A tire tread fluid pressure testing method and system

Abstract

The present invention relates to the technical field of tire fluid pressure testing. The present invention provides a tire tread fluid pressure testing method and system. The present invention improves the problem of low test accuracy in the prior art. By collecting a variety of data to train a neural network model, an initial control model is obtained. After receiving a test task, the control parameters of the test equipment are dynamically adjusted according to the task requirements, and the test data is collected in real time for iterative optimization to improve the test accuracy. If the error exceeds the range, the random forest model is trained using historical data for replacement. At the same time, the system can also simulate natural environmental conditions for testing to improve the authenticity of the test. The present invention significantly improves the accuracy of the test through intelligent and modular design.

Description

Technical Field

[0001] The present invention relates to the technical field of tire fluid pressure testing, and in particular to a tire tread fluid pressure testing method and system. Background Art

[0002] The tire tread fluid pressure test method involves measuring the pressure distribution and changes when the tire contacts the road or fluid under specific conditions. For example, on outdoor roads, especially on wet roads or icy and snowy roads, by controlling the water film depth (such as increasing to more than 7mm) and the vehicle speed (such as 200km / h-1), the changes in indicators such as the tire's steering performance, stability, and lateral grip can be observed. The tire tread fluid pressure test can simulate the hydroplaning phenomenon encountered by the tire in the actual use environment, understand the response characteristics of the tire tread under different fluid pressures, and provide a basis for the design and optimization of the tire.

[0003] Tire tread fluid pressure testing is affected by many factors, including the accuracy of the testing equipment, the stability of the testing environment, the operating level of the tester, etc., all of which affect the accuracy of the test data. In a complex and changeable testing environment, the existing technology is unable to test the tire tread fluid pressure and is unable to make adaptive adjustments according to the testing needs, resulting in reduced accuracy of the tire tread fluid pressure test. To address this technical pain point, the present invention provides a tire tread fluid pressure testing method and system. Summary of the invention

[0004] In view of the shortcomings of the prior art, the present invention provides a tire tread fluid pressure testing method and system to solve the problem that the prior art is unable to test the tire tread fluid pressure and cannot be adaptively adjusted according to test requirements, resulting in reduced accuracy of the tire tread fluid pressure test.

[0005] In order to solve the above technical problems, the specific technical solutions of the present invention are as follows:

[0006] In a first aspect, the present invention provides a tire tread fluid pressure testing method, comprising:

[0007] Step S101, obtaining pressure distribution data, environmental parameter data, vehicle driving parameter data, tire status data and timestamp data when the tire is in contact with the road surface or fluid, using the pressure distribution data, environmental parameter data, vehicle driving parameter data, tire status data and timestamp data when the tire is in contact with the road surface or fluid to train a neural network model, obtain a first tire tread fluid pressure test control model, receive a test task, match the test task in a preset error knowledge base, and generate preset error data corresponding to the test task;

[0008] Step S102, substituting the test task into the first tire tread fluid pressure test control model, outputting the first test equipment control parameter, sending the first test equipment control parameter to the test equipment, and collecting data during the operation of the test equipment to obtain the real-time data of the first test equipment;

[0009] Step S103, comparing the real-time data of the first test device with the expected data to obtain the first test device operation error data, and comparing the first test device operation error data with the corresponding preset error range value. If it exceeds the preset error range value, the test device control parameter is optimized to obtain the first optimized test device control parameter;

[0010] Step S104, send the first optimized test equipment control parameter to the test equipment, obtain the second test equipment operation error data, compare the second test equipment operation error data with the preset error range value, if it exceeds the preset error range value, continue to optimize the test equipment control parameter to obtain the second optimized test equipment control parameter, send the second optimized test equipment control parameter to the test equipment, obtain the third test equipment operation error data, compare the third test equipment operation error data with the preset error range value, if the third test equipment operation error data meets the preset error range value, stop the test Optimize the equipment control parameters. If the running error data of the third test equipment exceeds the preset error range value, obtain the data of step S101, step S102, step S103 and step S104 to obtain the data to be processed, pre-process the data to be processed, train the random forest model based on the pre-processed data, obtain the second tire tread fluid pressure test control model, replace the first tire tread fluid pressure test control model with the second tire tread fluid pressure test control model, substitute the test task into the second tire tread fluid pressure test control model, and output the adjusted test equipment control parameters;

[0011] Step S105, sending the adjusted test equipment control parameters to the test equipment, matching the test task in the preset natural environment model parameter library, obtaining the natural environment model parameters corresponding to the test task, substituting the natural environment simulation model parameters into the test equipment, and obtaining the tire tread fluid pressure test results.

[0012] Furthermore, in the tire tread fluid pressure testing method of the present invention, step S102 comprises:

[0013] The test task includes tire type parameters, road condition parameters, fluid type parameters and test speed parameters, and the tire type parameters, road condition parameters, fluid type parameters and test speed parameters are input into a first tire tread fluid pressure test control model;

[0014] The first tire tread fluid pressure test control model outputs first test equipment control parameters according to the input tire type parameters, road condition parameters, fluid type parameters and test speed parameters, and the first test equipment control parameters include the pressure measurement range, sampling frequency and test duration of the test equipment;

[0015] After the test equipment starts running, the data during the test is continuously monitored and collected to obtain the first test equipment real-time data. The first test equipment real-time data includes the real-time pressure value when the tire contacts the road surface or fluid, the status information of the test equipment, and the change value of the environmental parameters.

[0016] Furthermore, in the tire tread fluid pressure testing method of the present invention, step S104 comprises:

[0017] Starting from step S101, pressure distribution data, environmental parameter data, vehicle driving parameter data, tire status data and timestamp data when the tire contacts the road surface or fluid are obtained;

[0018] The first test device control parameter outputted in step S102, and the first test device operation error data and the second test device operation error data calculated in step S103;

[0019] Also obtaining the third test device operation error data calculated in step S104;

[0020] The random forest model is trained based on the data of step S101, step S102, step S103 and step S104 to obtain the second tire tread fluid pressure test control model:

[0021] replacing the second tire tread fluid pressure test control model with the first tire tread fluid pressure test control model being used;

[0022] The test task is substituted into the second tire tread fluid pressure test control model, and the adjusted test equipment control parameters are obtained according to the output of the second tire tread fluid pressure test control model.

[0023] Furthermore, in the tire tread fluid pressure testing method of the present invention, step S105 comprises:

[0024] The adjusted test equipment control parameters obtained in step S104 are sent to the test equipment via network transmission;

[0025] Accessing a preset natural environment model parameter library, the preset natural environment model parameter library includes model parameters under natural environment conditions, the model parameters under natural environment conditions include temperature parameters, humidity parameters, road surface material parameters, water film depth parameters and wind speed parameters;

[0026] Matching is performed in the natural environment model parameter library according to the test task to obtain the natural environment model parameters that meet the test task;

[0027] Substitute the matched natural environment model parameters into the test equipment, and the natural environment model parameters will be used to simulate the natural conditions in the actual test environment;

[0028] Performing a tire tread fluid pressure test, after the test equipment is set according to the adjusted test equipment control parameters and natural environment model parameters, starting to perform the tire tread fluid pressure test;

[0029] During the test, the test equipment will continuously measure and record the pressure distribution of the tire when it contacts the road or fluid according to the preset sampling frequency and test duration parameters;

[0030] After the test is completed, the result data of the tire tread fluid pressure test is obtained from the test equipment. The result data of the tire tread fluid pressure test includes the pressure value of the tire at the center of the tread, the pressure value of the tire at the shoulder, the tire pressure distribution diagram, and the pressure change curve over time.

[0031] In a second aspect, the present invention provides a tire tread fluid pressure testing system, which is applied to a tire tread fluid pressure testing method, comprising:

[0032] A data acquisition module, used to acquire pressure distribution data, environmental parameter data, vehicle driving parameter data, tire status data and timestamp data when the tire is in contact with the road surface or fluid, use the pressure distribution data, environmental parameter data, vehicle driving parameter data, tire status data and timestamp data when the tire is in contact with the road surface or fluid to train a neural network model, obtain a first tire tread fluid pressure test control model, receive a test task, match the test task in a preset error knowledge base, and generate preset error data corresponding to the test task;

[0033] A data acquisition module, used to substitute the test task into the first tire tread fluid pressure test control model, output the first test equipment control parameter, send the first test equipment control parameter to the test equipment, and collect data during the operation of the test equipment to obtain real-time data of the first test equipment;

[0034] A data optimization module is used to compare the real-time data of the first test device with the expected data to obtain the operation error data of the first test device, and compare the operation error data of the first test device with the corresponding preset error range value. If the preset error range value is exceeded, the control parameters of the test device are optimized to obtain the first optimized control parameters of the test device;

[0035] A data processing module, used for sending the first optimized test equipment control parameter to the test equipment, obtaining the second test equipment operation error data, comparing the second test equipment operation error data with the preset error range value, and if it exceeds the preset error range value, continuing to optimize the test equipment control parameter to obtain the second optimized test equipment control parameter, sending the second optimized test equipment control parameter to the test equipment, obtaining the third test equipment operation error data, comparing the third test equipment operation error data with the preset error range value, and if the third test equipment operation error data meets the preset error range value, stopping the optimization of the test equipment control parameter; if the third test equipment operation error data exceeds the preset error range value, acquiring data from the data acquisition module, the data acquisition module, the data optimization module and the data processing module to obtain the data to be processed, preprocessing the data to be processed, training the random forest model based on the preprocessed data, obtaining the second tire tread fluid pressure test control model, replacing the first tire tread fluid pressure test control model with the second tire tread fluid pressure test control model, substituting the test task into the second tire tread fluid pressure test control model, and outputting the adjusted test equipment control parameters;

[0036] The test result generation module is used to send the adjusted test equipment control parameters to the test equipment, match the test task in the preset natural environment model parameter library, obtain the natural environment model parameters corresponding to the test task, substitute the natural environment simulation model parameters into the test equipment, and obtain the tire tread fluid pressure test results.

[0037] Furthermore, in the tire tread fluid pressure testing system of the present invention, the data acquisition module is also used for:

[0038] The test task includes tire type parameters, road condition parameters, fluid type parameters and test speed parameters, and the tire type parameters, road condition parameters, fluid type parameters and test speed parameters are input into a first tire tread fluid pressure test control model;

[0039] The first tire tread fluid pressure test control model outputs first test equipment control parameters according to the input tire type parameters, road condition parameters, fluid type parameters and test speed parameters, and the first test equipment control parameters include the pressure measurement range, sampling frequency and test duration of the test equipment;

[0040] After the test equipment starts running, the data during the test is continuously monitored and collected to obtain the first test equipment real-time data. The first test equipment real-time data includes the real-time pressure value when the tire contacts the road surface or fluid, the status information of the test equipment, and the change value of the environmental parameters.

[0041] Furthermore, in the tire tread fluid pressure testing system of the present invention, the data processing module is also used for:

[0042] Starting from step S101, pressure distribution data, environmental parameter data, vehicle driving parameter data, tire status data and timestamp data when the tire contacts the road surface or fluid are obtained;

[0043] The first test device control parameter outputted in step S102, and the first test device operation error data and the second test device operation error data calculated in step S103;

[0044] Also obtaining the third test device operation error data calculated in step S104;

[0045] The random forest model is trained based on the data of step S101, step S102, step S103 and step S104 to obtain the second tire tread fluid pressure test control model:

[0046] replacing the second tire tread fluid pressure test control model with the first tire tread fluid pressure test control model being used;

[0047] The test task is substituted into the second tire tread fluid pressure test control model, and the adjusted test equipment control parameters are obtained according to the output of the second tire tread fluid pressure test control model.

[0048] Furthermore, in the tire tread fluid pressure testing system of the present invention, the test result generating module is further used for:

[0049] The adjusted test equipment control parameters obtained in step S104 are sent to the test equipment via network transmission;

[0050] Accessing a preset natural environment model parameter library, the preset natural environment model parameter library includes model parameters under natural environment conditions, the model parameters under natural environment conditions include temperature parameters, humidity parameters, road surface material parameters, water film depth parameters and wind speed parameters;

[0051] Matching is performed in the natural environment model parameter library according to the test task to obtain the natural environment model parameters that meet the test task;

[0052] Substitute the matched natural environment model parameters into the test equipment, and the natural environment model parameters will be used to simulate the natural conditions in the actual test environment;

[0053] Performing a tire tread fluid pressure test, after the test equipment is set according to the adjusted test equipment control parameters and natural environment model parameters, starting to perform the tire tread fluid pressure test;

[0054] During the test, the test equipment will continuously measure and record the pressure distribution of the tire when it contacts the road or fluid according to the preset sampling frequency and test duration parameters;

[0055] After the test is completed, the result data of the tire tread fluid pressure test is obtained from the test equipment. The result data of the tire tread fluid pressure test includes the pressure value of the tire at the center of the tread, the pressure value of the tire at the shoulder, the tire pressure distribution diagram, and the pressure change curve over time.

[0056] Beneficial effects of the present invention:

[0057] The present invention trains multi-source data through a neural network model, generates a first tire tread fluid pressure test control model, realizes dynamic adjustment of test equipment control parameters, and significantly improves test accuracy. Real-time comparison of test data with expected data, timely adjustment of control parameters, ensures that the test equipment operates stably within a preset error range, and further improves test accuracy.

[0058] The present invention can flexibly adjust the control parameters of the test equipment according to parameters such as different tire types, road conditions, fluid types and test speeds, so that the test method has stronger adaptability. After multiple iterations of optimization, if the error still exceeds the preset range, the present invention will train and replace it with a new random forest model to continuously improve the adaptability of the test. The modular system design is adopted to realize the automation and intelligence of the test process, reduce human intervention, and improve test efficiency. The test data is collected and analyzed in real time, and the test parameters are adjusted in time according to the data feedback, which effectively shortens the test cycle.

[0059] The present invention can substitute the natural environment model parameters into the test equipment, simulate the natural conditions in the actual test environment, and make the test results closer to the actual situation. The test method that simulates the real environment helps to more accurately evaluate the performance of the tire in actual use, and provides strong support for the improvement and optimization of the tire. Through the tire tread fluid pressure test method and system provided by the present invention, accurate and reliable data support can be obtained, providing a basis for tire design and optimization. By analyzing the test data under different conditions, we can deeply understand the response characteristics of the tire under different environments and usage conditions, and provide strong support for the improvement and innovation of the tire.

[0060] In summary, the present invention has achieved significant technical progress and application value in the field of tire tread fluid pressure testing, by improving test accuracy, enhancing test adaptability, improving test efficiency, simulating real environments and promoting tire design optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the technical solution of the present invention, the following is a brief introduction to the drawings required for use in the embodiments. Obviously, for ordinary technicians in this field, other drawings can be obtained based on the drawings without paying any creative labor.

[0062] Figure 1 A schematic flow chart of a tire tread fluid pressure testing method provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0063] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described in conjunction with the specific embodiments of the present invention and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. The technical solutions provided by the embodiments of the present invention are described in detail below in conjunction with the drawings. In order to better understand the purpose of the present invention, the present invention is further described in detail below.

[0064] The present invention provides a tire tread fluid pressure testing method and system, comprising:

[0065] In a first aspect, the present invention provides a tire tread fluid pressure testing method, comprising:

[0066] Step S101, obtaining pressure distribution data, environmental parameter data, vehicle driving parameter data, tire status data and timestamp data when the tire is in contact with the road surface or fluid, using the pressure distribution data, environmental parameter data, vehicle driving parameter data, tire status data and timestamp data when the tire is in contact with the road surface or fluid to train a neural network model, obtain a first tire tread fluid pressure test control model, receive a test task, match the test task in a preset error knowledge base, and generate preset error data corresponding to the test task;

[0067] Pressure distribution data: The pressure distribution data of the tire when it contacts the road surface or fluid is obtained through the pressure sensor or similar measuring equipment installed on the tire. These data include the pressure values ​​of the tire at different positions (such as the center of the tread, the shoulder, etc.).

[0068] Environmental parameter data: Collect relevant parameters of the test environment, such as temperature, humidity, road material, water film depth (if slippery roads are involved), wind speed, etc. These environmental parameters affect the contact pressure between the tire and the road or fluid.

[0069] Vehicle driving parameter data: Obtain relevant parameters during vehicle driving, such as speed, acceleration, steering angle, etc. These parameters reflect the dynamic state of the vehicle and have an impact on the tire tread fluid pressure.

[0070] Tire status data includes tire model, specification, air pressure, wear degree, etc. These data provide the current status of the tire and help to understand its tread fluid pressure more accurately.

[0071] Timestamped data: Record the timestamp of each data point so that the time factor can be taken into account in subsequent analysis.

[0072] Neural network model training: Use the acquired pressure distribution data, environmental parameter data, vehicle driving parameter data, tire status data and timestamp data as input to train the neural network model. The neural network model uses structures such as multi-layer perceptron (MLP), convolutional neural network (CNN) or recurrent neural network (RNN), depending on the characteristics of the data and modeling requirements. During the training process, by adjusting the parameters such as the weight and bias of the neural network, the model can accurately predict or classify the relevant conditions of the tire tread fluid pressure. After multiple iterations of training, the first tire tread fluid pressure test control model is obtained. The model can output the corresponding prediction results or control parameters based on the input data.

[0073] Receive test tasks and match them with the error knowledge base: Receive a specific test task, which includes testing the tread fluid pressure of a tire under specific conditions. Match the test task in a preset error knowledge base. The error knowledge base is a database containing a variety of test tasks and corresponding expected error ranges. Through matching, preset error data corresponding to the test task is generated. These data represent the allowable error range or expected test results under specific test conditions.

[0074] Step S101 completes the data acquisition, neural network model training, test task reception and error knowledge base matching, providing a basic control model and expected error data for subsequent steps.

[0075] Step S102, substituting the test task into the first tire tread fluid pressure test control model, outputting the first test equipment control parameter, sending the first test equipment control parameter to the test equipment, and collecting data during the operation of the test equipment to obtain the real-time data of the first test equipment;

[0076] Substitute the test task into the control model, and substitute the specific test task (including test conditions, test objectives, etc.) into the first tire tread fluid pressure test control model.

[0077] The first tire tread fluid pressure test control model performs calculations and processing based on the input test task combined with the neural network weights and bias parameters obtained through previous training.

[0078] Output the first test equipment control parameters, after being calculated and processed by the first tire tread fluid pressure test control model, output the first test equipment control parameters. These parameters include setting parameters of the test equipment, control parameters during the test, etc., which are used to guide the operation of the test equipment.

[0079] Send the control parameters to the test device, and send the output first test device control parameters to the test device through an appropriate communication method (such as wired connection, wireless transmission, network transmission, etc.). The test device can correctly receive and parse these control parameters and prepare to perform tests according to the parameters.

[0080] After the test equipment starts running, the data during its operation is collected in real time. These data include the working status of the test equipment, real-time data during the test (such as pressure value, temperature value, etc.), timestamp, etc. The data collection method is realized through hardware devices such as built-in sensors and data acquisition cards, and is also obtained through software interfaces.

[0081] After the data collection step, the real-time data of the first test device is obtained. These data reflect the operating status and test results of the test device under specific control parameters. The real-time data is preliminarily processed and analyzed, such as data cleaning, format conversion, etc., for use and analysis in subsequent steps.

[0082] Step S102 completes the process of substituting the test task into the first tire tread fluid pressure test control model, outputting the first test equipment control parameters, sending the control parameters to the test equipment, collecting data during the operation of the test equipment, and obtaining real-time data of the first test equipment.

[0083] Step S103, comparing the real-time data of the first test device with the expected data to obtain the first test device operation error data, and comparing the first test device operation error data with the corresponding preset error range value. If it exceeds the preset error range value, the test device control parameter is optimized to obtain the first optimized test device control parameter;

[0084] The real-time data of the first test device collected from the test device is compared with the expected data. The expected data is derived based on historical data, empirical models, or preset error data generated in the previous step. The comparison includes the value, trend, distribution, etc. of the data to ensure that the actual output of the test device is consistent with the expected results.

[0085] By comparing the real-time data with the expected data, the first test equipment operation error data is calculated. These error data represent the difference between the actual output of the test equipment and the expected result. The error data is expressed in the form of absolute value, relative value, standard deviation, etc., depending on the analysis requirements and the nature of the error.

[0086] The calculated first test equipment operation error data is compared with the corresponding preset error range value. The preset error range value is obtained in step S101 according to the matching of the test task and the error knowledge base, and represents the error range allowed under specific test conditions.

[0087] Determine whether the error data exceeds the preset error range value to determine whether the operating results of the test equipment meet the requirements.

[0088] If the operating error data of the first test device exceeds the preset error range value, it means that the operating result of the test device is inaccurate or unstable. In this case, it is necessary to optimize the control parameters of the test device to reduce the error and improve the accuracy of the test. The method of optimizing the control parameters of the test device includes adjusting the parameter value, changing the parameter combination, introducing a new control strategy, etc.

[0089] Through the optimization, the first optimized control parameters of the test equipment are obtained, and these parameters should be able to more accurately control the operation of the test equipment and make its real-time data closer to the expected data.

[0090] Step S103 completes the process of comparing the real-time data of the first test device with the expected data, calculating the operating error, comparing the error data with the preset error range value, and (if necessary) optimizing the control parameters of the test device. These steps are important links to ensure the accurate operation of the test device and the reliability of the test results. If the error is within the preset range, proceed to the next step or end the test; if the error exceeds the preset range, it is necessary to optimize and repeat this step until the error meets the requirements.

[0091] Step S104, send the first optimized test equipment control parameter to the test equipment, obtain the second test equipment operation error data, compare the second test equipment operation error data with the preset error range value, if it exceeds the preset error range value, continue to optimize the test equipment control parameter to obtain the second optimized test equipment control parameter, send the second optimized test equipment control parameter to the test equipment, obtain the third test equipment operation error data, compare the third test equipment operation error data with the preset error range value, if the third test equipment operation error data meets the preset error range value, stop the test Optimize the equipment control parameters. If the running error data of the third test equipment exceeds the preset error range value, obtain the data of step S101, step S102, step S103 and step S104 to obtain the data to be processed, pre-process the data to be processed, train the random forest model based on the pre-processed data, obtain the second tire tread fluid pressure test control model, replace the first tire tread fluid pressure test control model with the second tire tread fluid pressure test control model, substitute the test task into the second tire tread fluid pressure test control model, and output the adjusted test equipment control parameters;

[0092] The first optimized test equipment control parameters are sent to the test equipment to update its control parameters. After the test equipment is operated with the new control parameters, its real-time data is collected again and compared with the expected data to obtain the second test equipment operation error data.

[0093] Compare the second test equipment operation error data with the preset error range value to determine whether the error meets the requirements. If the second test equipment operation error data exceeds the preset error range value, it means that the optimized control parameters are still inaccurate, and it is necessary to continue to optimize the test equipment control parameters to obtain the second optimized test equipment control parameters. If the second test equipment operation error data meets the preset error range value, it is possible to stop optimizing the test equipment control parameters and consider that the current control parameters are sufficiently accurate.

[0094] The second optimized test equipment control parameter is sent to the test equipment, and the test is performed again to obtain the third test equipment operation error data. The third test equipment operation error data is compared with the preset error range value to determine whether the error meets the requirement.

[0095] If the running error data of the third test device meets the preset error range value, the optimization of the test device control parameters is stopped. If the running error data of the third test device still exceeds the preset error range value, it means that the current neural network model cannot meet the test requirements and needs to be further optimized or replaced.

[0096] The data in steps S101 to S104, including pressure distribution data, environmental parameter data, vehicle driving parameter data, tire status data, timestamp data, test equipment control parameters, test equipment operation error data, etc., are obtained as data to be processed. The data to be processed is preprocessed, such as data cleaning, feature extraction, normalization, etc., for subsequent use.

[0097] Based on the preprocessed data, the random forest model is trained to obtain the second tire tread fluid pressure test control model. The random forest model is an integrated learning method that improves the accuracy of prediction by constructing multiple decision trees and integrating their output results.

[0098] The second tire tread fluid pressure test control model replaces the first tire tread fluid pressure test control model as a new control model. Substitute the test task and output the adjusted test equipment control parameters. Substitute the test task into the second tire tread fluid pressure test control model and output the adjusted test equipment control parameters. The adjusted control parameters should be able to more accurately control the operation of the test equipment so that its real-time data is closer to the expected data.

[0099] Through the above steps, when the preset error range cannot be met after multiple optimizations, the present invention uses a random forest model for replacement to further improve the accuracy and stability of the tire tread fluid pressure test. The iterative optimization method helps to continuously approach the optimal solution and meet the test requirements.

[0100] Step S105, sending the adjusted test equipment control parameters to the test equipment, matching the test task in the preset natural environment model parameter library, obtaining the natural environment model parameters corresponding to the test task, substituting the natural environment simulation model parameters into the test equipment, and obtaining the tire tread fluid pressure test results.

[0101] The adjusted test equipment control parameters obtained by the second tire tread fluid pressure test control model in step S104 are sent to the test equipment. These parameters are optimized to more accurately control the operation of the test equipment.

[0102] The test task is matched in the preset natural environment model parameter library. This parameter library contains model parameters under various natural environment conditions, such as temperature, humidity, air pressure, wind speed, road surface material, water film depth, etc.

[0103] According to the specific requirements of the test task, select the matching natural environment model parameters from the parameter library. These parameters will be used to simulate the operation of the test equipment in the actual natural environment.

[0104] Substitute the matched natural environment simulation model parameters into the test equipment. This involves adjusting the settings of the test equipment to ensure that it can perform tests under simulated natural environment conditions. After substituting the parameters, the test equipment will simulate the corresponding natural environment conditions according to these parameters, providing an accurate test environment for tire tread fluid pressure testing.

[0105] Under simulated natural environmental conditions, the test equipment is used to test the tire tread fluid pressure. During the test, the test equipment will collect information such as pressure distribution data when the tire contacts the road or fluid. After the test is completed, the collected data is analyzed and processed to obtain the tire tread fluid pressure test results. These results include pressure distribution diagrams, pressure peaks, pressure change curves, etc., which are used to evaluate the performance of tires under specific natural environmental conditions.

[0106] Step S105 completes the process of sending the adjusted test equipment control parameters to the test equipment, matching the natural environment model parameters corresponding to the test task, substituting the natural environment simulation model parameters, and obtaining the tire tread fluid pressure test results. The test equipment accurately tests the tire tread fluid pressure under simulated natural environment conditions, providing data support for subsequent tire performance evaluation and optimization.

[0107] Specifically, the tire tread fluid pressure testing method of the present invention, step S102 comprises:

[0108] The test task includes tire type parameters, road condition parameters, fluid type parameters and test speed parameters, and the tire type parameters, road condition parameters, fluid type parameters and test speed parameters are input into a first tire tread fluid pressure test control model;

[0109] The first tire tread fluid pressure test control model outputs first test equipment control parameters according to the input tire type parameters, road condition parameters, fluid type parameters and test speed parameters, and the first test equipment control parameters include the pressure measurement range, sampling frequency and test duration of the test equipment;

[0110] After the test equipment starts running, the data during the test is continuously monitored and collected to obtain the first test equipment real-time data. The first test equipment real-time data includes the real-time pressure value when the tire contacts the road surface or fluid, the status information of the test equipment, and the change value of the environmental parameters.

[0111] The test task parameters include tire type parameters (such as tire specifications, materials, etc.), road condition parameters (such as road material, roughness, water film depth, etc.), fluid type parameters (such as fluid type, density, viscosity, etc.) and test speed parameters (such as vehicle speed, tire rotation speed, etc.).

[0112] The tire type parameter, road condition parameter, fluid type parameter and test speed parameter determined above are used as inputs and substituted into the first tire tread fluid pressure test control model. This model is constructed based on a neural network, a machine learning algorithm or other control theory, and can generate corresponding test equipment control parameters according to the input parameters.

[0113] The first tire tread fluid pressure test control model outputs the first test equipment control parameters based on the input parameters after internal calculation and processing. These control parameters specifically include the pressure measurement range of the test equipment (to ensure that the measurement accuracy and range meet the test requirements), the sampling frequency (to determine the intensiveness of data collection), and the test duration (to ensure that the test can cover the entire time period of interest).

[0114] The output first test device control parameter is sent to the test device, and the test device is started to run.

[0115] During the operation of the test equipment, its working status is continuously monitored to ensure that the equipment is tested according to the preset control parameters.

[0116] The built-in sensors and data acquisition system of the test equipment are used to continuously collect data during the test process. These data include the real-time pressure value when the tire contacts the road or fluid (reflecting the change of the fluid pressure on the tire tread), the status information of the test equipment (such as whether the equipment is operating normally, whether there are abnormal alarms, etc.), and the change values ​​of environmental parameters (such as temperature, humidity, air pressure and other environmental factors that affect the test results).

[0117] After data collection and preliminary processing, the real-time data of the first test equipment is obtained. These data are the basis for subsequent analysis, processing and optimization, and are also an important basis for evaluating tire performance.

[0118] By refining step S102, the tire tread fluid pressure testing method of the present invention is clearer and more specific, ensuring the accuracy of the testing process. At the same time, by real-time acquisition and monitoring of data during the testing process, it provides strong support for subsequent error analysis, model optimization and tire performance evaluation.

[0119] Specifically, the tire tread fluid pressure testing method of the present invention, step S104 comprises:

[0120] Starting from step S101, pressure distribution data, environmental parameter data, vehicle driving parameter data, tire status data and timestamp data when the tire contacts the road surface or fluid are obtained;

[0121] The first test device control parameter outputted in step S102, and the first test device operation error data and the second test device operation error data calculated in step S103;

[0122] Also obtaining the third test device operation error data calculated in step S104;

[0123] The random forest model is trained based on the data of step S101, step S102, step S103 and step S104 to obtain the second tire tread fluid pressure test control model:

[0124] replacing the second tire tread fluid pressure test control model with the first tire tread fluid pressure test control model being used;

[0125] The test task is substituted into the second tire tread fluid pressure test control model, and the adjusted test equipment control parameters are obtained according to the output of the second tire tread fluid pressure test control model.

[0126] Starting from step S101, the pressure distribution data when the tire contacts the road surface or fluid, environmental parameter data (such as temperature, humidity, air pressure, etc.), vehicle driving parameter data (such as speed, acceleration, etc.), tire status data (such as temperature, pressure, wear, etc.) and timestamp data are collected to ensure the integrity and timeliness of the data. At the same time, the first test equipment control parameters output in step S102 are obtained, which are the basis for the initial operation of the test equipment.

[0127] The first test device operation error data and the second test device operation error data calculated in step S103 are collected, and these data reflect the performance of the test device under the initial control parameters.

[0128] In step S104, according to the previous optimization results, the control parameters of the test equipment are continuously adjusted, and the test is performed to obtain the operation error data of the third test equipment. These data are important bases for further evaluation and optimization of the control model.

[0129] All collected data are preprocessed, including data cleaning, denoising, normalization, etc., to ensure data quality. Features are extracted from the preprocessed data, which should be able to reflect the information of tire tread fluid pressure test, such as the changing trend of pressure distribution, the influence of environmental parameters on test results, etc.

[0130] Based on the preprocessed data and extracted features, the random forest model is trained. Random forest is an ensemble learning method that improves the accuracy and stability of predictions by building multiple decision trees and combining their output results. During the training process, methods such as cross-validation are used to evaluate the performance of the model, and the model is adjusted and optimized based on the evaluation results.

[0131] When the random forest model is trained, it is replaced with the first tire tread fluid pressure test control model being used. This means that subsequent tests will use the new model to generate test equipment control parameters.

[0132] Substitute the test task into the second tire tread fluid pressure test control model, and output the adjusted test equipment control parameters according to the model's prediction results. These parameters should be able to more accurately control the operation of the test equipment and improve the accuracy and efficiency of the test.

[0133] By refining step S104, the tire tread fluid pressure test method of the present invention is more specific and operable, ensuring the continuity and optimization of the test process. At the same time, by introducing the random forest model and utilizing its powerful prediction ability, it provides strong support for the optimization of the control parameters of the test equipment, further improving the accuracy of the tire tread fluid pressure test.

[0134] Specifically, the tire tread fluid pressure testing method of the present invention, step S105 comprises:

[0135] The adjusted test equipment control parameters obtained in step S104 are sent to the test equipment via network transmission;

[0136] Accessing a preset natural environment model parameter library, the preset natural environment model parameter library includes model parameters under natural environment conditions, the model parameters under natural environment conditions include temperature parameters, humidity parameters, road surface material parameters, water film depth parameters and wind speed parameters;

[0137] Matching is performed in the natural environment model parameter library according to the test task to obtain the natural environment model parameters that meet the test task;

[0138] Substitute the matched natural environment model parameters into the test equipment, and the natural environment model parameters will be used to simulate the natural conditions in the actual test environment;

[0139] Performing a tire tread fluid pressure test, after the test equipment is set according to the adjusted test equipment control parameters and natural environment model parameters, starting to perform the tire tread fluid pressure test;

[0140] During the test, the test equipment will continuously measure and record the pressure distribution of the tire when it contacts the road or fluid according to the preset sampling frequency and test duration parameters;

[0141] After the test is completed, the result data of the tire tread fluid pressure test is obtained from the test equipment. The result data of the tire tread fluid pressure test includes the pressure value of the tire at the center of the tread, the pressure value of the tire at the shoulder, the tire pressure distribution diagram, and the pressure change curve over time.

[0142] The adjusted test equipment control parameters (including pressure measurement range, sampling frequency, test duration, etc.) obtained in step S104 are sent to the test equipment via network transmission (such as Wi-Fi, wired network, Bluetooth, etc.), ensuring that the test equipment can receive and correctly parse these parameters.

[0143] Access the preset natural environment model parameter library, which contains model parameters under various natural environment conditions to simulate the natural conditions in the actual test environment. These parameters include but are not limited to temperature parameters, humidity parameters, road surface material parameters, water film depth parameters, and wind speed parameters.

[0144] According to the specific requirements of the test task, the natural environment model parameter library is matched to find the natural environment model parameters that meet the test task requirements. The matching process involves comparing the environment description in the test task with the parameters in the parameter library and selecting the closest or most consistent parameter combination.

[0145] Substitute the matched natural environment model parameters into the test equipment. This usually involves adjusting the settings of the test equipment, such as the temperature controller, humidity controller, road simulator, etc., to ensure that the test equipment can simulate the natural environment conditions that meet the test task requirements.

[0146] After the test equipment is set up according to the adjusted test equipment control parameters and natural environment model parameters, the tire tread fluid pressure test begins. The test equipment will work according to the preset sampling frequency and test duration parameters.

[0147] During the test, the test equipment will continuously measure and record the pressure distribution of the tire when it contacts the road or fluid at a preset sampling frequency. This includes the pressure value of the tire at the center of the tread, the pressure value of the tire at the shoulder, and the pressure distribution diagram of the entire tread. At the same time, the pressure change curve over time is recorded for subsequent analysis.

[0148] After the test is completed, the tire tread fluid pressure test result data is obtained from the test equipment. These data are important basis for evaluating tire performance, including the tire pressure value at the center of the tread, the tire pressure value at the shoulder, the tire pressure distribution diagram, and the pressure change curve over time.

[0149] The acquired result data is post-processed and analyzed, such as calculating the average pressure value, maximum pressure value, pressure distribution uniformity and other indicators, and analyzing the pressure change trend over time, etc. This helps to gain a deeper understanding of the performance of the tire under specific natural environmental conditions.

[0150] In a second aspect, the present invention provides a tire tread fluid pressure testing system, which is applied to a tire tread fluid pressure testing method, comprising:

[0151] A data acquisition module, used to acquire pressure distribution data, environmental parameter data, vehicle driving parameter data, tire status data and timestamp data when the tire is in contact with the road surface or fluid, use the pressure distribution data, environmental parameter data, vehicle driving parameter data, tire status data and timestamp data when the tire is in contact with the road surface or fluid to train a neural network model, obtain a first tire tread fluid pressure test control model, receive a test task, match the test task in a preset error knowledge base, and generate preset error data corresponding to the test task;

[0152] A data acquisition module, used to substitute the test task into the first tire tread fluid pressure test control model, output the first test equipment control parameter, send the first test equipment control parameter to the test equipment, and collect data during the operation of the test equipment to obtain real-time data of the first test equipment;

[0153] A data optimization module is used to compare the real-time data of the first test device with the expected data to obtain the operation error data of the first test device, and compare the operation error data of the first test device with the corresponding preset error range value. If the preset error range value is exceeded, the control parameters of the test device are optimized to obtain the first optimized control parameters of the test device;

[0154] A data processing module, used for sending the first optimized test equipment control parameter to the test equipment, obtaining the second test equipment operation error data, comparing the second test equipment operation error data with the preset error range value, and if it exceeds the preset error range value, continuing to optimize the test equipment control parameter to obtain the second optimized test equipment control parameter, sending the second optimized test equipment control parameter to the test equipment, obtaining the third test equipment operation error data, comparing the third test equipment operation error data with the preset error range value, and if the third test equipment operation error data meets the preset error range value, stopping the optimization of the test equipment control parameter; if the third test equipment operation error data exceeds the preset error range value, acquiring data from the data acquisition module, the data acquisition module, the data optimization module and the data processing module to obtain the data to be processed, preprocessing the data to be processed, training the random forest model based on the preprocessed data, obtaining the second tire tread fluid pressure test control model, replacing the first tire tread fluid pressure test control model with the second tire tread fluid pressure test control model, substituting the test task into the second tire tread fluid pressure test control model, and outputting the adjusted test equipment control parameters;

[0155] The test result generation module is used to send the adjusted test equipment control parameters to the test equipment, match the test task in the preset natural environment model parameter library, obtain the natural environment model parameters corresponding to the test task, substitute the natural environment simulation model parameters into the test equipment, and obtain the tire tread fluid pressure test results.

[0156] Specifically, in the tire tread fluid pressure testing system of the present invention, the data acquisition module is also used for:

[0157] The test task includes tire type parameters, road condition parameters, fluid type parameters and test speed parameters, which are input into a first tire tread fluid pressure test control model. The first tire tread fluid pressure test control model outputs first test equipment control parameters according to the input tire type parameters, road condition parameters, fluid type parameters and test speed parameters. The first test equipment control parameters include a pressure measurement range, a sampling frequency and a test duration of the test equipment.

[0158] After the test equipment starts running, the data during the test is continuously monitored and collected to obtain the first test equipment real-time data. The first test equipment real-time data includes the real-time pressure value when the tire contacts the road surface or fluid, the status information of the test equipment, and the change value of the environmental parameters.

[0159] Specifically, in the tire tread fluid pressure testing system of the present invention, the data processing module is also used for:

[0160] Starting from step S101, pressure distribution data, environmental parameter data, vehicle driving parameter data, tire status data and timestamp data when the tire contacts the road surface or fluid are obtained;

[0161] The first test device control parameter outputted in step S102, and the first test device operation error data and the second test device operation error data calculated in step S103;

[0162] Also obtaining the third test device operation error data calculated in step S104;

[0163] The random forest model is trained based on the data of step S101, step S102, step S103 and step S104 to obtain the second tire tread fluid pressure test control model:

[0164] replacing the second tire tread fluid pressure test control model with the first tire tread fluid pressure test control model being used;

[0165] The test task is substituted into the second tire tread fluid pressure test control model, and the adjusted test equipment control parameters are obtained according to the output of the second tire tread fluid pressure test control model.

[0166] Specifically, in the tire tread fluid pressure testing system of the present invention, the test result generating module is further used for:

[0167] The adjusted test equipment control parameters obtained in step S104 are sent to the test equipment via network transmission;

[0168] Accessing a preset natural environment model parameter library, the preset natural environment model parameter library includes model parameters under natural environment conditions, the model parameters under natural environment conditions include temperature parameters, humidity parameters, road surface material parameters, water film depth parameters and wind speed parameters;

[0169] Matching is performed in the natural environment model parameter library according to the test task to obtain the natural environment model parameters that meet the test task;

[0170] Substitute the matched natural environment model parameters into the test equipment, and the natural environment model parameters will be used to simulate the natural conditions in the actual test environment;

[0171] Performing a tire tread fluid pressure test, after the test equipment is set according to the adjusted test equipment control parameters and natural environment model parameters, starting to perform the tire tread fluid pressure test;

[0172] During the test, the test equipment will continuously measure and record the pressure distribution of the tire when it contacts the road or fluid according to the preset sampling frequency and test duration parameters;

[0173] After the test is completed, the result data of the tire tread fluid pressure test is obtained from the test equipment. The result data of the tire tread fluid pressure test includes the pressure value of the tire at the center of the tread, the pressure value of the tire at the shoulder, the tire pressure distribution diagram, and the pressure change curve over time.

[0174] The present invention solves the problem in the prior art that tire tread fluid pressure testing cannot be adaptively adjusted, thereby reducing the test accuracy, by means of the following technical means:

[0175] The neural network model is trained using various data (including pressure distribution data, environmental parameter data, vehicle driving parameter data, tire status data, and timestamp data) when the tire contacts the road surface or fluid, and the first tire tread fluid pressure test control model is obtained. This step provides basic model support for subsequent tests. After receiving the test task, the present invention will match it in the preset error knowledge base and generate preset error data corresponding to the test task. This helps to set the expected range of the test error in advance and provide a basis for subsequent error analysis and optimization.

[0176] After substituting the test task into the first tire tread fluid pressure test control model, the test equipment control parameters are output, and data is collected in real time during the test. By comparing the real-time data with the expected data, the operation error is calculated, and the test equipment control parameters are optimized multiple times according to the error range value until the error is within the preset range. This step ensures that the parameters during the test can be dynamically adjusted according to the actual situation, thereby improving the accuracy of the test. If the error still exceeds the preset range after multiple optimizations, the present invention will train a random forest model based on historical data to obtain a second tire tread fluid pressure test control model, and use it to replace the currently used control model. This step provides additional optimization means for the test, further improving the accuracy of the test.

[0177] During the test process, the present invention will also substitute the adjusted test equipment control parameters and the natural environment model parameters matched from the preset natural environment model parameter library into the test equipment. This helps to simulate the actual test environment and improve the accuracy and authenticity of the test. The present invention provides modules such as data acquisition, data collection, data optimization, data processing and test result generation, and realizes the automation and intelligence of the test process in a systematic way. This reduces the impact of human factors on the test results and improves the efficiency and accuracy of the test. The method of the present invention includes multiple iterative optimization steps to ensure that the test equipment control parameters can gradually approach the optimal solution. This step further improves the accuracy and stability of the test through continuous optimization and adjustment.

[0178] The present invention makes full use of multiple data sources for comprehensive analysis and modeling, improving the generalization ability and adaptability of the model. This helps to better understand and predict the changes in tire tread fluid pressure and provide more accurate results for testing. The present invention effectively solves the problem of the inability to adapt tire tread fluid pressure testing in the prior art through the comprehensive application of technical means such as neural network model training, error knowledge base matching, dynamic adjustment of test equipment control parameters, random forest model optimization, natural environment simulation, modular system design, multiple iterative optimization and comprehensive data utilization, thereby improving the accuracy of the test.

Claims

1. A tire tread fluid pressure testing method, characterized in that: include: Step S101, obtaining pressure distribution data, environmental parameter data, vehicle driving parameter data, tire status data and timestamp data when the tire is in contact with the road surface or fluid, using the pressure distribution data, environmental parameter data, vehicle driving parameter data, tire status data and timestamp data when the tire is in contact with the road surface or fluid to train a neural network model, obtain a first tire tread fluid pressure test control model, receive a test task, match the test task in a preset error knowledge base, and generate preset error data corresponding to the test task; Step S102, substituting the test task into the first tire tread fluid pressure test control model, outputting the first test equipment control parameter, sending the first test equipment control parameter to the test equipment, and collecting data during the operation of the test equipment to obtain the real-time data of the first test equipment; Step S103, comparing the real-time data of the first test device with the expected data to obtain the first test device operation error data, and comparing the first test device operation error data with the corresponding preset error range value. If it exceeds the preset error range value, the test device control parameter is optimized to obtain the first optimized test device control parameter; Step S104, send the first optimized test equipment control parameter to the test equipment, obtain the second test equipment operation error data, compare the second test equipment operation error data with the preset error range value, if it exceeds the preset error range value, continue to optimize the test equipment control parameter to obtain the second optimized test equipment control parameter, send the second optimized test equipment control parameter to the test equipment, obtain the third test equipment operation error data, compare the third test equipment operation error data with the preset error range value, if the third test equipment operation error data meets the preset error range value, stop the test Optimize the equipment control parameters. If the running error data of the third test equipment exceeds the preset error range value, obtain the data of step S101, step S102, step S103 and step S104 to obtain the data to be processed, pre-process the data to be processed, train the random forest model based on the pre-processed data, obtain the second tire tread fluid pressure test control model, replace the first tire tread fluid pressure test control model with the second tire tread fluid pressure test control model, substitute the test task into the second tire tread fluid pressure test control model, and output the adjusted test equipment control parameters; Step S105, sending the adjusted test equipment control parameters to the test equipment, matching the test task in the preset natural environment model parameter library, obtaining the natural environment model parameters corresponding to the test task, substituting the natural environment simulation model parameters into the test equipment, and obtaining the tire tread fluid pressure test results.

2. The tire tread fluid pressure testing method according to claim 1, characterized in that: The step S102 includes: The test task includes tire type parameters, road condition parameters, fluid type parameters and test speed parameters, and the tire type parameters, road condition parameters, fluid type parameters and test speed parameters are input into a first tire tread fluid pressure test control model; The first tire tread fluid pressure test control model outputs first test equipment control parameters according to the input tire type parameters, road condition parameters, fluid type parameters and test speed parameters, and the first test equipment control parameters include the pressure measurement range, sampling frequency and test duration of the test equipment; After the test equipment starts running, the data during the test is continuously monitored and collected to obtain the first test equipment real-time data. The first test equipment real-time data includes the real-time pressure value when the tire contacts the road surface or fluid, the status information of the test equipment, and the change value of the environmental parameters.

3. The tire tread fluid pressure testing method according to claim 1, characterized in that: The step S104 includes: Starting from step S101, pressure distribution data, environmental parameter data, vehicle driving parameter data, tire status data and timestamp data when the tire contacts the road surface or fluid are obtained; The first test device control parameter outputted in step S102, and the first test device operation error data and the second test device operation error data calculated in step S103; Also obtaining the third test device operation error data calculated in step S104; The random forest model is trained based on the data of step S101, step S102, step S103 and step S104 to obtain the second tire tread fluid pressure test control model: replacing the second tire tread fluid pressure test control model with the first tire tread fluid pressure test control model being used; The test task is substituted into the second tire tread fluid pressure test control model, and the adjusted test equipment control parameters are obtained according to the output of the second tire tread fluid pressure test control model.

4. The tire tread fluid pressure testing method according to claim 1, characterized in that: The step S105 includes: The adjusted test equipment control parameters obtained in step S104 are sent to the test equipment via network transmission; Accessing a preset natural environment model parameter library, the preset natural environment model parameter library includes model parameters under natural environment conditions, the model parameters under natural environment conditions include temperature parameters, humidity parameters, road surface material parameters, water film depth parameters and wind speed parameters; Matching is performed in the natural environment model parameter library according to the test task to obtain the natural environment model parameters that meet the test task; Substitute the matched natural environment model parameters into the test equipment, and the natural environment model parameters will be used to simulate the natural conditions in the actual test environment; Performing a tire tread fluid pressure test, after the test equipment is set according to the adjusted test equipment control parameters and natural environment model parameters, starting to perform the tire tread fluid pressure test; During the test, the test equipment will continuously measure and record the pressure distribution of the tire when it contacts the road or fluid according to the preset sampling frequency and test duration parameters; After the test is completed, the result data of the tire tread fluid pressure test is obtained from the test equipment. The result data of the tire tread fluid pressure test includes the pressure value of the tire at the center of the tread, the pressure value of the tire at the shoulder, the tire pressure distribution diagram, and the pressure change curve over time.

5. A tire tread fluid pressure testing system, applied to the tire tread fluid pressure testing method according to any one of claims 1 to 4, characterized in that: include: A data acquisition module, used to acquire pressure distribution data, environmental parameter data, vehicle driving parameter data, tire status data and timestamp data when the tire is in contact with the road surface or fluid, use the pressure distribution data, environmental parameter data, vehicle driving parameter data, tire status data and timestamp data when the tire is in contact with the road surface or fluid to train a neural network model, obtain a first tire tread fluid pressure test control model, receive a test task, match the test task in a preset error knowledge base, and generate preset error data corresponding to the test task; A data acquisition module, used to substitute the test task into the first tire tread fluid pressure test control model, output the first test equipment control parameter, send the first test equipment control parameter to the test equipment, and collect data during the operation of the test equipment to obtain real-time data of the first test equipment; A data optimization module is used to compare the real-time data of the first test device with the expected data to obtain the operation error data of the first test device, and compare the operation error data of the first test device with the corresponding preset error range value. If the preset error range value is exceeded, the control parameters of the test device are optimized to obtain the first optimized control parameters of the test device; A data processing module, used for sending the first optimized test equipment control parameter to the test equipment, obtaining the second test equipment operation error data, comparing the second test equipment operation error data with the preset error range value, and if it exceeds the preset error range value, continuing to optimize the test equipment control parameter to obtain the second optimized test equipment control parameter, sending the second optimized test equipment control parameter to the test equipment, obtaining the third test equipment operation error data, comparing the third test equipment operation error data with the preset error range value, and if the third test equipment operation error data meets the preset error range value, stopping the optimization of the test equipment control parameter; if the third test equipment operation error data exceeds the preset error range value, acquiring data from the data acquisition module, the data acquisition module, the data optimization module and the data processing module to obtain the data to be processed, preprocessing the data to be processed, training the random forest model based on the preprocessed data, obtaining the second tire tread fluid pressure test control model, replacing the first tire tread fluid pressure test control model with the second tire tread fluid pressure test control model, substituting the test task into the second tire tread fluid pressure test control model, and outputting the adjusted test equipment control parameters; The test result generation module is used to send the adjusted test equipment control parameters to the test equipment, match the test task in the preset natural environment model parameter library, obtain the natural environment model parameters corresponding to the test task, substitute the natural environment simulation model parameters into the test equipment, and obtain the tire tread fluid pressure test results.

6. The tire tread fluid pressure testing system according to claim 5, characterized in that: The data acquisition module is also used for: The test task includes tire type parameters, road condition parameters, fluid type parameters and test speed parameters, and the tire type parameters, road condition parameters, fluid type parameters and test speed parameters are input into a first tire tread fluid pressure test control model; The first tire tread fluid pressure test control model outputs first test equipment control parameters according to the input tire type parameters, road condition parameters, fluid type parameters and test speed parameters, and the first test equipment control parameters include the pressure measurement range, sampling frequency and test duration of the test equipment; After the test equipment starts running, the data during the test is continuously monitored and collected to obtain the first test equipment real-time data. The first test equipment real-time data includes the real-time pressure value when the tire contacts the road surface or fluid, the status information of the test equipment, and the change value of the environmental parameters.

7. The tire tread fluid pressure testing system according to claim 5, characterized in that: The data processing module is further used for: Starting from step S101, pressure distribution data, environmental parameter data, vehicle driving parameter data, tire status data and timestamp data when the tire contacts the road surface or fluid are obtained; The first test device control parameter outputted in step S102, and the first test device operation error data and the second test device operation error data calculated in step S103; Also obtaining the third test device operation error data calculated in step S104; The random forest model is trained based on the data of step S101, step S102, step S103 and step S104 to obtain the second tire tread fluid pressure test control model: replacing the second tire tread fluid pressure test control model with the first tire tread fluid pressure test control model being used; The test task is substituted into the second tire tread fluid pressure test control model, and the adjusted test equipment control parameters are obtained according to the output of the second tire tread fluid pressure test control model.

8. The tire tread fluid pressure testing system according to claim 5, characterized in that: The test result generating module is further used for: The adjusted test equipment control parameters obtained in step S104 are sent to the test equipment via network transmission; Accessing a preset natural environment model parameter library, the preset natural environment model parameter library includes model parameters under natural environment conditions, the model parameters under natural environment conditions include temperature parameters, humidity parameters, road surface material parameters, water film depth parameters and wind speed parameters; Matching is performed in the natural environment model parameter library according to the test task to obtain the natural environment model parameters that meet the test task; Substitute the matched natural environment model parameters into the test equipment, and the natural environment model parameters will be used to simulate the natural conditions in the actual test environment; Performing a tire tread fluid pressure test, after the test equipment is set according to the adjusted test equipment control parameters and natural environment model parameters, starting to perform the tire tread fluid pressure test; During the test, the test equipment will continuously measure and record the pressure distribution of the tire when it contacts the road or fluid according to the preset sampling frequency and test duration parameters; After the test is completed, the result data of the tire tread fluid pressure test is obtained from the test equipment. The result data of the tire tread fluid pressure test includes the pressure value of the tire at the center of the tread, the pressure value of the tire at the shoulder, the tire pressure distribution diagram, and the pressure change curve over time.

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