A tire bulge detection method, device, equipment and medium

Abstract

The application provides a tire bulge detection method, device, equipment and medium, relates to the technical field of image processing, and is used for improving the detection efficiency, detection accuracy and safety of the tire bulge. The method comprises the following steps: acquiring a first 3D image of a tire to be detected rotating one circle at a first speed in a first time period; determining point cloud data corresponding to the first 3D image; wherein the point cloud data corresponding to the first 3D image is used for indicating position information of each point cloud on the surface of the tire to be detected; comparing the point cloud data corresponding to the first 3D image with point cloud data corresponding to a reference image to determine whether the tire to be detected has a bulge in the first time period; wherein the reference image is a 3D image of a tire without a bulge.

Description

Technical Field

[0001] This application relates to the field of image processing technology, and in particular to a method, apparatus, equipment and medium for detecting tire bulges. Background Technology

[0002] As people's living standards improve, cars have become commonplace in households, and the quality of car tires is crucial to everyone's driving safety. Normally, to ensure tire safety, rubber tires undergo rigorous quality testing before leaving the factory. However, during testing, substandard tires may develop bulges, leading to blowouts and serious damage to testing equipment. Therefore, it is essential to detect tire bulges promptly and halt tire durability testing to prevent blowouts.

[0003] Currently, tire factories typically use metal probes to detect bulges when conducting tire durability tests; an alarm is triggered when a bulge comes into contact with the probe. However, this contact-based method of measuring tire bulges has low accuracy and is quite dangerous. Summary of the Invention

[0004] This application provides a tire bulge detection method, apparatus, equipment, and storage medium to improve the detection efficiency, accuracy, and safety of tire bulges.

[0005] In a first aspect, this application provides a method for detecting tire bulges, the method comprising:

[0006] Acquire a first 3D image of the tire to be inspected rotating one revolution at a first speed in the first time period;

[0007] Determine the point cloud data corresponding to the first 3D image; wherein, the point cloud data corresponding to the first 3D image is used to indicate the position information of each point cloud on the surface of the tire to be detected;

[0008] The point cloud data corresponding to the first 3D image is compared with the point cloud data corresponding to the reference image to determine whether the tire to be detected has a bulge in the first time period; wherein, the reference image is a 3D image of a tire without a bulge.

[0009] In this embodiment, a 3D image of the tire to be inspected is used to detect whether the tire has a bulge. This non-contact inspection method improves the efficiency and safety of tire bulge detection compared to the method of detecting bulges with metal probes. Furthermore, the 3D image can display the left tread, right tread, and underside of the tire from all angles, allowing for a more comprehensive detection of bulges on all sides of the tire, thereby improving the accuracy of tire bulge detection.

[0010] In one possible embodiment, the tire without bulge and the tire to be detected are the same tire; before comparing the point cloud data corresponding to the first 3D image with the point cloud data corresponding to the reference image to determine whether the tire to be detected has a bulge in the first time period, the method further includes:

[0011] Multiple second 3D images of the tire to be tested rotating multiple times at a second speed during a second time period are acquired; wherein the second time period is before the first time period, and the second speed is less than the first speed;

[0012] Based on the point cloud data corresponding to the multiple second 3D images, determine the height of each point cloud in the multiple second 3D images;

[0013] The average height of the corresponding point clouds in the multiple second 3D images is taken to obtain the reference image.

[0014] In this embodiment, the reference image is automatically determined by the height difference information of multiple consecutive second 3D images, which can be used for bulge detection of tires of different specifications, and has high practicality and convenience.

[0015] In one possible embodiment, comparing the point cloud data corresponding to the first 3D image with the point cloud data corresponding to the reference image to determine whether the tire to be detected has a bulge during the first time period includes:

[0016] The first 3D image is divided into multiple block images; the size of each block image is smaller than a preset size.

[0017] Randomly select a target point cloud from each block image to obtain multiple target point clouds from the multiple block images;

[0018] If the height difference between any target point cloud and the corresponding point cloud in the reference image is greater than the bulge height threshold, then it is determined that the tire to be detected has a bulge in the first time period.

[0019] In this embodiment of the application, the first 3D image is divided into multiple block images. Only one point cloud in each block image needs to be detected, which can improve the detection speed and thus improve the detection efficiency of tire bulges.

[0020] In one possible embodiment, if the height difference between the actual height of any target point cloud and the height of the corresponding point cloud in the reference image is greater than a bulge height threshold, then it is determined that the tire to be detected has a bulge in the first time period, including:

[0021] If the height difference between the actual height of any target point cloud and the height of the corresponding point cloud in the reference image is greater than the bulge height threshold, then any image block is marked as a suspected bulge image.

[0022] Determine whether the width of a continuous point cloud region in the suspected bulge image is greater than a preset bulge diameter; wherein, the continuous point cloud region refers to at least two point clouds in the suspected bulge image whose height difference is greater than a bulge height threshold and whose positions are adjacent;

[0023] If the width of the continuous point cloud region is greater than the preset bulge diameter, then it is determined that the tire to be detected has a bulge in the first time period.

[0024] In this embodiment, by combining the two dimensions of height and width, it is possible to more accurately determine whether there is a bulge in the tire to be tested, and to effectively locate the bulge in the tire to be tested, thereby further improving the detection accuracy of tire bulges.

[0025] In one possible embodiment, after determining whether the width of a continuous point cloud region in the suspected bulge image is greater than a preset bulge diameter, the method further includes:

[0026] If the width of the continuous point cloud region is less than or equal to the preset bump diameter, the first 3D image is marked as a normal image and saved in the database, and the number of normal images recorded in the database is updated.

[0027] The baseline image is updated and the number of recorded normal images is set to 0 once the number of recorded normal images exceeds a first preset number.

[0028] In this embodiment, the surface expansion of the tire due to temperature rise under heavy load and high-speed movement is fully considered, and the reference image is updated in a timely manner to realize dynamic detection of tire bulges, which can reduce the false detection rate of tire bulges.

[0029] In one possible embodiment, after determining that the tire to be tested has a bulge during the first time period, the method further includes:

[0030] The first 3D image is marked as a bulge image, and the number of bulge images recorded in the database is updated;

[0031] If the number of recorded bulge images exceeds a second preset number, an alarm message is displayed, indicating that the tire under test has a bulge.

[0032] In this embodiment, after determining that the tire to be inspected has a bulge, an alarm message is displayed, which can promptly remind the inspector to conduct the inspection and prevent the tire with the bulge from bursting and damaging the inspection equipment.

[0033] Secondly, this application provides a tire bulge detection device, the device comprising:

[0034] The acquisition module is used to acquire a first 3D image of the tire to be detected rotating one revolution at a first speed in the first time period;

[0035] The determining module is used to determine the point cloud data corresponding to the first 3D image; wherein, the point cloud data corresponding to the first 3D image is used to indicate the position information of each point cloud on the surface of the tire to be detected;

[0036] The determining module is used to compare the point cloud data corresponding to the first 3D image with the point cloud data corresponding to the reference image to determine whether the tire to be detected has a bulge in the first time period; wherein, the reference image is a 3D image of a tire without a bulge.

[0037] In one possible embodiment, the tire without bulges and the tire to be detected are the same tire; the acquisition module is further configured to:

[0038] Before comparing the point cloud data corresponding to the first 3D image with the point cloud data corresponding to the reference image to determine whether the tire to be tested has a bulge in the first time period, multiple second 3D images of the tire to be tested rotating multiple times at a second speed in the second time period are acquired; wherein, the second time period is before the first time period, and the second speed is less than the first speed;

[0039] Based on the point cloud data corresponding to the multiple second 3D images, determine the height of each point cloud in the multiple second 3D images;

[0040] The average height of the corresponding point clouds in the multiple second 3D images is taken to obtain the reference image.

[0041] In one possible embodiment, the determining module is specifically used for:

[0042] The first 3D image is divided into multiple block images; the size of each block image is smaller than a preset size.

[0043] Randomly select a target point cloud from each block image to obtain multiple target point clouds from the multiple block images;

[0044] If the height difference between any target point cloud and the corresponding point cloud in the reference image is greater than the bulge height threshold, then it is determined that the tire to be detected has a bulge in the first time period.

[0045] In one possible embodiment, the determining module is specifically used for:

[0046] If the height difference between the actual height of any target point cloud and the height of the corresponding point cloud in the reference image is greater than the bulge height threshold, then any image block is marked as a suspected bulge image.

[0047] Determine whether the width of a continuous point cloud region in the suspected bulge image is greater than a preset bulge diameter; wherein, the continuous point cloud region refers to at least two point clouds in the suspected bulge image whose height difference is greater than a bulge height threshold and whose positions are adjacent;

[0048] If the width of the continuous point cloud region is greater than the preset bulge diameter, then it is determined that the tire to be detected has a bulge in the first time period.

[0049] In one possible embodiment, the device further includes a processing module, the processing module being configured to:

[0050] After determining whether the width of the continuous point cloud region in the suspected bulge image is greater than the preset bulge diameter, if the width of the continuous point cloud region is less than or equal to the preset bulge diameter, the first 3D image is marked as a normal image and saved in the database, and the number of normal images recorded in the database is updated.

[0051] The baseline image is updated and the number of recorded normal images is set to 0 once the number of recorded normal images exceeds a first preset number.

[0052] In one possible embodiment, the processing module is further configured to:

[0053] After determining that the tire to be detected has a bulge in the first time period, the first 3D image is marked as a bulge image, and the number of bulge images recorded in the database is updated;

[0054] If the number of recorded bulge images exceeds a second preset number, an alarm message is displayed, indicating that the tire under test has a bulge.

[0055] Thirdly, this application provides an electronic device, comprising:

[0056] Memory, used to store program instructions;

[0057] A processor is configured to invoke program instructions stored in the memory and execute the method described in any one of the first aspects according to the obtained program instructions.

[0058] Fourthly, this application provides a computer-readable storage medium storing a computer program, the computer program including program instructions, which, when executed by a computer, cause the computer to perform the method described in any one of the first aspects. Attached Figure Description

[0059] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0060] Figure 1 This is a schematic diagram illustrating an application scenario of a tire bulge detection method provided in an embodiment of this application.

[0061] Figure 2 This is a schematic diagram of a tire bulge detection system provided in an embodiment of this application;

[0062] Figure 3 The flowchart of a tire bulge detection method provided in this application embodiment Figure 1 ;

[0063] Figure 4 A schematic diagram of a single-frame image of the tire to be detected provided in an embodiment of this application;

[0064] Figure 5 A schematic diagram of a first 3D image of the tire to be inspected provided in an embodiment of this application;

[0065] Figure 6 The flowchart of a tire bulge detection method provided in this application embodiment Figure 2 ;

[0066] Figure 7 A schematic diagram of the structure of the tire bulge detection device provided in the embodiments of this application;

[0067] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0068] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application. Unless otherwise specified, the embodiments and features in the embodiments of this application can be arbitrarily combined with each other. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than that shown here.

[0069] The terms "first" and "second" in the specification, claims, and accompanying drawings of this application are used to distinguish different objects and not to describe a specific order. Furthermore, the term "comprising" and any variations thereof are intended to cover non-exclusive protection. For example, a process, method, system, product, or apparatus that comprises a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such processes, methods, products, or apparatus.

[0070] In this embodiment of the application, "multiple" can mean at least two, such as two, three or more, and this embodiment of the application does not impose any restrictions.

[0071] To facilitate understanding of the tire bulge method provided in the embodiments of this application, the background technology of the embodiments of this application will be introduced first.

[0072] Tires are typically made of black rubber, and their surfaces usually have tread patterns and lettering. Different types of tires have different section widths and section heights. For example, tire section widths range from 165mm to 215mm, and tire section heights range from 90mm to 120mm. During tire durability testing, pressure is applied to the tire to simulate load, and the tire is rotated at a preset speed under load to simulate high-speed driving on a real road surface. After a period of durability testing, some tires may develop bulges due to product defects. If these bulges are not detected in time, they will grow larger and eventually lead to a tire blowout, damaging the testing equipment.

[0073] To improve the efficiency, accuracy, and safety of tire bulge detection, this application provides a tire bulge detection method. The following is a brief introduction to the application scenarios to which the technical solution of this application is applicable. It should be noted that the application scenarios described below are for illustrative purposes only and not for limitation. In specific implementation, the technical solution provided by this application can be flexibly applied according to actual needs.

[0074] like Figure 1 The diagram shown illustrates an application scenario of a tire bulge detection method provided in this embodiment. This application scenario may include a detection device 10 and a 3D image acquisition device 11.

[0075] The 3D image acquisition device 11 is a device capable of acquiring 3D images, such as a 3D high-precision line laser camera. The detection device 10 can be a server that provides data storage and computation for the tire bulge detection process. It can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms, but it is not limited to these.

[0076] The detection device 10 may include one or more processors 101, a memory 102, and an I / O interface 103 for interacting with other devices. Furthermore, the detection device 10 may be configured with a database 104, which can be used to store 3D images, point cloud data, etc., involved in the solutions provided in the embodiments of this application. The memory 102 of the detection device 10 may store program instructions for the tire bulge detection method provided in the embodiments of this application. When these program instructions are executed by the processor 101, they can implement the steps of the tire bulge detection method provided in the embodiments of this application.

[0077] In one possible implementation, when the detection device 10 detects the 3D image acquired by the 3D image acquisition device 11 through the I / O interface 103, the processor 101 of the detection device 10 will run the program instructions of the tire bulge detection method stored in the memory 102 to perform bulge detection on the tire to be detected in the 3D image, thereby determining whether the tire to be detected has a bulge. The 3D image, point cloud data, etc. used during the execution of the program instructions will be stored in the database 104.

[0078] It should be noted that, Figure 1 Taking the detection device 10 and the 3D image acquisition device 11 as two independent devices as an example, in reality, the detection device 10 can also be coupled with the 3D image acquisition device 11 as a single device.

[0079] This involves the installation method of the 3D image acquisition device 11. Taking the 3D image acquisition device 11 as a 3D high-precision line laser camera 201 as an example, in one possible implementation, such as... Figure 2 The diagram shown is a schematic of a tire bulge detection system provided in an embodiment of this application. The tire bulge detection system includes a 3D high-precision line laser camera 201, a rotating drum 202, a wheel hub 203, a drive motor 204, a pressure bearing 205, and a tire 206.

[0080] Tire 206 is mounted on corresponding hub 203, which is in turn mounted on pressure bearing 205. Rotating drum 202 simulates the road surface, and pressure bearing 205 applies pressure to keep tire 206 pressed against the drum 202, thus simulating tire load. Drive motor 204 drives tire 206 to rotate at high speed, simulating actual tire usage and effectively mimicking tire condition during high-speed vehicle movement. A 3D high-precision line laser camera is fixed directly above tire 206, allowing real-time acquisition of 3D images of the rotating tire 206.

[0081] Of course, the methods provided in the embodiments of this application are not limited to... Figure 1 The application scenarios shown can also be used in other possible scenarios, and this application embodiment does not impose any limitations. Figure 1 The functions that the various devices in the application scenarios shown can achieve will be described in subsequent method embodiments, and will not be elaborated on here. Below, the methods of the embodiments of this application will be described in conjunction with the accompanying drawings.

[0082] like Figure 3 The diagram shows the flow chart of a tire bulge detection method provided in an embodiment of this application. Figure 1 This method can be achieved through Figure 1 The detection device 10 in the middle is used to perform the operation, and the specific process of the method is as described in S301-S303.

[0083] S301. Obtain a first 3D image of the tire to be tested rotating one revolution at a first speed in the first time period.

[0084] When the tire to be inspected rotates at a first speed during the first time period, the 3D image acquisition device can acquire the first 3D image of the tire to be inspected and send it to the inspection device. Alternatively, the inspection device can also acquire the first 3D image of the tire to be inspected on its own, for example, the inspection device is coupled with the function of the 3D image acquisition device.

[0085] Considering that bulges generally occur when the tire is rotating at high speed, in one possible embodiment, the first speed is greater than a preset speed, for example, 120 km / h, to ensure that the tire under test is rotating at high speed.

[0086] Using 3D image acquisition equipment as Figure 2 Taking the 3D high-precision line laser camera 201 in the tire bulge detection system shown below as an example, further details are provided below. Figure 2 This section describes the process of acquiring 3D images.

[0087] Before the formal inspection, the inspection equipment is connected to the 3D high-precision line laser camera 201, and the tire to be inspected is mounted on the wheel hub 203. Under the pressure of the pressure bearing 205, the tire is pressed tightly against the rotating drum 202. The drive motor 204 is then turned on, causing the tire to begin rotating under load, and the rotating drum 202 rotates along with the tire. At this time, the 3D high-precision line laser camera 201 triggers the imaging, emitting a blue line laser to illuminate the surface of the tire, achieving a full-range scan and thus obtaining the first 3D image of the tire.

[0088] It should be noted that each single-frame image captured by the 3D high-precision line laser camera 201 contains only partial information about the tire under inspection. To obtain complete information about the tire, images can be continuously acquired while the tire is rotating until it completes one revolution, thus obtaining multiple frames for the first time period. After obtaining these multiple frames for the first time period, the inspection equipment combines them to obtain the first 3D image of the tire under inspection.

[0089] like Figure 4 The figure shown is a schematic diagram of a single frame image of a tire to be tested provided in an embodiment of this application. The curves in the figure represent a partial outline of the surface of the tire to be tested.

[0090] S302. Determine the point cloud data corresponding to the first 3D image.

[0091] When the 3D high-precision line laser camera 201 emits laser lines towards the tire to be inspected, it emits multiple laser lines simultaneously. The laser points formed by each laser line on the tire can be called point clouds. The point cloud data corresponding to the first 3D image is used to indicate the positional information of each point cloud on the surface of the tire. For example, if a coordinate system is established in the first 3D image, with the width of the tire as the X-axis, the circumference as the Y-axis, and the tread pattern and thickness direction as the Z-axis, then the positional information of each point cloud is (x, y, z).

[0092] like Figure 5 The image shown is a schematic diagram of a first 3D image of the tire to be inspected provided in an embodiment of this application. The black portion represents the tire tread pattern, the tire width is the X-axis, the tire circumference is the Y-axis, and the tread pattern and tire thickness direction is the Z-axis.

[0093] S303. Compare the point cloud data corresponding to the first 3D image with the point cloud data corresponding to the reference image to determine whether the tire to be detected has a bulge in the first time period.

[0094] The reference image is a 3D image of a tire without a bulge. There are various types of tires without bulges, and the methods for obtaining the reference image differ accordingly, which will be described below.

[0095] In the first scenario, the tire without a bulge and the tire to be tested are two tires of the same type, meaning the tire without a bulge is another tire of the same type as the tire to be tested.

[0096] The testing equipment has a database containing 3D images of various types of normal tires. The testing equipment can obtain 3D images of other tires of the same type as the tire to be tested from the database as reference images.

[0097] The second scenario is that the tire without bulges is the same tire as the tire to be inspected.

[0098] Method 1: The testing equipment can acquire a second 3D image of the tire to be tested rotating one revolution at a second speed in a second time period, and use this second 3D image as a reference image.

[0099] The second time period is before the first time period, that is, before the tire to be tested develops a bulge. Considering that tires generally do not develop bulges when rotating at low speeds, the second speed is less than the first speed.

[0100] Method 2: The testing equipment can acquire multiple second 3D images of the tire to be tested rotating multiple times at a second speed in a second time period. Based on the point cloud data corresponding to the multiple second 3D images, the height of each point cloud in the multiple second 3D images is determined. The average height of the corresponding point clouds in the multiple second 3D images is taken to obtain a reference image.

[0101] The relationship between the second time period and the first time period, and the relationship between the second speed and the first speed, are discussed in the previous text and will not be repeated here.

[0102] For example, the tire to be tested is rotated at a constant speed for K revolutions to obtain K second 3D images. The average of each point in the K second 3D images is calculated in the Z direction:

[0103]

[0104] Where k represents the number of second 3D images, and (x, y) represents the plane position of point.

[0105] Considering that tire bulges are generally large in area, and that the Z-direction values ​​of the entire bulge area are abnormal when a bulge is detected, in order to improve the detection speed, in one possible embodiment, the detection device can perform block detection on the first 3D image, as described in S1.1-S1.3.

[0106] S1.1 Divide the first 3D image into multiple block images.

[0107] For example, the detection device can divide the first 3D image into N block images, where N can be a positive integer greater than 1. Each block image can have the same size, for example, all M*M. Alternatively, each block image can have a different size, but to ensure that the size of each block image is much smaller than the bulge diameter, the size of each block image is smaller than a preset size. The bulge diameter is determined based on historical bulge data, which includes the diameters of multiple bulges.

[0108] S1.2. Randomly select one target point cloud from each block image to obtain multiple target point clouds from multiple block images.

[0109] S1.3 If the height difference between the height of any target point cloud and the height of the corresponding point cloud in the reference image is greater than the bulge height threshold, then it is determined that the tire to be detected has a bulge in the first time period.

[0110] For example:

[0111]

[0112] in, Used to represent the height of the target point cloud. Used to indicate the height of the corresponding point cloud within the reference image, NG indicates that the image block is a suspected bulge image, and OK indicates that the image block is a normal image.

[0113] In practical applications, since the height of the tread pattern and text on a normal tire is usually less than 1mm, while the height of a bulge is greater than 2mm, the bulge height threshold can be set to 1mm to ensure that the tire tread pattern and text do not affect the detection of bulges.

[0114] It should be noted that S1.3 is not necessarily executed. If the height difference between the height of any target point cloud and the height of the corresponding point cloud in the reference image is less than or equal to the bulge height threshold, then it is determined that the tire to be detected does not have a bulge in the first time period.

[0115] Since the possibility of detection errors in a target point cloud due to unforeseen circumstances cannot be ruled out, in one possible embodiment, the detection device can, after determining that the height difference between the actual height of any target point cloud and the height of the corresponding point cloud in the reference image is greater than the bulge height threshold, further determine whether the tire to be detected has a bulge in the first time period based on the bulge width, as described in S2.1-S2.3.

[0116] S2.1 If the height difference between the actual height of any target point cloud and the height of the corresponding point cloud in the reference image is greater than the bulge height threshold, then any image will be marked as a suspected bulge image.

[0117] After the detection equipment judges each target point cloud, it can obtain at least one suspected bulge image.

[0118] S2.2 Determine whether the width of the continuous point cloud region in the suspected bulge image is greater than the preset bulge diameter.

[0119] In this context, a continuous point cloud region refers to at least two adjacent point clouds in a suspected bulge image whose height difference exceeds a bulge height threshold. If the X or Y values ​​of two point clouds differ by 1, they are considered adjacent. The width of the continuous point cloud region can be determined based on the X values ​​of each point cloud within that region. For example, point clouds with the same Y value are grouped together to obtain multiple point cloud groups. The sum of the X values ​​of each point cloud in each group is calculated, resulting in multiple sums of X values. The maximum value among these sums is taken as the width of the continuous point cloud region.

[0120] S2.3 If the width of the continuous point cloud region is greater than the preset bulge diameter, then it is determined that the tire to be detected has a bulge in the first time period.

[0121] For example, the detection device responds to user input by setting the user's input value to a preset bulge diameter. Or, for example, the detection device's database stores historical bulge data, which includes the diameters of multiple bulges, and sets the smallest diameter as the preset bulge diameter.

[0122] It should be noted that S2.3 is not necessarily executed. If the width of the continuous point cloud region is less than or equal to the preset bulge diameter, it is determined that the tire under test does not have a bulge in the first time period.

[0123] As the tire rotates at high speed for an extended period, it expands due to increased temperature. If the original reference image is used as the baseline continuously, false detections are likely to occur. Therefore, in one possible embodiment, the detection device can replace the reference image after a certain period of time to further improve detection accuracy.

[0124] Specifically, after determining whether the width of the continuous point cloud region in the suspected bulge image is greater than a preset bulge diameter, if the width of the continuous point cloud region is less than or equal to the preset bulge diameter, the first 3D image is marked as a normal image and saved in the database. The number of normal images recorded in the database is updated; for example, the number of normal images is incremented by 1 for each new normal image. This process continues until the number of recorded normal images exceeds a first preset number. At this point, the baseline image is updated, and the number of recorded normal images is set to 0.

[0125] Since the database stores normal images of the tire to be detected prior to the first time period, multiple normal images from consecutive time periods are selected. The average height of the corresponding point clouds in these normal images is then calculated to obtain a new reference image, which replaces the original reference image. The method for averaging the point cloud heights is explained in the preceding text and will not be repeated here.

[0126] In one possible embodiment, after determining that a bulge exists in the tire under test during a first time period, the first 3D image is marked as a bulge image, and the number of bulge images recorded in the database is updated, for example, by incrementing the number of bulge images by 1. If the number of recorded bulge images exceeds a second preset number, an alarm message is displayed. The alarm message indicates that a bulge exists in the tire under test, and may include the number of bulge images, the height and width of each bulge image, and may be either voice or text; this embodiment does not impose specific limitations. The user can freely set the second preset number, which is typically 1.

[0127] After seeing the alarm message, the inspector can manually disconnect. Figure 2 The power supply of the bulge detection system shown is used to stop the tire under test from rotating, thus preventing the tire from bursting after a bulge.

[0128] Considering that inspectors may not see the alarm information in time, in one possible embodiment, the inspection device can also send a notification to the relevant authorities after displaying the alarm information. Figure 2 The bulge detection system shown sends a stop command, which instructs the bulge detection system to stop working.

[0129] Please refer to Figure 6 The following is a flowchart of a tire bulge detection method provided in this application embodiment. Figure 2 The following is combined with Figure 6 This paper introduces the overall process of the tire bulge detection method provided in the embodiments of this application.

[0130] S601. Obtain the first 3D image of the tire to be inspected.

[0131] For instructions on how to obtain the content of the first 3D image, please refer to the previous discussion; it will not be repeated here.

[0132] S602. Select the reference image.

[0133] Please refer to the previous discussion on how to select the reference image; it will not be repeated here.

[0134] S603. Determine whether there is a bulge in the tire to be detected in the first 3D image.

[0135] For instructions on determining whether a tire to be inspected has a bulge, please refer to the previous discussion; it will not be repeated here. If no bulge is found, proceed to step S604. If a bulge is found, proceed to step S607.

[0136] S604, Increase the number of normal images by 1.

[0137] The detection device marks the first 3D image as a normal image and saves it in the database, updating the number of normal images recorded in the database.

[0138] S605. Determine whether the number of normal images is greater than the first preset number.

[0139] If the number of normal images is greater than the first preset number, then execute S606. If the number of normal images is less than or equal to the first preset number, then continue executing S601.

[0140] S606. Update the baseline image and set the number of recorded normal images to 0.

[0141] S607, Increase the number of bulge images by 1.

[0142] The detection device marks the first 3D image as a bulge image and updates the number of bulge images recorded in the database.

[0143] S608. Determine whether the number of bulge images is greater than the second preset number.

[0144] If the number of bulge images is greater than the second preset number, then execute S609. If the number of bulge images is less than or equal to the second preset number, then continue executing S601.

[0145] S609, Output alarm information and exit the tire bulge detection system.

[0146] The meaning of the alarm information and how to exit the tire bulge detection system are explained in the previous text and will not be repeated here.

[0147] In summary, the tire bulge detection method provided in this application achieves high efficiency, high accuracy, and automation in tire bulge detection through 3D images. The automated selection of reference images broadens the application scope of the detection method, updating the reference images makes the detection method more realistic, the region-divided detection method improves detection efficiency, and the use of width and height as two intuitive factors to determine the bulge improves detection accuracy.

[0148] like Figure 7 As shown, based on the same inventive concept, this application provides a tire bulge detection device, which is disposed in the detection equipment described above. The device 70 includes:

[0149] The acquisition module 701 is used to acquire a first 3D image of the tire to be detected rotating one revolution at a first speed in the first time period.

[0150] The determining module 702 is used to determine the point cloud data corresponding to the first 3D image; wherein, the point cloud data corresponding to the first 3D image is used to indicate the position information of each point cloud on the surface of the tire to be detected;

[0151] The determination module 702 is used to compare the point cloud data corresponding to the first 3D image with the point cloud data corresponding to the reference image to determine whether the tire to be detected has a bulge in the first time period; wherein, the reference image is a 3D image of a tire without a bulge.

[0152] In one possible embodiment, the tire without a bulge and the tire to be detected are the same tire; the acquisition module 701 is further configured to:

[0153] Before comparing the point cloud data corresponding to the first 3D image with the point cloud data corresponding to the reference image to determine whether there is a bulge in the tire to be detected in the first time period, multiple second 3D images of the tire to be detected rotating multiple times at a second speed in the second time period are acquired; wherein, the second time period is before the first time period, and the second speed is less than the first speed.

[0154] Based on the point cloud data corresponding to multiple second 3D images, determine the height of each point cloud in the multiple second 3D images;

[0155] The average height of the corresponding point cloud in multiple second 3D images is taken to obtain the baseline image.

[0156] In one possible embodiment, the determining module 702 is specifically used for:

[0157] The first 3D image is divided into multiple block images; the size of each block image is smaller than a preset size.

[0158] Randomly select one target point cloud from each block image to obtain multiple target point clouds from multiple block images;

[0159] If the height difference between any target point cloud and the corresponding point cloud in the reference image is greater than the bulge height threshold, then the tire to be detected is determined to have a bulge in the first time period.

[0160] In one possible embodiment, the determining module 702 is specifically used for:

[0161] If the height difference between the actual height of any target point cloud and the height of the corresponding point cloud in the reference image is greater than the bulge height threshold, then any image will be marked as a suspected bulge image.

[0162] Determine whether the width of a continuous point cloud region in a suspected bulge image is greater than a preset bulge diameter; wherein, a continuous point cloud region refers to at least two point clouds in the suspected bulge image whose height difference is greater than a bulge height threshold and whose positions are adjacent;

[0163] If the width of the continuous point cloud region is greater than the preset bulge diameter, it is determined that the tire under test has a bulge in the first time period.

[0164] In one possible embodiment, the device further includes a processing module 703, which is used for:

[0165] After determining whether the width of the continuous point cloud region in the suspected bulge image is greater than the preset bulge diameter, if the width of the continuous point cloud region is less than or equal to the preset bulge diameter, the first 3D image is marked as a normal image and saved in the database, and the number of normal images recorded in the database is updated.

[0166] Once the number of recorded normal images exceeds a first preset number, the baseline image is updated, and the number of recorded normal images is set to 0.

[0167] In one possible embodiment, the processing module 703 is further configured to:

[0168] After determining that the tire under test has a bulge in the first time period, the first 3D image is marked as a bulge image, and the number of bulge images recorded in the database is updated.

[0169] If the number of recorded bulge images exceeds the second preset number, an alarm message will be displayed, indicating that a bulge exists in the tire being inspected.

[0170] It should be noted that although several modules or sub-modules of the device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of the present invention, the features and functions of two or more modules described above can be embodied in a single unit. Conversely, the features and functions of a module described above can be further divided and embodied by multiple modules.

[0171] It should be noted that, Figure 7 The device can also be used to implement any of the tire bulge detection methods discussed above, which will not be elaborated here.

[0172] Based on the same inventive concept, this application also provides an electronic device, which is equivalent to the detection device discussed above. Please refer to... Figure 8 The device includes a processor 801 and a memory 802.

[0173] Memory 802 is used to store program instructions;

[0174] Processor 801 is used to call program instructions stored in memory 802 and execute them according to the obtained program instructions. Figure 3 The processor 801 can also implement any of the tire bulge detection methods. Figure 7 The functions of each module in the device shown.

[0175] This application embodiment does not limit the specific connection medium between the processor 801 and the memory 802. Figure 8 The example shown is the connection between processor 801 and memory 802 via bus 800. Bus 800 is... Figure 8 The connections between other components are indicated by thick lines and are for illustrative purposes only, not as limiting information. The 800 bus can be divided into address bus, data bus, control bus, etc., for ease of representation. Figure 8 The term is represented by a single thick line, but this does not imply that there is only one bus or one type of bus. Alternatively, the processor 801 can also be called a controller; there is no restriction on the name.

[0176] The processor 801 is the control center of the device. It can connect to various parts of the control device through various interfaces and lines. By running or executing instructions stored in memory 802 and calling data stored in memory 802, the processor can perform various functions and process data, thereby monitoring the device as a whole.

[0177] In one possible design, processor 801 may include one or more processing units. Processor 801 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the modem processor may also not be integrated into processor 801. In some embodiments, processor 801 and memory 802 may be implemented on the same chip; in some embodiments, they may also be implemented on separate chips.

[0178] The processor 801 can be a general-purpose processor, such as a central processing unit (CPU), digital signal processor, application-specific integrated circuit, field-programmable gate array or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the tire bulge detection method disclosed in the embodiments of this application can be directly manifested as being executed by a hardware processor, or executed by a combination of hardware and software modules within the processor.

[0179] Memory 802, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. Memory 802 may include at least one type of storage medium, such as flash memory, hard disk, multimedia card, card-type memory, random access memory (RAM), static random access memory (SRAM), programmable read-only memory (PROM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), magnetic storage, magnetic disk, optical disk, etc. Memory 802 can be any other medium capable of carrying or storing desired program code in the form of instructions or data structures that can be accessed by a computer, but is not limited thereto. In the embodiments of this application, memory 802 can also be a circuit or any other device capable of implementing storage functions for storing program instructions and / or data.

[0180] By designing and programming the processor 801, the code corresponding to the tire bulge detection method described in the foregoing embodiments can be embedded into the chip, enabling the chip to execute the code during operation. Figure 3 The steps of the tire bulge detection method are shown. How to design and program the processor 801 is a technique well-known to those skilled in the art and will not be elaborated upon here.

[0181] Based on the same inventive concept, embodiments of this application provide a computer-readable storage medium storing a computer program. The computer program includes program instructions, which, when executed by a computer, cause the computer to perform the tire bulge detection method described above. Since the principles and methods of solving the problem described above are similar, the implementation of the computer-readable storage medium can be found in the implementation of the method; repeated details will not be elaborated further.

[0182] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks. Alternatively, if the integrated units of the present invention are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiments of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

[0183] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0184] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for detecting tire bulges, characterized in that, The method includes: During the rotation of the tire under test, at least one second 3D image of the tire under test rotating at least one revolution at a second speed in a second time period is acquired, and a first 3D image of the tire under test rotating one revolution at a first speed in a first time period is acquired; wherein, the second time period is before the first time period, and the second speed is less than the first speed; Determine the point cloud data corresponding to the first 3D image; wherein, the point cloud data corresponding to the first 3D image is used to indicate the position information of each point cloud on the surface of the tire to be detected; A reference image is determined based on the at least one second 3D image. The point cloud data corresponding to the first 3D image is compared with the point cloud data corresponding to the reference image to determine whether the tire to be detected has a bulge in the first time period. The reference image is a 3D image of a tire without a bulge.

2. The method as described in claim 1, characterized in that, When the at least one second 3D image is multiple second 3D images, determining a reference image based on the at least one second 3D image includes: Based on the point cloud data corresponding to the multiple second 3D images, determine the height of each point cloud in the multiple second 3D images; The average height of the corresponding point clouds in the multiple second 3D images is taken to obtain the reference image.

3. The method as described in claim 1, characterized in that, The point cloud data corresponding to the first 3D image is compared with the point cloud data corresponding to the reference image to determine whether the tire to be detected has a bulge during the first time period, including: The first 3D image is divided into multiple block images; the size of each block image is smaller than a preset size. Randomly select one target point cloud from each block image to obtain multiple target point clouds from the multiple block images; If the height difference between the actual height of any target point cloud and the height of the corresponding point cloud in the reference image is greater than the bulge height threshold, then it is determined that the tire to be detected has a bulge in the first time period.

4. The method as described in claim 3, characterized in that, If the height difference between the actual height of any target point cloud and the height of the corresponding point cloud in the reference image is greater than the bulge height threshold, then it is determined that the tire to be detected has a bulge in the first time period, including: If the height difference between the actual height of any target point cloud and the height of the corresponding point cloud in the reference image is greater than the bulge height threshold, the corresponding block image is marked as a suspected bulge image. Determine whether the width of a continuous point cloud region in the suspected bulge image is greater than a preset bulge diameter; wherein, the continuous point cloud region refers to at least two point clouds in the suspected bulge image whose height difference is greater than a bulge height threshold and whose positions are adjacent; If the width of the continuous point cloud region is greater than the preset bulge diameter, then it is determined that the tire to be detected has a bulge in the first time period.

5. The method as described in claim 4, characterized in that, After determining whether the width of the continuous point cloud region in the suspected bulge image is greater than a preset bulge diameter, the method further includes: If the width of the continuous point cloud region is less than or equal to the preset bump diameter, the first 3D image is marked as a normal image and saved in the database, and the number of normal images recorded in the database is updated. The baseline image is updated and the number of recorded normal images is set to 0 once the number of recorded normal images exceeds a first preset number.

6. The method according to any one of claims 3-5, characterized in that, After determining that the tire under test has a bulge in the first time period, the method further includes: The first 3D image is marked as a bulge image, and the number of bulge images recorded in the database is updated; If the number of recorded bulge images exceeds a second preset number, an alarm message is displayed, indicating that the tire under test has a bulge.

7. A tire bulge detection device, characterized in that, The device includes: The acquisition module is configured to acquire at least one second 3D image of the tire under test rotating at least one revolution at a second speed in a second time period during the rotation of the tire under test, and to acquire a first 3D image of the tire under test rotating one revolution at a first speed in the first time period; and to determine a reference image based on the at least one second 3D image; wherein the second time period is before the first time period, and the second speed is less than the first speed; The determining module is used to determine the point cloud data corresponding to the first 3D image; wherein, the point cloud data corresponding to the first 3D image is used to indicate the position information of each point cloud on the surface of the tire to be detected; The determining module is used to compare the point cloud data corresponding to the first 3D image with the point cloud data corresponding to the reference image to determine whether the tire to be detected has a bulge in the first time period; wherein, the reference image is a 3D image of a tire without a bulge.

8. The apparatus as claimed in claim 7, characterized in that, When the at least one second 3D image is multiple second 3D images, the acquisition module is further configured to: Based on the point cloud data corresponding to the multiple second 3D images, determine the height of each point cloud in the multiple second 3D images; The average height of the corresponding point clouds in the multiple second 3D images is taken to obtain the reference image.

9. An electronic device, characterized in that, include: Memory, used to store program instructions; A processor is configured to invoke program instructions stored in the memory and execute the method of any one of claims 1-6 according to the obtained program instructions.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, the computer program including program instructions that, when executed by a computer, cause the computer to perform the method as described in any one of claims 1-6.

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