Hub defect detection method and hub defect detection equipment

Abstract

The invention provides a hub defect detection method and hub defect detection equipment. According to the wheel hub defect detection method, the model of the target wheel hub is identified, and the matched detection position calibration parameters and image acquisition setting parameters are obtained from the pre-constructed wheel hub model library, so that full-compatible detection of different models of wheel hubs is realized. Through orientation calibration and adjustment, it is ensured that the hub is located at the optimal detection position, and detection blind areas or errors caused by incorrect positions are avoided. According to the method, all key parts, including a bolt hole, a hub included angle, a spoke, a hub window, a rim side wall, a center hole, a wheel edge, a hub back cavity, a rim inner wall and the like, of the hub are comprehensively detected, and the defect detection result of the hub is determined by integrating all detection information. Generally speaking, the method effectively solves the problem that in the prior art, compatibility of various types of hubs is difficult, the accuracy and efficiency of detection are improved, and the quality and safety of the hubs are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of component defect detection, and in particular to a wheel hub defect detection method and wheel hub defect detection equipment. Background Art

[0002] As an important carrier of automobile safety and aesthetics, wheels often have the risk of multiple types of defects during the production process due to the characteristics of the manufacturing process and the complexity of the processing links.

[0003] Traditional optical inspection methods can achieve non-contact measurement to a certain extent, but the wide variety of wheel styles on the market makes it easy for certain wheels to have blind spots due to surface reflections, spoke obstructions, and deep holes, leading to inaccurate or incomplete inspection results. Therefore, wheel defect detection technologies struggle to be compatible with multiple wheel types. Summary of the Invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art. To this end, the present invention provides a wheel hub defect detection method and wheel hub defect detection device, which are compatible with various types of wheel hub detection.

[0005] A wheel hub defect detection method according to an embodiment of the first aspect of the present invention is applied to a wheel hub defect detection device, comprising:

[0006] Perform wheel hub model identification on the target wheel hub to determine the target wheel hub model;

[0007] Obtaining detection position calibration parameters and image acquisition setting parameters matching the target wheel hub model from a pre-built wheel hub model library;

[0008] Performing orientation calibration on the target wheel hub based on the detection position calibration parameters, and adjusting the target wheel hub to a calibration accommodation orientation;

[0009] Performing bolt hole defect detection and hub angle defect detection on the target hub in the calibrated accommodation position based on the image acquisition setting parameters to obtain bolt hole detection information and hub angle detection information;

[0010] Performing spoke defect detection on the target wheel hub in the calibrated accommodation position based on the image acquisition setting parameters to obtain spoke detection information;

[0011] Performing hub window defect detection and rim sidewall defect detection on the target hub in the calibrated accommodation position based on the image acquisition setting parameters to obtain hub window detection information and rim sidewall detection information;

[0012] Performing center hole defect detection and wheel rim defect detection on the target wheel hub in the calibration accommodation position based on the image acquisition setting parameters to obtain center hole detection information and wheel rim detection information;

[0013] Performing wheel hub back cavity defect detection and wheel rim inner wall defect detection on the target wheel hub in the calibrated accommodation position based on the image acquisition setting parameters to obtain wheel hub back cavity detection information and wheel rim inner wall detection information;

[0014] The hub defect detection result of the target hub is determined based on the bolt hole detection information, the hub angle detection information, the spoke detection information, the hub window detection information, the rim sidewall detection information, the center hole detection information, the wheel edge detection information, the hub back cavity detection information and the rim inner wall detection information.

[0015] According to some embodiments of the present invention, before acquiring the detection position calibration parameters and image acquisition setting parameters matching the target wheel hub model from the pre-built wheel hub model library, the process further includes pre-building the wheel hub model library, specifically including:

[0016] Obtaining three-dimensional wheel hub models corresponding to a plurality of candidate wheel hub models;

[0017] Performing dimension analysis based on the three-dimensional wheel hub models to obtain wheel hub dimension parameters that match each candidate wheel hub model;

[0018] Based on the wheel hub size parameters, position calibration parameter configuration is performed on each candidate wheel hub model to obtain detection position preset parameters matching each candidate wheel hub model;

[0019] Based on the wheel size parameters, image acquisition parameters are configured for each candidate wheel model to obtain image acquisition preset parameters matching each candidate wheel model;

[0020] The step of obtaining detection position calibration parameters and image acquisition setting parameters that match the target wheel hub model from the pre-built wheel hub model library includes:

[0021] Determining the candidate wheel hub model that matches the target wheel hub model from the wheel hub model library;

[0022] For the candidate wheel hub model that matches the target wheel hub model, the corresponding detection position preset parameters are determined as the detection position calibration parameters, and the corresponding image acquisition preset parameters are determined as the image acquisition setting parameters.

[0023] According to some embodiments of the present invention, the wheel hub defect detection device includes a first image acquisition device, and the azimuth calibration of the target wheel hub based on the detection position calibration parameter and the adjustment of the target wheel hub to the calibration accommodation position include:

[0024] transporting the target wheel hub to a first accommodation area;

[0025] Performing position recognition on the target wheel hub in the first accommodation area by the first image acquisition device to obtain a current accommodation position of the target wheel hub;

[0026] An orientation adjustment operation is performed on the target wheel hub accommodated in the first accommodation area based on the detection position calibration parameter, so as to adjust the target wheel hub from the current accommodation orientation to the calibration accommodation orientation.

[0027] According to some embodiments of the present invention, the performing position identification on the target wheel hub in the first accommodation area by the first image acquisition device to obtain the current accommodation position of the target wheel hub includes:

[0028] Capturing an image of the target wheel hub in the first accommodating area by the first image acquisition device to obtain a first wheel hub image;

[0029] Based on the valve hole position of the target wheel hub in the first wheel hub image, a current accommodation position of the target wheel hub is determined.

[0030] According to some embodiments of the present invention, the wheel hub defect detection device includes a second image acquisition device, the image acquisition setting parameters include bolt hole image acquisition parameters and hub angle image acquisition parameters, and the bolt hole defect detection and hub angle defect detection are performed on the target wheel hub in the calibration accommodation position based on the image acquisition setting parameters to obtain bolt hole detection information and hub angle detection information, including:

[0031] transporting the target wheel hub from the first accommodation area to the second accommodation area;

[0032] Using the second image acquisition device, acquiring an image of the target wheel hub in the second accommodating area based on the bolt hole image acquisition parameters to obtain a bolt hole image;

[0033] Using the second image acquisition device, acquiring an image of the target wheel hub in the second accommodating area based on the wheel hub angle image acquisition parameter to obtain a wheel hub angle image;

[0034] Performing defect recognition on the bolt hole image to obtain the bolt hole detection information;

[0035] Defect recognition is performed on the wheel hub angle image to obtain the wheel hub angle detection information.

[0036] According to some embodiments of the present invention, the wheel hub defect detection device includes a third image acquisition device, the image acquisition setting parameters include spoke image acquisition parameters, and performing spoke defect detection on the target wheel hub in the calibration accommodation position based on the image acquisition setting parameters to obtain spoke detection information includes:

[0037] transporting the target wheel hub from the second accommodating area to a third accommodating area;

[0038] Using the third image acquisition device, based on the spoke image acquisition parameters, an image of the target hub in the third accommodating area is acquired to obtain a spoke image;

[0039] Defect recognition is performed on the spoke image to obtain the spoke detection information.

[0040] According to some embodiments of the present invention, the wheel hub defect detection device includes a wheel hub rotation control assembly, and the step of acquiring an image of the target wheel hub in the third accommodating area based on the spoke image acquisition parameters by the third image acquisition device to obtain a spoke image includes:

[0041] Performing a rotation control operation on the target hub in the third accommodating area through the hub rotation control assembly;

[0042] During the execution of the rotation control operation, image acquisition is performed on the target hub to obtain spoke images at multiple image acquisition angles.

[0043] According to some embodiments of the present invention, the wheel hub defect detection device includes a fourth image acquisition device, the image acquisition setting parameters include wheel hub window image acquisition parameters and rim sidewall image acquisition parameters, and performing wheel hub window defect detection and rim sidewall defect detection on the target wheel hub in the calibration accommodation position based on the image acquisition setting parameters to obtain wheel hub window detection information and rim sidewall detection information includes:

[0044] transporting the target wheel hub from the third accommodating area to a fourth accommodating area;

[0045] Using the fourth image acquisition device, based on the hub window image acquisition parameters, an image of the target hub in the fourth accommodating area is acquired to obtain a hub window image;

[0046] Using the fourth image acquisition device, acquiring an image of the target wheel hub in the fourth accommodating area based on the rim sidewall image acquisition parameters to obtain a rim sidewall image;

[0047] Performing defect recognition on the wheel hub window image to obtain the wheel hub window detection information;

[0048] Defect recognition is performed on the rim sidewall image to obtain the rim sidewall detection information.

[0049] According to some embodiments of the present invention, the wheel hub defect detection equipment includes a fifth image acquisition device, the image acquisition setting parameters include center hole image acquisition parameters and wheel rim image acquisition parameters, and performing center hole defect detection and wheel rim defect detection on the target wheel hub in the calibration accommodation position based on the image acquisition setting parameters to obtain center hole detection information and wheel rim detection information includes:

[0050] transporting the target wheel hub from the fourth accommodating area to a fifth accommodating area;

[0051] Using the fifth image acquisition device, based on the center hole image acquisition parameters, an image of the target wheel hub in the fifth accommodating area is acquired to obtain a center hole image;

[0052] Using the fifth image acquisition device, based on the wheel rim image acquisition parameters, an image of the target wheel hub in the fifth accommodating area is acquired to obtain a wheel rim image;

[0053] Performing defect recognition on the center hole image to obtain the center hole detection information;

[0054] Defect recognition is performed on the wheel rim image to obtain the wheel rim detection information.

[0055] According to some embodiments of the present invention, the wheel hub defect detection equipment includes a sixth image acquisition device, the image acquisition setting parameters include wheel hub back cavity image acquisition parameters and rim inner wall image acquisition parameters, and the wheel hub back cavity defect detection and rim inner wall defect detection are performed on the target wheel hub in the calibration accommodation position based on the image acquisition setting parameters to obtain wheel hub back cavity detection information and rim inner wall detection information, including:

[0056] transporting the target wheel hub from the fifth accommodating area to a sixth accommodating area;

[0057] Using the sixth image acquisition device, based on the wheel hub back cavity image acquisition parameters, an image of the target wheel hub in the sixth accommodating area is acquired to obtain a wheel hub back cavity image;

[0058] Using the sixth image acquisition device, based on the rim inner wall image acquisition parameters, an image of the target wheel hub in the sixth accommodating area is acquired to obtain a rim inner wall image;

[0059] Performing defect recognition on the wheel hub back cavity image to obtain wheel hub back cavity detection information;

[0060] Defect recognition is performed on the rim inner wall image to obtain the rim inner wall detection information.

[0061] According to the wheel hub defect detection device of the second aspect embodiment of the present invention, the wheel hub defect detection device is used to perform defect detection on the target wheel hub by using the method described in any one of the embodiments of the first aspect of the present invention.

[0062] In a third aspect, an embodiment of the present invention provides an electronic device comprising: a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, it implements the wheel hub defect detection method as described in any one of the embodiments of the first aspect of the present invention.

[0063] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the storage medium stores a program, and the program is executed by a processor to implement the wheel hub defect detection method as described in any one of the embodiments of the first aspect of the present invention.

[0064] The wheel hub defect detection method and wheel hub defect detection device according to the embodiments of the present invention have at least the following beneficial effects:

[0065] The wheel hub defect detection method of the present invention realizes fully compatible detection of different wheel hub models by identifying the target wheel hub model and obtaining the matching detection position calibration parameters and image acquisition setting parameters from the pre-built wheel hub model library. Through orientation calibration and adjustment, the wheel hub is ensured to be in the optimal detection position, avoiding detection blind spots or errors caused by incorrect position. The method performs comprehensive inspections on various key parts of the wheel hub, including bolt holes, wheel hub angles, spokes, wheel hub windows, rim sidewalls, center holes, wheel edges, wheel hub back cavities and rim inner walls, and comprehensively determines the defect detection results of the wheel hub based on all the inspection information. Overall, the method effectively solves the problem of the existing technology being difficult to be compatible with multiple wheel hub models, improves the accuracy and efficiency of detection, and ensures the quality and safety of the wheel hub.

[0066] Additional aspects and advantages of the present invention will be set forth in part in the description which follows and, in part, will be obvious from the description which follows, or may be learned by practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments with reference to the accompanying drawings, in which:

[0068] Figure 1 A schematic flow chart of a wheel hub defect detection method provided by an embodiment of the present invention;

[0069] FIG2( a ) is a schematic diagram of the three-dimensional structure of a hub provided by an embodiment of the present invention;

[0070] FIG2( b ) is another schematic diagram of the three-dimensional structure of a hub provided by an embodiment of the present invention;

[0071] Figure 3 Another schematic flow chart of the wheel hub defect detection method provided by an embodiment of the present invention;

[0072] Figure 4 Another schematic flow chart of the wheel hub defect detection method provided by an embodiment of the present invention;

[0073] Figure 5 Another schematic flow chart of the wheel hub defect detection method provided by an embodiment of the present invention;

[0074] Figure 6 Another schematic flow chart of the wheel hub defect detection method provided by an embodiment of the present invention;

[0075] Figure 7 Another schematic flow chart of the wheel hub defect detection method provided by an embodiment of the present invention;

[0076] Figure 8 Another schematic flow chart of the wheel hub defect detection method provided by an embodiment of the present invention;

[0077] Figure 9 Another schematic flow chart of the wheel hub defect detection method provided by an embodiment of the present invention;

[0078] Figure 10 Another schematic flow chart of the wheel hub defect detection method provided by an embodiment of the present invention;

[0079] Figure 11 Another schematic flow chart of the wheel hub defect detection method provided by an embodiment of the present invention;

[0080] Figure 12 It is a structural schematic diagram of a wheel hub defect detection device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0081] The following describes embodiments of the present invention in detail. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended only to explain the present invention and are not to be construed as limiting the present invention.

[0082] As a key component of automotive safety and aesthetics, wheels often face multiple defects during production due to the inherent characteristics of the manufacturing process and the complexity of the processing steps. For example, gravity casting is prone to internal defects such as pinholes, air holes, and shrinkage cavities, while mechanical operations such as handling and polishing can cause surface damage such as bumps and scratches.

[0083] Traditional manual inspection methods rely primarily on visual observation and empirical judgment. However, due to the demands of high-speed production lines (such as short wheel intervals and high inspection timeliness) and diverse product specifications (such as frequent fixture changes for small batch orders), manual inspections struggle to meet the demands for efficiency and accuracy. Furthermore, manual inspections are prone to missed inspections or misjudgments due to visual fatigue and subjective bias, and are particularly incapable of identifying hidden defects such as tiny cracks and inclusions.

[0084] Although there are many wheel hub detection methods currently used in the industry, they all have certain limitations.

[0085] Mechanical measurement methods use tools such as calipers and gauges to accurately measure the key dimensions of the wheel hub, but they are often powerless for wheels with complex shapes, and the detection efficiency is low, making it difficult to meet the needs of rapid detection on large-scale production lines.

[0086] While traditional optical inspection methods can achieve non-contact measurement to a certain extent, they are prone to blind spots in wheel hub structures, such as reflective surfaces, spoke obstructions, and deep holes, leading to inaccurate or incomplete results. Non-destructive testing methods such as electromagnetic testing are primarily used to detect internal defects in wheels, but they are also limited by the wheel's material and structure, making them incompatible with various wheel types.

[0087] The present invention aims to solve at least one of the technical problems existing in the prior art. To this end, the present invention provides a wheel hub defect detection method and wheel hub defect detection device, which are compatible with various types of wheel hub detection.

[0088] The present invention will be further described below based on the accompanying drawings.

[0089] Reference Figure 1 The wheel hub defect detection method according to an embodiment of the present invention, applied to a wheel hub defect detection device, may include:

[0090] Step S101, performing wheel hub model identification on a target wheel hub to determine the target wheel hub model;

[0091] Step S102, obtaining detection position calibration parameters and image acquisition setting parameters matching the target wheel hub model from a pre-built wheel hub model library;

[0092] Step S103, calibrating the target wheel hub based on the detection position calibration parameters, and adjusting the target wheel hub to the calibration accommodation position;

[0093] Step S104, performing bolt hole defect detection and wheel angle defect detection on the target wheel hub in the calibrated accommodation position based on the image acquisition setting parameters, and obtaining bolt hole detection information and wheel angle detection information;

[0094] Step S105, performing spoke defect detection on the target hub in the calibrated accommodation position based on the image acquisition setting parameters to obtain spoke detection information;

[0095] Step S106, performing hub window defect detection and rim sidewall defect detection on the target hub in the calibrated accommodation position based on the image acquisition setting parameters, and obtaining hub window detection information and rim sidewall detection information;

[0096] Step S107, performing center hole defect detection and wheel rim defect detection on the target wheel hub in the calibrated accommodation position based on the image acquisition setting parameters, and obtaining center hole detection information and wheel rim detection information;

[0097] Step S108, performing wheel hub back cavity defect detection and rim inner wall defect detection on the target wheel hub in the calibrated accommodation orientation based on the image acquisition setting parameters, and obtaining wheel hub back cavity detection information and rim inner wall detection information;

[0098] Step S109, determining the hub defect detection result of the target hub based on the bolt hole detection information, hub angle detection information, spoke detection information, hub window detection information, rim sidewall detection information, center hole detection information, wheel edge detection information, hub back cavity detection information and rim inner wall detection information.

[0099] The wheel hub defect detection method of the present invention realizes fully compatible detection of different wheel hub models by identifying the target wheel hub model and obtaining the matching detection position calibration parameters and image acquisition setting parameters from the pre-built wheel hub model library. Through orientation calibration and adjustment, the wheel hub is ensured to be in the optimal detection position, avoiding detection blind spots or errors caused by incorrect position. The method performs comprehensive inspections on various key parts of the wheel hub, including bolt holes, wheel hub angles, spokes, wheel hub windows, rim sidewalls, center holes, wheel edges, wheel hub back cavities and rim inner walls, and comprehensively determines the defect detection results of the wheel hub based on all the inspection information. Overall, the method effectively solves the problem of the existing technology being difficult to be compatible with multiple wheel hub models, improves the accuracy and efficiency of detection, and ensures the quality and safety of the wheel hub.

[0100] In step S101 of some embodiments, a target wheel hub model is identified to determine the target wheel hub model;

[0101] It should be noted that, at this stage, the wheel hub defect detection device first identifies the model of the target wheel hub on the production line. In some embodiments, a barcode reader installed on the wheel hub defect detection device can read the QR code or barcode on the wheel hub to obtain the wheel hub model information.

[0102] In some embodiments, the wheel hub defect detection device's camera module can also capture an image of the target wheel hub. Image processing algorithms can then be used to extract key features of the hub hub, such as the hub's profile, spoke shape, and bolt hole distribution. These features can then be compared with hub models in a database to further confirm the hub model. This process ensures that the wheel hub defect detection device can accurately identify the specific model of the target hub, providing a foundation for subsequent inspections.

[0103] In step S102 of some embodiments, detection position calibration parameters and image acquisition setting parameters matching the target wheel hub model are obtained from a pre-built wheel hub model library;

[0104] It should be noted that the pre-built wheel model library stores detailed information on various wheel models, including detection position calibration parameters and image acquisition settings. The detection position calibration parameters guide the wheel defect detection equipment on how to adjust the wheel position and angle to ensure the wheel is in the optimal detection position. Image acquisition settings, including the camera's working distance, exposure time, and light source brightness, guide the camera on how to capture clear and accurate images. After determining the target wheel model, the wheel defect detection equipment can retrieve parameters matching that model from the wheel model library, preparing for subsequent inspections.

[0105] In step S103 of some embodiments, the target wheel hub is calibrated based on the detection position calibration parameters, and the target wheel hub is adjusted to the calibration accommodation position;

[0106] It should be noted that the wheel hub defect detection equipment can calibrate the target wheel hub's position based on the acquired detection position calibration parameters. Mechanical adjustment devices, such as centering rollers and jacking mechanisms, adjust the wheel hub to the calibrated accommodation position. This process ensures the optimal position and angle of the wheel hub in the wheel hub defect detection equipment, avoiding detection blind spots or errors caused by incorrect wheel hub positioning.

[0107] In some more specific embodiments, the lifting mechanism can lift the wheel hub to a predetermined height, and the centering roller can center the wheel hub to ensure that the center of the wheel hub is aligned with the center of the wheel hub defect detection device.

[0108] In step S104 of some embodiments, bolt hole defect detection and hub angle defect detection are performed on the target hub in the calibrated accommodation position based on the image acquisition setting parameters to obtain bolt hole detection information and hub angle detection information;

[0109] It should be noted that at this stage, the wheel hub defect detection equipment can use a high-resolution camera to capture images of the bolt holes and the hub angle of the wheel hub in the calibrated accommodation position based on image acquisition parameters. The camera captures images of the bolt holes and the angle area from multiple angles to ensure that the captured images are clear and complete. Then, using image processing algorithms such as edge detection and feature extraction, the bolt holes and the angle area in the image are analyzed to detect defects such as cracks, inconsistent hole diameters, and asymmetric angles. The test results are recorded as bolt hole detection information and hub angle detection information.

[0110] In step S105 of some embodiments, spoke defect detection is performed on the target wheel hub in the calibrated accommodation position based on the image acquisition setting parameters to obtain spoke detection information;

[0111] It should be noted that the wheel hub defect detection equipment uses a camera to capture images of the spoke area of ​​the wheel hub in its designated position, based on image acquisition parameters. The camera captures spoke images from multiple angles to ensure that the captured images cover all spoke areas. Image processing algorithms analyze spoke shape, texture, and other characteristics to detect defects such as cracks, deformation, and surface scratches. The test results are recorded as spoke inspection information.

[0112] In step S106 of some embodiments, a hub window defect detection and a rim sidewall defect detection are performed on the target hub in the calibrated accommodation position based on the image acquisition setting parameters to obtain hub window detection information and rim sidewall detection information;

[0113] It should be noted that the wheel hub defect detection equipment uses a camera to capture images of the hub window and rim sidewall in their designated positions, based on image acquisition parameters. The camera captures images of the window and sidewall from multiple angles to ensure clarity and completeness. Image processing algorithms analyze the shape and surface features of the window and sidewall to detect defects such as cracks, holes, and surface irregularities. The test results are recorded as hub window and rim sidewall inspection information.

[0114] In step S107 of some embodiments, center hole defect detection and wheel rim defect detection are performed on the target wheel hub in the calibrated accommodation position based on the image acquisition setting parameters to obtain center hole detection information and wheel rim detection information;

[0115] It should be noted that the wheel hub defect detection equipment uses a camera to capture images of the hub center hole and rim in the calibrated position, based on image acquisition parameters. The camera captures images of the center hole and rim from multiple angles, ensuring that the captured images cover all parts of these areas. Image processing algorithms analyze the shape, size, and other characteristics of the center hole and rim to detect defects such as cracks, inconsistent hole diameters, and surface scratches. The test results are recorded as center hole and rim detection information.

[0116] In step S108 of some embodiments, based on the image acquisition setting parameters, a wheel hub back cavity defect detection and a wheel rim inner wall defect detection are performed on the target wheel hub in the calibrated accommodation orientation to obtain wheel hub back cavity detection information and wheel rim inner wall detection information;

[0117] It should be noted that the wheel hub defect detection equipment uses a camera to capture images of the wheel hub back cavity and rim inner wall in the calibrated position, based on image acquisition parameters. The camera captures images of the back cavity and inner wall from multiple angles to ensure clarity and completeness. Image processing algorithms analyze the shape and surface features of the back cavity and inner wall to detect defects such as cracks, surface irregularities, and oxidation. The test results are recorded as wheel hub back cavity and rim inner wall inspection information.

[0118] In step S109 of some embodiments, the hub defect detection result of the target hub is determined based on the bolt hole detection information, the hub angle detection information, the spoke detection information, the hub window detection information, the rim sidewall detection information, the center hole detection information, the wheel edge detection information, the hub back cavity detection information and the rim inner wall detection information.

[0119] It's important to note that after inspecting every part of the wheel hub, the wheel hub defect detection equipment comprehensively analyzes all collected inspection information. Using pre-set defect judgment criteria and algorithms, the inspection results for each part are evaluated to determine the presence and severity of defects. Ultimately, the wheel hub defect detection equipment generates a wheel hub defect detection result for the target wheel hub based on all inspection information, including detailed information such as defect type, location, and size. This result can be used to guide subsequent production processes, such as repairing or scrapping defective wheels, to ensure the quality and safety of the final product.

[0120] According to some embodiments provided by the present invention, Figures 2(a) and 2(b) show schematic diagrams of the three-dimensional structure of the target wheel hub, presenting the detailed structure of the wheel hub from different perspectives, respectively, to facilitate understanding of the key parts of the wheel hub defect detection equipment during the detection process.

[0121] The wheel hub schematic in Figure 2(a) primarily shows the front view of the hub. The hub's center hole, bolt holes, and the arrangement of the spokes are visible. The center hole, where the hub connects to the vehicle's axle, typically has a regular circular structure. Bolt holes are evenly distributed around the center hole and are used to mount the tire and hub. Spokes extend outward from the center hole to the rim, forming the hub's primary support structure. Their shape and number vary depending on the hub model.

[0122] Figure 2(b) shows a top-down view of the wheel hub, providing detailed information from the top. The image clearly illustrates the hub's center hole, bolt holes, and spoke layout. The top view reveals the hub's complete circular outline, as well as the distribution and shape of the spokes. This perspective helps understand the overall structural layout of the hub and the relative positions of its various components.

[0123] It should be understood that Figures 2(a) and 2(b) help to clarify and understand the embodiment of the present invention in which various parts of the wheel hub are inspected for defects. For example, when inspecting bolt holes, attention should be paid to the hole shape, size, and presence of cracks or burrs. When inspecting spokes, the surface should be checked for scratches, deformation, or fractures. And when inspecting the center hole, the main focus should be on its roundness, surface quality, and internal defects.

[0124] Reference Figure 3 According to some embodiments of the present invention, before obtaining the detection position calibration parameters and image acquisition setting parameters matching the target wheel hub model from the pre-built wheel hub model library in step S102, the wheel hub model library is also pre-built, which may specifically include:

[0125] Step S301, obtaining a wheel hub three-dimensional model corresponding to a plurality of candidate wheel hub models;

[0126] Step S302: performing size analysis based on the three-dimensional models of each wheel hub to obtain wheel hub size parameters that match each candidate wheel hub model;

[0127] Step S303: Based on the wheel size parameters, position calibration parameters are configured for each candidate wheel model to obtain detection position preset parameters matching each candidate wheel model;

[0128] Step S304: configuring image acquisition parameters for each candidate wheel model based on the wheel size parameters to obtain image acquisition preset parameters matching each candidate wheel model;

[0129] In step S102, the detection position calibration parameters and image acquisition setting parameters matching the target wheel hub model are obtained from the pre-built wheel hub model library, which may include:

[0130] Step S305, determining an alternative wheel hub model that matches the target wheel hub model from the wheel hub model library;

[0131] Step S306 : for the candidate wheel hub model that matches the target wheel hub model, the corresponding detection position preset parameters are determined as detection position calibration parameters, and the corresponding image acquisition preset parameters are determined as image acquisition setting parameters.

[0132] In some embodiments, step S301 is to obtain three-dimensional wheel hub models corresponding to a plurality of candidate wheel hub models;

[0133] It should be noted that first, 3D wheel models corresponding to multiple candidate wheel models are obtained. These wheel models can be obtained in a variety of ways, such as directly importing CAD models provided by the wheel manufacturer or using 3D scanning equipment to reconstruct a 3D model of the actual wheel. These 3D wheel models contain detailed structural information about the wheel, providing the basis for subsequent parameter extraction and configuration.

[0134] In step S302 of some embodiments, dimension analysis is performed based on the three-dimensional models of each wheel hub to obtain wheel hub dimension parameters matching each candidate wheel hub model;

[0135] It should be noted that dimensional analysis is performed on each wheel hub 3D model to obtain the wheel hub dimensional parameters that match each candidate wheel hub model. This process involves measuring and extracting key dimensions from the 3D wheel hub model to obtain the wheel hub dimensional parameters. Specifically, wheel hub dimensional parameters may include hub diameter, width, center hole diameter, bolt hole location and size, spoke shape and size, etc. These wheel hub dimensional parameters are a crucial component of the wheel hub model library, providing accurate data support for subsequent detection position calibration and image acquisition parameter configuration.

[0136] In step S303 of some embodiments, based on the wheel size parameters, position calibration parameters are configured for each candidate wheel model to obtain detection position preset parameters matching each candidate wheel model;

[0137] It should be noted that, based on the extracted wheel size parameters, position calibration parameters are configured for each candidate wheel model to obtain detection position preset parameters that match each candidate wheel model. Position calibration parameters are primarily used to guide the wheel hub defect detection equipment in adjusting the wheel hub's position and angle for optimal detection. For example, these detection position preset parameters may include the ideal position coordinates, rotation angle, and lifting height of the wheel hub in the wheel hub defect detection equipment, ensuring that all parts of the wheel hub can be accurately inspected.

[0138] In step S304 of some embodiments, based on the wheel size parameters, image acquisition parameters are configured for each candidate wheel model to obtain preset image acquisition parameters that match each candidate wheel model;

[0139] It should be noted that, based on the wheel size parameters, image acquisition parameters are configured for each candidate wheel model to obtain image acquisition preset parameters that match each candidate wheel model. The image acquisition preset parameters may involve camera settings such as working distance, aperture size, exposure time, light source type and brightness, as well as image resolution and format.

[0140] In some embodiments, the image acquisition parameter configuration process may also involve presetting light source parameters, which may include the light source's angle, intensity, color, and lighting mode. These light source parameter configurations are intended to ensure that the captured images clearly and accurately reflect the details of each part of the wheel hub, thereby improving the accuracy of defect detection.

[0141] It should be understood that the configuration of these image acquisition preset parameters is intended to ensure that the acquired images can clearly and accurately reflect the details of various parts of the wheel hub, thereby improving the accuracy of defect detection.

[0142] In step S305 of some embodiments, determining an alternative wheel hub model that matches the target wheel hub model from a wheel hub model library;

[0143] It should be noted that determining the candidate wheel hub model that matches the target wheel hub model from the wheel hub model library may involve querying and matching the model information of the target wheel hub to find the wheel hub model that is closest or completely matched in the wheel hub model library.

[0144] In step S306 of some embodiments, for the candidate wheel hub model that matches the target wheel hub model, the corresponding detection position preset parameters are determined as detection position calibration parameters, and the corresponding image acquisition preset parameters are determined as image acquisition setting parameters.

[0145] It should be noted that for candidate wheel hub models matching the target wheel hub model, the corresponding detection position preset parameters are determined as detection position calibration parameters, and the corresponding image acquisition preset parameters are determined as image acquisition setting parameters. This step effectively applies the parameters in the pre-built model library to the actual inspection process, ensuring that the wheel hub defect inspection equipment can quickly and accurately adjust the inspection parameters based on the specific model of the current target wheel hub, achieving efficient and accurate inspection.

[0146] Through the embodiment shown in steps S301 to S306 of the present invention, the pre-construction and parameter configuration of the wheel hub model library provide strong support for the wheel hub defect detection equipment, making it compatible with multiple models of wheel hubs and performing customized detection for different models of wheel hubs, thereby significantly improving the accuracy and efficiency of detection.

[0147] Reference Figure 4 According to some embodiments of the present invention, the wheel hub defect detection device includes a first image acquisition device. Step S103 calibrates the position of the target wheel hub based on the detection position calibration parameter and adjusts the target wheel hub to the calibration accommodation position, which may include:

[0148] Step S401, transporting the target wheel hub to the first accommodation area;

[0149] Step S402: performing position recognition on the target wheel hub in the first accommodation area by a first image acquisition device to obtain a current accommodation position of the target wheel hub;

[0150] Step S403 : performing an orientation adjustment operation on the target wheel hub accommodated in the first accommodation area based on the detection position calibration parameter, so as to adjust the target wheel hub from the current accommodation orientation to the calibration accommodation orientation.

[0151] In some embodiments, step S401 is to transport the target wheel hub to a first accommodation area;

[0152] It should be noted that the target wheel hub is transported to the first accommodation area. This area is a location within the wheel hub defect detection equipment specifically designed for initial hub positioning and orientation calibration. The hub hub can be precisely moved to the first accommodation area using an automated conveying system, such as a roller conveyor or robotic arm. During this stage, ensuring the hub hub is stably and accurately positioned in the intended location is crucial, as this directly impacts subsequent orientation identification and adjustment operations.

[0153] In step S402 of some embodiments, the first image acquisition device is used to identify the position of the target wheel hub in the first accommodation area to obtain the current accommodation position of the target wheel hub;

[0154] It should be noted that the position of the target wheel hub located in the first accommodation area is identified by a first image acquisition device. The first image acquisition device may include a high-resolution camera and lighting system, capable of capturing detailed images of the wheel hub. These images are then transmitted to an image processing unit, where a dedicated image processing algorithm is used to analyze the current accommodation position of the wheel hub.

[0155] In some embodiments, these specialized image processing algorithms can be used to identify and extract key features of the wheel hub, such as bolt holes, center holes, spokes, etc., and use these features to determine the current position and angle of the wheel hub. This step aims to obtain the precise position of the wheel hub within the accommodation area, providing data support for subsequent orientation adjustments.

[0156] Reference Figure 5 According to some embodiments of the present invention, step S402 of performing position recognition on the target wheel hub in the first accommodation area by the first image acquisition device to obtain the current accommodation position of the target wheel hub may include:

[0157] Step S501, capturing an image of a target wheel hub in a first accommodating area by a first image capturing device to obtain a first wheel hub image;

[0158] Step S502 : determining the current accommodation position of the target wheel hub based on the valve hole position of the target wheel hub in the first wheel hub image.

[0159] It's important to note that the wheel hub defect inspection equipment transports the target wheel hub to the first accommodation area and places it there for stable positioning. This first accommodation area is a critical location in the inspection process, specifically used for initial positioning and orientation of the wheel hub. In this area, the position and orientation of the target wheel hub may vary due to various factors during transportation, necessitating precise orientation identification to determine the actual position and angle of the wheel hub.

[0160] In step S501 of some embodiments, an image of a target hub in a first accommodating area is captured by a first image capturing device to obtain a first hub image;

[0161] It should be noted that the wheel hub defect detection equipment activates the first image acquisition device to capture an image of the target wheel hub located in the first accommodation area. This first image acquisition device typically consists of a high-resolution camera and a corresponding lighting system, capable of capturing clear images of the wheel hub. The camera captures the wheel hub from a specific angle and distance, ensuring that the captured image accurately reflects the current condition of the wheel hub. This captured image, referred to as the first wheel hub image, contains detailed information about the wheel hub in its current accommodation orientation.

[0162] In step S502 of some embodiments, a current accommodation position of the target wheel hub is determined based on the valve hole position of the target wheel hub in the first wheel hub image.

[0163] It should be noted that the wheel hub defect detection equipment analyzes the first captured wheel hub image. Image processing algorithms can be used to identify the valve hole location of the target wheel hub within the image. The valve hole is a prominent feature on the wheel hub, typically located at a specific location on the rim, and is used for inflation and tire pressure adjustment. Because of its relatively fixed location and easy identification, the valve hole serves as an ideal reference point for determining wheel hub orientation.

[0164] In some embodiments, the current accommodation position of the target wheel hub in the first accommodation area may be calculated by identifying the position of the valve hole in the image through an image processing algorithm and combining the geometric parameters of the camera and calibration data.

[0165] In some more specific embodiments, after determining the current placement of the target wheel hub, the wheel hub defect detection device can further calculate the adjustment parameters required to adjust the wheel hub to the calibrated placement. These parameters will guide subsequent position adjustment operations, ensuring that the wheel hub can be accurately positioned in the optimal detection position, thereby providing reliable support for subsequent defect detection steps.

[0166] Through steps S501 and S502 of this embodiment of the present invention, the wheel hub defect detection device can efficiently and accurately determine the current position of the target wheel hub in the first accommodation area, laying the foundation for subsequent position adjustment and defect detection. This process not only improves detection accuracy and efficiency, but also reduces manual intervention, enhancing the automation and intelligence level of the entire detection process.

[0167] In step S403 of some embodiments, an orientation adjustment operation is performed on the target wheel hub accommodated in the first accommodation area based on the detection position calibration parameter, so as to adjust the target wheel hub from the current accommodation orientation to the calibration accommodation orientation.

[0168] It should be noted that the orientation adjustment operation is performed on the target wheel hub located in the first accommodation area based on the pre-acquired detection position calibration parameters. The detection position calibration parameters are pre-configured based on the three-dimensional model and dimensional parameters of the wheel hub, and may include the position coordinates and angle information of the wheel hub at the optimal detection position.

[0169] In some embodiments, the wheel hub defect detection device can control a mechanical adjustment device (such as a lifting mechanism, centering rollers, or a rotating platform) to precisely adjust the wheel hub based on the difference between the current wheel hub position and the calibration parameters. The goal of the adjustment is to move the wheel hub from its current storage position to the calibrated storage position, ensuring that all inspection areas of the wheel hub can be accurately inspected by the wheel hub defect detection device.

[0170] Reference Figure 6According to some embodiments of the present invention, the wheel hub defect detection device includes a second image acquisition device, and the image acquisition setting parameters include bolt hole image acquisition parameters and wheel hub angle image acquisition parameters. Step S104 performs bolt hole defect detection and wheel hub angle defect detection on the target wheel hub in the calibration accommodation position based on the image acquisition setting parameters to obtain bolt hole detection information and wheel hub angle detection information, which may include:

[0171] Step S601, transporting the target wheel hub from the first accommodation area to the second accommodation area;

[0172] Step S602: Using a second image acquisition device, based on bolt hole image acquisition parameters, acquire an image of the target wheel hub in the second accommodating area to obtain a bolt hole image.

[0173] Step S603, using a second image acquisition device, based on the wheel hub angle image acquisition parameter, an image of the target wheel hub in the second accommodating area is acquired to obtain a wheel hub angle image;

[0174] Step S604: performing defect recognition on the bolt hole image to obtain bolt hole detection information;

[0175] Step S605: performing defect recognition on the wheel hub angle image to obtain wheel hub angle detection information.

[0176] In some embodiments, step S601 is to transport the target wheel hub from the first accommodation area to the second accommodation area;

[0177] It's important to note that the wheel hub defect inspection equipment transports the target wheel hub from the first to the second storage area. This transfer is typically accomplished by an automated transport system, such as a robotic arm or conveyor belt, ensuring the hub remains stable during movement and accurately positioned within the second storage area. The second storage area is specifically designed for detailed inspection of bolt holes and wheel hub angles, with optimized structure and lighting conditions to ensure high-quality image acquisition.

[0178] In step S602 of some embodiments, an image of a target wheel hub in a second accommodating area is captured by a second image capturing device based on bolt hole image capturing parameters to obtain a bolt hole image;

[0179] It should be noted that the wheel hub defect detection equipment activates the second image acquisition device to capture images of the bolt hole area of ​​the target wheel hub according to preset bolt hole image acquisition parameters. Bolt hole image acquisition parameters include the camera's focal length, aperture size, exposure time, light source type, angle, and intensity. These parameters are pre-configured based on the wheel hub's 3D model and the geometric characteristics of the bolt holes to ensure that the captured images clearly display the bolt hole details and potential defects.

[0180] In step S603 of some embodiments, an image of a target wheel hub in the second accommodating area is captured by a second image capturing device based on a wheel hub angle image capturing parameter to obtain a wheel hub angle image;

[0181] It's important to note that the wheel hub defect inspection equipment again utilizes a second image acquisition device, this time capturing images of the wheel hub's angled area based on the wheel hub angle image acquisition parameters. These parameters are also carefully configured to accommodate the specific geometry of the wheel hub angle and the inspection requirements. Image acquisition of the angled area requires careful attention to the incident light angle and the camera's viewing angle to ensure that subtle features and potential defects in the angled area are captured.

[0182] In some embodiments, steps S604 to S605 include performing defect recognition on the bolt hole image to obtain bolt hole detection information, and performing defect recognition on the hub angle image to obtain hub angle detection information.

[0183] It should be noted that after acquiring the bolt hole and hub angle images, the hub defect detection equipment uses specialized image processing algorithms to analyze these images. For bolt hole images, the algorithm examines the hole's shape, size, edge integrity, and internal defects. For hub angle images, the algorithm evaluates the angle's angular accuracy, surface condition, and structural integrity. These analysis results are compiled into bolt hole and hub angle detection information for subsequent comprehensive evaluation.

[0184] Through the embodiment of the present invention, steps S601 to S605, the wheel hub defect detection equipment can efficiently and accurately detect defects in bolt holes and the included angle of the wheel hub, ensuring that the quality of these key parts of the wheel hub meets standards. This process not only improves detection accuracy and efficiency, but also reduces manual intervention, enhancing the automation and intelligence level of the entire detection process.

[0185] Reference Figure 7 According to some embodiments of the present invention, the wheel hub defect detection device includes a third image acquisition device, and the image acquisition setting parameters include spoke image acquisition parameters. Step S105 performs spoke defect detection on the target wheel hub in the calibration accommodation position based on the image acquisition setting parameters to obtain spoke detection information, which may include:

[0186] Step S701, transporting the target wheel hub from the second accommodation area to the third accommodation area;

[0187] Step S702, using a third image acquisition device to acquire an image of a target hub in a third accommodating area based on spoke image acquisition parameters to obtain a spoke image;

[0188] Step S703: performing defect recognition on the spoke image to obtain spoke detection information.

[0189] In some embodiments, step S701 is to transport the target wheel hub from the second accommodation area to the third accommodation area;

[0190] It's important to note that the wheel hub defect inspection equipment first transports the target hub from the second to the third storage area. This transfer is accomplished by a high-precision automated conveying system, ensuring the hub remains stable during movement and accurately positioned within the third storage area. The third storage area is designed with the specific requirements of spoke inspection in mind, with optimized structure and lighting conditions to ensure clear and accurate image capture.

[0191] In step S702 of some embodiments, an image of a target hub in a third accommodating area is captured by a third image capturing device based on spoke image capturing parameters to obtain a spoke image;

[0192] It should be noted that upon reaching the third accommodation area, the wheel hub defect detection equipment activates the third image acquisition device, which captures images of the spoke area of ​​the target hub based on preset spoke image acquisition parameters. These spoke image acquisition parameters are carefully configured to accommodate the complex spoke geometry and inspection requirements. These parameters include the camera's focal length, aperture size, exposure time, and the type, angle, and intensity of the light source. The third image acquisition device typically consists of a high-resolution camera and a specialized lighting system, capable of capturing spoke images from multiple angles, ensuring that the captured images clearly display spoke details and potential defects.

[0193] Reference Figure 8 According to some embodiments of the present invention, the wheel hub defect detection device includes a wheel hub rotation control assembly. Step S702 captures an image of the target wheel hub in the third accommodating area based on the spoke image capture parameters using a third image capture device to obtain a spoke image, which may include:

[0194] Step S801, performing a rotation control operation on a target wheel hub in a third accommodation area through a wheel hub rotation control assembly;

[0195] Step S802 : During the execution of the rotation control operation, image acquisition is performed on the target hub to obtain spoke images at multiple image acquisition angles.

[0196] In step S801 of some embodiments, a rotation control operation is performed on a target hub in a third accommodating area by a hub rotation control assembly;

[0197] It should be noted that before starting image acquisition, the wheel hub defect detection equipment first accurately transports the target wheel hub from the second accommodating area to the third accommodating area and places it stably. The third accommodating area is equipped with a wheel hub rotation control component, which can accurately control the rotation of the wheel hub to ensure that the wheel hub can rotate at a preset angle and speed during the image acquisition process. After the wheel hub rotation control component is started, the target wheel hub is precisely controlled. This component usually includes a high-precision rotating platform that can smoothly rotate the wheel hub at a preset rotation angle and speed. During the rotation process, the wheel hub rotation control component can adjust the wheel hub to multiple different angles to ensure that all parts of the spoke area can be fully inspected. This multi-angle rotation method can effectively avoid detection blind spots and ensure the comprehensiveness of image acquisition.

[0198] In step S802 of some embodiments, during the execution of the rotation control operation, image capture is performed on the target hub to obtain spoke images at multiple image capture angles.

[0199] It should be noted that while the wheel hub rotates, the third image acquisition device captures images of the spoke area at different rotation angles according to preset spoke image acquisition parameters. These parameters include the camera's focal length, aperture, exposure time, and the type, angle, and intensity of the light source. The third image acquisition device typically consists of a high-resolution camera and an appropriate lighting system, capable of capturing clear images of the spoke area. Through precise control of the wheel hub rotation control assembly, the camera captures images at each preset wheel hub rotation angle, thereby obtaining spoke images at multiple image acquisition angles. After capturing spoke images at multiple angles, the wheel hub defect detection equipment analyzes these images using specialized image processing algorithms. These algorithms can identify various defects in the spoke area, such as cracks, deformation, and surface scratches. By comparing the standard geometric features of the spoke with the captured image data, the algorithm can accurately locate and assess the severity of defects. These analysis results are compiled into spoke inspection information for subsequent comprehensive evaluation.

[0200] Through steps S801 and S802 in this embodiment of the present invention, the wheel hub defect detection equipment can efficiently and accurately detect defects in the spoke area, ensuring that the quality of this critical part of the wheel hub meets standards. This process not only improves detection accuracy and efficiency, but also reduces manual intervention, enhances the automation and intelligence level of the entire detection process, and provides strong guarantees for the overall performance and safety of the wheel hub.

[0201] In step S703 of some embodiments, defect recognition is performed on the spoke image to obtain spoke detection information.

[0202] It's important to note that after acquiring spoke images, the hub defect detection equipment uses image processing algorithms to analyze them. These algorithms can identify various defects in the spoke area, such as cracks, deformation, and surface scratches. By comparing the standard geometric features of the spoke with the acquired image data, the algorithms can accurately locate and assess the severity of defects. These analysis results are compiled into spoke inspection information for subsequent comprehensive evaluation.

[0203] The embodiment of the present invention, illustrated through steps S701 to S703, not only improves the accuracy and efficiency of spoke defect detection, but also reduces manual intervention, enhancing the automation and intelligence of the entire detection process. Through the high-precision image acquisition of the third image acquisition device and the in-depth analysis of the algorithm, the wheel hub defect detection equipment can ensure that the quality of the spoke area of ​​the hub meets strict standards, thereby safeguarding the overall performance and safety of the hub.

[0204] Reference Figure 9 According to some embodiments of the present invention, the wheel hub defect detection device includes a fourth image acquisition device, and the image acquisition setting parameters include wheel hub window image acquisition parameters and rim sidewall image acquisition parameters. Step S106 performs wheel hub window defect detection and rim sidewall defect detection on the target wheel hub in the calibration accommodation position based on the image acquisition setting parameters to obtain wheel hub window detection information and rim sidewall detection information, which may include:

[0205] Step S901, transporting the target wheel hub from the third accommodation area to the fourth accommodation area;

[0206] Step S902: Using a fourth image acquisition device, based on the hub window image acquisition parameters, an image of the target hub in the fourth accommodating area is acquired to obtain a hub window image.

[0207] Step S903, using a fourth image acquisition device to acquire an image of the target wheel hub in the fourth accommodating area based on the rim sidewall image acquisition parameters, to obtain a rim sidewall image;

[0208] Step S904, performing defect recognition on the wheel hub window image to obtain wheel hub window detection information;

[0209] Step S905 , performing defect recognition on the rim sidewall image to obtain rim sidewall detection information.

[0210] In some embodiments, step S901 is to transport the target wheel hub from the third accommodation area to the fourth accommodation area;

[0211] It should be noted that the wheel hub defect inspection equipment transports the target wheel hub from the third to the fourth storage area. This transfer is typically accomplished by an automated transport system, such as a robotic arm or conveyor belt, ensuring the wheel hub remains stable during movement and accurately positioned in the fourth storage area. The fourth storage area is specifically designed for detailed inspection of the wheel hub window and rim sidewall, with optimized structure and lighting conditions to ensure high-quality image acquisition.

[0212] In step S902 of some embodiments, a fourth image acquisition device is used to acquire an image of a target hub in a fourth accommodating area based on hub window image acquisition parameters to obtain a hub window image;

[0213] It should be noted that the wheel hub defect detection equipment activates the fourth image acquisition device to capture images of the hub window area of ​​the target wheel hub according to preset hub window image acquisition parameters. Hub window image acquisition parameters include the camera's focal length, aperture size, exposure time, light source type, angle, and intensity. These parameters are pre-configured based on the geometric characteristics of the hub window to ensure that the captured images clearly display the details and potential defects in the window area.

[0214] In step S903 of some embodiments, an image of the target wheel hub in the fourth accommodating area is captured by a fourth image capturing device based on the rim sidewall image capturing parameters to obtain a rim sidewall image;

[0215] It should be noted that the wheel hub defect inspection equipment again utilizes the fourth image acquisition device, this time capturing images of the wheel rim sidewall based on the rim sidewall image acquisition parameters. These parameters are also carefully configured to accommodate the specific geometry and inspection requirements of the rim sidewall. Image acquisition of the sidewall requires careful attention to the incident light angle and camera viewing angle to ensure that subtle features and potential defects are captured.

[0216] In steps S904 to S905 of some embodiments, defect recognition is performed on the hub window image to obtain hub window detection information, and defect recognition is performed on the rim sidewall image to obtain rim sidewall detection information.

[0217] It's important to note that after capturing images of the hub window and rim sidewall, the hub defect detection equipment uses specialized image processing algorithms to analyze these images. For hub window images, the algorithm examines the window's shape, size, edge integrity, and surface defects. For rim sidewall images, the algorithm assesses the sidewall's shape, surface condition, and structural integrity. These analysis results are compiled into hub window and rim sidewall inspection information for subsequent comprehensive evaluation.

[0218] Through the embodiment of the present invention, steps S901 to S905, the wheel hub defect detection equipment can efficiently and accurately detect defects in the wheel hub window and rim sidewall, ensuring that the quality of these critical parts of the wheel hub meets standards. This process not only improves detection accuracy and efficiency, but also reduces manual intervention, enhancing the automation and intelligence level of the entire detection process.

[0219] Reference Figure 10 According to some embodiments of the present invention, the wheel hub defect detection device includes a fifth image acquisition device, and the image acquisition setting parameters include center hole image acquisition parameters and wheel rim image acquisition parameters. Step S107 performs center hole defect detection and wheel rim defect detection on the target wheel hub in the calibration accommodation position based on the image acquisition setting parameters to obtain center hole detection information and wheel rim detection information, which may include:

[0220] Step S1001, transporting the target wheel hub from the fourth accommodation area to the fifth accommodation area;

[0221] Step S1002: Using a fifth image acquisition device, based on the center hole image acquisition parameters, an image of the target wheel hub in the fifth accommodating area is acquired to obtain a center hole image.

[0222] Step S1003, using a fifth image acquisition device to acquire an image of the target wheel hub in the fifth accommodating area based on the wheel rim image acquisition parameters, to obtain a wheel rim image;

[0223] Step S1004: performing defect recognition on the center hole image to obtain center hole detection information;

[0224] Step S1005 , performing defect recognition on the wheel edge image to obtain wheel edge detection information.

[0225] In some embodiments, step S1001 is to transport the target wheel hub from the fourth accommodation area to the fifth accommodation area;

[0226] It's important to note that the wheel hub defect inspection equipment transports the target hub from the fourth to the fifth storage area. This transfer process also relies on a precise automated conveying system to ensure the hub is stably and accurately placed in the predetermined position in the fifth storage area. The fifth storage area is designed for detailed inspection of the hub's center hole and rim. Its structural characteristics and lighting environment have been specially optimized to enhance the quality and accuracy of image acquisition.

[0227] In step S1002 of some embodiments, a fifth image acquisition device is used to acquire an image of the target hub in the fifth accommodating area based on the center hole image acquisition parameters to obtain a center hole image;

[0228] It should be noted that upon reaching the fifth accommodation area, the wheel hub defect inspection equipment activates the fifth image acquisition device, which captures images of the target wheel hub's center hole area based on preset center hole image acquisition parameters. These parameters are carefully configured to suit the circular geometry of the center hole and the inspection requirements. These parameters encompass the camera's focal length, aperture size, exposure time, and the type, angle, and intensity of the light source, ensuring that the captured images clearly display the center hole's details and potential defects.

[0229] In step S1003 of some embodiments, a fifth image acquisition device is used to acquire an image of the target wheel hub in the fifth accommodating area based on the wheel rim image acquisition parameters to obtain a wheel rim image;

[0230] It's important to note that the wheel hub defect detection equipment again utilizes the fifth image acquisition device to capture images of the wheel hub's rim area based on the rim image acquisition parameters. These parameters are also carefully configured to suit the rim's annular geometry and inspection requirements. During the acquisition process, these parameters prioritize the curvilinear nature of the wheel rim. By adjusting the camera angle and focal length, combined with appropriate lighting techniques, they ensure that subtle features and potential defects in the rim area are captured.

[0231] In steps S1004 to S1005 of some embodiments, defect recognition is performed on the center hole image to obtain center hole detection information, and defect recognition is performed on the wheel edge image to obtain wheel edge detection information.

[0232] It's important to note that after capturing images of the center hole and wheel rim, the wheel hub defect detection equipment analyzes these images using specialized image processing algorithms. For center hole images, the algorithm focuses on hole roundness, concentricity, wall smoothness, and the presence of defects such as cracks or burrs. For wheel rim images, the algorithm examines the rim's shape regularity, surface wear, and the presence of abnormalities such as deformation or notches. These analysis results are ultimately compiled into center hole and wheel rim inspection information, providing critical data support for subsequent comprehensive evaluations.

[0233] Through the embodiment of the present invention, steps S1001 to S1005, the wheel hub defect detection equipment can efficiently and accurately identify various defects in the center hole and rim areas, ensuring that the quality of these key areas of the wheel hub meets strict industry standards. This process not only improves the accuracy and efficiency of detection, but also significantly reduces manual intervention, further promoting the automation and intelligent development of the detection process, and providing a solid guarantee for the overall performance and safety of the wheel hub.

[0234] Reference Figure 11According to some embodiments of the present invention, the wheel hub defect detection device includes a sixth image acquisition device, and the image acquisition setting parameters include wheel hub back cavity image acquisition parameters and rim inner wall image acquisition parameters. Step S108 performs wheel hub back cavity defect detection and rim inner wall defect detection on the target wheel hub in the calibration accommodation position based on the image acquisition setting parameters to obtain wheel hub back cavity detection information and rim inner wall detection information, which may include:

[0235] Step S1101, transporting the target wheel hub from the fifth accommodation area to the sixth accommodation area;

[0236] Step S1102, using a sixth image acquisition device, based on the wheel hub back cavity image acquisition parameters, to acquire an image of the target wheel hub in the sixth accommodating area to obtain a wheel hub back cavity image;

[0237] Step S1103, using a sixth image acquisition device to acquire an image of the target wheel hub in the sixth accommodating area based on the rim inner wall image acquisition parameters, to obtain an image of the rim inner wall;

[0238] Step S1104, performing defect recognition on the wheel hub back cavity image to obtain wheel hub back cavity detection information;

[0239] Step S1105 , performing defect recognition on the rim inner wall image to obtain rim inner wall detection information.

[0240] In some embodiments, step S1101 is to transport the target wheel hub from the fifth accommodation area to the sixth accommodation area;

[0241] It's important to note that the wheel hub defect inspection equipment transports the target hub from the fifth to the sixth storage area. This transfer process also relies on a precise automated conveying system to ensure the hub is stably and accurately placed in the predetermined position in the sixth storage area. The sixth storage area is designed for detailed inspection of the hub's back cavity and rim inner wall. Its structural characteristics and lighting environment have been specially optimized to enhance image acquisition quality and accuracy.

[0242] In step S1102 of some embodiments, a sixth image acquisition device is used to acquire an image of a target wheel hub in a sixth accommodating area based on a wheel hub back cavity image acquisition parameter to obtain a wheel hub back cavity image;

[0243] It should be noted that upon reaching the sixth accommodation area, the wheel hub defect detection equipment activates the sixth image acquisition device, capturing images of the target wheel hub's back cavity area based on preset wheel hub back cavity image acquisition parameters. These parameters are carefully configured to accommodate the complex geometry of the back cavity and the inspection requirements. These parameters encompass the camera's focal length, aperture size, exposure time, and the type, angle, and intensity of the light source, ensuring that the captured images clearly display back cavity details and potential defects.

[0244] In step S1103 of some embodiments, a sixth image acquisition device is used to acquire an image of the target wheel hub in the sixth accommodating area based on the rim inner wall image acquisition parameters to obtain an image of the rim inner wall;

[0245] It should be noted that the wheel hub defect detection equipment again utilizes the sixth image acquisition device to capture images of the wheel hub's inner rim wall based on the rim inner wall image acquisition parameters. These parameters are also carefully configured to accommodate the specific geometry of the rim inner wall and the inspection requirements. During the acquisition process, the parameter settings prioritize the curvilinear nature of the rim inner wall. By adjusting the camera angle and focal length, combined with appropriate lighting techniques, they ensure that subtle features and potential defects in the rim inner wall area are captured.

[0246] In some embodiments, steps S1104 to S1105 perform defect recognition on the hub back cavity image to obtain hub back cavity detection information, and perform defect recognition on the rim inner wall image to obtain rim inner wall detection information.

[0247] It's important to note that after capturing images of the wheel hub back cavity and rim inner wall, the wheel hub defect detection equipment analyzes these images using specialized image processing algorithms. For wheel hub back cavity images, the algorithm focuses on the surface condition of the back cavity and the presence of defects such as cracks, oxidation, or corrosion. For rim inner wall images, the algorithm examines the inner wall's shape regularity, surface wear, and the presence of abnormalities such as deformation or notches. These analysis results are ultimately compiled into wheel hub back cavity and rim inner wall inspection information, providing critical data support for subsequent comprehensive evaluations.

[0248] Through the embodiment of the present invention, steps S1101 to S1105, the wheel hub defect detection equipment can efficiently and accurately identify various defects in the wheel hub back cavity and rim inner wall area, ensuring that the quality of the wheel hub in these critical areas meets strict industry standards. This process not only improves the accuracy and efficiency of detection, but also significantly reduces manual intervention, further promoting the automation and intelligent development of the detection process, and providing a solid guarantee for the overall performance and safety of the wheel hub.

[0249] According to the wheel hub defect detection device of the embodiment of the present invention, the wheel hub defect detection device is used to perform defect detection on a target wheel hub by using any wheel hub defect detection method according to the embodiment of the present invention.

[0250] It can be seen that the contents of the above-mentioned wheel hub defect detection method embodiment are all applicable to the embodiment of the present wheel hub defect detection device. The functions specifically implemented by the present wheel hub defect detection device embodiment are the same as those of the above-mentioned wheel hub defect detection method embodiment, and the beneficial effects achieved are also the same as those achieved by the above-mentioned wheel hub defect detection method embodiment.

[0251] Reference Figure 12 , Figure 12 The hardware structure of an electronic device according to another embodiment is shown. The electronic device may include:

[0252] The processor 1201 may be implemented as a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is configured to execute relevant programs to implement the technical solutions provided by the embodiments of the present invention.

[0253] The memory 1202 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 1202 can store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 1202 and is called by the processor 1201 to execute the wheel hub defect detection method of the embodiment of the present invention.

[0254] Input / output interface 1203, used to implement information input and output;

[0255] Communication interface 1204, used to implement communication interaction between this device and other devices, which can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WiFi, Bluetooth, etc.);

[0256] Bus 1205 , which transmits information between various components of the device (e.g., processor 1201 , memory 1202 , input / output interface 1203 , and communication interface 1204 );

[0257] The processor 1201 , the memory 1202 , the input / output interface 1203 and the communication interface 1204 are connected to each other in communication within the device via the bus 1205 .

[0258] An embodiment of the present invention further provides a computer program product, which includes a computer program. A processor of a computer device reads and executes the computer program, so that the computer device implements the above-mentioned wheel hub defect detection method.

[0259] The above is a specific description of the implementation methods of the present disclosure, but the present disclosure is not limited to the above implementation methods. Those skilled in the art can make various equivalent modifications or substitutions without violating the spirit of the present disclosure. These equivalent modifications or substitutions are all included in the scope defined by the claims of the present disclosure.

Claims

1. A wheel hub defect detection method, characterized in that: Applied to wheel hub defect detection equipment, including: Perform wheel hub model identification on the target wheel hub to determine the target wheel hub model; Obtaining detection position calibration parameters and image acquisition setting parameters matching the target wheel hub model from a pre-built wheel hub model library; Performing orientation calibration on the target wheel hub based on the detection position calibration parameters, and adjusting the target wheel hub to a calibration accommodation orientation; Performing bolt hole defect detection and hub angle defect detection on the target hub in the calibrated accommodation position based on the image acquisition setting parameters to obtain bolt hole detection information and hub angle detection information; Performing spoke defect detection on the target wheel hub in the calibrated accommodation position based on the image acquisition setting parameters to obtain spoke detection information; Performing hub window defect detection and rim sidewall defect detection on the target hub in the calibrated accommodation position based on the image acquisition setting parameters to obtain hub window detection information and rim sidewall detection information; Performing center hole defect detection and wheel rim defect detection on the target wheel hub in the calibration accommodation position based on the image acquisition setting parameters to obtain center hole detection information and wheel rim detection information; Performing wheel hub back cavity defect detection and wheel rim inner wall defect detection on the target wheel hub in the calibrated accommodation position based on the image acquisition setting parameters to obtain wheel hub back cavity detection information and wheel rim inner wall detection information; The hub defect detection result of the target hub is determined based on the bolt hole detection information, the hub angle detection information, the spoke detection information, the hub window detection information, the rim sidewall detection information, the center hole detection information, the wheel edge detection information, the hub back cavity detection information and the rim inner wall detection information.

2. A wheel hub defect detection method according to claim 1, characterized in that: Before obtaining the detection position calibration parameters and image acquisition setting parameters matching the target wheel hub model from the pre-built wheel hub model library, the wheel hub model library is pre-built, specifically including: Obtaining three-dimensional wheel hub models corresponding to a plurality of candidate wheel hub models; Performing dimension analysis based on the three-dimensional wheel hub models to obtain wheel hub dimension parameters that match each candidate wheel hub model; Based on the wheel hub size parameters, position calibration parameter configuration is performed on each candidate wheel hub model to obtain detection position preset parameters matching each candidate wheel hub model; Based on the wheel size parameters, image acquisition parameters are configured for each candidate wheel model to obtain image acquisition preset parameters matching each candidate wheel model; The step of obtaining detection position calibration parameters and image acquisition setting parameters that match the target wheel hub model from the pre-built wheel hub model library includes: Determining the candidate wheel hub model that matches the target wheel hub model from the wheel hub model library; For the candidate wheel hub model that matches the target wheel hub model, the corresponding detection position preset parameters are determined as the detection position calibration parameters, and the corresponding image acquisition preset parameters are determined as the image acquisition setting parameters.

3. A wheel hub defect detection method according to claim 1, characterized in that: The wheel hub defect detection device includes a first image acquisition device, and the orientation calibration of the target wheel hub is performed based on the detection position calibration parameter, and the target wheel hub is adjusted to the calibration accommodation orientation, including: transporting the target wheel hub to a first accommodation area; Performing position recognition on the target wheel hub in the first accommodation area by the first image acquisition device to obtain a current accommodation position of the target wheel hub; An orientation adjustment operation is performed on the target wheel hub accommodated in the first accommodation area based on the detection position calibration parameter, so as to adjust the target wheel hub from the current accommodation orientation to the calibration accommodation orientation.

4. A wheel hub defect detection method according to claim 3, characterized in that: The performing position identification on the target wheel hub in the first accommodation area by the first image acquisition device to obtain the current accommodation position of the target wheel hub includes: Capturing an image of the target wheel hub in the first accommodating area by the first image acquisition device to obtain a first wheel hub image; Based on the valve hole position of the target wheel hub in the first wheel hub image, a current accommodation position of the target wheel hub is determined.

5. A wheel hub defect detection method according to claim 3, characterized in that: The wheel hub defect detection device includes a second image acquisition device, the image acquisition setting parameters include bolt hole image acquisition parameters and wheel hub angle image acquisition parameters, and the bolt hole defect detection and wheel hub angle defect detection are performed on the target wheel hub in the calibration accommodation position based on the image acquisition setting parameters to obtain bolt hole detection information and wheel hub angle detection information, including: transporting the target wheel hub from the first accommodation area to the second accommodation area; Using the second image acquisition device, acquiring an image of the target wheel hub in the second accommodating area based on the bolt hole image acquisition parameters to obtain a bolt hole image; Using the second image acquisition device, acquiring an image of the target wheel hub in the second accommodating area based on the wheel hub angle image acquisition parameter to obtain a wheel hub angle image; Performing defect recognition on the bolt hole image to obtain the bolt hole detection information; Defect recognition is performed on the wheel hub angle image to obtain the wheel hub angle detection information.

6. A wheel hub defect detection method according to claim 5, characterized in that: The wheel hub defect detection device includes a third image acquisition device, the image acquisition setting parameters include spoke image acquisition parameters, and the spoke defect detection is performed on the target wheel hub in the calibration accommodation position based on the image acquisition setting parameters to obtain spoke detection information, including: transporting the target wheel hub from the second accommodating area to a third accommodating area; Using the third image acquisition device, based on the spoke image acquisition parameters, an image of the target hub in the third accommodating area is acquired to obtain a spoke image; Defect recognition is performed on the spoke image to obtain the spoke detection information.

7. A wheel hub defect detection method according to claim 6, characterized in that: The wheel hub defect detection device includes a fourth image acquisition device, the image acquisition setting parameters include wheel hub window image acquisition parameters and rim sidewall image acquisition parameters, and performing wheel hub window defect detection and rim sidewall defect detection on the target wheel hub in the calibration accommodation position based on the image acquisition setting parameters to obtain wheel hub window detection information and rim sidewall detection information includes: transporting the target wheel hub from the third accommodating area to a fourth accommodating area; Using the fourth image acquisition device, based on the hub window image acquisition parameters, an image of the target hub in the fourth accommodating area is acquired to obtain a hub window image; Using the fourth image acquisition device, acquiring an image of the target wheel hub in the fourth accommodating area based on the rim sidewall image acquisition parameters to obtain a rim sidewall image; Performing defect recognition on the wheel hub window image to obtain the wheel hub window detection information; Defect recognition is performed on the rim sidewall image to obtain the rim sidewall detection information.

8. A wheel hub defect detection method according to claim 7, characterized in that: The wheel hub defect detection device includes a fifth image acquisition device, the image acquisition setting parameters include a center hole image acquisition parameter and a wheel rim image acquisition parameter, and performing center hole defect detection and wheel rim defect detection on the target wheel hub in the calibration accommodation position based on the image acquisition setting parameters to obtain center hole detection information and wheel rim detection information, including: transporting the target wheel hub from the fourth accommodating area to a fifth accommodating area; Using the fifth image acquisition device, based on the center hole image acquisition parameters, an image of the target wheel hub in the fifth accommodating area is acquired to obtain a center hole image; Using the fifth image acquisition device, based on the wheel rim image acquisition parameters, an image of the target wheel hub in the fifth accommodating area is acquired to obtain a wheel rim image; Performing defect recognition on the center hole image to obtain the center hole detection information; Defect recognition is performed on the wheel rim image to obtain the wheel rim detection information.

9. A wheel hub defect detection method according to claim 8, characterized in that: The wheel hub defect detection device includes a sixth image acquisition device, the image acquisition setting parameters include wheel hub back cavity image acquisition parameters and rim inner wall image acquisition parameters, and the wheel hub back cavity defect detection and rim inner wall defect detection are performed on the target wheel hub in the calibration accommodation position based on the image acquisition setting parameters to obtain wheel hub back cavity detection information and rim inner wall detection information, including: transporting the target wheel hub from the fifth accommodating area to a sixth accommodating area; Using the sixth image acquisition device, based on the wheel hub back cavity image acquisition parameters, an image of the target wheel hub in the sixth accommodating area is acquired to obtain a wheel hub back cavity image; Using the sixth image acquisition device, based on the rim inner wall image acquisition parameters, an image of the target wheel hub in the sixth accommodating area is acquired to obtain a rim inner wall image; Performing defect recognition on the wheel hub back cavity image to obtain wheel hub back cavity detection information; Defect recognition is performed on the rim inner wall image to obtain the rim inner wall detection information.

10. A wheel hub defect detection device, characterized in that: The wheel hub defect detection device is used to perform defect detection on a target wheel hub using a wheel hub defect detection method according to any one of claims 1 to 9.

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