A method for measuring the depth of a tire pattern based on a point laser

Abstract

The present application relates to the technical field of automobile detection, and specifically relates to a novel tire pattern depth measurement method based on point laser, which comprises the following steps: step 1: dividing the measurement device into three equal parts, placing the tire in the divided interval one by one, and using the point laser sensor to scan back and forth three times to obtain the returned detection data, which is recorded as DataOne, DataTwo and DataThree; step 2: merging the DataOne, DataTwo and DataThree returned by the point laser sensor; step 3: performing secondary B-spline smoothing on the data; step 4: judging the turning point of the smoothed data; step 5: judging the groove area through the turning point; and step 6: traversing the turning point index set TP to calculate the jth tread pattern depth of the tire. The present application effectively improves the accuracy of using point laser to detect the tire pattern depth under the condition of parking by processing the point laser detection data through multi-position correction, introducing secondary B-spline for curve smoothing, and adding the discrimination of turning points.

Description

Technical Field

[0001] This invention relates to the field of automotive testing technology, specifically to a novel method for measuring tire tread depth based on point laser. Background Technology

[0002] The tire is a major component of a car's driving system. Tires are in direct contact with the ground and are closely related to driving safety, smoothness, comfort, and fuel economy. To ensure sufficient driving force and friction during vehicle operation, tires are designed with tread patterns to increase the coefficient of friction between the tire and the ground, increase driving force, reduce tire slippage, and prevent accidents. However, tire tread depth wears down and becomes shallower as the car's mileage increases. If the tread depth is too shallow, it will significantly reduce the tire's grip and its ability to retain and drain water. During driving, the driver will be more likely to feel the car veering off course or the tires slipping, posing a significant safety hazard.

[0003] Current existing technologies related to tire tread depth detection methods include: Patent Application No. 201080015419.4, titled "Method and Device for Determining Tread Depth of Vehicle Tires." This patent acquires signals from the tread pattern and reflected light fan-shaped area transverse to the tire's rotation direction using a light source. It then evaluates the signal of the reflected light fan-shaped area using triangulation and calculates the tread depth using the difference between the envelope of the tread grooves and their deepest point. This method is easily affected by weather conditions; for example, wet tires can cause reflections, leading to significant measurement errors. Patent Application No. 201710152842.2, titled "A Tire Tread Depth Measuring Device and Tire Tread Depth Calculation Method," uses a line laser and a CCD industrial camera capable of high-speed continuous shooting to capture multiple light stripe images formed on the tire tread at equal time intervals. The tire tread depth is obtained through spline fitting, spline interpolation, and polynomial fitting methods. This method has high hardware costs and is difficult to promote. Invention patent application number: 2022102568767, title: Method for measuring tire tread depth, method and system for measuring full circumference tread depth. This patent uses a fixedly set transmitting unit and receiving unit, and uses the triangulation method to measure the distance L1 from the outer surface of the tire tread to the transmitting unit and the distance L2 from the bottom surface of the tread to the transmitting unit. It also uses a fixedly set camera to obtain an image of the tire and uses a machine vision unit to identify the center coordinates O of the tire sidewall. This scheme depends on the position of the camera, and the measurement results will differ at different positions.

[0004] In summary, the current technical solutions have the following limitations: (1) The above algorithms are all relatively complex, the steps are cumbersome, and the calculation is difficult; (2) The applicable scope is relatively narrow; (3) The accuracy is generally not high. Summary of the Invention

[0005] To overcome the shortcomings of the existing technology, the purpose of this invention is to provide a tire tread depth measurement method based on point laser. It relies on a parking-type measurement device using point laser and processes the returned detection data through this invention.

[0006] The technical solution of the present invention is as follows:

[0007] A method for measuring tire tread depth based on point laser includes the following steps:

[0008] Step 1: Divide the measuring device into 3 equal segments, place the tire in the divided segments one by one, and use the point laser sensor to perform 3 back-and-forth sweeps to obtain the returned detection data, which are denoted as DataOne, DataTwo and DataThree, as shown in equations (1), (2) and (3).

[0009]

[0010]

[0011]

[0012] in, This represents the coordinates of the i-th point in DataOne. This represents the time when the i-th coordinate point in DataOne was collected. This represents the coordinates of the i-th point in DataTwo. This represents the time when the i-th coordinate point in DataTwo was collected. This represents the coordinates of the i-th point in DataThree. This represents the time taken to collect data at the i-th coordinate point in DataThree;

[0013] Step 2: Merge the DataOne, DataTwo, and DataThree data transmitted back from these point laser sensors. The specific steps are as follows:

[0014] Step 2.1: Calculate the average x-coordinates of the points in DataOne, DataTwo, and DataThree respectively, and denote them as Avg1, Avg2, and Avg3 respectively;

[0015] Step 2.2: Calculate the average value Mid of Avg1, Avg2 and Avg3 according to equation (4). According to equations (5), (6) and (7), the x-coordinates of the points in DataOne, DataTwo and DataThree are translated and updated respectively to obtain new DataOne, DataTwo and DataThree. Then, these three new sets are merged using equation (8) to obtain Data.

[0016] Mid=(Avg1+Avg2+Avg3) / 3 (4)

[0017]

[0018]

[0019]

[0020] Data=DataOne∪DataTwo∪DataThree={(x i ,y i ,t i )|i=1,…,n} (8)

[0021] where n=n1+n2+n3, n represents the number of elements in Data, (x i ,y i ) represents the coordinates of the i-th point in Data, t i represents the acquisition time of the i-th coordinate point in Data;

[0022] Step 2.3: For any i-th and (i+1)-th point in Data, perform outlier elimination in the following manner: if y i+1 -y i >D0 and t i+1 -t i <T0, the i-th point is determined as an outlier, and the i-th point is eliminated from Data; if y i -y i+1 >D0 and t i -t i+1 <T0, the (i+1)-th point is determined as an outlier, and the (i+1)-th point is eliminated from Data; this operation is repeated until no outliers remain; where T0 represents the threshold of the time difference between adjacent coordinate point acquisitions, and D0 represents the threshold of the ordinate difference between adjacent coordinate points;

[0023] Step 3: Perform quadratic B-spline smoothing on Data, and the specific steps are as follows:

[0024] Step 3.1: Correct the first and last points in Data according to equations (9) and (10);

[0025]

[0026]

[0027] where (x1,y1) is the first point in Data, (x n ,y n) is the end point in Data;

[0028] Step 3.2: Perform smoothing processing on Data in the following way: take any i-th, (i+1)-th, and (i+2)-th points; if i=1, update (x1, y1) and (x2, y2) according to Equation (14); if i=n-2, update (x n-1 ,y n-1 ) and (x n ,y n ); if 1<i<n-2, update (x i-1 ,y i-1 ) according to Equation (16); repeat this operation to obtain the smoothed Data;

[0029]

[0030]

[0031]

[0032]

[0033]

[0034]

[0035] where p0, p1 and p2 respectively represent different curve parameter weights, and Equations (11), (12) and (13) are quadratic B-spline basis functions;

[0036] Step 4: Perform turning point judgment on the smoothed Data, and the specific steps are as follows:

[0037] Step 4.1: Take any (i-2)-th, (i-1)-th, i-th, (i+1)-th, and (i+2)-th points to form a point set LP, as shown in Equation (17), use the least square method to perform straight line fitting on the points in the point set LP, and denote the obtained straight line as L i :y i =k i x+b i , i=1,2,..,n, where k i represents the slope of the straight line L i , b i represents the intercept of the straight line L i on the y-axis; then all the straight lines L i constitute a set Line, as shown in Equation (18);

[0038]

[0039] Line={L i|i=1,…,n} (18)

[0040] Step 4.2: Take any line L from the set Line, specifically the line L at the i-th and (i+1)-th positions. i and L i+1 Calculate L i and L i+1 The included angle θ between them is shown in equation (19);

[0041]

[0042] Step 4.3: If θ > θ0, then set the i-th point as a turning point; otherwise, set it as a non-turning point; where θ0 represents the angle threshold for determining the turning point.

[0043] Step 4.4: Extract the index values ​​of all turning points in Data and construct the turning point index set TP = {v} in ascending order. j |j=1,2,…,K}, where K represents the number of elements in TP, v j This represents the index value of the j-th turning point in TP;

[0044] Step 5: Determine the groove area by the turning point. The specific steps are as follows:

[0045] Step 5.1: Traverse the inflection point index set TP, for any j-th index value v j From the vth data j If there are C points on each side of a given point, and equation (20) is satisfied, then determine v. j If it is not a boundary point of the groove region, v j Remove from the inflection point index set TP; after the operation is completed, a new TP is obtained;

[0046]

[0047] in, Indicates the vth j The ordinate values ​​of each point, x k This represents the x-coordinate of the k-th point;

[0048] Step 6: Traverse the inflection point index set TP and calculate the tread depth of the j-th tread pattern of the tire, j = 1, 2, ..., K-1. The specific steps are as follows:

[0049] Step 6.1: Establish Connections and straight line L j Calculate the line L according to equation (21) j slope k j and intercept b j ;

[0050]

[0051] Among them, v j and v j+1 For the j-th and (j+1)-th index values ​​in the inflection point index set TP, and These represent the two boundary points of the j-th groove region. Indicates the vth j The x-coordinate of each point, Indicates the vth j The ordinate values ​​of each point;

[0052] Step 6.2: According to equation (22), find the index value i* of the element with the smallest ordinate corresponding to the element in Data. Then, according to equation (23), the j-th tire tread depth value Depth can be calculated. j .

[0053]

[0054] Depth j =x i* *k j +b j -y i* (twenty three)

[0055] Where, x i* Let y be the x-coordinate of the i*th point in Data. i* This is the ordinate value of the i*th point in Data.

[0056] Compared with the prior art, the beneficial results of the present invention are as follows: The present invention processes point laser detection data through multi-position correction, introduces quadratic B-splines for curve smoothing, and adds the discrimination of inflection points, which effectively improves the accuracy of using point laser to detect tire tread depth when parked. Attached Figure Description

[0057] Figure 1 Diagram of a tire inspection device;

[0058] Figure 2 To merge data images;

[0059] Figure 3 for Figure 2 The image after quadratic B-spline smoothing;

[0060] Figure 4 for Figure 3 The image after the turning point is determined. Detailed Implementation

[0061] The following examples illustrate in detail the specific implementation of the tire tread depth measurement method based on point laser of the present invention.

[0062] The tire tread depth measurement method based on point laser of the present invention specifically includes the following steps:

[0063] Step 1: Divide the measuring device into 3 equal segments, place the tire in the divided segments one by one, and use the point laser sensor to perform 3 back-and-forth sweeps to obtain the returned detection data, which are denoted as DataOne, DataTwo and DataThree, as shown in equations (1), (2) and (3).

[0064]

[0065]

[0066]

[0067] in, This represents the coordinates of the i-th point in DataOne. This represents the time when the i-th coordinate point in DataOne was collected. This represents the coordinates of the i-th point in DataTwo. This represents the time when the i-th coordinate point in DataTwo was collected. This represents the coordinates of the i-th point in DataThree. This indicates the time of data acquisition for the i-th coordinate point in DataThree. The tire measuring device is as follows: Figure 1 As shown. 1 represents the measurement start point, 2 represents the measurement end point, 3 represents the point laser sensor, 4 represents the lead screw slide, and A1 and A2 represent the segment points. The point laser sensor scans from 1 to 2 and then returns from 2 to 1.

[0068] Step 2: Combine the DataOne, DataTwo, and DataThree data transmitted back from these point laser sensors. The result is as follows: Figure 2 As shown, the specific steps are as follows:

[0069] Step 2.1: Calculate the average x-coordinates of the points in DataOne, DataTwo, and DataThree respectively, and denote them as Avg1, Avg2, and Avg3 respectively;

[0070] Step 2.2: Calculate the average Mid of Avg1, Avg2 and Avg3 according to Equation (4), perform translation update on the abscissas of the points in DataOne, DataTwo and DataThree respectively according to Equation (5), (6) and (7) to obtain new DataOne, DataTwo and DataThree, then combine these three new sets using Equation (8) to obtain Data;

[0071] Mid=(Avg1+Avg2+Avg3) / 3 (4)

[0072]

[0073]

[0074]

[0075] Data=DataOne∪DataTwo∪DataThree={(x i ,y i ,t i )i=1,…,n} (8)

[0076] where n=n1+n2+n3, n represents the number of elements in Data, (x i ,y i ) represents the coordinates of the i-th point in Data, t i represents the acquisition time of the i-th coordinate point in Data;

[0077] Step 2.3: For any i-th and (i+1)-th point in Data, perform outlier elimination in the following way: if y i+1 -y i >D0 and t i+1 -t i <T0, the i-th point is determined as an outlier, and the i-th point is eliminated from Data; if y i -y i+1 >D0 and t i -t i+1 <T0, the (i+1)-th point is determined as an outlier, and the (i+1)-th point is eliminated from Data; repeat this operation until there are no outliers; where T0 represents the threshold of the time difference between adjacent coordinate point acquisitions, D0 represents the threshold of the ordinate difference between adjacent coordinate points. In this example, T0=50ms, D0=2mm; Step 3: Perform quadratic B-spline smoothing on Data, the result is shown in Figure 3 , and the specific steps are as follows:

[0078] Step 3.1: Correct the first and last points in Data according to Equations (9) and (10);

[0079]

[0080]

[0081] where (x1, y1) is the first point in Data, (x n , y n ) is the last point in Data;

[0082] Step 3.2: Perform smoothing processing on Data in the following manner: take any arbitrary i-th, i+1-th, and i+2-th points; if i=1, update (x1, y1) and (x2, y2) according to Equation (14); if i=n-2, update (x n-1 , y n-1 ) and (x n , y n ) according to Equation (15); if 1<i<n-2, update (x i-1 , y i-1 ) according to Equation (16); repeat this operation to obtain the smoothed Data;

[0083]

[0084]

[0085]

[0086]

[0087]

[0088]

[0089] where p0, p1 and p2 respectively represent different curve parameter weights, and Equations (11), (12) and (13) are quadratic B-spline basis functions. In this example, p0=0, p1=0.5, p2=1;

[0090] Step 4: Perform turning point judgment on the smoothed Data, the result is as shown Figure 4 , and the specific steps are as follows:

[0091] Step 4.1: Take any arbitrary i-2-th, i-1-th, i-th, i+1-th, and i+2-th points to form a point set LP as shown in Equation (17), perform straight line fitting on the points in the point set LP using the least squares method, and denote the obtained straight line as L i : y i =k ix+b i , i = 1, 2, ..., n, where k i Represents line L i The slope, b i Represents line L i The y-intercept; then all lines L i The set Line is formed as shown in equation (18);

[0092]

[0093] Line = {L i |i=1,…,n} (18)

[0094] Step 4.2: Take any line L from the set Line, specifically the line L at the i-th and (i+1)-th positions. i and L i+1 Calculate L i and L i+1 The included angle θ between them is shown in equation (19);

[0095]

[0096] Step 4.3: If θ > θ0, then set the i-th point as a turning point; otherwise, set it as a non-turning point; where θ0 represents the angle threshold for determining the turning point, and in this example, θ0 = 30°;

[0097] Step 4.4: Extract the index values ​​of all turning points in Data and construct the turning point index set TP = {v} in ascending order. j |j=1,2,…,K}, where K represents the number of elements in TP, v j This represents the index value of the j-th turning point in TP;

[0098] Step 5: Determine the groove area by the turning point. The specific steps are as follows:

[0099] Step 5.1: Traverse the inflection point index set TP, for any j-th index value v j From the vth data j If there are C points on each side of a given point, and equation (20) is satisfied, then determine v. j If it is not a boundary point of the groove region, v j Remove from the inflection point index set TP; after the operation is completed, a new TP is obtained;

[0100]

[0101] in, Indicates the vth j The ordinate values ​​of each point, x kThis represents the x-coordinate of the k-th point.

[0102] In this example, C = 5;

[0103] Step 6: Traverse the inflection point index set TP, calculate the tread depth of the j-th tread pattern of the tire, j = 1, 2, ..., K-1. The depth calculation results are shown in Table 1. The specific steps are as follows:

[0104] Step 6.1: Establish Connections and straight line L j Calculate the line L according to equation (21) j slope k j and intercept b j ;

[0105]

[0106] Among them, v j and v j+1 For the j-th and (j+1)-th index values ​​in the inflection point index set TP, and These represent the two boundary points of the j-th groove region. Indicates the vth j The x-coordinate of each point, Indicates the vth j The ordinate values ​​of each point;

[0107] Step 6.2: According to equation (22), find the index value i* of the element with the smallest ordinate corresponding to the element in Data. Then, according to equation (23), the j-th tire tread depth value Depth can be calculated. j .

[0108]

[0109] Depth j =x i* *k j +b j -y i* (twenty three)

[0110] Where, x i* Let y be the x-coordinate of the i*th point in Data. i* This is the ordinate value of the i*th point in Data.

[0111] Table 1: Final Depth Calculation Chart

[0112] First pattern 6.67 6.56 The second pattern 7.18 7.14 The third pattern 7.40 7.32 Fourth pattern 6.67 6.59

[0113] The embodiments described in this specification are merely examples of implementations of the inventive concept. The scope of protection of this invention should not be considered as limited to the specific forms described in the embodiments. The scope of protection of this invention also extends to equivalent technical means that can be conceived by those skilled in the art based on the inventive concept.

Claims

1. A method for measuring tire tread depth based on point laser, characterized in that, Includes the following steps: Step 1: Divide the measuring device into 3 equal segments, place the tire in the divided segments one by one, and use the point laser sensor to perform 3 back-and-forth sweeps to obtain the returned detection data, which are recorded as DataOne, DataTwo and DataThree. Step 2: Merge the returned detection data DataOne, DataTwo, and DataThree. The specific steps are as follows: Step 2.1: Calculate the average x-coordinates of the points in DataOne, DataTwo, and DataThree respectively, and denote them as Avg1, Avg2, and Avg3 respectively; Step 2.2: Calculate the average value Mid of Avg1, Avg2 and Avg3 according to equation (4). According to equations (5), (6) and (7), the x-coordinates of the points in DataOne, DataTwo and DataThree are translated and updated respectively to obtain new DataOne, DataTwo and DataThree. Then, these three new sets are merged using equation (8) to obtain Data. (4)； (5)； (6)； (7)； (8)； Where n = n1 + n2 + n3, n represents the number of elements in Data. This represents the coordinates of the i-th point in Data. This indicates the time when the i-th coordinate point in Data was collected; Step 2.3: For any i-th and i+1-th points in Data, remove outliers; Step 3: Perform quadratic B-spline smoothing on the Data; Step 3.1: Correct the first and last points in the Data; Step 3.2: Perform smoothing processing on Data: take any i-th, (i+1)-th, and (i+2)-th points; if i=1, update (x1, y1) and (x2, y2) according to Equation (14); if i=n-2, update (x n-1 , y n-1 ) and (x n , y n ); if 1<i<n-2, update (x i-1 , y i-1 ); repeat this operation to obtain the smoothed Data; (11)； (12)； (13)； (14)； (15)； (16)； Where p0, p1 and p2 represent different curve parameter weights, and equations (11), (12) and (13) are quadratic B-spline basis functions; Step 4: Determine the turning point for the smoothed data; Step 4.1: Take any i-2, i-1, i, i+1, i+2 points to form a point set LP, as shown in equation (17). Use the least squares method to fit a straight line to the points in the point set LP, and denote the obtained straight line as L. i y i =k i x+b i Let i = 1, 2, ..., n, where k i Represents line L i The slope, b i Represents line L i The y-intercept; then all lines L i The set Line is formed as shown in equation (18); (17)； (18)； Step 4.2: Take any line L from the set Line, specifically the line L at the i-th and (i+1)-th positions. i and L i+1 Calculate L i and L i+1 The included angle θ between them is shown in equation (19); (19)； Step 4.3: If θ > θ0, then set the i-th point as a turning point; otherwise, set it as a non-turning point; where θ0 represents the angle threshold for determining the turning point. Step 4.4: Extract the index values ​​of all turning points in Data and construct a turning point index set TP={v} in ascending order. j | j=1, 2, …, K}, where K represents the number of elements in TP, v j This represents the index value of the j-th turning point in TP; Step 5: Identify the groove area by the turning point; Step 5.1: Traverse the inflection point index set TP, for any j-th index value v j From the vth data j If there are C points on each side of a given point, and equation (20) is satisfied, then determine v. j If it is not a boundary point of the groove region, v j Remove from the inflection point index set TP; after the operation is completed, a new TP is obtained; (20)； in, Indicates the vth j The ordinate values ​​of each point, x k This represents the x-coordinate of the k-th point; Step 6: Traverse the set of inflection point indices TP and calculate the tread depth of the j-th tread pattern of the tire, j=1,2,…,K-1; Step 6.1: Establish Connections and straight line L j Calculate the line L according to equation (21) j slope k j and intercept b j ; (21)； Among them, v j and v j+1 For the j-th and (j+1)-th index values ​​in the inflection point index set TP, and These represent the two boundary points of the j-th groove region. Indicates the vth j The x-coordinate of each point, Indicates the vth j The ordinate values ​​of each point; Step 6.2: Find the index value i* of the element with the smallest ordinate in Data according to equation (22), and calculate the j-th tire tread depth value Depth according to equation (23). j : (22)； (23)。 2. The method for measuring tire tread depth based on point laser according to claim 1, characterized in that, In step 1, DataOne, DataTwo, and DataThree are as shown in equations (1), (2), and (3); (1)； (2)； (3)； in, This represents the coordinates of the i-th point in DataOne. This represents the time when the i-th coordinate point in DataOne was collected. This represents the coordinates of the i-th point in DataTwo. This represents the time when the i-th coordinate point in DataTwo was collected. This represents the coordinates of the i-th point in DataThree. This represents the time taken to collect data at the i-th coordinate point in DataThree.

3. The method for measuring tire tread depth based on point laser according to claim 1, characterized in that, In step 2.3), outlier removal is performed as follows: If y i+1 -y i >D0 and t i+1 -t i <T0, it is determined that the i-th point is an abnormal point, and the i-th point is excluded from Data; if y i -y i+1 >D0 and t i -t i+1 <T0, it is determined that the (i+1)-th point is an abnormal point, and the (i+1)-th point is excluded from Data; this operation is repeated until there are no abnormal points; where T0 represents the threshold of the time difference between adjacent coordinate point acquisitions, and D0 represents the threshold of the ordinate difference between adjacent coordinate points.

4. The method for measuring tire tread depth based on point laser according to claim 1, characterized in that, In step 3.1, the first and last points in Data are corrected according to equations (9) and (10); (9)； (10) ； Where (x1, y1) is the first point in Data, (x n ,y n ) represents the end point in Data.

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