A method and system for predicting tire uniformity through scanning and pressure distribution of a finished tire

Abstract

The application provides a method and system for predicting tire uniformity by scanning and pressure distribution of a finished tire, comprising: obtaining tire point cloud data attributes, analyzing the point cloud data attributes, and removing noise points to obtain an original 2D point cloud graph, establishing a theoretical model reconstruction and an actual model reconstruction system based on the point cloud data attributes and the original 2D point cloud graph, determining the shape and volume of concave points or convex points of the tire deviating from the basic tire contour, and establishing a mass and size distribution graph, applying stress to the tire tread, and obtaining a stress distribution model of the tire tread, and establishing a tire uniformity two-dimensional model based on the mass and size distribution graph and the stress distribution graph of the tire tread to test the uniformity of the tire. The application achieves the purpose of predicting the force generated by the tire rotation at different speeds and the change of the force without traditional uniformity testing through simulation and point cloud processing of the finished tire.

Description

Technical Field

[0001] This invention relates to the field of simulation technology for testing the uniformity of finished tires, and in particular to a method and system for predicting tire uniformity of finished tires through scanning and pressure distribution. Background Technology

[0002] Tires are ring-shaped elastomers composed of various materials such as fibers, steel wires, and rubber. Due to manufacturing processes and design factors, tires are not perfectly uniform or symmetrical. This non-uniformity is mainly manifested in the unevenness of tire size, force, and mass. This includes: Radial force deviation (RFV), which is the tread's bouncy force when a tire under a certain load rolls at a certain speed. The greater the radial force deviation, the worse the ride comfort and the more likely it is to cause driver fatigue. Lateral force deviation (LFV) mainly reflects the tire's wobble. The greater the lateral force deviation, the more the car will wobble while driving, making it difficult for the driver to maintain control of the steering wheel, affecting handling stability, and also accelerating tire wear.

[0003] The uniformity of a tire is related to the symmetry of its axis of rotation. When a tire rotates, non-uniformities in its structure generate periodic force changes or impacts along the axis of rotation. These force changes cause vibrations that are transmitted through the suspension and can be felt in the seat and steering wheel.

[0004] Tire uniformity properties are generally classified into dimensional (or geometric) and mass variables. Uniformity testing typically evaluates uniformity by measuring the changes in forces generated by the tire during rotation. The testing method involves applying the tire to a drum simulating a road surface under a specified air pressure load. The drum is rotated while maintaining a slip angle and camber angle of "0". The magnitude and changes in forces generated during tire rotation are measured, including radial, lateral, and tangential forces. Generally, there are two methods for measuring tire uniformity: low-speed testing machines used in factories and high-speed testing machines used in research. However, due to the high cost and precision requirements of the equipment, even slight deviations during tire assembly and testing can cause significant errors. Therefore, predicting tire uniformity without relying on precision equipment is a pressing technical problem that needs to be solved by those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for predicting tire uniformity by scanning and pressure distribution of finished tires. This invention simulates finished tires and calculates the size and mass non-uniform distribution of deviations from the baseline through point cloud processing. Combined with the tire tread stress distribution, it can predict the magnitude and force changes generated when the tire rotates at different speeds without the need for traditional uniformity testing.

[0006] This invention improves upon existing methods for detecting tire uniformity using traditional low-speed testing machines and high-speed testing machines used in research. Because the testing equipment is precise and expensive, and requires high accuracy, even slight deviations during tire assembly and testing can cause significant errors. This invention uses point cloud processing to calculate the size and mass non-uniformity distribution of the deviation from the baseline. Combined with the tire tread stress distribution, it enables the prediction of the magnitude and changes in force generated when the tire rotates at different speeds without requiring a testing machine for uniformity testing.

[0007] This invention improves upon the existing traditional method for determining tire uniformity: under a specified air pressure load, the tire is applied to a drum simulating a road surface, the drum is rotated, and the tilt and roll angles are kept at "0". The magnitude and changes in the forces generated during tire rotation are then measured, including radial force, lateral force, and tangential force. However, this method has low detection efficiency and cannot effectively detect tires produced in large batches. This invention establishes a database by linking low-speed and high-speed uniformity of the tire, and through a calculation system, it can predict tire force variations and vibration magnitudes without uniformity testing, greatly improving detection efficiency.

[0008] To achieve the above objectives, the present invention provides the following technical solution:

[0009] A method for predicting tire uniformity of finished tires by scanning and pressure distribution, characterized in that it includes:

[0010] Step S1: Obtain tire point cloud data attributes, analyze the point cloud data attributes, and remove noise points to obtain the original 2D point cloud map;

[0011] Step S2: Based on the point cloud data attributes and the original 2D point cloud map, establish a theoretical model reconstruction and actual model reconstruction system. Based on the theoretical model reconstruction and actual model reconstruction, determine the shape and volume of the concave or convex points of the tire that deviate from the basic tire contour, and establish a mass and size distribution map.

[0012] Step S3: Apply stress to the tread of the tire and obtain a stress distribution model of the tread;

[0013] Step S4: Based on the mass and size distribution map and the stress distribution map of the tread, establish a two-dimensional model of tire uniformity to conduct a uniformity test on the tire, and predict the magnitude and change of the force generated by the tire when rotating at different speeds.

[0014] In some embodiments of this application, step S2 further includes:

[0015] The pixels in the original 2D point cloud image are rotated in parallel to obtain point cloud data, and the straight line fitted based on the pixels located on the tread of the tire in the point cloud data is parallel to the horizontal X-axis.

[0016] The concave or convex points are located by applying gradient analysis methods based on the point cloud data.

[0017] The volume of the concave or convex point is calculated using bilateral or unilateral measurements based on the point cloud data.

[0018] In some embodiments of this application, step S3 further includes:

[0019] Obtain the stress data of the tread and calculate the effective area of ​​the tread based on the stress data;

[0020] The stress in the tire tread is divided into multiple stress zones;

[0021] Based on the stress intervals and the stress data, calculate the stress distribution area of ​​each stress interval;

[0022] Calculate the ratio of the stress distribution area to the effective area in each stress interval to obtain the cumulative probability of stress distribution within the stress interval;

[0023] Based on the stress data and the cumulative probability of the stress distribution, the shape and volume parameters in the Weiber distribution function are calculated to obtain the stress distribution model.

[0024] In some embodiments of this application, the pixels in the original 2D point cloud image are rotated in parallel to obtain point cloud data such that the straight line fitted based on the pixels located on the tread surface in the point cloud data is parallel to the horizontal X-axis, including:

[0025] A first straight line is obtained by fitting a straight line to the first set of pixels after removing edge pixels in the original 2D point cloud map. The first rotation angle required to rotate the first straight line to be parallel to the horizontal X-axis is calculated. The first set of pixels is then rotated by the first rotation angle to obtain the first point cloud set.

[0026] The second rotation angle required to eliminate the influence of the concave or convex points is obtained from the first point cloud set, and a second point cloud set is obtained by removing the concave or convex points from the first point cloud set and rotating by the second rotation angle.

[0027] The third rotation angle required to eliminate the influence of interference points is obtained based on the second point cloud set;

[0028] The pixels in the original 2D point cloud image are rotated by the first rotation angle, the second rotation angle, and the third rotation angle respectively to obtain the point cloud data.

[0029] To achieve the above objectives, the present invention also provides a system for predicting tire uniformity of finished tires through scanning and pressure distribution, characterized in that it comprises:

[0030] The acquisition module is used to acquire tire point cloud data attributes, analyze the point cloud data attributes, and remove noise points to obtain the original 2D point cloud map.

[0031] The processing module is used to establish a theoretical model reconstruction and actual model reconstruction system based on the point cloud data attributes and the original 2D point cloud map, determine the shape and volume of the concave or convex points of the tire that deviate from the basic tire contour based on the theoretical model reconstruction and actual model reconstruction, and establish a mass and size distribution map.

[0032] The testing module is used to apply stress to the tread of the tire and obtain a stress distribution model of the tread.

[0033] The analysis module is used to establish a two-dimensional model of tire uniformity based on the mass and size distribution map and the stress distribution map of the tread to conduct uniformity tests on the tire and predict the magnitude and change of the force generated by the tire when rotating at different speeds.

[0034] In some embodiments of this application, the processing module is further configured to perform parallel rotation on the pixels in the original 2D point cloud image to obtain point cloud data, and to make the straight line fitted based on the pixels located on the tread of the tire in the point cloud data parallel to the horizontal X-axis.

[0035] The concave or convex points are located by applying gradient analysis methods based on the point cloud data.

[0036] The volume of the concave or convex point is calculated using bilateral or unilateral measurements based on the point cloud data.

[0037] In some embodiments of this application, the test module is further configured to acquire stress data of the tread and calculate the effective area of ​​the tread based on the stress data of the tread.

[0038] The stress in the tire tread is divided into multiple stress zones;

[0039] Based on the stress intervals and the stress data, calculate the stress distribution area of ​​each stress interval;

[0040] Calculate the ratio of the stress distribution area to the effective area in each stress interval to obtain the cumulative probability of stress distribution within the stress interval;

[0041] Based on the stress data and the cumulative probability of the stress distribution, the shape and volume parameters in the Weiber distribution function are calculated to obtain the stress distribution model.

[0042] In some embodiments of this application, the processing module is further configured to perform line fitting on the first set of pixels after removing edge pixels in the original 2D point cloud map to obtain a first straight line, calculate the first rotation angle required to rotate the first straight line to be parallel to the horizontal X-axis, and rotate the first set of pixels by the first rotation angle to obtain a first point cloud set.

[0043] The second rotation angle required to eliminate the influence of the concave or convex points is obtained from the first point cloud set, and a second point cloud set is obtained by removing the concave or convex points from the first point cloud set and rotating by the second rotation angle.

[0044] The third rotation angle required to eliminate the influence of interference points is obtained based on the second point cloud set;

[0045] The pixels in the original 2D point cloud image are rotated by the first rotation angle, the second rotation angle, and the third rotation angle respectively to obtain the point cloud data.

[0046] To achieve the above objectives, the present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor runs the computer program stored in the memory, the processor executes the method for predicting tire uniformity by scanning and pressure distribution of finished tires.

[0047] To achieve the above objectives, the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the processor performs the method for predicting tire uniformity of a finished tire by scanning and pressure distribution.

[0048] This invention provides a method and system for predicting tire uniformity of finished tires through scanning and pressure distribution. Compared with the prior art, its advantages are as follows:

[0049] This invention acquires and analyzes tire point cloud data attributes, removes noise points to obtain an original 2D point cloud image, and establishes a theoretical and practical model reconstruction system based on the point cloud data attributes and the original 2D point cloud image. Based on the theoretical and practical model reconstructions, the shape and volume of concave or convex points deviating from the basic tire contour are determined, and a mass and size distribution map is established. Stress is applied to the tire tread, and a stress distribution model of the tread is obtained. Based on the mass and size distribution map and the stress distribution map of the tread, a two-dimensional model of tire uniformity is established to perform tire uniformity testing and predict the magnitude and changes of force generated by the tire during rotation at different speeds. This invention calculates the non-uniformity of tire geometry and mass distribution through point cloud processing, analyzes the tread stress distribution by applying stress, correlates it with the tire's uniformity at low and high speeds, and establishes a database. Through a calculation system, it can predict the magnitude of tire force variations and vibrations without requiring uniformity testing, enabling efficient inspection of tires produced in large batches. Attached Figure Description

[0050] Figure 1 This is a flowchart of the method for predicting tire uniformity by scanning and pressure distribution of finished tires according to the present invention;

[0051] Figure 2 This is a functional block diagram of the system for predicting tire uniformity by scanning and pressure distribution of finished tires according to the present invention. Detailed Implementation

[0052] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0053] In the description of this application, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0054] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0055] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the communication between the inner sides of two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0056] Tire uniformity properties are generally classified into dimensional (or geometric) and mass variables. Uniformity testing typically evaluates uniformity by measuring the changes in forces generated by the tire during rotation. The testing method involves applying a tire to a drum simulating a road surface under a specified air pressure load. The drum is rotated while maintaining a slip and camber angle of "0". The magnitude and changes in forces generated during tire rotation are measured, including radial, lateral, and tangential forces. Generally, there are two methods for measuring tire uniformity: low-speed testing machines used in factories and high-speed testing machines used in research. However, due to the high cost and precision requirements of the equipment, even slight deviations during tire assembly and testing can cause significant errors. Therefore, predicting tire uniformity without relying on precision equipment is a pressing technical problem that needs to be solved by those skilled in the art.

[0057] Therefore, this invention provides a method and system for predicting tire uniformity of finished tires through scanning and pressure distribution. By using point cloud processing, the method calculates the size and mass non-uniform distribution of the deviation from the baseline, combines the tire tread stress distribution with low-speed and high-speed uniformity, establishes a database, and uses a calculation system to predict the magnitude and force changes generated when the tire rotates at different speeds without uniformity testing.

[0058] See Figure 1 As shown, the present invention provides a method for predicting tire uniformity of finished tires by scanning and pressure distribution, comprising:

[0059] Step S1: Obtain tire point cloud data attributes, analyze the point cloud data attributes, and remove noise points to obtain the original 2D point cloud map;

[0060] Step S2: Based on the point cloud data attributes and the original 2D point cloud map, establish a theoretical model reconstruction and actual model reconstruction system. Based on the theoretical model reconstruction and actual model reconstruction, determine the shape and volume of the concave or convex points of the tire that deviate from the basic tire contour, and establish a mass and size distribution map.

[0061] Step S3: Apply stress to the tire tread and obtain the stress distribution model of the tread;

[0062] Step S4: Based on the mass and size distribution map and the stress distribution map of the tread, establish a two-dimensional model of tire uniformity to conduct a uniformity test on the tire and predict the magnitude and change of the force generated by the tire when rotating at different speeds.

[0063] In one specific embodiment of this application, step S2 further includes:

[0064] The pixels in the original 2D point cloud image are rotated in parallel to obtain point cloud data, and the straight line fitted based on the pixels located on the tire tread in the point cloud data is parallel to the horizontal X-axis.

[0065] The gradient analysis method is applied to locate concave or convex points based on point cloud data;

[0066] The volume of concave or convex points is calculated using bilateral or unilateral measurements based on point cloud data.

[0067] Step S3 also includes:

[0068] Obtain the stress data of the tire tread and calculate the effective area of ​​the tire tread based on the stress data;

[0069] The stress on the tire tread is divided into multiple stress zones;

[0070] Based on the stress range and stress data, calculate the stress distribution area of ​​each stress range;

[0071] Calculate the ratio of the stress distribution area to the effective area in each stress interval to obtain the cumulative probability of stress distribution within the stress interval;

[0072] The shape and volume parameters in the Weiber distribution function are calculated based on stress data and cumulative probability of stress distribution to obtain a stress distribution model.

[0073] Its beneficial effects are as follows: by establishing mathematical models and numerical values ​​to reflect the distribution law and concentration effect of stress respectively, it is possible to reflect the distribution law and concentration effect of stress applied to the tire surface more intuitively and objectively. Through the stress distribution model, relevant data on the uniformity of the tire tread can be obtained more intuitively and accurately.

[0074] The pixels in the original 2D point cloud image are rotated in parallel to obtain point cloud data such that the straight line fitted based on the pixels located on the tread surface in the point cloud data is parallel to the horizontal X-axis, including:

[0075] The first straight line is obtained by fitting a straight line to the first set of pixels after removing edge pixels from the original 2D point cloud map. The first rotation angle required to rotate the first straight line to be parallel to the horizontal X-axis is calculated. The first set of pixels is rotated by the first rotation angle to obtain the first point cloud set.

[0076] The second rotation angle required to eliminate the influence of concave or convex points is obtained from the first point cloud set, and the second point cloud set is obtained by removing concave or convex points from the first point cloud set and rotating by the second rotation angle.

[0077] The third rotation angle required to eliminate the influence of interference points is obtained based on the second point cloud set;

[0078] The pixels in the original 2D point cloud image are rotated by the first rotation angle, the second rotation angle, and the third rotation angle respectively to obtain the point cloud data.

[0079] Its beneficial effects are as follows: the pixels in the original 2D point cloud map are rotated by the first rotation angle α so that the overall trend of the rotated pixels is parallel to the horizontal X-axis. The influence of concave or convex points can be eliminated by rotating by the second rotation angle β. The influence of interference points caused by the tire deviating from the basic tire part can be further eliminated by rotating by the third rotation angle γ. The final point cloud data is close to the horizontal X-axis, which can make the volume calculation of concave or convex points more accurate.

[0080] Based on the same technical concept, see [reference] Figure 2 As shown, the present invention also provides a system for predicting tire uniformity of finished tires by scanning and pressure distribution, comprising:

[0081] The acquisition module is used to acquire tire point cloud data attributes, analyze the point cloud data attributes, and remove noise points to obtain the original 2D point cloud map.

[0082] The processing module is used to establish a theoretical model reconstruction and actual model reconstruction system based on point cloud data attributes and the original 2D point cloud map. Based on the theoretical model reconstruction and actual model reconstruction, it determines the shape and volume of the concave or convex points of the tire that deviate from the basic tire contour, and establishes a mass and size distribution map.

[0083] The testing module is used to apply stress to the tire tread and obtain a stress distribution model of the tread.

[0084] The analysis module is used to build a two-dimensional model of tire uniformity based on the mass and size distribution map and the stress distribution map of the tread, to conduct tire uniformity tests, and to predict the magnitude and change of the force generated by the tire when rotating at different speeds.

[0085] In one specific embodiment of this application, the processing module is further configured to perform parallel rotation on the pixels in the original 2D point cloud image to obtain point cloud data, and to make the straight line fitted based on the pixels located on the tread of the tire in the point cloud data parallel to the horizontal X-axis.

[0086] The gradient analysis method is applied to locate concave or convex points based on point cloud data;

[0087] The volume of concave or convex points is calculated using bilateral or unilateral measurements based on point cloud data.

[0088] The testing module is also used to acquire tread stress data and calculate the effective tread area based on the tread stress data.

[0089] The stress on the tire tread is divided into multiple stress zones;

[0090] Based on the stress range and stress data, calculate the stress distribution area of ​​each stress range;

[0091] Calculate the ratio of the stress distribution area to the effective area in each stress interval to obtain the cumulative probability of stress distribution within the stress interval;

[0092] The shape and volume parameters in the Weiber distribution function are calculated based on stress data and cumulative probability of stress distribution to obtain a stress distribution model.

[0093] Its beneficial effects are as follows: by establishing mathematical models and numerical values ​​to reflect the distribution law and concentration effect of stress respectively, it is possible to reflect the distribution law and concentration effect of stress applied to the tire surface more intuitively and objectively. Through the stress distribution model, relevant data on the uniformity of the tire tread can be obtained more intuitively and accurately.

[0094] The processing module is also used to perform line fitting on the first set of pixels after removing edge pixels in the original 2D point cloud map to obtain a first straight line, calculate the first rotation angle required to rotate the first straight line to be parallel to the horizontal X-axis, and rotate the first set of pixels by the first rotation angle to obtain the first point cloud set.

[0095] The second rotation angle required to eliminate the influence of concave or convex points is obtained from the first point cloud set, and the second point cloud set is obtained by removing concave or convex points from the first point cloud set and rotating by the second rotation angle.

[0096] The third rotation angle required to eliminate the influence of interference points is obtained based on the second point cloud set;

[0097] The pixels in the original 2D point cloud image are rotated by the first rotation angle, the second rotation angle, and the third rotation angle respectively to obtain the point cloud data.

[0098] Its beneficial effects are as follows: the pixels in the original 2D point cloud map are rotated by the first rotation angle α so that the overall trend of the rotated pixels is parallel to the horizontal X-axis. The influence of concave or convex points can be eliminated by rotating by the second rotation angle β. The influence of interference points caused by the tire deviating from the basic tire part can be further eliminated by rotating by the third rotation angle γ. The final point cloud data is close to the horizontal X-axis, which can make the volume calculation of concave or convex points more accurate.

[0099] Based on the same technical concept, the present invention also discloses a computer device, including a memory and a processor. The memory stores a computer program. When the processor runs the computer program stored in the memory, the processor executes the method for predicting tire uniformity by scanning and pressure distribution of finished tires.

[0100] The computing device may include a processor, a communication interface, a memory, and a communication bus. The processor, communication interface, and memory communicate with each other via the communication bus. The communication interface is used to communicate with other devices, such as clients or other server network elements. The processor is used to execute programs, specifically the steps in the method embodiment for predicting tire uniformity by scanning and pressure distribution of finished tires.

[0101] Based on the same technical concept, the present invention also discloses a computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor, the processor executes the method for predicting tire uniformity by scanning and pressure distribution of the finished tire.

[0102] According to the first concept of the present invention, the present invention calculates the size and mass non-uniform distribution of the deviation from the baseline by point cloud processing, and combines it with the tread stress distribution of the tire, so as to predict the magnitude and force change of the tire when rotating at different speeds without the need for a testing machine to perform uniformity testing.

[0103] According to a second concept of the present invention, by combining the low-speed and high-speed uniformity of tires to establish a database, and through a calculation system, the invention can predict the magnitude of tire force variation and vibration without uniformity testing, thus greatly improving the detection efficiency.

[0104] In summary, this invention provides a method and system for predicting tire uniformity by scanning and pressure distribution of finished tires. By simulating finished tires and using point cloud processing, the method calculates the size and mass non-uniform distribution of deviations from the baseline. Combined with the tire tread stress distribution, it can predict the magnitude and force changes generated when the tire rotates at different speeds without the need for traditional uniformity testing.

[0105] The above description is merely one embodiment of the present invention, but it cannot be used to limit the scope of the present invention. Any structural changes made based on the present invention, as long as they do not lose the essence of the present invention, should be considered as falling within the protection scope of the present invention and subject to its restrictions.

[0106] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process and related descriptions of the system described above can be found in the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0107] It should be noted that the system provided in the above embodiments is only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the modules or steps in the embodiments of the present invention can be further decomposed or combined. For example, the modules in the above embodiments can be merged into one module, or further divided into multiple sub-modules to complete all or part of the functions described above. The names of the modules and steps involved in the embodiments of the present invention are only for distinguishing the various modules or steps and are not considered as an improper limitation of the present invention.

[0108] Those skilled in the art will recognize that the modules and method steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. The programs corresponding to the software modules and method steps can be placed in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disks, removable disks, CD-ROMs, or any other form of storage medium known in the art. To clearly illustrate the interchangeability of electronic hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in electronic hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the invention.

[0109] The term "comprising" or any other similar term is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus / device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent in such process, method, article, or apparatus / device.

[0110] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will all fall within the scope of protection of the present invention.

[0111] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention.

Claims

1. A method for predicting tire uniformity of finished tires by scanning and pressure distribution, characterized in that, include: Step S1: Obtain tire point cloud data attributes, analyze the point cloud data attributes, and remove noise points to obtain the original 2D point cloud map; Step S2: Based on the point cloud data attributes and the original 2D point cloud map, establish a theoretical model reconstruction and actual model reconstruction system. Based on the theoretical model reconstruction and actual model reconstruction, determine the shape and volume of the concave or convex points of the tire that deviate from the basic tire contour, and establish a mass and size distribution map. Step S3: Apply stress to the tread of the tire and obtain a stress distribution model of the tread; Step S4: Based on the mass and size distribution map and the stress distribution map of the tread, establish a two-dimensional model of tire uniformity to conduct a uniformity test on the tire, and predict the magnitude and change of the force generated by the tire when rotating at different speeds.

2. The method for predicting tire uniformity of a finished tire by scanning and pressure distribution according to claim 1, characterized in that, Step S2 also includes: The pixels in the original 2D point cloud image are rotated in parallel to obtain point cloud data, and the straight line fitted based on the pixels located on the tread of the tire in the point cloud data is parallel to the horizontal X-axis. The concave or convex points are located by applying gradient analysis methods based on the point cloud data. The volume of the concave or convex point is calculated using bilateral or unilateral measurements based on the point cloud data.

3. The method for predicting tire uniformity of a finished tire by scanning and pressure distribution according to claim 1, characterized in that, Step S3 also includes: Obtain the stress data of the tread and calculate the effective area of ​​the tread based on the stress data; The stress in the tire tread is divided into multiple stress zones; Based on the stress intervals and the stress data, calculate the stress distribution area of ​​each stress interval; Calculate the ratio of the stress distribution area to the effective area in each stress interval to obtain the cumulative probability of stress distribution within the stress interval; Based on the stress data and the cumulative probability of the stress distribution, the shape and volume parameters in the Weiber distribution function are calculated to obtain the stress distribution model.

4. The method for predicting tire uniformity of a finished tire by scanning and pressure distribution according to claim 2, characterized in that, The pixels in the original 2D point cloud image are rotated in parallel to obtain point cloud data such that the straight line fitted based on the pixels located on the tread surface in the point cloud data is parallel to the horizontal X-axis, including: A first straight line is obtained by fitting a straight line to the first set of pixels after removing edge pixels in the original 2D point cloud map. The first rotation angle required to rotate the first straight line to be parallel to the horizontal X-axis is calculated. The first set of pixels is then rotated by the first rotation angle to obtain the first point cloud set. The second rotation angle required to eliminate the influence of the concave or convex points is obtained from the first point cloud set, and a second point cloud set is obtained by removing the concave or convex points from the first point cloud set and rotating by the second rotation angle. The third rotation angle required to eliminate the influence of interference points is obtained based on the second point cloud set; The pixels in the original 2D point cloud image are rotated by the first rotation angle, the second rotation angle, and the third rotation angle respectively to obtain the point cloud data.

5. A system for predicting tire uniformity of finished tires by scanning and pressure distribution, characterized in that, include: The acquisition module is used to acquire tire point cloud data attributes, analyze the point cloud data attributes, and remove noise points to obtain the original 2D point cloud map. The processing module is used to establish a theoretical model reconstruction and actual model reconstruction system based on the point cloud data attributes and the original 2D point cloud map, determine the shape and volume of the concave or convex points of the tire that deviate from the basic tire contour based on the theoretical model reconstruction and actual model reconstruction, and establish a mass and size distribution map. The testing module is used to apply stress to the tread of the tire and obtain a stress distribution model of the tread. The analysis module is used to establish a two-dimensional model of tire uniformity based on the mass and size distribution map and the stress distribution map of the tread to conduct uniformity tests on the tire and predict the magnitude and change of the force generated by the tire when rotating at different speeds.

6. A system for predicting tire uniformity of a finished tire by scanning and pressure distribution according to claim 5, characterized in that, The processing module is also used to perform parallel rotation on the pixels in the original 2D point cloud image to obtain point cloud data, and to make the straight line fitted based on the pixels located on the tread of the tire in the point cloud data parallel to the horizontal X-axis. The concave or convex points are located by applying gradient analysis methods based on the point cloud data. The volume of the concave or convex point is calculated using bilateral or unilateral measurements based on the point cloud data.

7. A system for predicting tire uniformity of a finished tire by scanning and pressure distribution according to claim 5, characterized in that, The test module is also used to acquire stress data of the tread and calculate the effective area of ​​the tread based on the stress data of the tread. The stress in the tire tread is divided into multiple stress zones; Based on the stress intervals and the stress data, calculate the stress distribution area of ​​each stress interval; Calculate the ratio of the stress distribution area to the effective area in each stress interval to obtain the cumulative probability of stress distribution within the stress interval; Based on the stress data and the cumulative probability of the stress distribution, the shape and volume parameters in the Weiber distribution function are calculated to obtain the stress distribution model.

8. A system for predicting tire uniformity of a finished tire by scanning and pressure distribution according to claim 6, characterized in that, The processing module is further configured to perform line fitting on the first pixel set after removing edge pixels in the original 2D point cloud map to obtain a first straight line, calculate the first rotation angle required to rotate the first straight line to be parallel to the horizontal X-axis, and rotate the first pixel set by the first rotation angle to obtain the first point cloud set. The second rotation angle required to eliminate the influence of the concave or convex points is obtained from the first point cloud set, and a second point cloud set is obtained by removing the concave or convex points from the first point cloud set and rotating by the second rotation angle. The third rotation angle required to eliminate the influence of interference points is obtained based on the second point cloud set; The pixels in the original 2D point cloud image are rotated by the first rotation angle, the second rotation angle, and the third rotation angle respectively to obtain the point cloud data.

9. A computer device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program, and when the processor runs the computer program stored in the memory, the processor executes a method for predicting tire uniformity by scanning and pressure distribution of the finished tire according to any one of claims 1-4.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the processor performs a method for predicting tire uniformity by scanning and pressure distribution of the finished tire according to any one of claims 1-4.

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