A method for identifying and processing abnormal test data of tire ground contact pressure distribution detection system

Abstract

The present invention belongs to the technical field of tire manufacturing, and relates to a method for identifying and processing abnormal test data of a radial force loading platform and a pressure blanket for a vehicle tire ground pressure detection system. A method for identifying and processing abnormal test data of a tire ground pressure distribution detection system, the method comprising the following steps: 1) tire preparation; 2) selecting a control tire; 3) determining the control point position; 4) determining the difference in the position of the pressure blanket; 5) daily monitoring of the control tire; 6) abnormal detection of the verticality of the loading force and the platform; 7) detection of uneven damage to the sensing piece; 8) detection of overall damage to the sensing piece or failure of the control tire. The method uses multiple positions of a single control tire to identify common data abnormalities of the ground pressure distribution detection system, and the method is reliable, simple in procedure, and has high test efficiency.

Description

Technical Field

[0001] The invention belongs to the technical field of tire manufacturing, and relates to a method for identifying and processing abnormal test data of a radial force loading platform and a pressure blanket used in a ground contact pressure detection system of an automobile tire. Background Art

[0002] The tire ground pressure distribution performance test is an indispensable test item in the tire development process. Conventional tire external characteristics are reflected in the ground pressure distribution, including noise, wet grip, wear and handling stability. The tire ground pressure distribution test equipment generally consists of two parts, namely the loading platform and the pressure blanket. The loading platform mainly provides a platform for placing the pressure blanket and the loading of force. The numerical accuracy of the loading force, the accuracy of the radial loading direction of the force and the horizontality of the platform will affect the ground pressure distribution results. The pressure blanket consists of a sensing sheet and a data collector. The sensing sheet is covered with millimeter-level pressure sensors, which can record the size of the pressure and the composition of the graph, and record it through the data collector. The sensing sheet is a consumable part, and its pressure sensor will fail after a certain number of uses. The recommended number of uses is 1000 to 1500 times. However, in the actual ground pressure distribution test, the tire working conditions are complex, and the ground pressure distribution tests of small-load tires, large-load tires and run-flat tires must have different degrees of influence on the sensing sheet. In summary, the ground pressure distribution test involves many devices, and it is necessary to establish a method that can timely monitor whether the ground pressure distribution performance test data is valid and accurately find the cause of data abnormality. Summary of the invention

[0003] In order to solve the above-mentioned technical problems, the present invention provides a method for identifying and processing test data anomalies of a tire ground contact pressure distribution detection system. The method uses multiple positions of a single control tire to identify common data anomalies of the ground contact pressure distribution detection system. The method is reliable, simple in procedure and has high test efficiency.

[0004] In order to achieve the above-mentioned purpose, the present invention adopts the following technical solutions:

[0005] A method for identifying and processing abnormal test data of a tire ground contact pressure distribution detection system, the method comprising the following steps:

[0006] 1) Tire preparation

[0007] Select several tires of the same specification with a nominal section width of not less than 225mm, symmetrical tread and only three grooves. Install the test tires in a distributed manner and run them on a drum at a low speed to eliminate residual stress;

[0008] 2) Choose a control tire

[0009] Determine the ground pressure distribution test air pressure P and test load F, record and calculate the test data under the loading stable state, including: the coefficient of variation ε of the tire contact area S1, S2, S3, S4 in each quadrant, the ratio k of the difference in the footprint area between the inner and outer sides of the tire (A1-A2) to the total footprint area, and the tire hardness coefficient φ, see formula (1) to formula (3);

[0010]

[0011]

[0012]

[0013] The coordinate system for dividing quadrants takes the tire footprint center as the origin, the tire forward direction is the positive direction of the x-axis, and the tire outer side is the negative direction of the y-axis; the ground pressure distribution test conditions involved below are the same;

[0014] Conduct ground contact pressure distribution tests on each of the above tires at multiple locations on the tire, and select the tire with the smallest standard deviation of hardness coefficient at different locations on the tire as the control tire;

[0015] 3) Determine the control point

[0016] Four more ground contact pressure distribution tests were conducted at multiple locations of the control tire. Combining the data from the five tests, the location with the smallest standard deviation of the hardness coefficient at the same location at different times was selected as the control point. The standard deviation of the hardness coefficient at this location is recorded as Take the two largest values ​​and the smallest value of the hardness coefficient data measured by all control tires to calculate the standard deviation, which is recorded as The mean value of the hardness coefficient measured at the control points is

[0017] 4) Determine the difference in pressure blanket position

[0018] Fixed the tire control point position, carried out a ground pressure distribution test in the common area of ​​the pressure blanket, and after completing the test, fine-tuned the position of the pressure blanket sensor and carried out another ground pressure distribution test. A total of 5 tests were carried out to calculate the standard deviation of the tire hardness coefficient at different pressure blanket positions. Calculate the mean ε0 of the coefficient of variation of the contact area in the four quadrants measured at different pressure blanket positions;

[0019] 5) Daily monitoring of the fetus

[0020] Regularly use the control tire to conduct a ground pressure distribution monitoring test at the control point. Suppose the hardness coefficient measured in the nth daily monitoring test is The coefficient of variation of the contact area of ​​the control tire in the four quadrants is ε n, the ratio of the difference in the footprint area between the inner and outer sides of the tire to the total footprint area k n ;

[0021] 6) Abnormal detection of loading force and platform verticality

[0022] If |k n |>1.5%, or k n―2 , k n―1 , k n are greater than 1%, or k n―2 , k n―1 , k n If both are less than -1%, it is judged that the verticality of the applied radial force is abnormal, and the camber angle of the loading force needs to be calibrated;

[0023] 7) Detection of uneven damage of sensor sheet

[0024] If the verticality of the applied radial force is not judged to be abnormal, but ε n >3%+ε0, it is judged that the sensor sheet is unevenly damaged. At this time, you can choose to avoid the quadrant where the sensor sheet is more damaged for testing; if it is impossible to avoid it, or after avoiding it, ε n If it is still greater than 3%+ε0, replace the sensor directly;

[0025] 8) Detection of overall damage to the sensor or failure of the control tire

[0026] If the verticality of the applied radial force does not exceed the standard, and ε n ≤3%+ε0, standard deviation σ of daily monitoring and control tire hardness coefficient calculated according to formulas (4), (5) and (6) n , and the limit value σ0 used to determine whether the ground pressure distribution test data is abnormal;

[0027]

[0028]

[0029]

[0030] If σ n ≤σ0, the overall sensor status of the equipment is good; if σ n >σ0, it is necessary to carry out ground pressure distribution tests at multiple positions of the control tire. If the maximum standard deviation δ of the hardness coefficients measured at three positions in different positions is greater than σ0, it is determined that the control tire has failed and needs to be replaced. Otherwise, it is determined that the sensor of the ground pressure distribution detection system is abnormal. It is necessary to calibrate the sensor of the loading platform force first, and choose whether to replace the sensor piece based on the calibration result.

[0031] Furthermore, the present invention also discloses a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement step 6) to step 8) in the method.

[0032] Furthermore, the present invention also discloses a computer-readable storage medium on which a computer program or instruction is stored. When the computer program or instruction is executed by a processor, step 6) to step 8) of the method are implemented.

[0033] Furthermore, the present invention also discloses a computer program product, including a computer program or an instruction, which implements step 6) to step 8) in the method when executed by a processor.

[0034] Beneficial effects of the present invention

[0035] (1) The daily monitoring test of the present invention only involves one control tire and ground contact pressure distribution test. The method is reliable, simple in procedure and high in test efficiency.

[0036] (2) The present invention can effectively identify whether the radial force in the ground contact pressure distribution detection system is vertical, whether the sensing piece has been damaged beyond the permitted limits, whether the control tire has failed, and whether the sensor is abnormal. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is the coordinate system of the ground pressure distribution test footprint.

[0038] Figure 2 This is the ground pressure distribution detection system status monitoring flow chart. DETAILED DESCRIPTION

[0039] The technical solution of the present invention is further illustrated below through specific implementation cases.

[0040] Select 5 225 / 55R16 tires with symmetrical treads and only 3 tread grooves, numbered 1# to 5#, install the test tires and run them on a drum tester at low speed for 1 hour, and leave them at room temperature for 3 hours. Divide the tire into 5 equal parts, and conduct a ground pressure distribution test at each equal point with a test load of 6762N and a test pressure of 180kPa. The hardness coefficient data is shown in Table 1:

[0041] Table 1 Individual hardness coefficients of different tires

[0042]

[0043] The 2# tire with the smallest standard deviation at different positions was determined as the control tire, and the ground contact pressure distribution test was continued for 3 times at its 5 equally divided points. The hardness coefficient test data is shown in Table 2:

[0044] Table 2 Reproducibility of hardness coefficient at different tire positions

[0045]

[0046] Determine the first equally divided point with the smallest standard deviation of different times as the control point, σ φmin =0.0084, the minimum value of the measured control tire hardness coefficient is 1.5629, and the two maximum values ​​are 1.6162 and 1.6111 respectively. The calculated σ φmax =0.0294. The mean value of the hardness coefficient of the control point is calculated as φ0 = 1.5792.

[0047] Use the control point position, and conduct a ground pressure distribution test in the common area of ​​the pressure blanket sensing piece and the area about 1 cm above, below, left and right. The hardness coefficients are 1.5781, 1.5865, 1.6023, 1.5956, and 1.6085 respectively. The standard deviation of the hardness coefficients at different sensing piece positions is σ φ0 =0.0122. The coefficients of variation of the contact areas of the four quadrants are 1.34%, 1.27%, 1.61%, 1.52%, and 1.65%, respectively, and their average ε0 = 1.48%. The sensor status normal limit σ0 = 0.0354 is calculated using formula (4).

[0048] The control tire and its control points were used to conduct a weekly ground contact pressure distribution test system test data abnormality monitoring test. The test data for the first 20 weeks, a total of 20 times, are shown in Table 3:

[0049] Table 3 Reproducibility of hardness coefficient at different tire positions

[0050]

[0051]

[0052] σ n Refer to formulas (5) and (6) for calculation.

[0053] In the first 19 monitoring tests, k n The absolute value of is less than 1.5%, and there has not been a situation where it is greater than 1% or less than -1% for at least three consecutive times; ε n All less than 3% + 1.48%; σ n All of them are less than σ0, indicating that the verticality of radial force loading was normal during the first 19 monitoring times, the pressure blanket sensor did not suffer from serious uneven damage, and the data output by the equipment was stable. 20 It can be seen that the loading verticality is normal, but ε 20=4.6%>3%+1.48%, indicating that the pressure blanket sensor has been seriously unevenly damaged. If not handled in time, the existence of this phenomenon may mislead tire developers. From the historical data of the contact area of ​​the four quadrants, it is found that the damage degree of the second and third quadrants in the tire footprint data is greater than that of the first and fourth quadrants. The main damaged area of ​​the sensor cannot be avoided, so the sensor is replaced and retested.

[0054] The above is a description of the embodiments of the present invention. Through the above description of the disclosed embodiments, professionals and technicians in the field can implement or use the present invention. Various modifications to these embodiments will be apparent to professionals and technicians in the field. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown in this article, but will conform to the widest range consistent with the principles and novelties disclosed herein.

Claims

1. A method for identifying and processing abnormal test data of a tire ground contact pressure distribution detection system, the method comprising the following steps: 1) Tire preparation Select several tires of the same specification with a nominal section width of not less than 225mm, symmetrical tread and only three tread grooves; install the test tires in a distributed manner and run them on a drum at a low speed to eliminate residual stress; 2) Choose a control tire Determine the ground pressure distribution test air pressure P and test load F, record and calculate the test data under the loading stable state, including: the coefficient of variation ε of the tire contact area S1, S2, S3, S4 in each quadrant, the ratio k of the difference in the footprint area between the inner and outer sides of the tire (A1-A2) to the total footprint area, and the tire hardness coefficient φ, see formula (1) to formula (3); Formula (1) Formula (2) Formula (3) in, A1 and A2 are the footprint areas on the inner and outer sides of the tire. The coordinate system for dividing the quadrants takes the tire footprint center as the origin, the tire forward direction is the positive direction of the x-axis, and the outer side of the tire is the negative direction of the y-axis. The ground pressure distribution test conditions involved below are the same; Conduct ground contact pressure distribution tests on each of the above tires at multiple locations on the tire, and select the tire with the smallest standard deviation of hardness coefficient at different locations on the tire as the control tire; 3) Determine the control point Four more ground contact pressure distribution tests were conducted at multiple locations of the control tire. Combining the data from the five tests, the location with the smallest standard deviation of the hardness coefficient at the same location at different times was selected as the control point. The standard deviation of the hardness coefficient at this location is recorded as , take the two largest values ​​and the smallest value of the hardness coefficient data measured by all control tires to calculate the standard deviation, recorded as ; Take the mean value of the hardness coefficient measured at the control point as φ0; 4) Determine the difference in pressure blanket position Fixed the tire control point position, carried out a ground pressure distribution test in the common area of ​​the pressure blanket, and after completing the test, fine-tuned the position of the pressure blanket sensor and carried out another ground pressure distribution test. A total of 5 tests were carried out to calculate the standard deviation of the tire hardness coefficient at different pressure blanket positions. , calculate the mean value ε0 of the coefficient of variation of the contact area of ​​the four quadrants measured at different pressure blanket positions; 5) Daily monitoring of the fetus Use the control tire to conduct a ground pressure distribution monitoring test at the control point regularly. Suppose the hardness coefficient measured in the nth daily monitoring test is φ n , the coefficient of variation of the contact area of ​​the control tire in the four quadrants is ε n , the ratio of the difference in the footprint area between the inner and outer sides of the tire to the total footprint area k n ; 6) Abnormal detection of loading force and platform verticality if ,or , , All greater than 1%, or , , If both are less than -1%, it is judged that the verticality of the applied radial force is abnormal, and the camber angle of the loading force needs to be calibrated; 7) Detection of uneven damage of sensor sheet If the verticality of the applied radial force is not judged to be abnormal, but >3%+ , it is determined that the sensor sheet is unevenly damaged. At this time, you can choose to avoid the quadrant where the sensor sheet is more damaged for testing; if it is impossible to avoid it, or after avoiding it Still greater than 3%+ Then directly replace the sensor piece; 8) Detection of overall damage to the sensor or failure of the control tire If the radial force is applied within the verticality limit, and ≤3%+ , the standard deviation of the daily monitoring and control tire hardness coefficient calculated according to formulas (4), (5) and (6) , and the limit value used to determine whether the ground pressure distribution test data is abnormal ; Among them: The mean value of the hardness coefficient measured at the control point is , the hardness coefficient measured by the nth daily monitoring test is The tire hardness coefficient value for the i-th time in the control cycle is ; like ≤ The overall sensor status of the device is good; if > , then it is necessary to carry out ground contact pressure distribution tests at multiple locations of the control tire. If the maximum standard deviation δ of the hardness coefficients measured at three locations in different locations is greater than , it is determined that the control tire has failed and needs to be replaced. Otherwise, it is determined that the ground pressure distribution detection system sensor is abnormal. It is necessary to calibrate the loading platform force sensor first and choose whether to replace the sensor piece based on the calibration result.

2. A computer 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 steps 1) to 8) of the method of claim 1.

3. A computer-readable storage medium having a computer program or instruction stored thereon, characterized in that: When the computer program or instruction is executed by a processor, steps 1) to 8) of the method according to claim 1 are implemented.

4. A computer program product comprising a computer program or instructions, characterized in that When the computer program or instruction is executed by a processor, steps 1) to 8) of the method according to claim 1 are implemented.

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