Tire detection method, device and equipment and computer readable storage medium

Abstract

The invention relates to the technical field of tire detection, and discloses a tire detection method, device and equipment and a computer readable storage medium, and the method comprises the steps: controlling a laser detector to vertically emit laser to the surface of a target tire after a vehicle is powered on, and receiving a laser feedback signal generated when the laser irradiates the target tire; based on the laser feedback signal, determining a three-dimensional space coordinate of each pixel point on the surface of the target tire, and generating a real-time feedback image of the target tire according to the three-dimensional space coordinate of each pixel point on the surface of the target tire; and comparing the real-time feedback image with a standard factory image of the target tire to generate an anomaly detection result of the target tire. By means of the technical scheme, accurate detection of the tire condition can be achieved, the limitation of a human eye observation mode is solved, the tire state can be detected in real time, potential safety hazards can be found in time, the driving safety is effectively improved, and the life and property safety of a driver and passengers is guaranteed.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of tire detection, in particular to a tire detection method, device, equipment and computer readable storage medium. BACKGROUND

[0002] In the process of using a vehicle, the state of a tire has a crucial influence on driving safety. In the prior art, the state of a tire is usually roughly estimated by means of human eyes. However, this approach has many limitations. The resolution capability of human eyes is limited, and real-time detection of the state of a tire cannot be achieved by human eyes. This makes a tire, when there is a potential safety hazard, unable to be discovered and handled in time, thereby easily leading to the occurrence of a safety accident and threatening the life and property safety of a driver and passengers. SUMMARY

[0003] In view of the above problems, the present application provides a tire detection method, device, equipment and computer readable storage medium, which are used to solve the problem that real-time and accurate tire detection cannot be performed in the prior art.

[0004] According to an aspect of an embodiment of the present application, a tire detection method is provided, and the method comprises the following steps: When a vehicle is powered on, a laser detector is controlled to vertically emit laser light to a surface of a target tire, and a laser feedback signal generated by the laser light irradiated to the target tire is received; wherein the laser detector is arranged on an inner side of an arch cover directly above a surface centerline of the target tire; Based on the laser feedback signal, three-dimensional space coordinates of each pixel point on the surface of the target tire are determined, and a real-time feedback image of the target tire is generated according to the three-dimensional space coordinates of each pixel point on the surface of the target tire; Based on comparison between the real-time feedback image and a standard factory image of the target tire, an abnormality detection result of the target tire is generated.

[0005] In an optional manner, the laser detector comprises a laser emitter and a laser receiver; and the step of determining the three-dimensional space coordinates of each pixel point on the surface of the target tire based on the laser feedback signal further comprises the following steps: According to a time difference between an emission time and a receiving time of each pixel point on the surface of the target tire in the laser feedback signal, real-time distance values of the laser emitter to each pixel point are calculated; wherein the laser feedback signal is received by the laser receiver; According to the real-time distance values of the laser emitter to each pixel point, a horizontal offset of each pixel point is determined; A three-dimensional coordinate system is established with the position of the laser emitter as the coordinate origin, and a three-dimensional space coordinate of each pixel point is generated based on the real-time distance value and the horizontal offset of each pixel point.

[0006] In an alternative manner, the step of generating the real-time feedback image of the target tire based on the three-dimensional space coordinates of each pixel point on the surface of the target tire further comprises: A two-dimensional plane coordinate system is established based on the surface of the target tire, and a two-dimensional position coordinate of each pixel point is generated by projecting the three-dimensional space coordinate of each pixel point onto the two-dimensional plane coordinate system. The height value in the three-dimensional space coordinate of each pixel point is fused with the two-dimensional position coordinate to generate the real-time feedback image containing depth information.

[0007] In an alternative manner, the step of generating the abnormal detection result of the target tire by comparing the real-time feedback image with the standard factory image of the target tire further comprises: The pixel depth values of the real-time feedback image and the standard factory image of the target tire are compared to obtain the depth difference value of each pixel point. Based on the distribution characteristics and value size of the depth difference value of the pixel point, it is determined whether the target tire is abnormal. If there is an abnormality, the abnormal detection result containing the abnormal type and the abnormal position is generated.

[0008] In an alternative manner, the step of determining whether the target tire is abnormal based on the distribution characteristics and value size of the depth difference value of the pixel point further comprises: When a first pixel point cluster with a depth value continuously higher than the average value of the neighborhood is identified in the real-time feedback image, the first pixel point cluster is marked as a tread pattern area; and / or, when a second pixel point cluster with a depth value continuously lower than the average value of the neighborhood is identified in the real-time feedback image, the second pixel point cluster is marked as a tread groove area. If the cumulative amount of the depth difference value of the pixel points in the tread pattern area and / or the tread groove area exceeds a first threshold value, it is determined that the target tire is abnormal. The pixel points with depth difference values in the tread pattern area and / or the tread groove area are marked as the abnormal position, and the abnormal type is determined as wear abnormality.

[0009] In an alternative manner, the step of determining whether the target tire is abnormal based on the distribution characteristics and value size of the depth difference value of the pixel point further comprises: When a target connected domain composed of a continuous preset number of pixels exists in the real-time feedback image, the target connected domain is marked as a tire tread crack region; If the depth difference of each pixel in the tire tread crack region exceeds a second threshold value, it is determined that the target tire has an abnormality; The tire tread crack region is marked as the abnormal position, and the abnormal type is determined as a crack abnormality.

[0010] In an optional manner, the step of determining whether the target tire has an abnormality based on the distribution characteristics and value size of the depth difference of the pixels further includes: When a third pixel cluster with an absolute value of the depth difference greater than or equal to a third threshold value and a consistent sign of the depth difference is identified in the real-time feedback image, the third pixel cluster is marked as a tire tread deformation region, and it is determined that the target tire has an abnormality; The tire tread deformation region is marked as the abnormal position, and the abnormal type is determined as a bulge abnormality or a depression abnormality according to the sign of the depth difference of the tire tread deformation region.

[0011] In an optional manner, the step of determining whether the target tire has an abnormality based on the distribution characteristics and value size of the depth difference of the pixels further includes: When a closed ring pixel cluster with a depth difference less than or equal to a fourth threshold value is identified in the real-time feedback image, and a convex pixel with a depth difference greater than or equal to a fifth threshold value exists in the center of the closed ring pixel cluster, the closed ring pixel cluster is marked as a tire tread groove region, and it is determined that the target tire has an abnormality; The tire tread groove region is marked as the abnormal position, and the abnormal type is determined as a groove abnormality.

[0012] In an optional manner, a washing nozzle is arranged on the laser emitter, and a micro-pump connected to a washing kettle is arranged in the washing nozzle; the method further includes: When a laser blocking signal representing an abnormality of the laser emitter is received, the micro-pump is controlled to drive the washing nozzle to clean the surface of the laser emitter.

[0013] According to another aspect of the embodiments of the present application, a tire detection device is provided, including: An acquisition module is configured to control a laser detector to vertically emit laser light to the surface of a target tire after the vehicle is powered on, and receive a laser feedback signal generated by the laser light irradiated to the target tire; wherein the laser detector is arranged on the inner side of the wheel arch directly above the surface centerline of the target tire; generating module, based on the laser feedback signal, determining the three-dimensional space coordinates of each pixel point on the target tire surface, and generating a real-time feedback image of the target tire according to the three-dimensional space coordinates of each pixel point on the target tire surface; The detection module compares the real-time feedback image with a standard factory image of the target tire to generate an abnormality detection result of the target tire.

[0014] According to another aspect of the embodiments of the present application, a tire detection device is provided, comprising: a controller; a memory for storing one or more programs, which, when executed by the controller, cause the controller to implement the tire detection method of the present application.

[0015] According to still another aspect of the embodiments of the present application, a computer-readable storage medium is provided, which stores at least one executable instruction, which, when executed on a tire detection device, causes the tire detection device to perform the operations of the tire detection method of the present application.

[0016] The embodiments of the present application can achieve accurate detection of the tire condition by controlling the laser detector to vertically emit laser light to the target tire surface after the vehicle is powered on, receiving the laser feedback signal generated by the laser light irradiated to the target tire, determining the three-dimensional space coordinates of each pixel point on the target tire surface based on the laser feedback signal, generating a real-time feedback image of the target tire according to the three-dimensional space coordinates of each pixel point on the target tire surface, comparing the real-time feedback image with a standard factory image of the target tire to generate an abnormality detection result of the target tire, solving the limitations of the human eye observation method, and achieving real-time detection of the tire state, timely discovery of potential safety hazards, effective improvement of driving safety, and protection of the life and property safety of the driver and passengers.

[0017] The above description is only a summary of the technical solutions of the embodiments of the present application, in order to more clearly understand the technical means of the embodiments of the present application, which can be implemented according to the content of the specification, and in order to make the above and other purposes, features and advantages of the embodiments of the present application more obvious and easy to understand, the following specific embodiments of the present application are described. BRIEF DESCRIPTION OF DRAWINGS

[0018] The accompanying drawings are only used to illustrate the embodiments, and are not considered as limiting the present application. Moreover, the same reference signs are used to represent the same components throughout the drawings.

[0019] Figure 1 The flowchart of the embodiments of the tire detection method provided by the present application is shown.

[0020] Figure 2 A structural schematic diagram of an embodiment of a tire detection device provided by the present application is shown.

[0021] Figure 3 A structural schematic diagram of an embodiment of a tire detection device provided by the present application is shown. DETAILED DESCRIPTION

[0022] The exemplary embodiments will be described in detail herein with reference to the attached drawings. In the following description, the same numbers are used to designate the same elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not meant to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the present application as detailed in the appended claims.

[0023] The block diagrams shown in the drawings are merely functional entities, and do not necessarily have to correspond to physically independent entities. That is, the functional entities can be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0024] The flowcharts shown in the drawings are merely exemplary illustrations, and do not necessarily include all contents and operations / steps, nor do they have to be executed in the order described. For example, some operations / steps can be further divided, and some operations / steps can be combined or partially combined, so the actual execution order can be changed according to actual conditions.

[0025] In the present application, "a plurality of" means two or more. The "and / or" describes the association between the associated objects, which means that there can be three relationships, for example, A and / or B can mean that A exists alone, A and B exist together, and B exists alone. The character " / " generally means that the associated objects before and after are in an "or" relationship.

[0026] The purpose is that in the process of using a car, the state of the tire has a crucial influence on driving safety. In the prior art, the state of the tire is usually roughly estimated by the human eye, but this method has many limitations. The resolving power of the human eye is limited, and real-time detection of the state of the tire cannot be achieved by human eye observation. This makes the tire not be discovered and handled in time when there is a potential safety hazard, thereby easily leading to the occurrence of safety accidents, and threatening the life and property safety of the driver and passengers. Based on this: Figure 1 A flowchart of a first embodiment of a tire detection method provided by the present application is shown, which is executed by a vehicle controller. Please refer to Figure 1 The method comprises the following steps: Step S110: When the vehicle is powered on, the laser detector is controlled to vertically emit laser light to the surface of the target tire, and receive the laser feedback signal generated by the laser light irradiating the target tire.

[0027] In this embodiment, the vehicle can be an electric vehicle or a range extender vehicle, which is not limited herein. The laser detector is arranged on the inner side of the wheel arch directly above the surface centerline of the target tire, for vertically emitting laser light to the surface of the target tire and receiving the laser feedback signal. The target tire refers to the tire of the vehicle scanned by the laser detector, including the tread pattern, tread groove and sidewall area. The laser feedback signal refers to the light signal reflected or scattered after the laser light irradiates the surface of the target tire, which is captured by the laser receiver and carries the tire surface topography information.

[0028] Specifically, when the vehicle is powered on, the vehicle controller sends a laser detection signal to the laser detector, controls the laser detector to vertically emit laser light to the surface of the target tire, and receives the laser feedback signal generated by the laser light irradiating the surface of the target tire through the laser detector.

[0029] It should be noted that the number of target tires in this embodiment is at least one. When the number of target tires is greater than one, a laser detector is arranged on the inner side of the wheel arch directly above the surface centerline of each target tire, and each laser detector has the same working principle and independently performs tire detection. For the sake of convenience, this embodiment takes one as an example for description, which does not mean that multiple target tires cannot be detected at the same time.

[0030] Step S120: Based on the laser feedback signal, the three-dimensional space coordinates of each pixel point on the surface of the target tire are determined, and based on the three-dimensional space coordinates of each pixel point on the surface of the target tire, a real-time feedback image of the target tire is generated.

[0031] In this embodiment, the pixel point on the surface of the target tire refers to the smallest detection unit of the tire surface divided by laser scanning, and each pixel point corresponds to a unique three-dimensional space coordinate. The real-time feedback image refers to a tire surface development image containing depth information generated based on the three-dimensional space coordinates of all pixel points on the surface of the target tire.

[0032] Specifically, the vehicle controller performs signal conversion and analysis on the laser feedback signal, obtains the three-dimensional space coordinates of each pixel point on the surface of the target tire, and generates a real-time feedback image of the target tire based on the three-dimensional space coordinates of all pixel points on the surface of the target tire.

[0033] Step S130: Based on the real-time feedback image and the standard factory image of the target tire, an abnormality detection result of the target tire is generated.

[0034] The standard factory image refers to the 3D image data of the tire surface stored at the time the vehicle leaves the factory, including tread groove depth and original topographic features. The abnormality detection result is generated by comparing the real-time feedback image with the standard factory image to determine whether there is a wheel abnormality. If no abnormality is found, the detection result directly outputs no abnormality. If an abnormality is found, the abnormality information, including the type and location of the abnormality, is output.

[0035] Specifically, the vehicle controller compares the real-time feedback image with the standard factory image of the target tire, and generates a detection result of whether there is any abnormality in the target tire based on the image comparison result.

[0036] The technical solution of this embodiment can achieve accurate detection of tire conditions, solve the limitations of human visual observation, detect tire status in real time, promptly discover potential safety hazards, effectively improve driving safety, and protect the lives and property of drivers and passengers.

[0037] In one optional embodiment, the laser detector includes a laser emitter and a laser receiver. The laser emitter is a laser projection module with integrated optical components that emits a rectangular scanning laser beam perpendicular to the tire surface. The laser receiver is a component that receives the laser signal reflected by the tire and converts it into an electrical signal. It should be noted that the laser detector also includes a laser controller; this laser controller is used to receive laser detection signals sent by the vehicle controller and, based on the laser detection signals, activate the laser emitter to emit laser light perpendicularly to the target vehicle surface.

[0038] The step of determining the three-dimensional spatial coordinates of each pixel point on the target tire surface based on the laser feedback signal further includes: The real-time distance value from the laser transmitter to each pixel point is calculated based on the time difference between the emission time and the reception time corresponding to each pixel point on the target tire surface in the laser feedback signal.

[0039] The laser feedback signal is received by the laser receiver. The real-time distance value is the distance from the laser transmitter to the target tire surface pixel at the current moment, calculated using the speed of light based on the time difference between the laser emission time and the laser reception time.

[0040] Specifically, the vehicle controller uses the laser feedback signal to determine the time difference between the laser emission and laser reception times for each pixel on the target tire surface. Using the speed of light constant and this time difference, the vehicle controller calculates the straight-line distance from the laser emitter to each pixel using the time-of-flight ranging principle. This straight-line distance is the real-time distance value. It should be noted that the real-time distance value is equal to the speed of light multiplied by the time difference divided by two.

[0041] According to the real-time distance value of the laser emitter to each pixel point, the horizontal offset of each pixel point is determined.

[0042] The horizontal offset refers to the planar offset of the pixel point relative to the vertical direction of the laser emitter, which is calculated by a trigonometric function based on the real-time distance value.

[0043] Specifically, while the laser emitter vertically emits a laser beam, the laser controller records the corresponding laser emission angle of each pixel point in real time, which is referred to as the laser deflection angle. Based on the light outlet of the laser emitter as a reference point and in combination with the corresponding laser emission angle of each pixel point, a trigonometric function is used to calculate the horizontal offset of each pixel point relative to the vertical projection position of the reference point.

[0044] It should be noted that the calculation formula of the trigonometric function is S=d*tanθ; S is the horizontal offset, d is the real-time distance value of the pixel point, and θ is the laser deflection angle.

[0045] A three-dimensional coordinate system is established with the position of the laser emitter as the origin, and in combination with the real-time distance value and the horizontal offset of each pixel point, the three-dimensional space coordinates of each pixel point are generated.

[0046] Specifically, a three-dimensional coordinate system is established with the position of the laser emitter as the origin, the depth coordinate value is determined by the real-time distance value of each pixel point, and the planar coordinate value is calculated in combination with the horizontal offset of each pixel point, so as to obtain the three-dimensional space coordinates of each pixel point.

[0047] It should be noted that in this embodiment, for a vehicle equipped with a variable suspension, the suspension height adjustment will cause the vertical distance from the tire surface to the inner side of the wheel arch to dynamically change. The vehicle controller pre-stores a reference distance value A (unit: centimeter) when the suspension is at a standard height. When the suspension performs height adjustment, the minimum height change ΔH (unit: centimeter) of a single adjustment is set. When the suspension is adjusted up or down once, the standard distance from the tire surface to the wheel arch directly above the tire is A±ΔH centimeters, and the subsequent suspension height adjustment is sequentially applied to eliminate the interference of the suspension height change on the tire appearance detection.

[0048] In the above optional manner, the position information of each pixel point on the tire surface can be accurately determined, which provides strong support for generating an accurate real-time feedback image and improves the accuracy of tire detection.

[0049] In an optional manner, the step of generating the real-time feedback image of the target tire according to the three-dimensional space coordinates of each pixel point on the surface of the target tire further comprises: A two-dimensional plane coordinate system of the target tire surface development is established, and the three-dimensional space coordinates of each pixel point are projected to the two-dimensional plane coordinate system to generate two-dimensional position coordinates of each pixel point.

[0050] The two-dimensional plane coordinate system refers to a two-dimensional coordinate grid established after the tire surface is developed, and is used to map the plane position of the three-dimensional space coordinates. The two-dimensional position coordinates refer to the (X, Y) plane position components formed after the three-dimensional space coordinates of the pixel points are projected to the two-dimensional plane coordinate system.

[0051] Specifically, the target tire surface is developed into a rectangular plane area, and a two-dimensional plane coordinate system is established with the tire center line as the reference axis. The plane position components (X, Y) in the three-dimensional space coordinates (X, Y, Z) of each pixel point are directly mapped to the two-dimensional plane coordinate system to generate corresponding two-dimensional position coordinates (X', Y').

[0052] The height value in the three-dimensional space coordinates of each pixel point is fused with the two-dimensional position coordinates to generate the real-time feedback image containing depth information.

[0053] Specifically, the Z component (height value) in the three-dimensional space coordinates of each pixel point is extracted, and the height value in the three-dimensional space coordinates of each pixel point is converted into a corresponding gray value according to a preset depth-gray conversion rule. The gray value of each pixel point is combined with the corresponding two-dimensional position coordinates to obtain a real-time feedback image containing two-dimensional position and depth information.

[0054] It should be noted that the standard tread height Z0 is set as the reference gray value G0, and the offset ΔZ = Z - Z0 of the height value of each pixel point from the standard tread height is calculated. When ΔZ > 0 (convex region), a gray value lower than G0 is generated, and the gray scale reduction is proportional to ΔZ. When ΔZ < 0 (concave region), a gray value higher than G0 is generated, and the gray scale increase is proportional to |ΔZ|.

[0055] In the above optional mode, the depth information of the tire surface is retained, and it is convenient to compare and analyze with the standard factory image, which can more accurately identify the abnormal conditions of the tire and enhance the reliability of the detection result.

[0056] In an optional mode, the step of comparing the real-time feedback image with the standard factory image of the target tire to generate an abnormal detection result of the target tire further comprises: The pixel depth values of the real-time feedback image and the standard factory image of the target tire are compared to obtain the depth difference value of each pixel.

[0057] The depth difference value refers to the difference in height value of the same pixel point in the real-time feedback image and the standard factory image.

[0058] Specifically, the real-time feedback image and the standard factory image are mapped in the same two-dimensional coordinate system in terms of spatial position, and the depth values of the pixel points in the same plane coordinates are extracted. The difference between the depth value of each pixel point in the real-time feedback image and the depth value of the corresponding position in the standard factory image is calculated to obtain the depth difference value of each pixel point.

[0059] Based on the distribution characteristics and value size of the depth difference value of the pixel points, it is determined whether the target tire is abnormal.

[0060] The distribution characteristics and value size refer to the spatial aggregation state and numerical range of the depth difference value on the tire surface, which are used to determine the abnormal type.

[0061] If there is an abnormality, the abnormality detection result including the abnormal type and the abnormal position is generated.

[0062] The abnormal type and the abnormal position refer to the tire damage category (including but not limited to wear abnormality, crack abnormality, deformation abnormality, and groove abnormality) and its coordinate region on the tire surface.

[0063] In the above optional mode, the accurate detection and positioning of various abnormal conditions of the tire are realized, which helps to discover and handle tire problems in time and further improves the driving safety.

[0064] In an optional mode, the step of determining whether the target tire is abnormal based on the distribution characteristics and value size of the depth difference value of the pixel points further comprises: When a first pixel point cluster with a depth value continuously higher than the average value of the neighborhood is identified in the real-time feedback image, the first pixel point cluster is marked as a tread pattern area; and / or, when a second pixel point cluster with a depth value continuously lower than the average value of the neighborhood is identified in the real-time feedback image, the second pixel point cluster is marked as a tread groove area.

[0065] The tread pattern area is a three-dimensional texture structure composed of raised rubber blocks on the tire ground surface, and its three-dimensional topography shows periodic distribution of raised features. The tread groove area is a longitudinal or transverse groove structure between the tread blocks on the tire ground surface, and its three-dimensional topography shows continuous linear recess features. The two together form the functional texture of the tire tread, in which the pattern area provides grip, and the groove area is used for drainage and mud removal.

[0066] It should be noted that the first pixel point cluster corresponding to the tread pattern area refers to a closed area that is relatively convex in three-dimensional space, and the depth value of any pixel point in the closed area is at least 1 mm higher than that of the adjacent non-pattern area. The pixel point cluster has the following characteristics: containing not less than 50 continuous pixel points, the cluster boundary curvature radius is greater than 5 mm, and the depth value variance in the cluster is less than 0.2 mm. The second linear pixel point cluster corresponding to the tread groove area refers to a continuous linear depression in three-dimensional space, and the depth value of any pixel point in the continuous linear depression is at least 2 mm lower than that of the adjacent pattern area. The linear pixel point cluster has the following characteristics: the number of pixel points in the width direction is between 3-20 pixels, the length direction extends more than 70% of the tire tread width, and the length-width ratio of the cluster is greater than 5:1.

[0067] If the cumulative amount of depth difference of the pixel points in the tread pattern area and / or the tread groove area exceeds the first threshold value, it is determined that the target tire is abnormal; the pixel points with depth difference in the tread pattern area and / or the tread groove area are marked as the abnormal position, and the abnormal type is determined as wear abnormality.

[0068] Wherein, the first threshold value is 2 mm by default, and can also be set according to actual conditions. According to actual conditions, only the cumulative amount of depth difference of the tread pattern area exceeds the first threshold value (such as when the central part of the pattern is abnormally worn due to long-term high-speed driving of the vehicle), only the cumulative amount of depth difference of the tread groove area exceeds the first threshold value (such as when the groove is filled and hardened due to driving on a gravel road), and the cumulative amount of the tread pattern area and the tread groove area exceeds the first threshold value at the same time (such as the overall rubber degradation of the tire serving for a long time), there is no limitation here.

[0069] In the above optional mode, the depth value abnormal pixel point cluster is further identified, the tire wear abnormality is determined, the abnormal position and type are accurately determined, the actual detection basis and reference are provided for the user, and corresponding measures are taken in time to ensure driving safety.

[0070] In an optional mode, the step of determining whether the target tire is abnormal based on the distribution characteristics and value size of the depth difference of the pixel points further comprises: When the target connected domain composed of a continuous preset number of pixel points exists in the real-time feedback image, the target connected domain is marked as a tread crack area.

[0071] Wherein, the target connected domain refers to a pixel cluster that all depth difference values are less than zero, satisfies the eight-neighbor connectedness, and the number of continuous pixels is greater than or equal to four.

[0072] If the depth difference of each pixel point in the tread crack area exceeds the second threshold value, it is determined that the target tire is abnormal.

[0073] The second threshold value is -2 mm by default, and can be adjusted according to actual conditions, which is not limited herein.

[0074] The tire tread crack area is marked as the abnormal position, and the abnormal type is determined as a crack abnormality.

[0075] Specifically, all pixel points with a depth difference value less than zero in the real-time feedback image are searched, a pixel cluster meeting eight-neighbor connectivity and having a continuous pixel number greater than or equal to four is identified as a target connected domain (tire tread crack area), and the depth difference value of each pixel point in the target connected domain is verified. If the depth difference value of all pixel points is less than or equal to -2 mm, all pixel point coordinates of the tire tread crack area are marked as abnormal positions, and the abnormal type is determined as a crack abnormality.

[0076] It should be noted that the connected domain identification needs to meet the minimum linear feature constraint, that is, the aspect ratio is greater than three to one, and the verification process excludes pixel interference with a non-negative depth difference value.

[0077] In the above optional mode, the target connected domain is further identified as a tire tread crack area, a crack abnormality is determined, potential tire crack problems are accurately found, timely warnings are given, more serious consequences caused by crack expansion are prevented, and driving safety is further enhanced.

[0078] In an optional mode, the step of determining whether the target tire has an abnormality based on the distribution characteristics and value of the depth difference value of the pixel points further includes: When a third pixel cluster with an absolute value of the depth difference value greater than or equal to a third threshold value and a consistent sign is identified in the real-time feedback image, the third pixel cluster is marked as a tire deformation area, and it is determined that the target tire has an abnormality.

[0079] The tire deformation area refers to a local surface distortion area of a tire surface caused by internal structure damage, which has a three-dimensional appearance of a closed surface abnormal bulge or depression formed by continuous pixel points, a significant height mutation from a neighboring normal area, and a discontinuous curvature change, including but not limited to physical forms such as bulges (protrusions), collapses (depressions), and wave deformations. The third threshold value is 3 mm by default, and can be adjusted according to actual conditions, which is not limited herein.

[0080] Specifically, a closed pixel cluster with a clear boundary is identified as a candidate deformation area in the real-time feedback image, the depth difference value of each pixel point in the candidate deformation area is verified, and if the absolute value of the depth difference value of all pixel points is greater than or equal to 3 mm and the sign is consistent, the candidate deformation area is the third pixel cluster and is marked as a tire deformation area.

[0081] The tire deformation area is marked as the abnormal position, and the abnormal type is determined as a bulge abnormality or a depression abnormality according to the depth difference value sign of the tire deformation area.

[0082] When the depth difference value sign is positive, the abnormal type is determined as a bulge abnormality; and when the depth difference value sign is negative, the abnormal type is determined as a depression abnormality.

[0083] In the optional manner described above, a pixel point cluster with a large depth difference value absolute value and a consistent sign is further identified as a tire deformation area, a bulge or depression abnormality is determined, a tire deformation problem is accurately found, driving risks caused by deformation are avoided, and driving stability and safety are improved.

[0084] In an optional manner, the step of determining whether the target tire has an abnormality based on the distribution characteristics and value size of the depth difference value of the pixel points further includes: When a closed ring-shaped pixel point cluster with a depth difference value less than or equal to a fourth threshold value is identified in the real-time feedback image, and a convex pixel point with a depth difference value greater than or equal to a fifth threshold value exists in the center of the closed ring-shaped pixel point cluster, the closed ring-shaped pixel point cluster is marked as a tire groove area, and it is determined that the target tire has an abnormality.

[0085] The tire groove area is marked as the abnormal position, and the abnormal type is determined as a groove abnormality.

[0086] The tire groove area refers to a ring-shaped recessed structure on the tire surface caused by foreign matter penetration, which has a three-dimensional topography of a closed ring-shaped depth mutation area centered on the foreign matter penetration point, a steep increase in the inner edge of the ring, a smooth transition from the outer edge to the normal tire surface, and a uniformity deviation of the ring width of less than 20%, which is different from the linear characteristics of the tire groove trace. The fourth threshold value is -1.5 mm by default, and the fifth threshold value is 0.5 mm by default, which can also be adjusted according to actual conditions without limitation.

[0087] Specifically, a closed ring-shaped pixel point cluster with a radial depth gradient distribution is identified in the real-time feedback image as a groove area candidate, the depth difference value of each pixel point covered by the ring-shaped pixel point cluster is checked, and if the depth difference values of all pixel points are less than or equal to -1.5 mm, and there is a convex pixel point with a depth difference value greater than or equal to 0.5 mm in the center of the ring, then all pixel point coordinates of the ring-shaped pixel point cluster are marked as abnormal positions, and the abnormal type is determined as a groove abnormality.

[0088] It should be noted that the annular structure needs to meet the geometric constraints that the uniformity deviation of the annular width is not more than 20%, and the difference between the outer edge depth and the background tread depth is within the range of ±0.3 mm, and finally the foreign matter material characteristics of the annular core protruding point are verified by laser reflection spectrum.

[0089] In addition, after determining the abnormal position and the abnormal type, abnormal feedback information containing the abnormal position and the abnormal type is output through the large screen of the vehicle machine, and is intuitively displayed through a visual interface (for example, the abnormal position in the three-dimensional view of the target tire is displayed in red, and the color depth is dynamically adjusted according to the size of the depth difference) to prompt the user to pay attention to the maintenance of the tire.

[0090] In the above optional manner, the closed annular pixel point cluster and the center protruding pixel point are further identified as the tread groove area, and the groove abnormality is determined, which can effectively find the problem of foreign matter piercing into the tire, prevent the tire performance from being affected by the groove abnormality, and ensure the driving safety of the vehicle.

[0091] In an optional manner, a washing nozzle is arranged on the laser emitter, and a micro pump connected to a washing kettle is arranged in the washing nozzle; the method further comprises: When a laser shielding signal representing an abnormality of the laser emitter is received, the micro pump is controlled to drive the washing nozzle to clean the surface of the laser emitter.

[0092] The washing nozzle is a cleaning structure integrated on the surface of the laser emitter and provided with the micro pump, and is used for spraying cleaning liquid. The micro pump is a micro pump body arranged in the washing nozzle and driven by the laser controller to deliver the cleaning liquid of the washing kettle. The washing kettle refers to a container storing the cleaning liquid and connected to the washing nozzle through a pipeline. The laser shielding signal refers to an abnormal alarm signal sent by the laser controller when dust coverage causes the laser to be unable to emit.

[0093] In the above optional manner, by designing the washing nozzle and the micro pump on the laser emitter, the surface of the emitter can be cleaned in time when the laser shielding signal is received, the normal operation of the laser emitter and the accuracy of the emitted laser are ensured, and thus the reliability of the obtained laser feedback signal is ensured, and the stability and reliability of the tire detection are improved.

[0094] Figure 2 The structure schematic diagram of an embodiment of a tire detection device provided by the application is shown. Please refer to Figure 2 As shown in the figure, the device 300 comprises an acquisition module 310, a generation module 320 and a detection module 330.

[0095] The acquisition module 310 is configured to control the laser detector to vertically emit laser light to a target tire surface after the vehicle is powered on, and receive a laser feedback signal generated by the laser light irradiated to the target tire; wherein the laser detector is arranged on the inner side of the wheel arch directly above the surface centerline of the target tire. The generation module 320 is configured to determine three-dimensional space coordinates of each pixel point on the target tire surface based on the laser feedback signal, and generate a real-time feedback image of the target tire according to the three-dimensional space coordinates of each pixel point on the target tire surface. The detection module 330 is configured to compare the real-time feedback image with a standard factory image of the target tire, and generate an abnormality detection result of the target tire.

[0096] In an optional manner, the laser detector includes a laser emitter and a laser receiver; and the acquisition module 310 is specifically configured to: control the laser emitter to vertically emit laser light to the target tire surface, and receive the laser feedback signal generated by the laser light irradiated to the target tire surface through the laser receiver.

[0097] In an optional manner, the laser detector includes a laser emitter and a laser receiver; and the generation module 320 is specifically configured to: calculate real-time distance values of the laser emitter to each pixel point according to a time difference between an emission time and a receiving time of each pixel point on the target tire surface in the laser feedback signal; wherein the laser feedback signal is received by the laser receiver; determine a horizontal offset of each pixel point according to the real-time distance values of the laser emitter to each pixel point; establish a three-dimensional coordinate system with the position of the laser emitter as the coordinate origin, and generate three-dimensional space coordinates of each pixel point by combining the real-time distance values and the horizontal offset of each pixel point.

[0098] In an optional manner, the generation module 320 is specifically configured to: establish a two-dimensional plane coordinate system of the target tire surface, project the three-dimensional space coordinates of each pixel point to the two-dimensional plane coordinate system, and generate two-dimensional position coordinates of each pixel point; fuse the height value in the three-dimensional space coordinates of each pixel point with the two-dimensional position coordinates, and generate the real-time feedback image containing depth information.

[0099] In an optional manner, the detection module 330 is specifically configured to: The real-time feedback image and the standard factory image of the target tire are compared in terms of pixel depth values to obtain a depth difference value of each pixel; Based on the distribution characteristics and value size of the depth difference value of each pixel, it is determined whether the target tire has an abnormality; If there is an abnormality, the abnormality detection result including the abnormality type and the abnormality position is generated.

[0100] In an optional manner, the detection module 330 is specifically configured to: When a first pixel point cluster with a depth value continuously higher than the average value of the neighborhood is identified in the real-time feedback image, the first pixel point cluster is marked as a tread pattern region; and / or, when a second pixel point cluster with a depth value continuously lower than the average value of the neighborhood is identified in the real-time feedback image, the second pixel point cluster is marked as a tread groove region; If the depth difference value accumulation amount of the pixel points in the tread pattern region and / or the tread groove region exceeds a first threshold value, it is determined that the target tire has an abnormality; The pixel points with a depth difference value in the tread pattern region and / or the tread groove region are marked as the abnormality position, and the abnormality type is determined as a wear abnormality.

[0101] In an optional manner, the detection module 330 is specifically configured to: When a target connected domain composed of a continuous preset number of pixel points exists in the real-time feedback image, the target connected domain is marked as a tread crack region; If the depth difference value of each pixel point in the tread crack region exceeds a second threshold value, it is determined that the target tire has an abnormality; The tread crack region is marked as the abnormality position, and the abnormality type is determined as a crack abnormality.

[0102] In an optional manner, the detection module 330 is specifically configured to: When a third pixel point cluster with a depth difference value absolute value greater than or equal to a third threshold value and a consistent depth difference value sign is identified in the real-time feedback image, the third pixel point cluster is marked as a tread deformation region, and it is determined that the target tire has an abnormality; The tread deformation region is marked as the abnormality position, and the abnormality type is determined as a bulge abnormality or a depression abnormality according to the depth difference value sign of the tread deformation region.

[0103] In an optional manner, the detection module 330 is specifically configured to: When a closed ring pixel cluster with a depth difference less than or equal to a fourth threshold is identified in the real-time feedback image, and a protruding pixel with a depth difference greater than or equal to a fifth threshold exists in the center of the closed ring pixel cluster, the closed ring pixel cluster is marked as a tread groove area, and it is determined that the target tire has an abnormality. The tread groove area is marked as the abnormal position, and the abnormal type is determined as a groove abnormality.

[0104] In an optional manner, a washing nozzle is arranged on the laser emitter, and a micro pump connected to a washing kettle is arranged in the washing nozzle; the device further comprises a cleaning module; the cleaning module is configured to: When a laser blocking signal representing an abnormality of the laser emitter is received, the micro pump is controlled to drive the washing nozzle to clean the surface of the laser emitter.

[0105] The technical scheme of the embodiment can realize accurate detection of the tire condition, solve the limitations of the human eye observation mode, can detect the tire state in real time, discover potential safety hazards in time, effectively improve the driving safety, and protect the life and property safety of the driver and passengers.

[0106] It should be noted that the tire detection device provided in the above embodiment and the tire detection method provided in the above embodiment belong to the same concept, and the specific manner in which each module and unit performs the operation has been described in detail in the method embodiment, which will not be described here.

[0107] Figure 3 An embodiment of a tire detection device provided by the present application is shown in a structural schematic diagram, which shows a structural schematic diagram of a computer system suitable for implementing the tire detection device of the embodiment of the present application, and the specific implementation of the tire detection device is not limited in the specific implementation of the embodiment of the present application.

[0108] Please refer to Figure 3 As shown in the figure, the tire detection device comprises a controller, and a memory configured to store one or more programs, when the one or more programs are executed by the controller, the controller implements the above-mentioned tire detection method.

[0109] Please continue to refer to Figure 3As shown, the computer system 500 of the tire detection apparatus includes a central processing unit (CPU) 501 which can perform various appropriate actions and processes, such as executing the methods in the above-described embodiments, according to programs stored in a read-only memory (ROM) 502 or loaded from the storage section 508 into a random access memory (RAM) 503. Various programs and data required for system operation are also stored in the RAM 503. The CPU 501, the ROM 502, and the RAM 503 are connected to each other through a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0110] Connected to the I / O interface 505 are an input section 506 including a keyboard, a mouse, etc.; an output section 507 including a display such as a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the I / O interface 505 as necessary. A removable recording medium 511 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc. is attached to the drive 510 as necessary, so that a computer program read therefrom is installed in the storage section 508 as necessary.

[0111] In particular, according to embodiments of the present application, the processes described above with reference to the flowcharts can be implemented as a computer software program. For example, embodiments of the present application include a computer program product comprising a computer program carried on a computer readable medium, the computer program containing a computer program for executing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via the communication section 509, and / or installed from the removable recording medium 511. When the computer program is executed by the central processing unit (CPU) 501, various functions defined in the system of the present application are performed.

[0112] Another aspect of the present application also provides a computer readable storage medium, wherein at least one executable instruction is stored in the storage medium, and the executable instruction, when executed on a tire detection device, causes the tire detection device to perform the operations of the tire detection method as described above. The computer readable storage medium can be included in the tire detection device described in the above embodiments, or can exist separately without being assembled into the electronic device.

[0113] Another aspect of the present application also provides a computer program product or computer program, which includes at least one executable instruction, and the executable instruction, when executed on a tire detection device, causes the tire detection device to perform the tire detection method as described above.

[0114] The executable instruction can be specifically used to cause the tire detection device to perform the following operations: When the vehicle is powered on, a laser detector is controlled to emit laser light vertically to a target tire surface, and a laser feedback signal generated by the laser light irradiated to the target tire is received; wherein the laser detector is arranged on the inner side of the wheel arch directly above the middle line of the surface of the target tire; Based on the laser feedback signal, three-dimensional space coordinates of each pixel point on the surface of the target tire are determined, and a real-time feedback image of the target tire is generated according to the three-dimensional space coordinates of each pixel point on the surface of the target tire; Based on the comparison between the real-time feedback image and a standard factory image of the target tire, an abnormality detection result of the target tire is generated.

[0115] In an optional manner, the laser detector includes a laser emitter and a laser receiver; and the step of determining the three-dimensional space coordinates of each pixel point on the surface of the target tire based on the laser feedback signal further includes: According to the time difference between the emission time and the receiving time of each pixel point on the surface of the target tire in the laser feedback signal, real-time distance values of the laser emitter to each pixel point are calculated; wherein the laser feedback signal is received by the laser receiver; According to the real-time distance values of the laser emitter to each pixel point, horizontal offset amounts of each pixel point are determined; A three-dimensional coordinate system is established with the position of the laser emitter as the coordinate origin, and the three-dimensional space coordinates of each pixel point are respectively generated in combination with the real-time distance values and the horizontal offset amounts of each pixel point.

[0116] In an optional manner, the step of generating the real-time feedback image of the target tire according to the three-dimensional space coordinates of each pixel point on the surface of the target tire further includes: establishing a two-dimensional plane coordinate system of the target tire surface development, projecting the three-dimensional space coordinates of each pixel point to the two-dimensional plane coordinate system to generate a two-dimensional position coordinate of each pixel point; fusing the height value in the three-dimensional space coordinates of each pixel point with the two-dimensional position coordinate to generate the real-time feedback image containing depth information.

[0117] In an optional manner, the step of comparing the real-time feedback image with the standard factory image of the target tire to generate an abnormality detection result of the target tire further includes: comparing the pixel depth values of the real-time feedback image and the standard factory image of the target tire to obtain a depth difference value of each pixel point; determining whether the target tire is abnormal based on the distribution characteristics and value size of the depth difference value of the pixel point; if there is an abnormality, generating the abnormality detection result containing an abnormality type and an abnormality position.

[0118] In an optional manner, the step of determining whether the target tire is abnormal based on the distribution characteristics and value size of the depth difference value of the pixel point further includes: when a first pixel point cluster with a depth value continuously higher than the average value of the neighborhood is identified in the real-time feedback image, marking the first pixel point cluster as a tread pattern area; and / or, when a second pixel point cluster with a depth value continuously lower than the average value of the neighborhood is identified in the real-time feedback image, marking the second pixel point cluster as a tread groove area; if the depth difference value accumulation of the pixel points in the tread pattern area and / or the tread groove area exceeds a first threshold value, it is determined that the target tire is abnormal; marking the pixel points with a depth difference value in the tread pattern area and / or the tread groove area as the abnormal position, and determining the abnormality type as a wear abnormality.

[0119] In an optional manner, the step of determining whether the target tire is abnormal based on the distribution characteristics and value size of the depth difference value of the pixel point further includes: when a target connected domain consisting of a continuous preset number of pixel points exists in the real-time feedback image, marking the target connected domain as a tread crack area; if the depth difference value of each pixel point in the tread crack area exceeds a second threshold value, it is determined that the target tire is abnormal; marking the tread crack area as the abnormal position, and determining the abnormality type as a crack abnormality.

[0120] In an optional mode, the step of determining whether the target tire is abnormal based on the distribution characteristics and value of the depth difference of the pixel points further comprises: When a third pixel point cluster with an absolute value of the depth difference greater than or equal to a third threshold value and a consistent sign of the depth difference is identified in the real-time feedback image, the third pixel point cluster is marked as a tire tread deformation area, and it is determined that the target tire is abnormal; The tire tread deformation area is marked as the abnormal position, and the abnormal type is determined as a bulge abnormality or a depression abnormality according to the sign of the depth difference of the tire tread deformation area.

[0121] In an optional mode, the step of determining whether the target tire is abnormal based on the distribution characteristics and value of the depth difference of the pixel points further comprises: When a closed ring-shaped pixel point cluster with a depth difference less than or equal to a fourth threshold value is identified in the real-time feedback image, and a convex pixel point with a depth difference greater than or equal to a fifth threshold value exists in the center of the closed ring-shaped pixel point cluster, the closed ring-shaped pixel point cluster is marked as a tire tread groove area, and it is determined that the target tire is abnormal; The tire tread groove area is marked as the abnormal position, and the abnormal type is determined as a groove abnormality.

[0122] In an optional mode, a washing nozzle is arranged on the laser emitter, and a micro pump connected to a washing kettle is arranged in the washing nozzle; the method further comprises: When a laser blocking signal representing an abnormality of the laser emitter is received, the micro pump is controlled to drive the washing nozzle to clean the surface of the laser emitter.

[0123] The technical scheme of the embodiment can accurately detect the condition of the tire, solve the limitations of the human eye observation method, and can detect the tire state in real time, discover potential safety hazards in a timely manner, effectively improve driving safety, and protect the life and property safety of drivers and passengers.

[0124] It should be noted that the computer-readable medium in the embodiments of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination thereof. The computer-readable storage medium may, for example, be an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or apparatus, or any combination thereof. More specific examples of the computer-readable storage medium can include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this application, the computer-readable storage medium can be any tangible medium that contains or stores a program used by an instruction execution system, apparatus or device, and can be used or combined with the same. In this application, the computer-readable signal medium can include a data signal carried in a baseband or as a part of a carrier wave, which carries computer-readable computer programs. Such a propagated data signal can take various forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable medium other than the computer-readable storage medium, which can send, transmit, propagate or transport a program for use by or in connection with an instruction execution system, apparatus or device. The computer programs contained in the computer-readable medium can be transmitted by any suitable medium, including but not limited to wireless, wired, or the like, or any suitable combination thereof.

[0125] The flowcharts and block diagrams in the drawings illustrate the possible implementation architectures, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In the flowcharts or block diagrams, each block can represent a module, a program segment or a part of code, which contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions noted in the blocks can occur in a different order from that noted in the drawings. For example, two blocks represented in succession can actually be executed substantially in parallel, and sometimes in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams or flowcharts, and the combination of blocks in the block diagrams or flowcharts, can be implemented by a dedicated hardware-based system for implementing the specified functions or operations, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0126] The units described in the embodiments of the present application can be implemented by software, or by hardware, or by a combination of software and hardware. The units described can also be located in a single processor. In some cases, the names of the units do not limit the units themselves.

[0127] According to an aspect of the embodiments of the present application, a computer system is also provided, which includes a central processing unit (CPU) that can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) or a program loaded from a storage section into a random access memory (RAM), such as performing the method in the above embodiments. In the RAM, various programs and data required for system operation are also stored. The CPU, the ROM, and the RAM are connected to each other through a bus. An input / output (I / O) interface is also connected to the bus.

[0128] The following components are connected to the I / O interface: an input section including a keyboard, a mouse, etc.; an output section including a display such as a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section including a hard disk, etc.; and a communication section including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section performs communication processing via a network such as the Internet. A drive is also connected to the I / O interface as necessary. A removable recording medium, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is attached to the drive as necessary, so that a computer program read therefrom is installed into the storage section as necessary.

[0129] The above merely describes the preferred exemplary embodiments of the present application, and is not intended to limit the implementation of the present application. Those skilled in the art can easily make corresponding modifications or variations according to the main idea and spirit of the present application, and the scope of protection of the present application should be subject to the scope of protection as claimed by the claims.

Claims

1. A tire detection method, characterized in that: The method comprises: When the vehicle is powered on, the laser detector is controlled to emit laser light vertically toward the surface of the target tire and receive a laser feedback signal generated by the laser irradiating the target tire; wherein the laser detector is arranged on the inner side of the wheel arch just above the center line of the surface of the target tire; Determining the three-dimensional spatial coordinates of each pixel point on the target tire surface based on the laser feedback signal, and generating a real-time feedback image of the target tire according to the three-dimensional spatial coordinates of each pixel point on the target tire surface; Based on the comparison between the real-time feedback image and the standard factory image of the target tire, an abnormality detection result of the target tire is generated.

2. The method according to claim 1, characterized in that The laser detector includes: a laser transmitter and a laser receiver; the step of determining the three-dimensional spatial coordinates of each pixel point on the target tire surface based on the laser feedback signal further includes: Calculating the real-time distance value from the laser transmitter to each pixel point based on the time difference between the emission time and the reception time corresponding to each pixel point on the target tire surface in the laser feedback signal; wherein the laser feedback signal is received by the laser receiver; Determine the horizontal offset of each pixel point according to the real-time distance value from the laser emitter to each pixel point; A three-dimensional coordinate system is established with the position of the laser emitter as the coordinate origin, and the three-dimensional spatial coordinates of each pixel point are generated by combining the real-time distance value and horizontal offset of each pixel point.

3. The method according to claim 1, characterized in that The step of generating a real-time feedback image of the target tire according to the three-dimensional spatial coordinates of each pixel point on the surface of the target tire further includes: Establishing a two-dimensional plane coordinate system for the target tire surface, projecting the three-dimensional spatial coordinates of each pixel point onto the two-dimensional plane coordinate system, and generating the two-dimensional position coordinates of each pixel point; The height value in the three-dimensional space coordinates of each pixel point is fused with the two-dimensional position coordinates to generate the real-time feedback image containing depth information.

4. The method according to claim 3, characterized in that The step of generating an abnormality detection result of the target tire based on comparing the real-time feedback image with the standard factory image of the target tire further includes: Comparing pixel depth values ​​of the real-time feedback image with the standard factory image of the target tire to obtain a depth difference value for each pixel; Determine whether the target tire has an abnormality based on the distribution characteristics and value of the depth difference of the pixel points; If an abnormality exists, the abnormality detection result including the abnormality type and abnormal location is generated.

5. The method according to claim 4, characterized in that The step of determining whether the target tire has an abnormality based on the distribution characteristics and value of the depth difference of the pixel points further includes: When a first pixel cluster having depth values ​​continuously higher than a neighborhood average is identified in the real-time feedback image, the first pixel cluster is marked as a tread pattern region; and / or when a second pixel cluster having depth values ​​continuously lower than a neighborhood average is identified in the real-time feedback image, the second pixel cluster is marked as a tread groove region; If the accumulated depth difference of the pixels in the tread pattern area and / or the tread groove area exceeds a first threshold, it is determined that the target tire has an abnormality; Pixel points with depth differences in the tread pattern area and / or the tread groove area are marked as abnormal positions, and the abnormality type is determined to be wear abnormality.

6. The method according to claim 4, characterized in that The step of determining whether the target tire has an abnormality based on the distribution characteristics and value of the depth difference of the pixel points further includes: When a target connected domain consisting of a preset number of consecutive pixel points exists in the real-time feedback image, marking the target connected domain as a tread crack area; If the depth difference of each pixel point in the tread crack area exceeds a second threshold, it is determined that the target tire has an abnormality; The tread crack area is marked as the abnormal position, and the abnormality type is determined to be a crack abnormality.

7. The method according to claim 4, characterized in that The step of determining whether the target tire has an abnormality based on the distribution characteristics and value of the depth difference of the pixel points further includes: When a third pixel cluster is identified in the real-time feedback image, wherein the absolute values ​​of the depth differences are all greater than or equal to a third threshold and the depth differences have the same signs, the third pixel cluster is marked as a tread deformation area, and the target tire is determined to be abnormal. The tread deformation area is marked as the abnormal position, and the abnormality type is determined to be a bulge abnormality or a depression abnormality according to the depth difference sign of the tread deformation area.

8. The method according to claim 4, characterized in that The step of determining whether the target tire has an abnormality based on the distribution characteristics and value of the depth difference of the pixel points further includes: When a closed ring-shaped pixel cluster with a depth difference less than or equal to a fourth threshold value is identified in the real-time feedback image, and a raised pixel point with a depth difference greater than or equal to a fifth threshold value exists at the center of the closed ring-shaped pixel cluster, the closed ring-shaped pixel cluster is marked as a tread groove area, and the target tire is determined to have an abnormality; The tread groove area is marked as the abnormal position, and the abnormality type is determined to be a groove abnormality.

9. The method according to any one of claims 2 to 8, characterized in that The laser emitter is provided with a washing nozzle, and the washing nozzle has a built-in micro pump connected to a washing pot; the method further comprises: When a laser blocking signal indicating an abnormality of the laser emitter is received, the micro pump is controlled to drive the washing nozzle to clean the surface of the laser emitter.

10. A tire detection device, characterized in that: The device comprises: an acquisition module, configured to control a laser detector to emit a laser perpendicularly to a target tire surface when the vehicle is powered on, and to receive a laser feedback signal generated by the laser irradiating the target tire; wherein the laser detector is disposed on the inner side of a wheel arch directly above the centerline of the target tire surface; a generating module, which determines the three-dimensional spatial coordinates of each pixel point on the surface of the target tire based on the laser feedback signal, and generates a real-time feedback image of the target tire according to the three-dimensional spatial coordinates of each pixel point on the surface of the target tire; The detection module compares the real-time feedback image with a standard factory image of the target tire to generate an abnormality detection result of the target tire.

11. A tire detection device, characterized in that: include: Controller; The memory is used to store one or more programs. When the one or more programs are executed by the controller, the controller implements the tire detection method according to any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that The storage medium stores at least one executable instruction. When the executable instruction is executed on the tire detection device / equipment, the tire detection device / equipment performs the operation of the tire detection method according to any one of claims 1 to 9.

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