Description of the Drawings

[0034] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0035] Figure 1 A schematic diagram of a flow chart of an automobile parts installation deformation analysis method provided in an embodiment of the present application;

[0036] Figure 2 A schematic diagram of the structure of an automobile part installation deformation analysis device provided in an embodiment of the present application. [Specific implementation method]

[0037] In order to better understand the technical solution of this specification, the embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0038] It should be clear that the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this specification.

[0039] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit this specification. The singular forms of "a", "said" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0040] The current analytical methods have problems that need to be solved:

[0041] 1. Single and assembly parts need to develop inspection tools for measurement. Inspection tools for each part cannot be universal, and the investment in inspection tools is huge.

[0042] 2. The assembly can only judge whether installation deformation occurs by the matching gap or fit between parts. It is impossible to accurately judge whether the fit is just right or has interference deformation;

[0043] 3. The transfer of size problems from single parts to assemblies and the analysis of deformation problems rely on manual experience and cannot correspond accurately, requiring repeated mold modifications and multiple rounds of verification.

[0044] In view of this, the embodiment of the present application provides a method for analyzing the installation deformation of automobile parts. In this method, by obtaining the point cloud of a single part before assembly and the point cloud data of the assembly after assembly, the multi-directional visual information of the parts and the assembly can be comprehensively and visually grasped. Then, the point cloud data of the installed single part and the assembly are aligned and measured in a virtual environment, which can significantly save the related costs of the development, production, and maintenance of the inspection tool of the traditional analysis method. After that, visual image data is generated based on the alignment result, and the installation deformation area is determined therefrom. The installation deformation factor can be measured and quantified through the installation deformation area, and finally the part mold repair information is output according to the quantified installation deformation factor. That is, after the point cloud of the single part before installation and the assembly after installation is aligned, the interference data between the installed part and the installed part in the installation deformation area and the back of the part can be quantitatively measured, and then accurate part rectification data can be provided, thereby significantly reducing the cost of repeated mold repair of parts.

[0045] The technical solution protected by the embodiments of the present application is described in detail below with reference to the accompanying drawings.

[0046] See also Figure 1 , is a flow chart of a method for analyzing the installation deformation of automobile parts provided in an embodiment of the present application. The flow chart of the method is described as follows:

[0047] Step S1, obtaining at least first point cloud data of an installation single part and second point cloud data of an assembly after the installation single part and the installed single part are assembled;

[0048] Specifically, mature visual measurement equipment can be used to scan single parts and assemblies. For example, the single installed part to be measured can be placed on a bracket with at least three points of support to obtain the front and back point cloud data of the single installed part in a free state (non-clamped); and, not excluded, the single installed part that matches the single installed part can also be used to obtain point cloud data using the same scanning method. Afterwards, the assembly obtained by assembling the single installed part and the single installed part can also be scanned and the assembly point cloud data can be obtained using the above method.

[0049] In this embodiment, it is mentioned that visual measurement methods such as laser scanning or blue light photography can be used to obtain continuous data of all surface features on the front and back sides of the measured parts and assemblies, while traditional inspection fixtures or three-coordinate measurement methods can only obtain circumferential matching points or discrete measurement point data of the target.

[0050] Step S2, fitting and aligning the first point cloud data with the second point cloud data;

[0051] The actual operation method of aligning point cloud data can be referred to as follows: import the above-mentioned single part point cloud and the assembly point cloud obtained by matching these parts into software such as but not limited to Polyworks. In Polyworks software, the assembly point cloud data is used as the reference object, the point cloud data of the installed single part scanned in the free state is used as the target object, and the outer surface of the non-matching area of ​​the installed single part and the installed single part is selected as the alignment area, and the first point cloud data is aligned with the second point cloud data using the fitting alignment method. In this embodiment, the point cloud data of the installed single part and the assembly are used to align and measure in a virtual environment, which can significantly save the related costs of the development, production, and maintenance of the inspection tool of the traditional analysis method.

[0052] Step S3, generating visual image data based on the alignment result, and determining the installation deformation area according to the image data;

[0053] Specifically, the point cloud data of a single part before installation and the assembly after installation can be aligned and measured head-on, and a corresponding data color map can be generated to visually observe the area where the deformation problem occurs.

[0054] For example, in an example of determining an installation deformation area, a color scale based on the deformation amount of the part can be set, such as deformation amount (-0.5-0.5) for green, (>0.5) for yellow, and (<-0.5) for light blue, and then a color map is generated using software such as Polyworks. When a yellow area appears, it means that after the part is installed, interference deformation occurs in this area due to interference between the installing single part and the installed single part.

[0055] Step S4, using the installation deformation area, determining and quantifying the installation deformation factor;

[0056] In combination with the previous example, a cross section of the first point cloud data and the second point cloud data can be made in the yellow area. In the cross-sectional data, the intrusion value of the first point cloud data relative to the second point cloud data is measured. This value is the quantitative representation of the interference between the installed single part and the installed single part. In other words, the factors causing the installation deformation are also determined. The process of quantifying the deformation of parts and the interference between matching parts can accurately quantify the areas hidden on the back (reverse) of the parts that cannot be measured by traditional means.

[0057] Step S5: output part mold repair information according to the quantified installation deformation factor.

[0058] Finally, through the above processing process, the parts can be effectively and accurately ground, and then the new parts after mold repair can be installed and verified. That is, after aligning the point cloud of the single part before installation with the point cloud of the assembly after installation, the interference data between the installed part and the installed part in the installation deformation area and the back of the part can be quantitatively measured, and then accurate rectification data can be provided. This method significantly reduces the cost of repeated mold repair of parts.

[0059] See also Figure 2 Based on the same inventive concept, the embodiment of the present application also provides an automobile parts installation deformation analysis device, the device comprising:

[0060] The point cloud data acquisition module 201 is used to obtain at least first point cloud data of the installation single part and second point cloud data of the assembly after the installation single part and the installed single part are assembled;

[0061] A point cloud data alignment module 202, used to align the first point cloud data with the second point cloud data;

[0062] A deformation region visualization module 203 is used to generate visualized image data based on the alignment result, and determine the installation deformation region according to the image data;

[0063] The deformation factor quantification determination module 204 is used to determine and quantify the installation deformation factor using the installation deformation area;

[0064] The mold repair information output module 205 is used to output the part mold repair information according to the quantified installation deformation factor.

[0065] Optionally, the deformation factor quantitative determination module is specifically used to: construct cross-sectional data of the first point cloud data and the second point cloud data based on the installation deformation area; and determine the intrusion value of the first point cloud data relative to the second point cloud data in the cross-sectional data.

[0066] Based on the same inventive concept, an embodiment of the present application also provides an electronic device, including at least one processor, which is used to execute a computer program stored in a memory to implement the flow chart steps of the above-mentioned automobile part installation deformation analysis method provided in the embodiment of the present application.

[0067] Optionally, the processor may specifically be a central processing unit, a specific ASIC, or one or more integrated circuits for controlling program execution.

[0068] Optionally, the electronic device may further include a memory connected to at least one processor, and the memory may include ROM, RAM, and disk storage. The memory is used to store data required by the processor when it is running, that is, it stores instructions that can be executed by at least one processor, and at least one processor executes the methods mentioned in the above embodiments by executing the instructions stored in the memory. Among them, the number of memories is one or more. Among them, the number of memories is one or more.

[0069] An embodiment of the present application also provides a computer storage medium, wherein the computer storage medium stores computer instructions. When the computer instructions are executed on a computer, the computer executes the methods mentioned in the above embodiments.

[0070] The above description is only a preferred embodiment of this specification and is not intended to limit this specification. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of this specification should be included in the scope of protection of this specification.

Claims

1. A method for analyzing the installation deformation of automobile parts, characterized in that: The method comprises: At least obtain first point cloud data of the installation single part and second point cloud data of the assembly after the installation single part and the installed single part are assembled; Aligning the first point cloud data with the second point cloud data; Generate visual image data based on the alignment results, and determine the installation deformation area according to the image data; Using the installation deformation area, determine and quantify the installation deformation factor; Output part mold modification information according to the quantified installation deformation factor.

2. The automobile parts installation deformation analysis method according to claim 1, characterized in that: The aligning the first point cloud data with the second point cloud data comprises: The first point cloud data is used as a target object and the second point cloud data is used as a reference object; The outer surfaces of the non-matching areas of the mounting single part and the mounted single part are selected as the alignment area, and the target object is frontally aligned with the reference object using the fitting method.

3. The automobile parts installation deformation analysis method according to claim 2, characterized in that: Determining the installation deformation area according to the image data includes: Pre-set several color levels corresponding to the degree of deformation of parts; Using the front alignment result of the installed single part and the assembly, and combining it with the color scale, a data color map is generated; According to the different color areas presented in the data color map, the target area where the installation deformation occurs is determined.

4. The automobile parts installation deformation analysis method according to claim 1, characterized in that: The determining and quantifying of the installation deformation factors includes: Based on the installation deformation area, constructing cross-sectional data of the first point cloud data and the second point cloud data; The intrusion value of the first point cloud data relative to the second point cloud data is determined in the cross-sectional data.

5. The automobile parts installation deformation analysis method according to any one of claims 1 to 4, characterized in that: The point cloud data acquisition method includes: using a visual measurement device to scan the point cloud data of at least the front and back sides of a single part and an assembly in a free state.

6. The automobile parts installation deformation analysis method according to claim 5, characterized in that: The point cloud data acquisition method specifically includes: acquiring continuous point cloud data of all surface features on both the front and back sides of a single part and an assembly.

7. An automobile parts installation deformation analysis device, characterized in that: The device comprises: A point cloud data acquisition module, used for acquiring at least first point cloud data of an installed single part and second point cloud data of an assembly after the installed single part and the installed single part are assembled; A point cloud data alignment module, used to align the first point cloud data with the second point cloud data; A deformation area visualization module is used to generate visualized image data based on the alignment result, and determine the installation deformation area according to the image data; A deformation factor quantification determination module is used to determine and quantify the installation deformation factor using the installation deformation area; The mold repair information output module is used to output the part mold repair information according to the quantified installation deformation factor.

8. The automobile parts installation deformation analysis device according to claim 7, characterized in that: The deformation factor quantitative determination module is specifically used to: construct cross-sectional data of the first point cloud data and the second point cloud data based on the installation deformation area; and determine the intrusion value of the first point cloud data relative to the second point cloud data in the cross-sectional data.

9. An electronic device, characterized in that: include: One or more processors, a memory and one or more computer programs, wherein the one or more computer programs are stored in the memory, and the one or more computer programs include instructions, which, when executed by the electronic device, enable the electronic device to execute the automobile part installation deformation analysis method according to any one of claims 1 to 6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the automobile part installation deformation analysis method according to any one of claims 1 to 6 is implemented.

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