Automobile flywheel gear ring detection method, device and equipment

Abstract

The invention is suitable for the technical field of automobile part detection, and particularly relates to an automobile flywheel gear ring detection method, device and equipment, and the method comprises the steps: obtaining an image of an automobile flywheel gear ring; processing the automobile flywheel gear ring image to obtain a flywheel gear ring enhanced image; analyzing according to the enhanced image of the flywheel gear ring to obtain an optimized contour of the flywheel gear ring; analyzing according to the flywheel gear ring optimized contour to obtain tooth number data and tooth size data; wherein the tooth number data is used for reflecting the number of normal teeth of the automobile flywheel gear ring, and the tooth size data is used for reflecting the tooth thickness of each tooth and the tooth pitch between two adjacent teeth. According to the method, through multistage optimization, the precision and efficiency of automobile flywheel gear ring detection are improved, so that the authenticity and reliability of a detection result are improved.

Description

Technical Field

[0001] The present application belongs to the technical field of automobile parts detection, and in particular, relates to a method, device and equipment for detecting an automobile flywheel ring gear. Background Art

[0002] The automobile flywheel ring gear is one of the key components of the automobile flywheel assembly. Its defects and size determine the dynamic characteristics and working efficiency of the automobile when starting. Improper control of precision, time and temperature during the manufacturing process of flywheel ring gear blank forging, quenching treatment, high-temperature tempering, etc. will cause the flywheel ring gear root fracture defects, poor meshing with the gear teeth, and then lead to various degrees of wear, tooth gnawing and tooth breaking, and finally the defects damage the ring gear, and the engine starts unsteadily. In order to ensure the smooth meshing, transmission and disengagement of the engine drive gear and the engine flywheel ring gear, it is particularly important to detect the defects and dimensions of the flywheel ring gear before leaving the factory. The defect and dimension detection is mainly aimed at the detection of defects such as missing teeth and residual teeth in the flywheel ring gear, as well as the dimensional measurement of important parameters such as tooth thickness and tooth pitch. With the advancement of industrial technology, the development of machine vision technology has greatly improved the various disadvantages of manual inspection, and a large number of automated instruments and technologies are replacing manual operation and manual inspection.

[0003] In the related technology, due to the influence of external environmental changes (such as noise interference, light source changes, etc.), errors may occur when using machine vision technology to detect the appearance dimensions of the automobile flywheel ring gear, thereby reducing the accuracy of the automobile flywheel ring gear detection data. In order to reduce the analysis error caused by the influence of external environmental changes, the method of using multi-angle shooting and analysis is feasible, but it will greatly reduce the detection efficiency. Summary of the invention

[0004] The embodiments of the present application provide a method, device and equipment for detecting a flywheel ring gear of an automobile, which can solve the problem that errors may be generated when using machine vision technology to detect the appearance dimensions of the flywheel ring gear of an automobile, the accuracy of the automobile flywheel ring gear detection data is reduced, and the detection efficiency is reduced.

[0005] In a first aspect, an embodiment of the present application provides a method for detecting a flywheel ring gear of an automobile, comprising: Acquire an image of a flywheel ring gear of an automobile; wherein the image of the flywheel ring gear of an automobile is a grayscale image used to indicate the appearance of the flywheel ring gear of the automobile; Processing the automobile flywheel ring gear image to obtain a flywheel ring gear enhanced image; Analyze the enhanced image of the flywheel gear ring to obtain an optimized profile of the flywheel gear ring; According to the optimized profile of the flywheel gear ring, the tooth number data and tooth size data are obtained; wherein the tooth number data is used to reflect the number of normal teeth of the automobile flywheel gear ring, and the tooth size data is used to reflect the tooth thickness of each tooth and the tooth pitch between two adjacent teeth.

[0006] The above technical solutions in the embodiments of the present application have at least the following technical effects: The present application provides a method for detecting a flywheel gear ring of an automobile, which obtains a grayscale image of a flywheel gear ring of an automobile, and then processes the flywheel gear ring image to obtain an enhanced image of the flywheel gear ring; then analyzes the enhanced image of the flywheel gear ring to obtain an optimized contour of the flywheel gear ring; and analyzes the optimized contour of the flywheel gear ring to obtain tooth number data and tooth size data; wherein the tooth number data is used to reflect the number of normal teeth of the flywheel gear ring of the automobile, and the tooth size data is used to reflect the tooth thickness of each tooth and the tooth pitch between two adjacent teeth. The method can reduce the influence of changes in the external environment by optimizing the image of the flywheel gear ring of the automobile, and optimizes the enhanced image of the flywheel gear ring after optimization again, so that the optimized contour of the flywheel gear ring can truly reflect the actual size of the flywheel gear ring of the automobile, that is, through multi-level optimization, the accuracy, robustness and efficiency of the detection of the flywheel gear ring of the automobile are improved, thereby improving the authenticity and reliability of the detection result; at the same time, there is no need to perform multi-angle shooting analysis, and only by optimizing the analysis of the flywheel gear ring image of the automobile, the detection efficiency is greatly improved.

[0007] In a possible implementation manner of the first aspect, processing the image of the automobile flywheel ring gear to obtain an enhanced image of the flywheel ring gear includes: Analyze the automobile flywheel ring gear image to obtain a first grayscale value; wherein the first grayscale value is used to reflect the original grayscale value of each pixel in the automobile flywheel ring gear image; After the automobile flywheel gear ring image is processed by mean filtering, a second grayscale value is obtained; wherein the second grayscale value is used to reflect the grayscale value of the pixel point after the automobile flywheel gear ring image is processed by mean filtering; Get contrast enhancement factor; Performing analysis according to the first grayscale value, the second grayscale value and the contrast enhancement factor to obtain an optimized grayscale value; A flywheel ring gear enhanced image is obtained based on the optimized grayscale value.

[0008] In a possible implementation manner of the first aspect, analyzing the enhanced image of the flywheel ring gear to obtain an optimized profile of the flywheel ring gear includes: Analyze the pixel points reflected by the flywheel gear ring enhanced image to obtain a plurality of first edge points and a plurality of second edge points; wherein the intensity gradient of the first edge point is greater than a first preset threshold, and the intensity gradient of the second edge point is less than the first preset threshold and greater than the second preset threshold; Analyze the distance between the first edge point and the nearest second edge point to obtain a plurality of third edge points; wherein the third edge points are some pixel points among the plurality of the second edge points; The plurality of first edge points are connected with the plurality of third edge points to obtain an optimized profile of the flywheel ring gear.

[0009] In a possible implementation of the first aspect, the analyzing according to the optimized profile of the flywheel ring gear to obtain the tooth number data and the tooth size data includes: Analyze according to the optimized profile of the flywheel gear ring to obtain a first circular profile; wherein the first circular profile is used to reflect the profile of the maximum inscribed circle of the tooth reflected by the optimized profile of the flywheel gear ring; Analyze the optimized profile of the flywheel gear ring and the first circular profile to obtain data on the number of teeth; When the tooth number data is normal, an analysis is performed according to the optimized profile of the flywheel gear ring to obtain a second circular profile; wherein the second circular profile is used to reflect the profile of the pitch circle of the optimized profile of the flywheel gear ring; The tooth size data is obtained by analyzing the optimized profile of the flywheel gear ring and the second circular profile.

[0010] In a possible implementation manner of the first aspect, the analyzing according to the optimized profile of the flywheel ring gear and the first circular profile to obtain the tooth number data includes: Performing optimization processing according to the first circular contour to obtain a third circular contour; Performing differential processing on the optimized flywheel gear ring profile and the third circular profile to obtain a gear profile; wherein the gear profile is used to reflect the profile of the gear of the flywheel gear ring of the automobile; The gear profile is analyzed to obtain the data of the number of teeth.

[0011] In a possible implementation manner of the first aspect, analyzing according to the gear profile to obtain tooth number data includes: Analyze the gear profile to obtain area information, perimeter information and convex shape factor of each tooth; wherein the area information is used to reflect the size of the area surrounded by the tooth profile, the perimeter information is used to reflect the edge length of the tooth, and the convex shape factor is used to reflect the ratio of the area of ​​the tooth to the area of ​​its convex hull; Calculating an area mean of the area information of all teeth, a perimeter mean of the perimeter information of all teeth, and a convexity shape factor mean of the convexity shape factors of all teeth; Get the area screening coefficient interval, perimeter screening coefficient interval and convexity shape factor coefficient interval; The area screening coefficient interval is weighted to the area mean to obtain an area allowable range, the perimeter screening coefficient interval is weighted to the perimeter mean to obtain a perimeter allowable range, and the convexity shape factor coefficient interval is weighted to the convexity shape factor mean to obtain a convexity shape factor allowable range; The area information, the circumference information and the convex shape factor of each tooth are compared and screened based on the allowable range of area, the allowable range of circumference and the allowable range of convex shape factor to obtain tooth number data; wherein the area information, the circumference information and the convex shape factor of the tooth reflected in the tooth number data are all within the allowable range of area, the allowable range of circumference and the allowable range of convex shape factor.

[0012] In a possible implementation manner of the first aspect, the analyzing according to the optimized profile of the flywheel ring gear and the second circular profile to obtain the tooth size data includes: Performing differential calculation based on the optimized profile of the flywheel gear ring and the second circular profile to obtain tooth thickness profile information; wherein the tooth thickness profile information is used to reflect the actual profile of each tooth of the automobile flywheel gear ring; The tooth size data is obtained by analyzing the second circular profile and the tooth thickness profile information.

[0013] In a possible implementation manner of the first aspect, the obtaining tooth size data by analyzing the second circular profile and the tooth thickness profile information includes: Calculating the intersection information of the second circular contour and the contour reflected in the tooth thickness contour information; wherein the intersection information is used to reflect the coordinates of the intersection of the second circular contour and the tooth thickness contour information; According to the intersection information, the distance between the leftmost coordinate and the rightmost coordinate of each tooth thickness profile in the tooth thickness profile information is calculated in sequence to obtain the tooth thickness data of the tooth size data; The distance between the leftmost coordinate of one tooth thickness profile in the tooth thickness profile information and the leftmost coordinate of the adjacent tooth thickness profile is calculated in sequence according to the intersection information to obtain the pitch data of the tooth size data.

[0014] In a second aspect, an embodiment of the present application provides a vehicle flywheel ring gear detection device, comprising: An acquisition module, used for acquiring an image of a flywheel ring gear of an automobile; wherein the image of the flywheel ring gear of an automobile is a grayscale image used to indicate the appearance of the flywheel ring gear of the automobile; An enhancement module, used for processing the image of the automobile flywheel ring gear to obtain an enhanced image of the flywheel ring gear; A first analysis module is used to analyze the flywheel gear ring enhancement image to obtain an optimized profile of the flywheel gear ring; The second analysis module is used to analyze according to the optimized profile of the flywheel ring gear to obtain tooth number data and tooth size data; wherein the tooth number data is used to reflect the number of normal teeth of the automobile flywheel ring gear, and the tooth size data is used to reflect the tooth thickness of each tooth and the tooth pitch between two adjacent teeth.

[0015] In a third aspect, an embodiment of the present application provides an automobile flywheel ring gear detection device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements any of the methods described in the first aspect when executing the computer program.

[0016] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described in any one of the above-mentioned first aspects is implemented.

[0017] In a fifth aspect, an embodiment of the present application provides a computer program product. When the computer program product is run on an automobile flywheel ring gear detection device, the automobile flywheel ring gear detection device executes the automobile flywheel ring gear detection method described in any one of the above-mentioned first aspects.

[0018] It can be understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0020] Figure 1 It is a flow chart of a method for detecting a flywheel ring gear of an automobile provided in an embodiment of the present application; Figure 2 It is a schematic diagram of the implementation flow of the automobile flywheel ring gear detection method provided in the embodiment of the present application; Figure 3It is a structural schematic diagram of an automobile flywheel ring gear detection device provided in an embodiment of the present application; Figure 4 It is a structural schematic diagram of the automobile flywheel ring gear detection equipment provided in an embodiment of the present application. DETAILED DESCRIPTION

[0021] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0022] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0023] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0024] As used in the specification of this application and the appended claims, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting" depending on the context. Similarly, the phrase "if it is determined" or "if the described condition or event is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce the described condition or event is detected" or "in response to detecting the described condition or event" depending on the context.

[0025] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0026] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0027] The automobile flywheel ring gear is one of the key components of the automobile flywheel assembly. Its defects and size determine the dynamic characteristics and working efficiency of the automobile when starting. Improper control of precision, time and temperature during the manufacturing process of flywheel ring gear blank forging, quenching treatment, high-temperature tempering, etc. will cause the flywheel ring gear root fracture defects, poor meshing with the gear teeth, and then lead to various degrees of wear, tooth gnawing and tooth breaking, and finally the defects damage the ring gear, and the engine starts unsteadily. In order to ensure the smooth meshing, transmission and disengagement of the engine drive gear and the engine flywheel ring gear, it is particularly important to detect the defects and dimensions of the flywheel ring gear before leaving the factory. The defect and dimension detection is mainly aimed at the detection of defects such as missing teeth and residual teeth in the flywheel ring gear, as well as the dimensional measurement of important parameters such as tooth thickness and tooth pitch. With the advancement of industrial technology, the development of machine vision technology has greatly improved the various disadvantages of manual inspection, and a large number of automated instruments and technologies are replacing manual operation and manual inspection.

[0028] In the related technology, due to the influence of external environmental changes (such as noise interference, light source changes, etc.), errors may occur when using machine vision technology to detect the appearance dimensions of the automobile flywheel ring gear, thereby reducing the accuracy of the automobile flywheel ring gear detection data. In order to reduce the analysis error caused by the influence of external environmental changes, the method of using multi-angle shooting and analysis is feasible, but it will greatly reduce the detection efficiency.

[0029] To solve the above problems, the embodiment of the present application provides a method, device and equipment for detecting a flywheel ring gear of an automobile. In the method, a flywheel ring gear image of an automobile is obtained as a grayscale image indicating the appearance of the flywheel ring gear of an automobile; then the flywheel ring gear image is processed to obtain an enhanced image of the flywheel ring gear; then the enhanced image of the flywheel ring gear is analyzed to obtain an optimized contour of the flywheel ring gear; the optimized contour of the flywheel ring gear is analyzed to obtain the number of teeth data and tooth size data; wherein the number of teeth data is used to reflect the number of normal teeth of the flywheel ring gear of an automobile, and the tooth size data is used to reflect the tooth thickness of each tooth and the tooth pitch between two adjacent teeth. The method can reduce the influence of external environmental changes by optimizing the image of the automobile flywheel gear ring, and optimizes the enhanced image of the optimized flywheel gear ring again so that the optimized contour of the flywheel gear ring can truly reflect the actual size of the automobile flywheel gear ring, that is, through multi-level optimization, the accuracy, robustness and efficiency of automobile flywheel gear ring detection are improved, thereby improving the authenticity and reliability of the detection result; at the same time, there is no need to perform multi-angle shooting analysis, and the detection efficiency is greatly improved only by optimizing the analysis of the automobile flywheel gear ring image.

[0030] The automobile flywheel ring gear detection method provided in the embodiment of the present application can be applied to an automobile flywheel ring gear detection device. At this time, the automobile flywheel ring gear detection device is the executor of the automobile flywheel ring gear detection method provided in the embodiment of the present application. The embodiment of the present application does not impose any restrictions on the specific type of the automobile flywheel ring gear detection device.

[0031] For example, the automobile flywheel ring gear detection device can be on a terminal device such as a mobile phone, a tablet computer, a wearable device, an augmented reality (AR) / virtual reality (VR) device, a laptop computer, an ultra-mobile personal computer (UMPC), a netbook, a personal digital assistant (PDA), a desktop computer, a smart large screen, a smart TV, a handheld device with wireless communication function, a computing device or other processing device connected to a wireless modem, a single-chip microcomputer, an Internet of Things terminal, a computer, a laptop computer, a handheld communication device, a handheld computing device, a satellite wireless device, a wireless modem card, a customer premises equipment (CPE), etc.

[0032] In order to better understand the automobile flywheel ring gear detection method provided in the embodiment of the present application, the specific implementation process of the automobile flywheel ring gear detection method provided in the embodiment of the present application is exemplarily introduced below.

[0033] Figure 1 and Figure 2 A schematic flow chart of a method for detecting a flywheel ring gear of an automobile provided in an embodiment of the present application is shown. The method for detecting a flywheel ring gear of an automobile comprises: S100, obtaining an image of a flywheel ring gear of an automobile; wherein the image of the flywheel ring gear of an automobile is a grayscale image used to indicate the appearance of the flywheel ring gear of the automobile.

[0034] It can be understood that the image of the automobile flywheel ring gear is obtained by photographing the automobile flywheel ring gear through an industrial camera or other imaging equipment after a light source is irradiated on the top of the automobile flywheel ring gear, and then the image is converted into grayscale.

[0035] S200, processing the image of the automobile flywheel ring gear to obtain an enhanced image of the flywheel ring gear.

[0036] It can be understood that the flywheel gear ring enhanced image refers to the image obtained after edge optimization of the acquired automobile flywheel gear ring image. Exemplarily, the automobile flywheel gear ring image can be processed by mean filtering and then analyzed with the original image to obtain a new grayscale value of each pixel, and then the flywheel gear ring enhanced image is generated according to the new grayscale value; the flywheel gear ring enhanced image can also be obtained through a machine learning model, that is, the automobile flywheel gear ring image can be input into a convolutional neural network model, and the convolutional neural network model then outputs the corresponding flywheel gear ring enhanced image, etc., but not limited to this. The convolutional neural network model is trained with multiple sets of training data, and each set of training data in the multiple sets of training data includes an automobile flywheel gear ring image and a flywheel gear ring enhanced image.

[0037] In a possible implementation, in step S200, the image of the flywheel ring gear of the automobile is processed to obtain an enhanced image of the flywheel ring gear, including: S210, analyzing the image of the automobile flywheel ring gear to obtain a first grayscale value; wherein the first grayscale value is used to reflect the original grayscale value of each pixel in the image of the automobile flywheel ring gear.

[0038] It can be understood that when the automobile flywheel ring gear is converted into grayscale through an imaging device, each pixel point can be recorded and packaged to obtain a first grayscale value, or the automobile flywheel ring gear image can be directly converted through inverse Fourier to obtain the first grayscale value, etc., but not limited to this.

[0039] S220, performing mean filtering on the image of the automobile flywheel ring gear to obtain a second grayscale value; wherein the second grayscale value is used to reflect the grayscale value of the pixel point after the image of the automobile flywheel ring gear is subjected to mean filtering.

[0040] It can be understood that mean filtering refers to replacing the original grayscale value of each pixel in the image by calculating the average value of each pixel and the pixels in its surrounding neighborhood. That is, traverse each pixel in the image and take it as the center point. For each center point, extract the pixel values ​​of the preset neighborhood around it. For example, for a 3x3 filter kernel, extract a 3x3 neighborhood, and so on; then calculate the average value of all pixel values ​​in the neighborhood, assign the calculated average value to the pixel value of the center point, and replace the original pixel value. The preset neighborhood is a pre-set domain range, which can be manually input by humans or obtained in an image optimization database, etc., but is not limited to this. The image optimization database refers to a database containing a preset neighborhood. These data can be obtained through laboratory experiments, on-site measurements and monitoring, and previous experience. After obtaining, the collected data is sorted, classified and archived, useful information and rules are extracted, and the relevant data is saved in the database to form an image optimization database.

[0041] S230, obtaining a contrast enhancement factor.

[0042] It can be understood that the contrast enhancement factor refers to the degree of enhancement of the image contrast, and the contrast enhancement factor is a preset value, which can be manually input by humans, or obtained from an image optimization database, etc., but is not limited thereto. The image optimization database also includes the contrast enhancement factor.

[0043] S240, analyzing the first grayscale value, the second grayscale value and the contrast enhancement factor to obtain an optimized grayscale value.

[0044] Exemplarily, the first grayscale value and the second grayscale value corresponding to each pixel can be substituted into the optimization function: optimized grayscale value = (second grayscale value - first grayscale value) × contrast enhancement factor + second grayscale value to obtain the optimized grayscale value of each pixel, wherein the obtained optimized grayscale value can round the floating point number to the nearest integer, for example, when the calculated optimized grayscale value is 135.8, the optimized grayscale value can be 136, when the calculated optimized grayscale value is 132.3, the optimized grayscale value can be 132, and so on. The first grayscale value, the second grayscale value and the contrast enhancement factor can also be input into the learning model, and the learning model then outputs the corresponding optimized grayscale value, etc., but is not limited thereto. The learning model is trained through multiple sets of training data, and each set of training data in the multiple sets of training data includes the first grayscale value, the second grayscale value and the contrast enhancement factor and the corresponding optimized grayscale value.

[0045] S250, the enhanced image of the flywheel gear ring is obtained based on the optimized grayscale value.

[0046] It can be understood that the flywheel ring gear enhanced image can be obtained by directly converting the optimized grayscale value into an image format.

[0047] With this setting, for the specific shape of the automobile flywheel ring gear, which contains multiple faces and teeth, the contrast of the image can be flexibly adjusted by using mean filtering processing and referencing the contrast enhancement factor, making the key areas in the image (such as the tooth top and tooth root) more prominent, thereby significantly improving the processing effect of the automobile flywheel ring gear image, improving the subsequent detection efficiency, and enhancing the reliability of the data.

[0048] S300, analyzes the enhanced image of the flywheel ring gear to obtain an optimized profile of the flywheel ring gear.

[0049] It can be understood that the optimized contour of the flywheel gear ring refers to the contour that can reflect the real size of the flywheel gear ring. For example, the optimized contour of the flywheel gear ring can be obtained by statistically analyzing and classifying the pixel points reflected by the enhanced image of the flywheel gear ring, optimizing different pixel points respectively, and connecting the optimized pixel points; or the flywheel gear ring enhanced image can be analyzed using a convolutional neural network model to output the corresponding optimized contour of the flywheel gear ring, etc., but not limited thereto.

[0050] In a possible implementation, in step S300, analyzing the enhanced image of the flywheel ring gear to obtain an optimized profile of the flywheel ring gear includes: S310, analyzing the pixel points reflected by the flywheel ring gear enhanced image to obtain multiple first edge points and multiple second edge points; wherein the intensity gradient of the first edge point is greater than the first preset threshold, and the intensity gradient of the second edge point is less than the first preset threshold and greater than the second preset threshold.

[0051] It can be understood that the intensity gradient refers to the degree of brightness change between pixels, and the intensity gradient of each pixel in the image can be calculated by a gradient operator (such as a Sobel operator, a Canny operator, etc.). The first preset threshold and the second preset threshold are both preset intensity gradient values, which can be manually input or obtained from an image optimization database, etc., but are not limited thereto.

[0052] S320, analyzing the distance between the first edge point and the nearest second edge point to obtain a plurality of third edge points; wherein the third edge points are some pixel points among the plurality of second edge points.

[0053] It can be understood that by calculating the distance between each second edge point and the first edge point in sequence, a second edge point whose distance between the second edge point and the first edge point is equal to the preset distance is screened out, which is the third edge point.

[0054] S330, connecting the plurality of first edge points with the plurality of third edge points to obtain an optimized profile of the flywheel ring gear.

[0055] It can be understood that the connection method is to integrate the third edge point with the first edge point to generate a comprehensive edge point set, then mark the comprehensive edge point set in a binary image, and finally use the contour detection algorithm to connect the comprehensive edge points to generate the optimized contour of the flywheel ring gear.

[0056] Such a setting makes the contour of the flywheel ring gear clearer and more complete, and improves the consistency between the contour of the flywheel ring gear obtained by analysis and its actual contour, thereby improving the accuracy and reliability of detection and providing a high-quality image basis for subsequent defect detection and quality control.

[0057] S400, analyzing the optimized profile of the flywheel gear ring to obtain tooth number data and tooth size data; wherein the tooth number data is used to reflect the number of normal teeth of the automobile flywheel gear ring, and the tooth size data is used to reflect the tooth thickness of each tooth and the tooth pitch between two adjacent teeth.

[0058] Exemplarily, the flywheel gear ring optimized contour analysis can be used to calculate the inscribed circle formed by each pixel point and other pixel points on the contour, and the largest inscribed circle can be obtained by comparative analysis. After the inscribed circle is optimized, the optimized maximum inscribed circle is analyzed with the flywheel gear ring optimized contour to obtain the contour of the teeth of the flywheel gear ring. The tooth number data can be obtained by calculating the area, circumference and other parameters reflected in the tooth contour. The position coordinates of the concave and convex points can also be directly analyzed through the flywheel gear ring optimized contour. The position and number of tooth roots and tooth tops can be determined by statistically analyzing the positional relationship of the position coordinates of the concave and convex points to obtain the tooth number data, and so on, but not limited to this. The contour of the pitch circle can be obtained by analyzing the optimized contour of the flywheel gear ring, and the tooth thickness contour of each tooth can be obtained by analyzing the optimized contour of the flywheel gear ring and the contour of the pitch circle. The tooth pitch of two adjacent teeth can be obtained through the contour of the pitch circle and the tooth thickness contour, and the tooth size data including the tooth thickness and the tooth pitch can be obtained. The distance between one concave point and two adjacent concave points can also be directly calculated through the optimized contour of the flywheel gear ring to obtain the tooth thickness and the tooth pitch, and so on, but not limited to this.

[0059] In a possible implementation, in step S400, the tooth number data and tooth size data are obtained by analyzing the optimized profile of the flywheel ring gear, including: S410, analyzing the optimized profile of the flywheel gear ring to obtain a first circular profile; wherein the first circular profile is used to reflect the profile of the maximum inscribed circle of the tooth reflected by the optimized profile of the flywheel gear ring.

[0060] It can be understood that the traversal algorithm can be used to sequentially form an inscribed circle with each pixel point in the optimized contour of the flywheel ring gear and other pixel points on the contour, and then after comparison and analysis, the inscribed circle with the largest radius is taken as the first circular contour; the optimized contour of the flywheel ring gear can also be input into the learning model, and the learning model then outputs the corresponding first circular contour, and so on, but not limited to this.

[0061] S420, analyzing the optimized profile of the flywheel ring gear and the first circular profile to obtain data on the number of teeth.

[0062] Exemplarily, the first circular contour can be optimized in one step, and then analyzed and processed together with the optimized contour of the flywheel ring gear to obtain the gear contour, and the tooth number data can be obtained through the gear contour; the optimized contour of the flywheel ring gear and the first circular contour can also be input into the learning model, and the learning model outputs the corresponding tooth number data, etc., but is not limited to this.

[0063] In a possible implementation, in step S420, the tooth number data is obtained by analyzing the optimized profile of the flywheel ring gear and the first circular profile, including: S421, performing optimization processing according to the first circular contour to obtain a third circular contour.

[0064] It can be understood that there is usually an arc at the root of the tooth in the optimized contour of the flywheel ring gear. The radius of the first circular contour can be increased by a preset radius value as the radius value of the third circular contour to reduce the analysis error caused by the arc. The preset radius value is a pre-set value, which can be manually input or obtained from the image optimization database, etc., but is not limited to this.

[0065] S422, performing differential processing based on the optimized profile of the flywheel ring gear and the third circular profile to obtain a gear profile; wherein the gear profile is used to reflect the profile of the gear of the flywheel ring gear of the automobile.

[0066] It can be understood that the differential processing refers to removing the portion covered by the third circular contour from the optimized contour of the flywheel ring gear, and the portion of the optimized gear of the flywheel ring gear that is not covered by the third circular contour is the gear contour.

[0067] S423, analyzing the gear profile to obtain the number of teeth data.

[0068] It can be understood that the size and shape of each tooth reflected in the gear profile can be analyzed to obtain data for each tooth, and the number of teeth data can be obtained by comparing and analyzing the data; the gear profile can also be input into a learning model, and the learning model outputs the corresponding number of teeth data, and so on, but not limited to this.

[0069] With such a setting, the gear profile is obtained by differential processing between the optimized circular profile and the optimized profile of the flywheel ring gear, which can reduce the interference of other profiles during tooth detection, thereby improving the accuracy of tooth number data analysis.

[0070] In a possible implementation, in step S423, analyzing the gear profile to obtain the tooth number data includes: S4231, analyze the gear contour to obtain the area information, perimeter information and convex shape factor of each tooth; the area information is used to reflect the size of the area enclosed by the tooth contour, the perimeter information is used to reflect the edge length of the tooth, and the convex shape factor is used to reflect the ratio of the area of ​​the tooth to the area of ​​its convex hull.

[0071] It can be understood that the convex hull refers to the smallest convex polygon containing the contour. The area, perimeter and convex hull of the contour of each tooth can be calculated using image processing tools, and the convex shape factor of each tooth can be obtained through the area and the area of ​​the convex hull.

[0072] S4232, calculating the area mean of the area information of all teeth, the perimeter mean of the perimeter information of all teeth, and the convexity shape factor mean of the convexity shape factors of all teeth.

[0073] It can be understood that the mean area = the sum of the areas of each tooth ÷ the number of teeth (the number of teeth is the number of normal teeth plus the number of abnormal teeth), and the same is true for the mean circumference and the mean convexity shape factor. For example, suppose there are 5 tooth contours, whose areas are 100, 110, 120, 130, and 140 square pixels, respectively, and whose perimeters are 50, 55, 60, 65, and 70 pixels, respectively, and whose convexity shape factors are 0.95, 0.96, 0.97, 0.98, and 0.99, respectively. Then the mean area is 120[(100+110+120+130+140)÷5] pixels, the mean perimeter is 60[(50+55+60+65+70)÷5] pixels, the mean convexity shape factor is 0.97[(0.95+0.96+0.97+0.98+0.99)÷5], and so on.

[0074] S4233, obtaining the area screening coefficient interval, the perimeter screening coefficient interval and the convexity shape factor coefficient interval.

[0075] It can be understood that the area screening coefficient interval, the perimeter screening coefficient interval and the convex shape factor coefficient interval are pre-set interval ranges, which can be manually input or obtained from the analysis database, etc., but are not limited thereto. The analysis database contains the area screening coefficient intervals, the perimeter screening coefficient intervals and the convex shape factor coefficient intervals corresponding to automobile flywheel ring gears of different specifications.

[0076] S4234, weight the area screening coefficient interval to the area mean to obtain the area allowable range, weight the perimeter screening coefficient interval to the perimeter mean to obtain the perimeter allowable range, and weight the convexity shape factor coefficient interval to the convexity shape factor mean to obtain the convexity shape factor allowable range.

[0077] It can be understood that the area allowable range = area screening coefficient interval × area mean, that is, the upper and lower limits of the area screening coefficient interval can be multiplied by the area mean, and the two numbers obtained are used as the upper and lower limits of the area allowable range. The same is true for the perimeter allowable range and the convex shape factor allowable range. For example, assuming that the area mean is 120 pixels, the area screening coefficient interval is [0.9, 1.1], and the area allowable range is [108 (120×0.9), 132 (120×1.1)] pixels, and so on.

[0078] S4235, the area information, circumference information and convex shape factor of each tooth are compared and screened based on the allowable range of area, the allowable range of circumference and the allowable range of convex shape factor to obtain the tooth number data; wherein the area information, circumference information and convex shape factor of the tooth reflected in the tooth number data are all within the allowable range of area, the allowable range of circumference and the allowable range of convex shape factor.

[0079] It can be understood that the corresponding teeth whose area information, circumference information and convex shape factor reflected in the tooth number data are outside the allowable range of area, the allowable range of circumference and the allowable range of convex shape factor are residual teeth or missing teeth. For example, suppose there are five tooth contours, whose areas are 100, 110, 120, 130, 140 square pixels, perimeters are 50, 55, 60, 65, 70 pixels, convexity shape factors are 0.95, 0.96, 0.97, 0.98, 0.99, the area tolerance range is [108, 132] pixels, the perimeter tolerance range is [54, 66] pixels, and the convexity shape factor tolerance range is [0.92, 1.02]. The tooth area of ​​140 is not within the area tolerance range, but its perimeter and convexity shape factor are within the tolerance range. The tooth corresponding to the tooth contour is an abnormal tooth, and the others are normal teeth, and so on. The number of normal teeth is counted to obtain the tooth number data.

[0080] With this setting, by extracting the area information, circumference information and convex shape factor of each tooth and analyzing the tooth contour from multiple angles, it can not only comprehensively reflect the geometric characteristics of the tooth, but also effectively identify and classify normal teeth and abnormal teeth by calculating the mean and setting the allowable range, thereby reducing misjudgments and missed detections and improving the accuracy and reliability of detection.

[0081] S430, when there is no abnormality in the tooth number data, analyzing is performed according to the optimized profile of the flywheel ring gear to obtain a second circular profile; wherein the second circular profile is used to reflect the profile of the pitch circle of the optimized profile of the flywheel ring gear.

[0082] It can be understood that when the number of teeth data is abnormal, in order to improve the detection efficiency, the next step of analysis may not be required, and the automobile flywheel ring gear needs to be reworked or scrapped. For example, the root circle can be obtained by fitting the coordinates of the concave points in the optimized contour of the flywheel ring gear, and the top circle can be obtained by fitting the coordinates of the convex points in the optimized contour of the flywheel ring gear, and then the average of the radius of the root circle and the radius of the top circle is calculated as the radius of the second circular contour.

[0083] S440, analyzing the optimized profile of the flywheel gear ring and the second circular profile to obtain tooth size data.

[0084] Exemplarily, the tooth thickness and tooth pitch in the tooth size data can be obtained by calculating the distance between the intersection of the second circular contour and the optimized contour of the flywheel ring gear; the optimized contour of the flywheel ring gear and the second circular contour can also be input into the learning model, and the learning model outputs the corresponding tooth thickness and tooth pitch, etc., but is not limited to this.

[0085] With such arrangement, by further optimizing and analyzing the optimized contour of the flywheel ring gear, a first circular contour and a second circular contour are obtained, thereby reducing errors caused by irregular contours and further improving the accuracy and reliability of detection.

[0086] In a possible implementation, in step S440, analyzing the optimized profile of the flywheel ring gear and the second circular profile to obtain tooth size data includes: S441, performing differential calculation based on the optimized profile of the flywheel gear ring and the second circular profile to obtain tooth thickness profile information; wherein the tooth thickness profile information is used to reflect the actual profile of each tooth of the automobile flywheel gear ring.

[0087] It can be understood that, through differential calculation, the partial contour of the flywheel gear ring optimized contour outside the second circular contour area is retained, that is, the tooth thickness contour information.

[0088] S442, analyzing the second circular profile and the tooth thickness profile information to obtain tooth size data.

[0089] Exemplarily, the tooth thickness and tooth pitch in the tooth size data can be calculated based on the intersection information of the second circular contour and the tooth thickness contour, or the second circular contour and tooth thickness contour information can be input into the learning model, and the learning model outputs the corresponding tooth thickness and tooth pitch, etc., but is not limited to this.

[0090] In a possible implementation, in step S442, the tooth size data is obtained by analyzing the second circular profile and the tooth thickness profile information, including: S4421, calculating the intersection information between the second circular contour and the contour reflected in the tooth thickness contour information; wherein the intersection information is used to reflect the coordinates of the intersection of the second circular contour and the tooth thickness contour information.

[0091] It can be understood that all intersection points can be substituted into the same two-dimensional coordinate system to obtain the position information of each intersection point.

[0092] S4422, calculating the distance between the leftmost coordinate and the rightmost coordinate of each tooth thickness profile in the tooth thickness profile information in sequence according to the intersection information, and obtaining the tooth thickness data of the tooth size data.

[0093] It can be understood that according to the intersection information, the leftmost and rightmost coordinates of each tooth are determined, and then the leftmost and rightmost coordinates are connected. The connecting line segment is the tooth thickness of the tooth. S4423, calculating the distance between the leftmost coordinate of one tooth thickness profile in the tooth thickness profile information and the leftmost coordinate of the adjacent tooth thickness profile in sequence according to the intersection information, and obtaining the pitch data of the tooth size data.

[0094] It can be understood that the leftmost coordinate of one tooth thickness profile is connected with the leftmost coordinate of the adjacent tooth thickness profile, and the connecting line segment is the tooth thickness of the two teeth.

[0095] In this way, through the above scheme, the tooth size data of the flywheel gear ring can be quickly and accurately extracted, including tooth thickness and tooth pitch. This method not only improves the accuracy and efficiency of detection, but also enhances the robustness and standardization of detection, providing strong technical support for the quality control and fault diagnosis of the flywheel gear ring.

[0096] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0097] Corresponding to the automobile flywheel ring gear detection method described in the above embodiment, the embodiment of the present application also provides an automobile flywheel ring gear detection device, and each module of the device can implement each step of the automobile flywheel ring gear detection method. Figure 3 A structural block diagram of an automobile flywheel ring gear detection device provided in an embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown.

[0098] Reference Figure 3 , the automobile flywheel gear ring detection device comprises: The acquisition module is used to acquire the image of the flywheel ring gear of the automobile; wherein the image of the flywheel ring gear of the automobile is used to indicate the grayscale image of the appearance of the flywheel ring gear of the automobile.

[0099] The enhancement module is used to process the image of the automobile flywheel ring gear to obtain an enhanced image of the flywheel ring gear.

[0100] The first analysis module is used to analyze the enhanced image of the flywheel ring gear to obtain an optimized contour of the flywheel ring gear.

[0101] The second analysis module is used to analyze the optimized profile of the flywheel gear ring to obtain the tooth number data and tooth size data. The tooth number data is used to reflect the number of normal teeth of the automobile flywheel gear ring, and the tooth size data is used to reflect the tooth thickness of each tooth and the tooth pitch between two adjacent teeth.

[0102] It should be noted that the information interaction, execution process and other contents between the above-mentioned modules are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0103] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above modules is used as an example for illustration. In actual applications, the above functions can be assigned to different modules as needed, that is, the internal structure of the device can be divided into different modules to complete all or part of the functions described above. The modules in the embodiment can be integrated into a processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the modules in the above device can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0104] The present application also provides a vehicle flywheel ring gear detection device, Figure 4 This is a schematic diagram of the structure of a vehicle flywheel ring gear detection device 6 provided in an embodiment of the present application. Figure 4 As shown, the automobile flywheel ring gear detection device 6 of this embodiment includes: at least one processor 60 ( Figure 4 Only one is shown), at least one memory 61 ( Figure 4Only one is shown in the figure) and a computer program 62 stored in the at least one memory 61 and executable on the at least one processor 60. When the processor 60 executes the computer program 62, the automobile flywheel ring gear detection device 6 implements the steps in any of the above-mentioned automobile flywheel ring gear detection method embodiments, or the automobile flywheel ring gear detection device 6 implements the functions of each module in the above-mentioned device embodiments.

[0105] Exemplarily, the computer program 62 may be divided into one or more modules / units, which are stored in the memory 61 and executed by the processor 60 to complete the present application. The one or more modules / units may be a series of computer program instruction segments capable of completing specific functions, which are used to describe the execution process of the computer program 62 in the automobile flywheel ring gear detection device 6.

[0106] The automobile flywheel gear ring detection device 6 can be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The automobile flywheel gear ring detection device can include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art can understand that Figure 4 It is only an example of the automobile flywheel ring gear detection device 6 and does not constitute a limitation of the automobile flywheel ring gear detection device 6. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components, for example, it may also include input and output devices, network access devices, buses, etc.

[0107] The processor 60 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0108] In some embodiments, the memory 61 may be an internal storage unit of the automobile flywheel gear ring detection device 6, such as a hard disk or memory of the automobile flywheel gear ring detection device 6. In other embodiments, the memory 61 may also be an external storage device of the automobile flywheel gear ring detection device 6, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the automobile flywheel gear ring detection device 6. Further, the memory 61 may also include both the internal storage unit of the automobile flywheel gear ring detection device 6 and an external storage device. The memory 61 is used to store an operating system, an application program, a boot loader (BootLoader), data and other programs, such as the program code of the computer program, etc. The memory 61 may also be used to temporarily store data that has been output or is to be output.

[0109] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in any of the above method embodiments are implemented.

[0110] An embodiment of the present application provides a computer program product. When the computer program product is run on an automobile flywheel ring gear detection device, the automobile flywheel ring gear detection device implements the steps in any of the above-mentioned method embodiments.

[0111] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the automobile flywheel ring gear detection device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, RandomAccess Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, a USB flash drive, a mobile hard disk, a disk or an optical disk.

[0112] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0113] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0114] In the embodiments provided in the present application, it should be understood that the disclosed automobile flywheel ring gear detection equipment and devices can be implemented in other ways. For example, the above-described automobile flywheel ring gear detection device embodiment is only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation. For example, multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or modules, which can be electrical, mechanical or other forms.

[0115] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0116] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for detecting a flywheel ring gear of an automobile, characterized in that: include: Acquire an image of a flywheel ring gear of an automobile; wherein the image of the flywheel ring gear of an automobile is a grayscale image used to indicate the appearance of the flywheel ring gear of the automobile; Processing the automobile flywheel ring gear image to obtain a flywheel ring gear enhanced image; Analyze the enhanced image of the flywheel gear ring to obtain an optimized profile of the flywheel gear ring; Analyze the optimized profile of the flywheel gear ring to obtain the data of the number of teeth and the data of tooth size; wherein the data of the number of teeth is used to reflect the number of normal teeth of the flywheel gear ring of the automobile, and the data of tooth size is used to reflect the tooth thickness of each tooth and the tooth pitch between two adjacent teeth; The step of analyzing the optimized profile of the flywheel gear ring to obtain the tooth number data and tooth size data includes: Analyze according to the optimized profile of the flywheel gear ring to obtain a first circular profile; wherein the first circular profile is used to reflect the profile of the maximum inscribed circle of the tooth reflected by the optimized profile of the flywheel gear ring; Analyze the optimized profile of the flywheel gear ring and the first circular profile to obtain data on the number of teeth; When the tooth number data is normal, an analysis is performed according to the optimized profile of the flywheel gear ring to obtain a second circular profile; wherein the second circular profile is used to reflect the profile of the pitch circle of the optimized profile of the flywheel gear ring; The tooth size data is obtained by analyzing the optimized profile of the flywheel gear ring and the second circular profile.

2. The method for detecting a flywheel ring gear of an automobile according to claim 1, characterized in that: The step of processing the automobile flywheel gear ring image to obtain a flywheel gear ring enhanced image includes: Analyze the automobile flywheel ring gear image to obtain a first grayscale value; wherein the first grayscale value is used to reflect the original grayscale value of each pixel in the automobile flywheel ring gear image; After the automobile flywheel gear ring image is processed by mean filtering, a second grayscale value is obtained; wherein the second grayscale value is used to reflect the grayscale value of the pixel point after the automobile flywheel gear ring image is processed by mean filtering; Get contrast enhancement factor; Performing analysis according to the first grayscale value, the second grayscale value and the contrast enhancement factor to obtain an optimized grayscale value; A flywheel ring gear enhanced image is obtained based on the optimized grayscale value.

3. The method for detecting a flywheel ring gear of an automobile as claimed in claim 1, characterized in that: The step of analyzing the enhanced image of the flywheel gear ring to obtain an optimized profile of the flywheel gear ring includes: Analyze the pixel points reflected by the flywheel gear ring enhanced image to obtain a plurality of first edge points and a plurality of second edge points; wherein the intensity gradient of the first edge point is greater than a first preset threshold, and the intensity gradient of the second edge point is less than the first preset threshold and greater than the second preset threshold; Analyze the distance between the first edge point and the nearest second edge point to obtain a plurality of third edge points; wherein the third edge points are some pixel points among the plurality of the second edge points; The plurality of first edge points are connected with the plurality of third edge points to obtain an optimized profile of the flywheel ring gear.

4. The method for detecting a flywheel ring gear of an automobile as claimed in claim 1, characterized in that: The step of analyzing the optimized profile of the flywheel gear ring and the first circular profile to obtain the tooth number data includes: Performing optimization processing according to the first circular contour to obtain a third circular contour; Performing differential processing on the optimized flywheel gear ring profile and the third circular profile to obtain a gear profile; wherein the gear profile is used to reflect the profile of the gear of the flywheel gear ring of the automobile; The gear profile is analyzed to obtain the data of the number of teeth.

5. The method for detecting a flywheel ring gear of an automobile as claimed in claim 4, characterized in that: The step of analyzing the gear profile to obtain the tooth number data includes: Analyze the gear profile to obtain area information, perimeter information and convex shape factor of each tooth; wherein the area information is used to reflect the size of the area surrounded by the tooth profile, the perimeter information is used to reflect the edge length of the tooth, and the convex shape factor is used to reflect the ratio of the area of ​​the tooth to the area of ​​its convex hull; Calculating an area mean of the area information of all teeth, a perimeter mean of the perimeter information of all teeth, and a convexity shape factor mean of the convexity shape factors of all teeth; Get the area screening coefficient interval, perimeter screening coefficient interval and convexity shape factor coefficient interval; The area screening coefficient interval is weighted to the area mean to obtain an area allowable range, the perimeter screening coefficient interval is weighted to the perimeter mean to obtain a perimeter allowable range, and the convexity shape factor coefficient interval is weighted to the convexity shape factor mean to obtain a convexity shape factor allowable range; The area information, the circumference information and the convex shape factor of each tooth are compared and screened based on the allowable range of area, the allowable range of circumference and the allowable range of convex shape factor to obtain tooth number data; wherein the area information, the circumference information and the convex shape factor of the tooth reflected in the tooth number data are all within the allowable range of area, the allowable range of circumference and the allowable range of convex shape factor.

6. The method for detecting a flywheel ring gear of an automobile as claimed in claim 1, characterized in that: The step of analyzing the optimized profile of the flywheel gear ring and the second circular profile to obtain tooth size data includes: Performing differential calculation based on the optimized profile of the flywheel gear ring and the second circular profile to obtain tooth thickness profile information; wherein the tooth thickness profile information is used to reflect the actual profile of each tooth of the automobile flywheel gear ring; The tooth size data is obtained by analyzing the second circular profile and the tooth thickness profile information.

7. The method for detecting a flywheel ring gear of an automobile as claimed in claim 6, characterized in that: The step of analyzing the second circular profile and the tooth thickness profile information to obtain tooth size data includes: Calculating the intersection information of the second circular contour and the contour reflected in the tooth thickness contour information; wherein the intersection information is used to reflect the coordinates of the intersection of the second circular contour and the tooth thickness contour information; According to the intersection information, the distance between the leftmost coordinate and the rightmost coordinate of each tooth thickness profile in the tooth thickness profile information is calculated in sequence to obtain the tooth thickness data of the tooth size data; The distance between the leftmost coordinate of one tooth thickness profile in the tooth thickness profile information and the leftmost coordinate of the adjacent tooth thickness profile is calculated in sequence according to the intersection information to obtain the pitch data of the tooth size data.

8. A vehicle flywheel ring gear detection device, characterized in that: include: An acquisition module, used for acquiring an image of a flywheel ring gear of an automobile; wherein the image of the flywheel ring gear of an automobile is a grayscale image used to indicate the appearance of the flywheel ring gear of the automobile; An enhancement module, used for processing the image of the automobile flywheel ring gear to obtain an enhanced image of the flywheel ring gear; A first analysis module is used to analyze the flywheel gear ring enhancement image to obtain an optimized profile of the flywheel gear ring; A second analysis module is used to analyze according to the optimized profile of the flywheel gear ring to obtain tooth number data and tooth size data; wherein the tooth number data is used to reflect the number of normal teeth of the automobile flywheel gear ring, and the tooth size data is used to reflect the tooth thickness of each tooth and the tooth pitch between two adjacent teeth; Wherein, the second analysis module is further used for: Analyze according to the optimized profile of the flywheel gear ring to obtain a first circular profile; wherein the first circular profile is used to reflect the profile of the maximum inscribed circle of the tooth reflected by the optimized profile of the flywheel gear ring; Analyze the optimized profile of the flywheel gear ring and the first circular profile to obtain data on the number of teeth; When the tooth number data is normal, an analysis is performed according to the optimized profile of the flywheel gear ring to obtain a second circular profile; wherein the second circular profile is used to reflect the profile of the pitch circle of the optimized profile of the flywheel gear ring; The tooth size data is obtained by analyzing the optimized profile of the flywheel gear ring and the second circular profile.

9. An automobile flywheel ring gear detection device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 7 when executing the computer program.

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