Tire condition management device, tire condition management method, and program

Abstract

To easily and accurately measure the depth of the tread grooves. [Solution] The tire condition management device 1 includes a control unit 13, which acquires the cross-sectional profile of the tire tread groove, corrects the cross-sectional profile using the AsLs method so that the height difference on both sides of the tread groove is reduced, and measures the depth of the tread groove from the corrected cross-sectional profile.

Description

Technical Field

[0001] The present disclosure relates to a tire condition management device, a tire condition management method, and a program.

Background Art

[0002] Conventionally, a technique for calculating the depth of a tread groove of a tire has been known. For example, in Patent Document 1, based on three-dimensional coordinate data representing a point group included in the surface of the tread portion of a tire, a normal vector of the surface at each point included in the point group is calculated, a position where the points included in the point group are moved in the direction based on the normal vector is calculated, and a technique for calculating the depth of the tread groove based on a comparison of the nearest neighboring points before and after the movement of the points is disclosed.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] It is desired to measure the depth of the tread groove more easily and with higher accuracy.

[0005] In view of such circumstances, an object of the present disclosure is to provide a tire condition management device, a tire condition management method, and a program capable of easily and accurately measuring the depth of a tread groove.

Means for Solving the Problems

[0006] The gist of the present disclosure for solving the above problems is as follows.

[0007] (1) A tire condition management device comprising a control unit, wherein the control unit acquires the cross-sectional profile of the tire tread groove, corrects the cross-sectional profile using the AsLs method so as to reduce the height difference between both sides of the tread groove, and measures the depth of the tread groove from the corrected cross-sectional profile.

[0008] (2) The tire condition management device according to (1), wherein the control unit acquires three-dimensional coordinate data of the tire, transforms the coordinates of the three-dimensional coordinate data with respect to the tread surface in the three-dimensional coordinate data, and then acquires the cross-sectional profile.

[0009] (3) The tire condition management device according to (2), wherein the control unit generates an approximate surface by approximating the tread surface using the RANSAC method, and obtains the cross-sectional profile after transforming the coordinates of the three-dimensional coordinate data with respect to the approximate surface.

[0010] (4) The tire condition management device according to (1), wherein the control unit acquires three-dimensional coordinate data of the tire and acquires the cross-sectional profile from the three-dimensional coordinate data by ray casting.

[0011] (5) The tire condition management device according to (1), wherein the control unit acquires the cross-sectional profile measured by the line laser.

[0012] (6) The tire condition management device according to any one of (1) to (5), wherein the control unit measures the normal distance from the bottom of the tread groove to the tread surface as the depth of the tread groove based on the cross-sectional profile.

[0013] (7) The tire condition management device according to any one of (2) to (6), wherein the control unit acquires depth data of the tire using laser light, generates a depth map showing the depth for each pixel and a confidence map showing the confidence level of the depth from the depth data, and converts the depth map into three-dimensional coordinate data after removing data whose confidence level is below a threshold, or converts the depth map into three-dimensional coordinate data and then removes data whose confidence level is below a threshold to obtain the three-dimensional coordinate data.

[0014] (8) A tire condition management method comprising the steps of: a tire condition management device acquiring a cross-sectional profile of the tire tread groove; correcting the cross-sectional profile using the AsLs method so that the height difference between both sides of the tread groove is reduced; and measuring the depth of the tread groove from the corrected cross-sectional profile.

[0015] (9) A program to cause a computer to function as a tire condition management device as described in any of (1) through (7). [Effects of the Invention]

[0016] According to this disclosure, it becomes possible to easily and accurately measure the depth of the tread grooves. [Brief explanation of the drawing]

[0017] [Figure 1] This is a block diagram showing an example configuration of a tire condition management device according to one embodiment. [Figure 2] This figure shows an example of a depth map and a confidence map. [Figure 3] This figure shows an example of a depth map and confidence map for a frame where 3D coordinate data acquisition failed. [Figure 4] This figure shows an example of 3D coordinate data for a tire. [Figure 5] This figure shows an example of planar approximation of the tread surface in 3D coordinate data. [Figure 6]It is a diagram showing an example of a cross-section for obtaining a profile in three-dimensional coordinate data. [Figure 7] It is a diagram showing an example of a cross-sectional profile of a tread groove obtained from three-dimensional coordinate data. [Figure 8] It is a diagram showing an example of a conventional manual measurement method for the depth of a tread groove. [Figure 9] It is a diagram for explaining the definition of the depth of a tread groove. [Figure 10] It is a diagram showing an example of correction of a cross-sectional profile using the AsLs method. [Figure 11] It is a diagram showing an example of correction of a cross-sectional profile using the AsLs method. [Figure 12] It is a flowchart showing an example of the procedure of a tire state management method according to an embodiment.

Mode for Carrying Out the Invention

[0018] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. However, note that the drawings are schematic, and the ratios of each dimension and the like may be different from the actual ones.

[0019] FIG. 1 shows a configuration example of a tire state management device according to an embodiment. The tire state management device 10 shown in FIG. 1 includes an input unit 11, a sensing unit 12, a control unit 13, a storage unit 14, and an output unit 15. The tire state management device 10 may further include a communication I / F such as a LAN (Local Area Network) I / F in order to be communicable with an external device.

[0020] The tire state management device 10 is, for example, a smartphone, a tablet, a PC (Personal Computer), or the like.

[0021] The input unit 11 is, for example, a physical key, a capacitive key, a pointing device, or a touchscreen integrated with a display. The input unit 11 accepts operations to input data used for the operation of the tire condition management device 10. Instead of being provided in the tire condition management device 10, the input unit 11 may be connected to the tire condition management device 10 as an external input device. Any interface compatible with standards such as USB (Universal Serial Bus), HDMI (High-Definition Multimedia Interface) (registered trademark), and Bluetooth (registered trademark) can be used as the connection interface.

[0022] The sensing unit 12 senses the tire, measures (acquires) tire depth data, and stores the measured depth data in the storage unit 14. The sensing unit 12 stores the measured depth data in the storage unit 14. The tire is not particularly limited, but may be an OR (Off The Road) tire mounted on a construction vehicle, mining vehicle, etc., a truck or bus tire, an airplane tire, a passenger car tire, etc.

[0023] The sensing unit 12 includes, for example, a laser scanner that scans the tire using laser light, such as a LiDAR (Light Detection And Ranging) system, and a camera that takes images of the tire. Instead of being provided in the tire condition management device 10, the laser scanner or camera of the sensing unit 12 may be connected to the tire condition management device 10 as an external input device.

[0024] The storage unit 14 includes one or more memories. The memories are, for example, semiconductor memory, magnetic memory, optical memory, etc. Semiconductor memory is, for example, RAM (random access memory), ROM (read-only memory), flash memory, etc. RAM is, for example, SRAM (static random access memory), DRAM (dynamic random access memory), etc. ROM is, for example, EEPROM (electrically erasable programmable read-only memory). Flash memory is, for example, SSD (solid-state drive). Magnetic memory is, for example, HDD (hard disk drive). The storage unit 14 functions as, for example, main memory, auxiliary memory, cache memory, etc.

[0025] The output unit 15 is, for example, an LCD (liquid crystal display), an organic EL (electroluminescent) display, or a speaker. The output unit 15 presents the data created by the control unit 13 to the user. Instead of being provided in the tire condition management device 10, the output unit 15 may be connected to the tire condition management device 10 as an external output device. Any interface compatible with standards such as USB, HDMI, and Bluetooth can be used as the connection interface.

[0026] The control unit 13 may be composed of dedicated hardware such as an ASIC (Application Specific Integrated Circuit) or FPGA (Field-Programmable Gate Array), or it may be composed of a processor, or it may include both. The control unit 13 controls each part of the tire condition management device 10 and executes processes related to the operation of the tire condition management device 10.

[0027] The control unit 13 shown in Figure 1 comprises a data acquisition unit 131, a cross-sectional profile acquisition unit 132, and an RTD (remaining tread depth) measurement unit 133.

[0028] The data acquisition unit 131 acquires tire depth data from the storage unit 14.

[0029] Furthermore, the data acquisition unit 131 uses AR functionality to generate data indicating the depth for each pixel (hereinafter referred to as a "depth map") and data indicating the confidence level of said depth (hereinafter referred to as a "confidence map") from the depth data. The data acquisition unit 131 may also utilize the AR functionality pre-installed in the tire condition management device 10. For example, some smartphones are equipped with a framework called ARKit as an AR function, which can generate a confidenceMap as a confidence map and a depthMap as a depth map. For details on ARKit, please refer to the references listed below. [References] “Framework ARKit”, [online], [Accessed August 23, 2024], Internet<URL:https: / / developer.apple.com / documentation / arkit / ardepthdata>

[0030] The data acquisition unit 131 removes data with low confidence (i.e., below a threshold) from the depth map based on the confidence map. Figure 2 shows an example of a depth map and a confidence map. Figure 2(a) is an example of a depth map, and Figure 2(b) is an example of a confidence map. Pixel A in Figure 2(b) has a confidence level below a threshold. The data acquisition unit 131 can filter out data with low confidence by deleting the data corresponding to pixel A from the depth map.

[0031] The data acquisition unit 131 may acquire depth maps and confidence maps for multiple frames (for example, 30 frames), and then perform the above filtering after removing data from frames where the average value of the confidence map is low (i.e., below a threshold). The data acquisition unit 131 converts the array of depth maps into 3D coordinate data by multiplying it by a matrix of camera parameters, position parameters, etc. The data acquisition unit 131 may also perform processing such as noise reduction and smoothing of the 3D coordinate data using existing techniques. The data acquisition unit 131 outputs the processed 3D coordinate data to the storage unit 14. Figure 3 shows an example of a depth map and confidence map for a frame in which 3D coordinate data acquisition failed. Figure 3(a) is an example of a depth map, and Figure 3(b) is an example of a confidence map. This figure shows an example where the confidence level for the entire frame is 0.

[0032] In the example above, the data acquisition unit 131 removed low-confidence data from the depth map before converting the depth map into 3D coordinate data. However, this order may be reversed. That is, the data acquisition unit 131 may convert the depth map into 3D coordinate data by assigning a unique ID to each piece of 3D coordinate data and the coordinate values ​​of the pixels in the confidence map or depth map, and then remove low-confidence data from the 3D coordinate data. In this case, the data size will be larger, but it will be possible to analyze which parts of the 3D coordinate data have low or high confidence levels, which will be useful for evaluating and improving measurement methods and algorithms.

[0033] Figure 4 shows an example of tire 3D coordinate data (3D point cloud data) D. The central depression is the tread groove T.

[0034] The cross-sectional profile acquisition unit 132 approximates the tread surface in the 3D coordinate data acquired and processed by the data acquisition unit 131 using a plane to generate an approximate surface. The RANSAC (Random Sample Consensus) method can be used to generate the approximate surface. In the RANSAC method, three points are randomly selected from the 3D coordinate data, and the plane with the smallest error is detected to perform plane approximation.

[0035] Figure 5 shows an example of an approximate surface S obtained by approximating the tread surface of the 3D coordinate data D shown in Figure 4 using the RANSAC method. The RANSAC method is excellent at extracting the desired approximation line / approximation surface from data containing outliers, and can approximate the tread surface in a plane even when tread grooves T are present, as shown in Figure 5.

[0036] The sensing unit 12 determines the coordinate system of the 3D coordinate data. For example, in the coordinate system of the 3D coordinate data, the direction of gravity is the Y-axis, the camera direction is the Z-axis, and the direction perpendicular to them is the X-axis. Therefore, the depth direction of the tread groove cannot be determined in this state. To address this, the cross-sectional profile acquisition unit 132 may transform the coordinates of the 3D coordinate data based on an approximate plane. For example, the cross-sectional profile acquisition unit 132 transforms the XYZ axes of the 3D coordinate data so that the approximate plane is the XY plane (Z=0). That is, one axis of the approximate plane is set as the X-axis, and the other axis of the approximate plane is set as the Y-axis. The position of the origin can be any position within the approximate plane. By performing this coordinate transformation of the 3D coordinate data, the depth direction of the tread groove becomes the direction perpendicular to the XY plane (parallel to the Z-axis).

[0037] The cross-sectional profile acquisition unit 132 acquires the cross-sectional profile of the tread groove from the 3D coordinate data. Specifically, the cross-sectional profile acquisition unit 132 acquires the coordinate values ​​of the tread groove in a plane perpendicular to the approximate surface of the tread surface (the YZ plane after coordinate transformation of the 3D coordinate data) as the cross-sectional profile of the tread groove. The value of the X coordinate can be arbitrary.

[0038] Figure 6 shows an example of a cross-section C from which a profile is obtained. The XYZ axes shown in Figure 6 are coordinate axes transformed so that the approximation plane S is the XY plane (Z=0). Cross-section C is a plane perpendicular to the approximation plane S of the tread surface.

[0039] Figure 7 shows an example of a cross-sectional profile P of a tread groove obtained from 3D coordinate data D. When the output unit 15 displays the cross-sectional profile P, it may simultaneously display the 3D coordinate data D in the vicinity of the cross-sectional profile P, as shown in Figure 7, or it may simultaneously display the scale of the cross-sectional profile P.

[0040] The RTD measurement unit 133 measures the tread groove depth (remaining groove depth) from the cross-sectional profile acquired by the cross-sectional profile acquisition unit 132.

[0041] Figure 8 shows an example of a conventional manual method for measuring tread groove depth. When measuring tread groove depth manually, the reference surface of a depth gauge is typically brought into contact with the tire tread surface to measure the tread groove depth. However, this method yields different results depending on how the reference surface of the depth gauge is applied. In the present invention, the tire condition management device 10 automatically measures the tread groove depth from the cross-sectional profile, eliminating measurement variations between users. However, it is necessary to define the length from which the tread groove depth is defined.

[0042] Therefore, as shown in Figure 9, the normal distance L from the tread surface or approximation surface S to the bottom B of the tread groove T may be defined as the depth of the tread groove. Alternatively, the longest distance among multiple normals from the tread surface or approximation surface S to the tread groove may be defined as the depth of the tread groove.

[0043] Because the rate of tire wear is not uniform, uneven wear occurs, as shown in Figures 8 and 9, and the height of the land area R may differ on both sides of the tread groove T. It is also desirable to consider the curvature of the tire. Therefore, the RTD measurement unit 133 may correct the cross-sectional profile so that the height difference of the land area on both sides of the tread groove is reduced. In other words, the RTD measurement unit 133 may correct the baseline (tread surface) of the cross-sectional profile to the Y axis (see Figure 6). The AsLs (Asymmetric least squares smoother) method can be used to obtain the baseline. The AsLs method is sometimes referred to as the ALS method.

[0044] Figures 10 and 11 show examples of cross-sectional profile correction using the AsLs method. Note that the cross-sectional profiles shown in Figures 10 and 11 have been inverted vertically so that the tread groove depth is a positive value. Figure 10 shows an example of cross-sectional profile correction when the baseline parameter th is set to 1. In the left panel of Figure 10, the straight line shows the cross-sectional profile before correction, and the dashed line shows the baseline obtained by the AsLs method. By subtracting the baseline from the cross-sectional profile before correction, the corrected cross-sectional profile shown in the right panel of Figure 10 is obtained. In the corrected cross-sectional profile, the values ​​in the areas circled in the cross-sectional profile before correction are corrected to 0.

[0045] Figure 11 shows an example of correcting the cross-sectional profile when the baseline parameter th is set to 10. In the left panel of Figure 11, the straight line shows the cross-sectional profile before correction, and the dashed line shows the baseline obtained by the AsLs method. By subtracting the baseline from the cross-sectional profile before correction, the corrected cross-sectional profile shown in the right panel of Figure 11 is obtained. In the corrected cross-sectional profile, the values ​​in the areas circled in the cross-sectional profile before correction are corrected to 0.

[0046] As can be seen from the comparison between Figure 10 and Figure 11, the smaller the baseline parameter th, the more sensitively the baseline follows the cross-sectional profile, and the larger the baseline parameter th, the less sensitive the baseline follows the cross-sectional profile. Thus, using the AsLs method, the baseline can be easily changed simply by changing the baseline parameter th. Note that the value of the baseline parameter th may be changeable by the user during measurement.

[0047] The RTD measurement unit 133 determines the peak value of the corrected cross-sectional profile as the tread groove depth. In the example shown in Figure 10, the tread groove depth determined from the corrected cross-sectional profile is 79.4 mm. In the example shown in Figure 11, the tread groove depth determined from the corrected cross-sectional profile is 82.0 mm.

[0048] Next, a tire condition management method according to one embodiment will be described. Figure 12 is a flowchart showing an example of the procedure for the tire condition management method.

[0049] In step S101, the user operates the tire condition management device 10 to take a picture of the tire, and the data acquisition unit 131 acquires the tire's three-dimensional coordinate data. The output unit 15 may display the tire's three-dimensional coordinate data on the screen.

[0050] In step S102, the cross-sectional profile acquisition unit 132 approximates the tread surface in a planar manner using methods such as the RANSAC method.

[0051] In step S103, the cross-sectional profile acquisition unit 132 transforms the coordinates of the 3D coordinate data based on the tread surface (approximate surface).

[0052] In step S104, the cross-sectional profile acquisition unit 132 acquires a cross-sectional profile in a plane perpendicular to the tread surface (approximate surface) (i.e., the cross-sectional profile of the tread groove).

[0053] In step S105, the RTD measurement unit 133 corrects the cross-sectional profile using the AsLs method or the like so that the height difference between both sides of the tread groove is reduced. The output unit 15 may display the cross-sectional profile of the tread groove before or after correction on the screen. In this case, the output unit 15 may display the cross-sectional profile of the tread groove superimposed on the 3D coordinate data.

[0054] In step S106, the RTD measuring unit 133 measures the depth of the tread groove from the cross-sectional profile. For example, the RTD measuring unit 133 measures the tread groove depth as the normal distance from the approximation surface to the bottom of the tread groove. The output unit 15 may display the tread groove depth on the screen.

[0055] <Variation> The cross-sectional profile acquisition unit 132 may acquire the cross-sectional profile of the tread groove from the 3D coordinate data using the ray-casting method.

[0056] Alternatively, the sensing unit 12 may be a line laser. In that case, the sensing unit 12 senses the tire, measures the tire's two-dimensional coordinate data, and stores it in the storage unit 14. The data acquisition unit 131 acquires the tire's two-dimensional coordinate data from the storage unit 14. By irradiating the tread surface perpendicularly with the laser output from the line laser, the cross-sectional profile acquisition unit 132 can acquire the cross-sectional profile of the tread groove measured by the line laser.

[0057] Thus, in this invention, the cross-sectional profile of the tire tread groove is obtained, and the depth of the tread groove is measured from the cross-sectional profile. Therefore, the depth of the tread groove can be measured easily and with high accuracy.

[0058] Furthermore, the RANSAC method can generate an approximate surface that approximates the tread surface in 3D coordinate data, and the cross-sectional profile in a plane perpendicular to the approximate surface can be obtained as the cross-sectional profile of the tread groove. In addition, coordinate transformation of 3D coordinate data can be performed based on the approximate surface. Moreover, the AsLs method can be used to correct the cross-sectional profile so that the height difference on both sides of the tread groove is reduced. Furthermore, the depth of the tread groove can be defined by measuring the normal distance from the bottom of the tread groove to the tread surface as the depth of the tread groove. Thus, it becomes possible to measure the depth of the tread groove with higher accuracy.

[0059] <Program> To enable the tire condition management device 10 described above to function, a computer capable of executing program instructions can also be used. The program instructions may be program code, code segments, etc., for performing the necessary tasks.

[0060] The control unit 13 is a processor such as a CPU (Central Processing Unit), MPU (Micro Processing Unit), GPU (Graphics Processing Unit), DSP (Digital Signal Processor), or SoC (System on a Chip), and may be composed of multiple processors of the same or different types. The processor performs the above-described processing by reading and executing a program from the storage unit 14. At least a part of these processing contents may be implemented in hardware.

[0061] The program may be recorded on a computer-readable recording medium. Using such a medium, the program can be installed on the computer. The recording medium on which the program is recorded may be a non-transitory recording medium. Non-transitory recording media are not particularly limited, but may include, for example, CD-ROMs, DVD-ROMs, or USB (Universal Serial Bus) memory. Alternatively, the program may be downloaded from an external device via a network.

[0062] Although the embodiments described above are representative examples, it will be apparent to those skilled in the art that many modifications and substitutions are possible within the spirit and scope of the present invention. Therefore, the present invention should not be interpreted as being limited by the embodiments described above, and various modifications or changes are possible without departing from the scope of the claims. For example, it is possible to integrate multiple component blocks shown in the configuration diagram of the embodiments, or to divide a single component block. Furthermore, it is possible to integrate multiple steps shown in the flowchart of the embodiments into one, or to divide a single step. Contribution to the United Nations-led Sustainable Development Goals (SDGs)

[0063] The SDGs have been proposed to realize a sustainable society. One embodiment of this disclosure is considered to be a technology that can contribute to "No. 9 - Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation," among others. [Explanation of symbols]

[0064] 10. Tire condition management device 11 Input section 12 Sensing Unit 13 Control Unit 14 Storage section 15 Output section 131 Data Acquisition Unit 132 Sectional Profile Acquisition Section 133 RTD measurement section

Claims

1. A tire condition management device comprising a control unit, The control unit, Obtain the cross-sectional profile of the tire tread groove, The cross-sectional profile is corrected using the AsLs method so that the difference in height between both sides of the tread groove is reduced. A tire condition management device that measures the depth of the tread groove from the corrected cross-sectional profile.

2. The control unit, We obtain the 3D coordinate data of the tire, The tire condition management device according to claim 1, wherein the coordinates of the three-dimensional coordinate data are transformed based on the tread surface in the three-dimensional coordinate data, and the cross-sectional profile is obtained.

3. The control unit, An approximate surface is generated by approximating the aforementioned tread surface using the RANSAC method. The tire condition management device according to claim 2, wherein the coordinates of the three-dimensional coordinate data are transformed with respect to the approximate surface, and then the cross-sectional profile is obtained.

4. The control unit, We obtain the 3D coordinate data of the tire, The tire condition management device according to claim 1, wherein the cross-sectional profile is obtained from the three-dimensional coordinate data by ray casting.

5. The tire condition management device according to claim 1, wherein the control unit acquires the cross-sectional profile measured by a line laser.

6. The tire condition management device according to claim 1, wherein the control unit measures the normal distance from the bottom of the tread groove to the tread surface as the depth of the tread groove, based on the cross-sectional profile.

7. The control unit, Depth data of the tire is acquired using laser light. From the aforementioned depth data, a depth map showing the depth for each pixel and a confidence map showing the confidence level of said depth are generated. The tire condition management device according to claim 2, wherein the depth map is converted to three-dimensional coordinate data after removing data with a reliability below a threshold, or the depth map is converted to three-dimensional coordinate data and then data with a reliability below a threshold is removed to obtain the three-dimensional coordinate data.

8. The tire condition management device, Steps include obtaining the cross-sectional profile of the tire tread groove, The steps include correcting the cross-sectional profile using the AsLs method so that the difference in height between both sides of the tread groove is reduced, A step of measuring the depth of the tread groove from the corrected cross-sectional profile, A method for managing tire condition.

9. A program for causing a computer to function as a tire condition management device according to any one of claims 1 to 7.

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