Tire eccentricity determination method and device, electronic equipment and medium
By performing image processing and Fourier transform on tire surface information, the tire eccentricity is calculated, and the problems of cumbersome and inefficient manual operation in the prior art are solved, achieving more efficient and accurate detection.
Patent Information
- Application Number
- CN202510157098.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-02-12
- Publication Date
- 2025-05-16
AI Technical Summary
In the prior art, tire eccentricity detection relies on manual operation, resulting in cumbersome operation, low efficiency, and easy to cause problems of collision with tires, resulting in detection failure.
By acquiring tire surface information to form an image to be processed, data in the area to be detected is extracted, invalid data removal and Fourier transformation are performed, and tire eccentricity is calculated, including fluctuation values, harmonic values, bulge values and depression values.
It improves the accuracy and efficiency of tire eccentricity detection, expands the detection area, simplifies the operation process, and improves the accuracy of detection.
Smart Images
Figure CN120013922A_ABST
Abstract
Description
Technical Field
[0001] The present disclosure relates to the technical field of tire testing, and in particular to a method, device, electronic device and medium for determining tire eccentricity. Background Art
[0002] Tires are circular elastic rubber products that roll on the ground and are installed on various vehicles or machines. They are usually installed on metal rims, can support the vehicle body, buffer external impacts, achieve contact with the road surface and ensure the driving performance of the vehicle. Tires are often used under complex and harsh conditions. They are subjected to various deformations, loads, forces, and high and low temperature effects when driving, so they must have high load-bearing performance, traction performance, and buffering performance. At the same time, they are also required to have high wear resistance and flex resistance, as well as low rolling resistance and heat generation.
[0003] Tires are the only parts of a car that come into contact with the ground. The performance of tires directly affects the safety of vehicle drivers and passengers. The importance of tire performance can be imagined. For this reason, various countries have also made clear requirements for tire safety performance.
[0004] In order to improve the safety of tires, it is necessary to test the eccentricity of the tires. The tire eccentricity device is a special equipment for fully automatic online detection of tire fluctuations, harmonics, bulges and depressions.
[0005] In the prior art, when measuring eccentricity through a tire eccentricity device, the measurement is mainly performed manually, which is not only cumbersome and inefficient, but also has poor consistency in multiple operations. In addition, manual operation is prone to causing tire collisions, resulting in detection failure.
[0006] Therefore, how to improve the accuracy and efficiency of tire eccentricity detection during the tire eccentricity detection process is a technical problem that technical personnel in this field need to solve urgently. Summary of the invention
[0007] The embodiments of the present disclosure provide a method, device, electronic device and medium for determining the eccentricity of a tire. For a detection area of a to-be-tested image formed by the tire to be tested, the embodiments of the present disclosure can calculate the eccentricity of the tire to be tested through the detection area, thereby improving accuracy and calculation efficiency.
[0008] In one aspect, an embodiment of the present disclosure provides a method for determining tire eccentricity, the method comprising: Acquiring an image to be processed formed based on surface information of the tire to be tested; Acquire the data to be processed in the to-be-detected area in the above-mentioned image to be processed, wherein the above-mentioned data to be processed includes at least two groups of one-dimensional arrays; Removing invalid data from each one-dimensional array of the data to be processed to obtain the data to be processed after the invalid data is removed; Performing Fourier transformation on each one-dimensional array of the data to be processed after the invalid data is removed, to obtain the data to be processed after Fourier transformation; The tire eccentricity is calculated for the Fourier transformed data to be processed to determine the eccentricity of the tire to be tested.
[0009] In an optional embodiment, the tire eccentricity is calculated for the data to be processed after the Fourier transform to determine the eccentricity of the tire to be tested, including: for each group of one-dimensional arrays in the data to be processed after the Fourier transform, the difference between the maximum value and the minimum value in each group of one-dimensional arrays is determined, and the difference between the maximum value and the minimum value in each group of one-dimensional arrays is recorded as the fluctuation value; for the fluctuation values corresponding to each obtained one-dimensional array, the maximum fluctuation value among the fluctuation values corresponding to each one-dimensional array is determined, and the maximum fluctuation value is used as the tire fluctuation value of the tire to be tested, wherein the eccentricity of the tire to be tested includes the tire fluctuation value.
[0010] In an optional embodiment, the above-mentioned calculation of tire eccentricity of the data to be processed after the Fourier transform to determine the eccentricity of the above-mentioned tire to be tested includes: for each group of one-dimensional arrays in the data to be processed after the Fourier transform, determining the harmonic components based on integer multiples of the fundamental wave in each group of one-dimensional arrays, wherein the above-mentioned fundamental wave is determined after Fourier transforming each group of one-dimensional arrays in the data to be processed after the invalid data is removed; for the harmonic components corresponding to each obtained one-dimensional array, determining the maximum harmonic component among the harmonic components corresponding to each one-dimensional array, and using the above-mentioned maximum harmonic component as the tire first harmonic of the above-mentioned tire to be tested, wherein the eccentricity of the above-mentioned tire to be tested includes the above-mentioned tire first harmonic.
[0011] In an optional embodiment, the above-mentioned calculation of tire eccentricity of the data to be processed after the Fourier transform is performed to determine the eccentricity of the tire to be tested, including: for each group of one-dimensional arrays in the data to be processed after the Fourier transform, a translation operation is performed on each group of one-dimensional data based on a preset window to determine the bulge value and the depression value in each group of one-dimensional array; for the bulge values corresponding to each obtained one-dimensional array, the maximum bulge value among the bulge values corresponding to each one-dimensional array is determined, and the above-mentioned maximum bulge value is used as the tire bulge value of the tire to be tested, wherein the eccentricity of the tire to be tested includes the above-mentioned tire bulge value; for the depression values corresponding to each obtained one-dimensional array, the maximum depression value among the depression values corresponding to each one-dimensional array is determined, and the above-mentioned maximum depression value is used as the tire depression value of the tire to be tested, wherein the eccentricity of the tire to be tested includes the above-mentioned tire depression value.
[0012] In an optional embodiment, performing a translation operation on each set of one-dimensional data based on a preset window to determine the bulge value and the concave value in each set of one-dimensional array includes: For any set of one-dimensional data, a translation operation is sequentially performed on the set of one-dimensional data based on the preset window; For a group of selected data segments selected when any one of the group of one-dimensional data is translated by the preset window, dividing the selected data segments into left data and right data based on the preset window; Determine the minimum values of the left portion of data and the right portion of data, respectively, record them as left minimum value and right minimum value, and determine the middle value located between the left minimum value and the right minimum value based on the left minimum value and the right minimum value; Determine the bulge value and the depression value to be selected corresponding to the selected data segment in the following manner: The selected bulge value = middle value - (left minimum value + right minimum value) / 2; The selected concave value = (left minimum value + right minimum value) / 2-middle value; Until the above-mentioned preset window translation operation is completed for all the selected data segments in the above-mentioned group of one-dimensional data, if there is at least one to-be-selected bulge value and at least one to-be-selected depression value, then the largest to-be-selected bulge value is selected from the above-mentioned at least one to-be-selected bulge value to be determined as the corresponding bulge value of the above-mentioned group of one-dimensional arrays, and the largest to-be-selected depression value is selected from the above-mentioned at least one to-be-selected depression value to be determined as the depression value of the above-mentioned group of one-dimensional arrays.
[0013] In an optional embodiment, the above-mentioned acquisition of the image to be processed formed based on the surface information of the tire to be tested includes: collecting the surface information of the tire to be tested based on the tire information scanning module and the encoder, and obtaining height information about the distance between the surface of the tire to be tested and the tire information scanning module; determining the maximum height value and the minimum height value in the above-mentioned height information; and performing image drawing based on the above-mentioned maximum height value and the above-mentioned minimum height value, and a preset color template to obtain the above-mentioned image to be processed.
[0014] On the one hand, an embodiment of the present disclosure provides a device for determining tire eccentricity, the device comprising: A first acquisition module, used for acquiring an image to be processed formed based on surface information of the tire to be tested; A second acquisition module is used to acquire the data to be processed in the to-be-detected area in the to-be-processed image, wherein the data to be processed includes at least two groups of one-dimensional arrays; A first processing module is used to remove invalid data from each one-dimensional array in the above-mentioned data to be processed, so as to obtain the data to be processed after the invalid data is removed; A second processing module is used to perform Fourier transform on each one-dimensional array of the data to be processed after the invalid data is removed, so as to obtain the data to be processed after Fourier transform; The determination module is used to calculate the tire eccentricity of the data to be processed after the Fourier transform, and determine the eccentricity of the tire to be tested.
[0015] In an optional embodiment, the above-mentioned determination module is specifically used to: for each group of one-dimensional arrays in the data to be processed after the above-mentioned Fourier transform, determine the difference between the maximum value and the minimum value in each group of one-dimensional arrays, and record the difference between the maximum value and the minimum value in each group of one-dimensional arrays as the fluctuation value; for the fluctuation values corresponding to each obtained one-dimensional array, determine the maximum fluctuation value among the fluctuation values corresponding to each one-dimensional array, and use the above-mentioned maximum fluctuation value as the tire fluctuation value of the above-mentioned tire to be tested, wherein the eccentricity of the above-mentioned tire to be tested includes the above-mentioned tire fluctuation value.
[0016] In an optional embodiment, the determination module is specifically used to: for each group of one-dimensional arrays in the data to be processed after the Fourier transform, determine the harmonic components based on integer multiples of the fundamental wave in each group of one-dimensional arrays, wherein the fundamental wave is determined after Fourier transforming each group of one-dimensional arrays in the data to be processed after the invalid data is removed; for the harmonic components corresponding to each obtained one-dimensional array, determine the maximum harmonic component among the harmonic components corresponding to each one-dimensional array, and use the maximum harmonic component as the first harmonic of the tire to be tested, wherein the eccentricity of the tire to be tested includes the first harmonic of the tire.
[0017] In an optional embodiment, the above-mentioned determination module is specifically used for: for each group of one-dimensional arrays in the data to be processed after the above-mentioned Fourier transform, performing a translation operation on each group of one-dimensional data based on a preset window, and determining the bulge value and the depression value in each group of one-dimensional array; for the bulge values corresponding to each obtained one-dimensional array, determining the maximum bulge value among the bulge values corresponding to each one-dimensional array, and using the above-mentioned maximum bulge value as the tire bulge value of the above-mentioned tire to be tested, wherein the eccentricity of the above-mentioned tire to be tested includes the above-mentioned tire bulge value; for the depression values corresponding to each obtained one-dimensional array, determining the maximum depression value among the depression values corresponding to each one-dimensional array, and using the above-mentioned maximum depression value as the tire depression value of the above-mentioned tire to be tested, wherein the eccentricity of the above-mentioned tire to be tested includes the above-mentioned tire bulge value.
[0018] In an optional embodiment, the above-mentioned determination module is specifically used for: For any set of one-dimensional data, a translation operation is sequentially performed on the set of one-dimensional data based on the preset window; For a group of selected data segments selected when any one of the group of one-dimensional data is translated by the preset window, dividing the selected data segments into left data and right data based on the preset window; Determine the minimum values of the left portion of data and the right portion of data, respectively, record them as left minimum value and right minimum value, and determine the middle value located between the left minimum value and the right minimum value based on the left minimum value and the right minimum value; Determine the bulge value and the depression value to be selected corresponding to the selected data segment in the following manner: The selected bulge value = middle value - (left minimum value + right minimum value) / 2; The selected concave value = (left minimum value + right minimum value) / 2-middle value; Until the above-mentioned preset window translation operation is completed for all the selected data segments in the above-mentioned group of one-dimensional data, if there is at least one to-be-selected bulge value and at least one to-be-selected depression value, then the largest to-be-selected bulge value is selected from the above-mentioned at least one to-be-selected bulge value to be determined as the corresponding bulge value of the above-mentioned group of one-dimensional arrays, and the largest to-be-selected depression value is selected from the above-mentioned at least one to-be-selected depression value to be determined as the depression value of the above-mentioned group of one-dimensional arrays.
[0019] In an optional embodiment, the first acquisition module is specifically used to: collect surface information of the tire to be tested based on the tire information scanning module and the encoder, and obtain height information about the distance between the surface of the tire to be tested and the tire information scanning module; determine the maximum height value and the minimum height value in the height information; and draw an image based on the maximum height value and the minimum height value, as well as a preset color template, to obtain the image to be processed.
[0020] On the one hand, an embodiment of the present disclosure provides an electronic device, which includes a processor and a memory, which are interconnected; the memory is used to store computer programs; the processor is configured to execute a method provided by any possible implementation of the above-mentioned method for determining tire eccentricity when calling the above-mentioned computer program.
[0021] On the one hand, an embodiment of the present disclosure provides a computer-readable storage medium storing a computer program, which is executed by a processor to implement a method provided by any possible implementation of the above-mentioned method for determining tire eccentricity.
[0022] On the one hand, an embodiment of the present disclosure provides a computer program product or a computer program, the computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the method provided by any possible implementation of the above-mentioned method for determining tire eccentricity.
[0023] The technical solution provided by the present disclosure has the following beneficial effects: first, an image to be processed formed based on the surface information of the tire to be tested is obtained, the image to be processed includes a region to be detected, the data to be processed in the region to be detected is obtained, the data to be processed includes at least two groups of one-dimensional arrays, each group of one-dimensional arrays in the data to be processed is subjected to an invalid data removal operation, the data to be processed after the invalid data is removed is obtained, each group of one-dimensional arrays in the data to be processed after the invalid data is removed is subjected to a Fourier transform operation, the data to be processed after the Fourier transform is obtained, the tire eccentricity is calculated for the Fourier transformed data to determine the eccentricity of the tire to be tested. Through the embodiments of the present disclosure, on the one hand, the tire eccentricity can be calculated based on the region to be detected of the image to be processed, which greatly expands the detection area of the tire eccentricity and improves the calculation efficiency of the eccentricity detection. On the other hand, the eccentricity is calculated by the image to be processed, and the invalid data removal operation and the Fourier transform operation are adopted, which not only improves the convenience of the eccentricity calculation, but also improves the accuracy of the eccentricity calculation. BRIEF DESCRIPTION OF THE DRAWINGS
[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings required for describing the embodiments of the present disclosure are briefly introduced below.
[0025] Figure 1 A schematic flow chart of a method for determining tire eccentricity provided in an embodiment of the present disclosure; Figure 2 A schematic diagram of an image to be processed provided by an embodiment of the present disclosure; Figure 3 A schematic structural diagram of a device for determining tire eccentricity provided in an embodiment of the present disclosure; Figure 4 A schematic diagram of the structure of an electronic device for determining tire eccentricity provided in an embodiment of the present disclosure. DETAILED DESCRIPTION
[0026] The embodiments of the present disclosure are described below in conjunction with the drawings in the present disclosure. It should be understood that the implementation methods described below in conjunction with the drawings are exemplary descriptions for explaining the technical solutions of the embodiments of the present disclosure and do not constitute a limitation on the technical solutions of the embodiments of the present disclosure.
[0027] It will be understood by those skilled in the art that, unless specifically stated, the singular forms "one", "above", and "the" used herein may also include plural forms. It should be further understood that the terms "including" and "comprising" used in the embodiments of the present disclosure refer to that the corresponding features can be implemented as the presented features, information, data, steps, operations, elements and / or components, but do not exclude the implementation as other features, information, data, steps, operations, elements, components and / or combinations thereof supported by the technical field. It should be understood that when we refer to an element as being "connected" or "coupled" to another element, the one element may be directly connected or coupled to the other element, or may refer to the one element and the other element establishing a connection relationship through an intermediate element. In addition, the "connection" or "coupling" used herein may include wireless connection or wireless coupling. The term "and / or" used herein indicates at least one of the items defined by the term, for example, "A and / or B" or "A, B" indicates implementation as "A", or implementation as "B", or implementation as "A and B".
[0028] In order to make the objectives, technical solutions and advantages of the present disclosure more clear, the embodiments of the present disclosure will be further described in detail below with reference to the accompanying drawings.
[0029] See also Figure 1 , Figure 1 A schematic diagram of a method for determining tire eccentricity provided in an embodiment of the present disclosure is shown in FIG. Figure 1 As shown, the method for determining tire eccentricity provided by the embodiment of the present disclosure includes the following steps: Step S101, obtaining an image to be processed formed based on surface information of a tire to be tested; Step S102, obtaining the data to be processed in the to-be-detected area in the to-be-processed image, wherein the data to be processed includes at least two groups of one-dimensional arrays; Step S103, removing invalid data from each one-dimensional array of the data to be processed, to obtain the data to be processed after the invalid data is removed; Step S104, performing Fourier transform on each one-dimensional array of the data to be processed after the invalid data is removed, to obtain the data to be processed after Fourier transform; Step S105, calculating the tire eccentricity of the Fourier transformed data to be processed to determine the eccentricity of the tire to be tested.
[0030] Optionally, a line scan sensor may be used to collect height information of the surface of the tire to be tested that is consistent with the rotation direction of the encoder, wherein the line scan sensor may be understood as a laser sensor, and the height information is formed by the distance from the line scan sensor to the surface of the tire to be tested. The scanning sensor is a sensor that reads only one pixel at a time, and usually scans the image row by row or column by column during the exposure time to generate an image point by point. In this embodiment, the line scan sensor may draw a 2D image (plane image) with different colors according to different height information, and the 2D image is the above-mentioned image to be processed.
[0031] In order to more clearly understand the formation process of the image to be processed, how to obtain the image to be processed is described in detail below in conjunction with an embodiment.
[0032] In an optional embodiment, the step of obtaining the image to be processed formed based on the surface information of the tire to be tested includes: Collecting surface information of the tire to be tested based on the tire information scanning module and the encoder, and obtaining height information about the distance between the surface of the tire to be tested and the tire information scanning module; Determine the maximum height value and the minimum height value in the above height information; Based on the maximum height value, the minimum height value, and the preset color template, image drawing is performed to obtain the image to be processed.
[0033] Optionally, the tire information scanning module is the line scanning sensor. The tire information scanning module and the encoder can be rotated to scan the surface information of the tire to be tested, and obtain the height information about the distance between the tire information scanning module and the surface of the tire to be tested.
[0034] The preset color template has colors that can increase from dark blue to dark red. The setting procedure is as follows: m_palette = new List <color>(); m_palette.Add(Color.FromArgb(0,0,160)); …… m_palette.Add(Color.FromArgb(128,64,64)); m_palette.Add(Color.FromArgb(211,211,211)); m_res_palette = new List <color>(m_palette); Then, the maximum value Max (i.e., the maximum height value) and the minimum value Min (i.e., the minimum height value) are found using the collected height information. Based on the maximum value Max and the minimum value Min, the height interval is determined. The height interval is the interval of the corresponding color array. The minimum value Min corresponds to dark blue, and the maximum value Max corresponds to dark red. According to this correspondence, the image is drawn based on the color template to obtain the above 2D image (i.e., the image to be processed). Figure 2 As shown, Figure 2 A schematic diagram of an image to be processed provided in an embodiment of the present disclosure. Figure 2 The image to be processed shown in the figure is a grayscale image. In actual application, the image drawn is a color 2D image. In this way, the distance between the line scan sensor and the tire to be tested can be better displayed. For example, the redder the color, the closer the distance between the line scan sensor and the tire surface, which better reflects the different heights of the tires.
[0035] Then, the area to be processed is selected on the image to be processed, and the area is the above-mentioned area to be detected. The selection criteria of the area to be detected is a smooth area, that is, an area without characters or patterns. The area to be detected is manually preset, such as Figure 2 As shown in the figure, the black frame area is the area to be detected.
[0036] Based on the area to be detected, the data to be processed in the area is obtained, that is, the image information of the area to be detected is converted into array information, wherein the data to be processed includes at least two groups of one-dimensional arrays. It can be understood that the amount of the data to be processed is related to the size of the area to be detected. The larger the area to be detected, the larger the amount of data to be processed, and the larger the area to be detected, the faster the speed of detecting the eccentricity of the tire to be tested.
[0037] For each one-dimensional array in the data to be processed, invalid data is removed from the one-dimensional data. If invalid data exists, the invalid data is removed, and based on other valid data, the data at the position of the original invalid data is determined to obtain the data to be processed after the invalid data is removed. For example, assume that any one-dimensional array is as follows: [535.4774,535.4606,3.40282346638529E+38,535.4718,535.5082,535.5894,535.6286], where 3.40282346638529E+38 is the invalid data in the one-dimensional array. The data is removed and the median filter is used to fill the gap, that is, the average of the two data before and after the invalid data is used as the new data at the invalid data position, and the new one-dimensional array is obtained after the invalid data is removed from the one-dimensional array. It should be noted that the present disclosure does not make any limitation on how to fill the data at the invalid data position.
[0038] When invalid data removal is performed on all one-dimensional arrays in the data to be processed, the data to be processed after the invalid data is removed can be obtained.
[0039] Then, each one-dimensional array of the data to be processed after the invalid data is removed is subjected to Fourier transformation to obtain the data to be processed after Fourier transformation. Then, the tire eccentricity is calculated for the data to be processed after Fourier transformation to determine the eccentricity of the tire to be tested, wherein the tire eccentricity refers to the fluctuation, harmonic, bulge and depression of the tire.
[0040] Through the embodiments of the present disclosure, on the one hand, the eccentricity of the tire can be calculated based on the area to be detected of the image to be processed, which greatly expands the detection area of the tire eccentricity and improves the calculation efficiency of the eccentricity detection. On the other hand, the eccentricity is calculated by using the image to be processed and using invalid data removal operations and Fourier transform operations, which not only improves the convenience of the eccentricity calculation but also improves the accuracy of the eccentricity calculation.
[0041] In order to more clearly explain how the tire eccentricity is calculated, the following uses several examples to illustrate the tire eccentricity of fluctuation, harmonics, bulges and depressions.
[0042] The tire fluctuation value is determined as follows: In an optional embodiment, the above-mentioned calculation of the tire eccentricity of the data to be processed after the Fourier transformation to determine the eccentricity of the tire to be tested includes: For each group of one-dimensional arrays in the data to be processed after Fourier transformation, determine the difference between the maximum value and the minimum value in each group of one-dimensional arrays, and record the difference between the maximum value and the minimum value in each group of one-dimensional arrays as a fluctuation value; For the fluctuation values corresponding to each one-dimensional array obtained, the maximum fluctuation value among the fluctuation values corresponding to each one-dimensional array is determined, and the above maximum fluctuation value is used as the tire fluctuation value of the above tire to be tested, wherein the eccentricity of the above tire to be tested includes the above tire fluctuation value.
[0043] Optionally, an example is provided below to illustrate: Assume that the data to be processed after Fourier transformation contains the following one-dimensional arrays: Array 1 [data1, data2, data3, data4, data5, data6]; Array 2 [data7, data8, data9, data10, data11, data12] Array 3 [data 13, data 14, data 15, data 16, data 17, data 18] Array 4 [data 19, data 20, data 21, data 22, data 23, data 24] For the above-mentioned one-dimensional arrays, determine the difference between the maximum and minimum values in each group of one-dimensional arrays, and record the difference between the maximum and minimum values in each group of one-dimensional arrays as the fluctuation value of the one-dimensional array. In this way, assuming that the maximum value in array 1 is data 1 and the minimum value is data 4, the difference between data 1 and data 4 is recorded as the fluctuation value of array 1. Similarly, the fluctuation values corresponding to arrays 2, 3, and 4 can be obtained.
[0044] Then, based on the fluctuation values corresponding to each one-dimensional array, the maximum fluctuation value among the fluctuation values corresponding to each one-dimensional array is determined. In this way, for the fluctuation value corresponding to array 1, the fluctuation value corresponding to array 2, the fluctuation value corresponding to array 3, and the fluctuation value corresponding to array 4, assuming that the largest fluctuation value among these fluctuation values is the fluctuation value corresponding to array 3, then the fluctuation value corresponding to array 3 can be used as the tire fluctuation value of the tire to be tested.
[0045] Through the embodiments of the present disclosure, the fluctuation value of the tire can be quickly determined by mathematical calculations, thereby improving the calculation efficiency of the tire fluctuation value. At the same time, the tire fluctuation value is determined by the difference between the maximum value and the minimum value, thereby improving the accuracy of calculating the tire fluctuation value.
[0046] The first harmonic of the tire is determined as follows: In an optional embodiment, the above-mentioned calculation of the tire eccentricity of the data to be processed after the Fourier transformation to determine the eccentricity of the tire to be tested includes: For each group of one-dimensional arrays in the data to be processed after the Fourier transform, determine the harmonic components based on integer multiples of the fundamental wave in each group of one-dimensional arrays, wherein the fundamental wave is determined after Fourier transforming each group of one-dimensional arrays in the data to be processed after the invalid data is removed; For the harmonic components corresponding to each obtained one-dimensional array, the maximum harmonic component among the harmonic components corresponding to each one-dimensional array is determined, and the maximum harmonic component is used as the tire first harmonic of the tire to be tested, wherein the eccentricity of the tire to be tested includes the tire first harmonic.
[0047] Optionally, an example is provided below to illustrate: Assume that the data to be processed after Fourier transformation contains the following one-dimensional arrays: Array 1 [data1, data2, data3, data4, data5, data6]; Array 2 [data7, data8, data9, data10, data11, data12] Array 3 [data 13, data 14, data 15, data 16, data 17, data 18] Array 4 [data 19, data 20, data 21, data 22, data 23, data 24] For the above-mentioned one-dimensional arrays, determine the harmonic components based on the fundamental wave integer multiples in each group of one-dimensional arrays, where the fundamental wave refers to the sine wave component equal to the longest period of a complex periodic oscillation, and the frequency corresponding to this period is called the fundamental wave frequency. The fundamental wave is determined by Fourier transforming each group of one-dimensional arrays in the data to be processed after removing invalid data.
[0048] Based on the harmonic components corresponding to each one-dimensional array, the maximum harmonic component among the harmonic components corresponding to each one-dimensional array is determined. In this way, for the harmonic components corresponding to array 1, array 2, array 3, and array 4, assuming that the largest harmonic component among these harmonic components is the harmonic component corresponding to array 4, then the harmonic component corresponding to array 4 can be used as the first harmonic of the tire to be tested.
[0049] Through the embodiments of the present disclosure, the first harmonic of the tire can be quickly determined by mathematical calculation, which not only improves the calculation efficiency of the first harmonic of the tire, but also improves the accuracy of calculating the first harmonic of the tire.
[0050] The tire bulge value and tire dent value are determined as follows: In an optional embodiment, the above-mentioned calculation of the tire eccentricity of the data to be processed after the Fourier transformation to determine the eccentricity of the tire to be tested includes: For each group of one-dimensional arrays in the data to be processed after Fourier transformation, a translation operation is performed on each group of one-dimensional data based on a preset window to determine the bulge value and the concave value in each group of one-dimensional array; For the bulge values corresponding to the obtained one-dimensional arrays, determine the maximum bulge value among the bulge values corresponding to the one-dimensional arrays, and use the maximum bulge value as the tire bulge value of the tire to be tested, wherein the eccentricity of the tire to be tested includes the tire bulge value; For the obtained depression values corresponding to each one-dimensional array, determine the maximum depression value among the depression values corresponding to each one-dimensional array, and use the above maximum depression value as the tire depression value of the tire to be tested, wherein the eccentricity of the tire to be tested includes the above tire depression value.
[0051] Optionally, an example is provided below to illustrate: Assume that the data to be processed after Fourier transformation contains the following one-dimensional arrays: Array 1 [data1, data2, data3, data4, data5, data6]; Array 2 [data7, data8, data9, data10, data11, data12] Array 3 [data 13, data 14, data 15, data 16, data 17, data 18] Array 4 [data 19, data 20, data 21, data 22, data 23, data 24] For the above-mentioned one-dimensional arrays, a translation operation may be performed on each group of one-dimensional data based on a preset window to determine the bulge value and the concave value in each group of one-dimensional array.
[0052] Based on the bulge values corresponding to each one-dimensional array, the maximum bulge value among the bulge values corresponding to each one-dimensional array is determined. In this way, for the bulge values corresponding to array 1, array 2, array 3 and array 4, assuming that the largest bulge value among these bulge values is the bulge value corresponding to array 2, then the bulge value corresponding to array 2 can be used as the tire bulge value of the tire to be tested.
[0053] Based on the depression values corresponding to each one-dimensional array, the maximum depression value among the depression values corresponding to each one-dimensional array is determined. In this way, for the depression values corresponding to array 1, array 2, array 3, and array 4, assuming that the largest depression value among these depression values is the depression value corresponding to array 1, then the depression value corresponding to array 1 can be used as the tire depression value of the tire to be tested.
[0054] In order to more clearly illustrate the process of performing translation operation based on a preset window, a detailed description is given below with reference to an example.
[0055] In an optional embodiment, performing a translation operation on each set of one-dimensional data based on a preset window to determine the bulge value and the concave value in each set of one-dimensional array includes: For any set of one-dimensional data, a translation operation is sequentially performed on the set of one-dimensional data based on the preset window; For a group of selected data segments selected when any one of the group of one-dimensional data is translated by the preset window, dividing the selected data segments into left data and right data based on the preset window; Determine the minimum values of the left portion of data and the right portion of data, respectively, record them as left minimum value and right minimum value, and determine the middle value located between the left minimum value and the right minimum value based on the left minimum value and the right minimum value; Determine the bulge value and the depression value to be selected corresponding to the selected data segment in the following manner: The selected bulge value = middle value - (left minimum value + right minimum value) / 2; The selected concave value = (left minimum value + right minimum value) / 2-middle value; Until the above-mentioned preset window translation operation is completed for all the selected data segments in the above-mentioned group of one-dimensional data, if there is at least one to-be-selected bulge value and at least one to-be-selected depression value, then the largest to-be-selected bulge value is selected from the above-mentioned at least one to-be-selected bulge value to be determined as the corresponding bulge value of the above-mentioned group of one-dimensional arrays, and the largest to-be-selected depression value is selected from the above-mentioned at least one to-be-selected depression value to be determined as the depression value of the above-mentioned group of one-dimensional arrays.
[0056] Optionally, an example is provided below to illustrate: For the preset window, the window is the interval of the median filter. Assuming that 16 degrees is the preset window, each group of one-dimensional arrays contains 2048 data points, that is, 91 data points are used as the window. For each group of one-dimensional arrays, the preset window is used for translation. For any group of selected data segments selected when the preset window is translated, the group of selected data segments is divided into two parts, and the minimum value of the left part of the data is found, recorded as the left minimum value, and the minimum value of the right part of the data is found, recorded as the right minimum value, and the value in the middle of the left minimum value and the right minimum value is determined, recorded as the middle value.
[0057] Determine the candidate bulge value and candidate concave value corresponding to the selected data segment in the following manner: The selected bulge value = middle value - (left minimum value + right minimum value) / 2; The selected concave value = (left minimum value + right minimum value) / 2-middle value; For any group of one-dimensional arrays, the loop is continued until all the data in the one-dimensional array are translated and operated. If there is at least one bulge value to be selected and at least one concave value to be selected, the largest bulge value to be selected is selected from the at least one bulge value to be selected as the bulge value of the corresponding group of one-dimensional arrays, and the largest concave value to be selected from the at least one concave value to be selected is selected as the concave value of the group of one-dimensional arrays.
[0058] Among them, according to the mutual exclusion principle of bulge and depression, at the same position, if a bulge value is determined at that position, then there will be no depression value at that position.
[0059] Through the embodiments of the present disclosure, the tire bulge value and the tire depression value can be quickly determined by mathematical calculation, which not only improves the calculation efficiency of the tire bulge value and the tire depression value, but also improves the accuracy of calculating the tire bulge value and the tire depression value.
[0060] The embodiment of the present disclosure provides a device for determining tire eccentricity, such as Figure 3 As shown, the tire eccentricity determination device 10 may include: a first acquisition module 101, a second acquisition module 102, a first processing module 103, a second processing module 104 and a determination module 105, wherein: A first acquisition module 101 is used to acquire an image to be processed formed based on surface information of the tire to be tested; A second acquisition module 102 is used to acquire the data to be processed in the to-be-detected area in the to-be-processed image, wherein the data to be processed includes at least two groups of one-dimensional arrays; The first processing module 103 is used to remove invalid data from each one-dimensional array of the data to be processed to obtain the data to be processed after the invalid data is removed; The second processing module 104 is used to perform Fourier transform on each one-dimensional array of the data to be processed after the invalid data is removed, so as to obtain the data to be processed after Fourier transform; The determination module 105 is used to calculate the tire eccentricity of the data to be processed after the Fourier transformation, so as to determine the eccentricity of the tire to be tested.
[0061] In an optional embodiment, the determination module 105 is specifically used to: for each group of one-dimensional arrays in the data to be processed after the Fourier transform, determine the difference between the maximum value and the minimum value in each group of one-dimensional arrays, and record the difference between the maximum value and the minimum value in each group of one-dimensional arrays as the fluctuation value; for the fluctuation values corresponding to each obtained one-dimensional array, determine the maximum fluctuation value among the fluctuation values corresponding to each one-dimensional array, and use the maximum fluctuation value as the tire fluctuation value of the tire to be tested, wherein the eccentricity of the tire to be tested includes the tire fluctuation value.
[0062] In an optional embodiment, the determination module 105 is specifically used to: for each group of one-dimensional arrays in the data to be processed after the Fourier transform, determine the harmonic components based on integer multiples of the fundamental wave in each group of one-dimensional arrays, wherein the fundamental wave is determined after Fourier transforming each group of one-dimensional arrays in the data to be processed after the invalid data is removed; for the harmonic components corresponding to each obtained one-dimensional array, determine the maximum harmonic component among the harmonic components corresponding to each one-dimensional array, and use the maximum harmonic component as the first harmonic of the tire to be tested, wherein the eccentricity of the tire to be tested includes the first harmonic of the tire.
[0063] In an optional embodiment, the determination module 105 is specifically used for: for each group of one-dimensional arrays in the data to be processed after the Fourier transform, performing a translation operation on each group of one-dimensional data based on a preset window, and determining the bulge value and the depression value in each group of one-dimensional array; for the bulge values corresponding to each one-dimensional array obtained, determining the maximum bulge value among the bulge values corresponding to each one-dimensional array, and using the maximum bulge value as the tire bulge value of the tire to be tested, wherein the eccentricity of the tire to be tested includes the tire bulge value; for the depression values corresponding to each one-dimensional array obtained, determining the maximum depression value among the depression values corresponding to each one-dimensional array, and using the maximum depression value as the tire depression value of the tire to be tested, wherein the eccentricity of the tire to be tested includes the tire depression value.
[0064] In an optional embodiment, the determination module 105 is specifically configured to: For any set of one-dimensional data, a translation operation is sequentially performed on the set of one-dimensional data based on the preset window; For a group of selected data segments selected when any one of the group of one-dimensional data is translated by the preset window, dividing the selected data segments into left data and right data based on the preset window; Determine the minimum values of the left portion of data and the right portion of data, respectively, record them as left minimum value and right minimum value, and determine the middle value located between the left minimum value and the right minimum value based on the left minimum value and the right minimum value; Determine the bulge value and the depression value to be selected corresponding to the selected data segment in the following manner: The selected bulge value = middle value - (left minimum value + right minimum value) / 2; The selected concave value = (left minimum value + right minimum value) / 2-middle value; Until the above-mentioned preset window translation operation is completed for all the selected data segments in the above-mentioned group of one-dimensional data, if there is at least one to-be-selected bulge value and at least one to-be-selected depression value, then the largest to-be-selected bulge value is selected from the above-mentioned at least one to-be-selected bulge value to be determined as the corresponding bulge value of the above-mentioned group of one-dimensional arrays, and the largest to-be-selected depression value is selected from the above-mentioned at least one to-be-selected depression value to be determined as the depression value of the above-mentioned group of one-dimensional arrays.
[0065] In an optional embodiment, the first acquisition module 101 is specifically used to: collect surface information of the tire to be tested based on the tire information scanning module and the encoder, and obtain height information about the distance between the surface of the tire to be tested and the tire information scanning module; determine the maximum height value and the minimum height value in the height information; and draw an image based on the maximum height value and the minimum height value, as well as a preset color template, to obtain the image to be processed.
[0066] Through the embodiments of the present disclosure, on the one hand, the eccentricity of the tire can be calculated based on the area to be detected of the image to be processed, which greatly expands the detection area of the tire eccentricity and improves the calculation efficiency of the eccentricity detection. On the other hand, the eccentricity is calculated by using the image to be processed and using invalid data removal operations and Fourier transform operations, which not only improves the convenience of the eccentricity calculation but also improves the accuracy of the eccentricity calculation.
[0067] The device of the embodiment of the present disclosure can execute the method provided by the embodiment of the present disclosure, and its implementation principle is similar and has corresponding technical effects. The actions performed by each module in the device of each embodiment of the present disclosure correspond to the steps in the method of each embodiment of the present disclosure. For the detailed functional description of each module of the device, please refer to the description in the corresponding method shown in the previous text, which will not be repeated here.
[0068] An embodiment of the present disclosure provides an electronic device (computer device / equipment / system), including a memory, a processor, and a computer program stored in the memory, and the processor executes the above computer program to implement the steps of the method provided in any optional embodiment of the present disclosure.
[0069] In an alternative embodiment, an electronic device is provided, such as Figure 4 As shown, Figure 4 The electronic device 4000 shown includes: a processor 4001 and a memory 4003. The processor 4001 and the memory 4003 are connected, such as through a bus 4002. Optionally, the electronic device 4000 may also include a transceiver 4004, which may be used for data interaction between the electronic device and other electronic devices, such as data transmission and / or data reception. It should be noted that in actual applications, the transceiver 4004 is not limited to one, and the structure of the electronic device 4000 does not constitute a limitation on the embodiments of the present disclosure.
[0070] Processor 4001 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of the present invention. Processor 4001 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.
[0071] The bus 4002 may include a path to transmit information between the above components. The bus 4002 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 4002 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.
[0072] The memory 4003 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), magnetic disk storage media, other magnetic storage devices, or any other medium that can be used to carry or store computer programs and can be read by a computer, without limitation herein.
[0073] The memory 4003 is used to store the computer program for executing the embodiment of the present disclosure, and the execution is controlled by the processor 4001. The processor 4001 is used to execute the computer program stored in the memory 4003 to implement the steps shown in the above method embodiment.
[0074] An embodiment of the present disclosure provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps and corresponding contents of the aforementioned method embodiment can be implemented.
[0075] The embodiments of the present disclosure also provide a computer program product, including a computer program, which can implement the steps and corresponding contents of the aforementioned method embodiments when executed by a processor.
[0076] It should be understood that, although the flowchart of the embodiment of the present disclosure indicates each operation step by arrows, the implementation order of these steps is not limited to the order indicated by the arrows. Unless clearly stated herein, in some implementation scenarios of the embodiment of the present disclosure, the implementation steps in each flowchart can be executed in other orders according to demand. In addition, some or all of the steps in each flowchart may include multiple sub-steps or multiple stages based on the actual implementation scenario. Some or all of these sub-steps or stages can be executed at the same time, and each sub-step or stage in these sub-steps or stages can also be executed at different times. In scenarios with different execution times, the execution order of these sub-steps or stages can be flexibly configured according to demand, and the embodiment of the present disclosure does not limit this.
[0077] The above are only optional implementation methods for some implementation scenarios of the present disclosure. It should be pointed out that for ordinary technicians in this technical field, without departing from the technical concept of the scheme of the present disclosure, other similar implementation methods based on the technical ideas of the present disclosure are also within the protection scope of the embodiments of the present disclosure.< / color> < / color>
Claims
1. A method for determining tire eccentricity, characterized in that: The method comprises: Acquiring an image to be processed formed based on surface information of the tire to be tested; Acquire data to be processed in the to-be-detected area in the to-be-processed image, wherein the data to be processed includes at least two groups of one-dimensional arrays; Removing invalid data from each one-dimensional array of the data to be processed to obtain the data to be processed after the invalid data is removed; Performing Fourier transformation on each one-dimensional array of the data to be processed after the invalid data is removed, to obtain the data to be processed after Fourier transformation; The tire eccentricity is calculated for the Fourier transformed data to be processed to determine the eccentricity of the tire to be tested.
2. The method according to claim 1, characterized in that The step of calculating the tire eccentricity of the Fourier transformed data to be processed to determine the eccentricity of the tire to be tested comprises: For each group of one-dimensional arrays in the to-be-processed data after the Fourier transform, determine the difference between the maximum value and the minimum value in each group of one-dimensional arrays, and record the difference between the maximum value and the minimum value in each group of one-dimensional arrays as a fluctuation value; For the obtained fluctuation values corresponding to each one-dimensional array, determine the maximum fluctuation value among the fluctuation values corresponding to each one-dimensional array, and use the maximum fluctuation value as the tire fluctuation value of the tire to be tested, wherein the eccentricity of the tire to be tested includes the tire fluctuation value.
3. The method according to claim 1, characterized in that: The step of calculating the tire eccentricity of the Fourier transformed data to be processed to determine the eccentricity of the tire to be tested comprises: For each group of one-dimensional arrays in the data to be processed after the Fourier transform, determine the harmonic components based on integer multiples of the fundamental wave in each group of one-dimensional arrays, wherein the fundamental wave is determined after Fourier transforming each group of one-dimensional arrays in the data to be processed after removing invalid data; For the harmonic components corresponding to the obtained one-dimensional arrays, the maximum harmonic component among the harmonic components corresponding to the one-dimensional arrays is determined, and the maximum harmonic component is used as the first harmonic of the tire to be tested, wherein the eccentricity of the tire to be tested includes the first harmonic of the tire.
4. The method according to claim 1, characterized in that: The step of calculating the tire eccentricity of the Fourier transformed data to be processed to determine the eccentricity of the tire to be tested comprises: For each group of one-dimensional arrays in the data to be processed after the Fourier transform, a translation operation is performed on each group of one-dimensional data based on a preset window to determine the bulge value and the concave value in each group of one-dimensional array; For the bulge values corresponding to the obtained one-dimensional arrays, determine the maximum bulge value among the bulge values corresponding to the one-dimensional arrays, and use the maximum bulge value as the tire bulge value of the tire to be tested, wherein the eccentricity of the tire to be tested includes the tire bulge value; For the obtained depression values corresponding to each one-dimensional array, determine the maximum depression value among the depression values corresponding to each one-dimensional array, and use the maximum depression value as the tire depression value of the tire to be tested, wherein the eccentricity of the tire to be tested includes the tire depression value.
5. The method according to claim 4, characterized in that The performing a translation operation on each group of one-dimensional data based on a preset window to determine the bulge value and the concave value in each group of one-dimensional array includes: For any set of one-dimensional data, performing translation operation on the set of one-dimensional data in sequence based on the preset window; For a group of selected data segments selected when any one of the group of one-dimensional data is translated by the preset window, dividing the selected data segments into left part data and right part data based on the preset window; Determine the minimum values in the left part of the data and the right part of the data, respectively, record them as the left minimum value and the right minimum value, and determine the middle value located between the left minimum value and the right minimum value based on the left minimum value and the right minimum value; Determine the bulge value and the concave value to be selected corresponding to the selected data segment in the following manner: The selected bulge value = middle value - (left minimum value + right minimum value) / 2; The selected concave value = (left minimum value + right minimum value) / 2-middle value; Until the preset window translation operation is completed for all selected data segments in the group of one-dimensional data, if there is at least one bulge value to be selected and at least one depression value to be selected, the largest bulge value to be selected is selected from the at least one bulge value to be selected as the corresponding bulge value of the group of one-dimensional arrays, and the largest depression value to be selected is selected from the at least one depression value to be selected as the depression value of the group of one-dimensional arrays.
6. The method according to claim 1, characterized in that The step of obtaining an image to be processed formed based on the surface information of the tire to be tested comprises: Collecting surface information of the tire to be tested based on a tire information scanning module and an encoder, and obtaining height information about the distance between the surface of the tire to be tested and the tire information scanning module; Determine a maximum height value and a minimum height value in the height information; Based on the maximum height value, the minimum height value, and a preset color template, image drawing is performed to obtain the image to be processed.
7. A device for determining tire eccentricity, characterized in that: The device comprises: A first acquisition module, used for acquiring an image to be processed formed based on surface information of the tire to be tested; A second acquisition module is used to acquire the data to be processed in the to-be-detected area in the to-be-processed image, wherein the data to be processed includes at least two groups of one-dimensional arrays; A first processing module is used to remove invalid data from each one-dimensional array in the data to be processed to obtain the data to be processed after the invalid data is removed; A second processing module is used to perform Fourier transform on each one-dimensional array of the data to be processed after the invalid data is removed, so as to obtain the data to be processed after Fourier transform; The determination module is used to calculate the tire eccentricity of the data to be processed after the Fourier transformation, so as to determine the eccentricity of the tire to be tested.
8. An electronic device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 6.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.
10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.