A tire quality evaluation method and system

Abstract

The present invention relates to the technical field of tire quality evaluation, specifically to a tire quality evaluation method and system, the method comprising the following steps: performing quality inspection on tires to be inspected, obtaining a first evaluation information set of the tires to be inspected; establishing an evaluation information processing model, processing the first evaluation information set through the evaluation information processing model, and obtaining a second evaluation information set of the tires to be inspected; constructing a tire quality evaluation system according to the second evaluation information set, the tire quality evaluation system comprising a primary evaluation index, a secondary evaluation index, and a tertiary evaluation index; utilizing the second evaluation information set and the tire quality evaluation system to perform quality evaluation on the tires to be inspected, and screening out high-quality tires based on the evaluation results. The present invention establishes a tire information processing model and a quality evaluation system, realizes a systematic and standardized evaluation of tire quality, and improves the objectivity and accuracy of the evaluation results.

Description

Technical Field

[0001] The present invention relates to the technical field of tire quality evaluation, and in particular to a tire quality evaluation method and system. Background Art

[0002] With the rapid development of the automobile industry and the increasing requirements of consumers for driving safety, comfort and energy efficiency, tires, as an important part of automobiles, have become particularly important for quality evaluation. At present, there are challenges and problems in the field of tire quality evaluation to varying degrees. Due to the differences in materials, structures and manufacturing processes of tires from different manufacturers and different models, as well as the diversity of testing conditions and methods, there are inconsistencies in tire testing and evaluation results. At the same time, there is a lack of unified evaluation standards, and there is no widely recognized and uniformly applicable evaluation standard, which makes it difficult to directly compare and learn from the evaluation results.

[0003] Existing tire quality evaluation methods often focus on the evaluation of a certain aspect or a certain performance indicator, lacking comprehensive and integrated considerations. In actual applications, tire quality involves multiple aspects, and the evaluation results of a single indicator are difficult to fully reflect the overall performance of the tire. In addition, existing evaluation methods have technical bottlenecks in data collection, processing and analysis, making it difficult to ensure the accuracy and reliability of the evaluation results, and difficult to achieve in-depth mining and effective use of test data.

[0004] In order to solve the above-mentioned problems, it is necessary to propose a new tire quality evaluation method, which can standardize the evaluation process, set multi-dimensional evaluation indicators, and adopt advanced data collection and processing technology to comprehensively, accurately and efficiently evaluate tire quality. This will not only help solve current problems in the field of tire quality evaluation, but also promote technological innovation and high-quality development of the tire industry. Summary of the invention

[0005] In view of the shortcomings of the existing methods and the needs of practical applications, the present invention constructs a standardized evaluation process, introduces a multi-dimensional evaluation system, and integrates advanced data processing technology, which is conducive to achieving the comprehensiveness, accuracy and efficiency of tire quality evaluation, thereby effectively responding to the challenges faced by the current tire quality evaluation field, not only providing a scientific basis for the accurate evaluation of tire quality, but also greatly promoting the technological innovation and quality upgrade of the tire industry, and promoting the sustainable and healthy development of the entire industry. On the one hand, the present invention provides a tire quality evaluation method, which includes the following steps: performing quality inspection on the tire to be inspected to obtain a first evaluation information set of the tire to be inspected; establishing an evaluation information processing model, processing the first evaluation information set through the evaluation information processing model, and obtaining a second evaluation information set of the tire to be inspected; constructing a tire quality evaluation system according to the second evaluation information set, the tire quality evaluation system includes a first-level evaluation index, a second-level evaluation index and a third-level evaluation index; using the second evaluation information set and the tire quality evaluation system to perform quality evaluation on the tire to be inspected, and screening out high-quality tires based on the evaluation results. The present invention can avoid the one-sidedness caused by a single indicator evaluation through a multi-dimensional evaluation index system, can more accurately reflect the overall performance of the tire, and ensure the objectivity and effectiveness of the tire quality evaluation results.

[0006] Optionally, the step of establishing an evaluation information processing model, processing the first evaluation information set through the evaluation information processing model, and obtaining a second evaluation information set of the tire to be tested includes: establishing an evaluation information processing model based on the characteristics of the first evaluation information set and the evaluation target of tire quality, the evaluation information processing model including a sampling point data optimization function and an intelligent clustering analysis function. The second evaluation information set of the tire to be tested is obtained through the sampling point data optimization function and the intelligent clustering analysis function. The present invention establishes an evaluation information processing model through the sampling point data optimization function and the intelligent clustering analysis function, and processes the first evaluation information set accordingly to obtain the second evaluation information set, so that the present invention can be adaptively adjusted according to different tire types, test conditions or evaluation targets, thereby improving the practicality and value of the relevant models.

[0007] Optionally, the sampling point data optimization function satisfies the following relationship:

[0008]

[0009] in, After optimization, The data of the sampling points, Indicates The number of data input layers of sampling points, Indicates the sampling point The received signal vector of the input layer, represents the channel matrix, Indicates the sampling point The noise coefficient of the received signal at the input layer, Indicates The matrix bias matrix corresponding to the sampling points, Indicates the sampling point The weight coefficient of the input layer. The data optimization function of the present invention fully considers the differences between different sampling points or different input layers, which not only helps to eliminate or reduce outliers or interference factors in the data, but also enhances the adaptability of the data to changes in external conditions and improves the robustness of the data.

[0010] Optionally, the intelligent clustering analysis function satisfies the following relationship:

[0011]

[0012] in, represents the discretized data set, represents the number of samples in the data set, Represents the first The coordinates of the samples, Represents the first The intelligent clustering analysis function of the present invention can classify similar samples into the same cluster and separate samples with large differences, which can effectively reduce the influence of noise and outliers on clustering results, thereby improving the accuracy of data processing.

[0013] Optionally, the tire quality evaluation system is constructed according to the second evaluation information set, and the tire quality evaluation system includes primary evaluation indicators, secondary evaluation indicators and tertiary evaluation indicators, including: setting primary evaluation indicators according to the second evaluation information set, the primary evaluation indicators include tire uniformity; setting secondary evaluation indicators according to the second evaluation information set, the secondary evaluation indicators include tire physical and mechanical properties; setting tertiary evaluation indicators according to the second evaluation information set, the tertiary evaluation indicators include tire chemical composition; and constructing a tire quality evaluation system by combining the tire uniformity, the tire physical and mechanical properties and the tire chemical composition. The present invention sets a multi-level evaluation indicator, which can cover multiple aspects of tire quality, divides and considers different characteristics and performances of tires, and helps to more accurately reflect the overall quality level of tires.

[0014] Optionally, the tire quality evaluation system is constructed according to the second evaluation information set, and the tire quality evaluation system includes primary evaluation indicators, secondary evaluation indicators and tertiary evaluation indicators, including: weight coefficients corresponding to different evaluation indicators in the tire quality evaluation system are analyzed based on the tire quality evaluation system and the second evaluation information set. The present invention analyzes the weight coefficients of different evaluation indicators, which can clarify the importance and influence of each indicator in tire quality evaluation, and helps to give higher attention to key indicators during the evaluation process, thereby improving the accuracy and reliability of the evaluation results.

[0015] Optionally, the tire uniformity satisfies the following relationship:

[0016]

[0017] in, represents the lateral force, represents the first force of the component load cell, represents the second force of the component load cell, represents the spindle radius, Indicates tire radius;

[0018]

[0019] in, represents the radial force, represents the distance between sensors, represents the first force of the component load cell, represents the second force of the component load cell, Indicates tire width.

[0020] The present invention calculates the lateral force and radial force of the tire through mathematical formulas, and then analyzes the uniform force applied to the tire, which helps to reduce errors caused by subjective judgment and improve the objectivity and accuracy of the evaluation results.

[0021] Optionally, the method of using the second evaluation information set and the tire quality evaluation system to perform quality evaluation on the tire to be tested, and selecting high-quality tires based on the evaluation results includes: obtaining preliminary quality evaluation results of the tire to be tested through the tire quality evaluation system; establishing an evaluation result standardization model based on standard conditions of the tire quality evaluation system; and using the evaluation result standardization model to perform standardization processing on the preliminary quality evaluation results to obtain standardized quality evaluation results. The standardization processing flow of the present invention enables the quality evaluation results of different tires to have the same dimension and scale, thereby enhancing the comparability of the evaluation results.

[0022] Optionally, the use of the second evaluation information set and the tire quality evaluation system to perform quality evaluation on the tire to be tested, and screening out high-quality tires based on the evaluation results includes: performing quality analysis on the tire to be tested based on the standardized quality evaluation results to obtain multi-dimensional quality evaluation results, the multi-dimensional quality evaluation results including uniformity evaluation results, mechanical performance evaluation results, and chemical composition evaluation results of the tire to be tested, so as to screen out high-quality tires. The present invention decomposes tire quality into multiple dimensions for evaluation, which can more accurately identify high-quality tires, making the tire quality evaluation method more rigorous and accurate.

[0023] In the second aspect, in order to efficiently execute a tire quality evaluation method provided by the present invention, the present invention also provides a tire quality evaluation system, including a processor, an input device, an output device and a memory, wherein the processor, the input device, the output device and the memory are interconnected, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the tire quality evaluation method as described in the first aspect of the present invention. The tire quality evaluation system of the present invention has a compact structure and stable performance, and can stably execute the tire quality evaluation method provided by the present invention, thereby improving the overall applicability and practical application ability of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 is a flow chart of the tire quality evaluation method of the present invention;

[0025] Figure 2 It is a schematic diagram of the processing flow of the second evaluation information set of the tire to be tested in the tire quality evaluation method of the present invention;

[0026] Figure 3 It is a schematic diagram of the tire uniformity measurement principle in the tire quality evaluation method of the present invention;

[0027] Figure 4 It is a structural diagram of the tire quality evaluation system of the present invention. DETAILED DESCRIPTION

[0028] See also Figure 1 The present invention constructs a standardized evaluation process, establishes a multi-dimensional evaluation system, and integrates advanced data processing technology to further ensure the comprehensiveness, accuracy and efficiency of the tire quality evaluation method, and screen out high-quality tires based on the quality evaluation results. The present invention provides a tire quality evaluation method, which includes the following steps:

[0029] S1. Performing quality inspection on the tire to be inspected to obtain a first evaluation information set of the tire to be inspected. The specific implementation steps and contents are as follows:

[0030] In this embodiment, the tire to be inspected is subjected to quality inspection to obtain its first evaluation information set.

[0031] First, the standards on which the tire testing is based are clarified. The testing standards in the embodiment include but are not limited to national standards, industry standards or enterprise-defined standards, based on which the consistency and comparability of the testing process and results can be ensured.

[0032] According to the tire testing requirements, corresponding testing equipment is prepared, which mainly includes uniformity testing machines, mechanical properties testing machines, chemical composition analyzers, etc. In the embodiment, it is necessary to ensure that the equipment is calibrated and in good working condition.

[0033] Furthermore, the tires to be inspected are marked and classified to ensure that each tire has a unique identification code for subsequent data tracking and recording.

[0034] 2. Tire appearance inspection stage

[0035] Mainly through visual observation of the tire surface, check whether the tire to be tested has appearance defects such as cracks, bulges, scratches, uneven wear, etc.; use measuring tools to check whether the key dimensions of the tire to be tested, such as diameter, width, tread pattern depth, etc., meet the specification requirements.

[0036] 3. Tire uniformity testing stage

[0037] Install the tire to be tested on a dynamic balancing machine, rotate the tire and measure its imbalance to obtain dynamic balance related data of the tire to be tested. At the same time, use special equipment to measure the radial and lateral runout of the tire to be tested during rotation, which will help the subsequent analysis of the roundness and coaxiality of the tire to be tested.

[0038] 4. Tire Mechanical Performance Testing Stage

[0039] The embodiment simulates the stress conditions of the tire to be tested in actual use, and performs pressure tests, tensile tests, etc. to evaluate the strength and durability of the tire. At the same time, the rolling resistance of the tire to be tested is measured under specific conditions, which helps to evaluate the energy-saving performance of the tire to be tested. It is also necessary to obtain relevant information such as the wear resistance and service life of the tire to be tested through simulated road driving tests.

[0040] 5. Tire chemical composition analysis stage

[0041] Chemical analysis methods can be used to analyze the composition of the tire materials to be tested, such as rubber type, additive content, etc. At the same time, it is necessary to test whether the tires to be tested contain heavy metals, harmful substances, etc. to ensure that the tire products comply with relevant regulations and standards.

[0042] 6. Recording and sorting of tire quality inspection information

[0043] The results of the above tests are recorded in detail, including but not limited to the test time, test conditions, test results, etc., and then sorted to obtain a first evaluation information set of the tire to be tested in the embodiment, which contains specific information of the tire to be tested in each test dimension.

[0044] Furthermore, the method for obtaining the first evaluation information set of the tire to be tested in the present embodiment is only an optional condition of the present invention. In other embodiments, the method for obtaining the evaluation information can be flexibly adjusted according to the actual situation of the tire to be tested and the collection requirements of the evaluation information. Different tire types, specifications, uses and production batches have different quality characteristics and testing requirements. Flexible adjustment of the method for obtaining the evaluation information in the embodiment can significantly improve the accuracy and reliability of the test results and provide more powerful information support for quality assessment.

[0045] S2. Establish an evaluation information processing model, process the first evaluation information set of step S1 through the evaluation information processing model, and obtain a second evaluation information set of the tire to be tested. The specific implementation steps and contents are as follows:

[0046] An evaluation information processing model is established based on the first evaluation information set feature and the tire quality evaluation target of this embodiment. The evaluation information processing model in the embodiment mainly includes a sampling point data optimization function and an intelligent clustering analysis function, and its specific contents are as follows:

[0047] The sampling point data optimization function can filter out the most representative data points from the first evaluation information set to reduce the amount of data processing and improve the accuracy of the analysis results. The sampling point data optimization function performs data dimension reduction, feature selection and importance evaluation on the first evaluation information set, and preprocesses and optimizes the first evaluation information set.

[0048] The sampling point data optimization function mainly selects the features that have the greatest impact on tire quality for subsequent analysis based on the tire evaluation objectives, removes irrelevant or weakly related features, and improves the model's interpretability and predictive capabilities. At the same time, the importance of different input layers is evaluated to provide guidance for subsequent clustering analysis or classification tasks.

[0049] The above sampling point data optimization function satisfies the following relationship:

[0050]

[0051] in, After optimization, The data of the sampling points, Indicates The number of data input layers of sampling points, Indicates the sampling point The received signal vector of the input layer, represents the channel matrix, Indicates the sampling point The noise coefficient of the received signal at the input layer, Indicates The matrix bias matrix corresponding to the sampling points, Indicates the sampling point The weight coefficients of the input layer.

[0052] Sampling points refer to the first evaluation information set. In order to obtain key information of tire evaluation for subsequent analysis, a series of time points are set as data collection samples at preset time intervals in the embodiment. The above points are called sampling points, and the sampling points are determined in chronological order.

[0053] The data of the optimized sampling points refers to the data corresponding to different sampling points after being optimized by the sampling point data optimization function. The above data has removed noise, redundant or irrelevant information and can more accurately reflect the characteristics and status of the evaluation information at the sampling point.

[0054] Each data sampling point can be regarded as an independent data set, and its internal structure consists of multiple data layers. The above number of layers indirectly reflects the complexity and diversity of data at different sampling points. Each layer of data carries specific attribute characteristics and state information. The relevant characteristics and states together define the overall data characteristics of the sampling point. Therefore, different data sampling points correspond to different layer structures, data attribute characteristics, and state characteristics.

[0055] The received signal vectors of different input layers at the sampling points refer to the set of all signals or data points received by different input layers at the specific sampling points.

[0056] The channel matrix refers to the matrix form of the transmission probability of a discrete single-symbol channel. In the multi-input multi-output tire quality evaluation system, it is a matrix that describes the relationship between each transmitting antenna and receiving antenna during the signal transmission process.

[0057] The noise coefficient of different input layers at different sampling points is an important parameter to measure the signal quality of the input layer. The noise coefficient can also be defined as the ratio of the input signal-to-noise ratio to the output signal-to-noise ratio, expressed in decibels. In different input layers at different sampling points, the noise coefficient reflects the degree to which the signal quality of the input layer is degraded due to the introduction of internal noise in the system when receiving the signal.

[0058] The bias matrix refers to the predicted value or output value of the sampling point data optimization function when there is no input feature. There is a bias term that can be used to adjust the threshold of different sampling point data, based on which bias correction or adjustment is performed on different sampling points.

[0059] The weight values ​​corresponding to the input features or variables in different input layers at the sampling point. The above weight values ​​determine how the various input features are weighted and combined when the data passes through this layer. In addition, the specific value and calculation method of the weight coefficient need to be based on the application scenario and specific structure of the tire to be tested, and the appropriate weight coefficient calculation method and adjustment strategy should be selected.

[0060] In the embodiment, the weight coefficient is set and selected based on the data acquisition parameters. For reference factors, please refer to Table 1 for details.

[0061] Table 1 Reference factors in the process of setting weight coefficients

[0062]

[0063] In this embodiment, there are a total of N sampling points in each data cycle, based on which the frequency domain theoretical value of the signal can be calculated , and the sampling frequency.

[0064] The theoretical value of the signal frequency domain in the embodiment satisfies the following relationship:

[0065]

[0066] in, Represents the frequency domain theoretical value of the data signal, Indicates the rotation speed during the tire dynamic imbalance detection process.

[0067] The sampling frequency satisfies the following relationship:

[0068]

[0069] in, represents the sampling frequency of the data signal, Indicates the rotation speed during the tire dynamic imbalance detection process. Indicates the number of sampling points in each tire information acquisition cycle.

[0070] Furthermore, in this embodiment, after the first evaluation information set is optimized, the following relationship is satisfied:

[0071]

[0072] in, represents the data set of optimized sampling points, Represents the data of the first sampling point after optimization, Represents the data of the second sampling point after optimization, After optimization, The data of the sampling points.

[0073] In the embodiment, the intelligent clustering analysis function groups the optimized sampling point data according to similarities or differences to form different tire quality evaluation category information or grade data sets, providing more intuitive information classification results for subsequent tire quality evaluation.

[0074] In the embodiment, the intelligent clustering analysis function can select a suitable clustering algorithm such as K-means, hierarchical clustering, DBSCAN, etc. according to the characteristics of the sampling point data set and the tire quality evaluation requirements. Each algorithm has its unique advantages and applicable scenarios, and can be reasonably selected and adjusted according to the specific situation.

[0075] At the same time, the clustering results need to be evaluated. In the embodiment, the silhouette coefficient, Calinski-Harabasz index and other indicators can be used to evaluate the quality of the clustering results. At the same time, the clustering results are interpreted and verified in combination with the actual situation of the tire evaluation information to be tested, thereby ensuring the accuracy and rationality of the second evaluation information set of the tire to be tested.

[0076] The second evaluation information set of the tire to be tested is obtained through the above sampling point data optimization function and intelligent clustering analysis function, and its specific content is as follows:

[0077] In this embodiment, the sampling point data optimization function and the intelligent clustering analysis function cooperate with each other and act on the first evaluation information set. First, the data is preprocessed and screened by the optimization function to improve the data quality; then, the data is classified and processed by the clustering analysis function to obtain the second evaluation information set of the tire to be tested. The above process not only improves the efficiency and accuracy of the evaluation method, but also provides strong data support for subsequent decision support.

[0078] The above intelligent clustering analysis function satisfies the following relationship:

[0079]

[0080] in, represents the discretized data set, represents the number of samples in the data set, Represents the first The coordinates of the samples, Represents the first The samples are in the cluster center of the cluster.

[0081] The discretized data set refers to discretizing the optimized first evaluation information set, thereby converting the continuous data values ​​in the evaluation information set into discrete, limited categories and feature information intervals.

[0082] The number of samples in a data set refers to the total number of data sampling points contained in the data set.

[0083] The coordinates of different samples in a data set refer to the position representation of different samples in a multidimensional space. It can be used to describe the specific positions of different data sampling points in a certain dimensional space. In the embodiment, the data set is multidimensional and contains multiple features or attributes. Different samples can be represented by a coordinate vector, and each component of the vector corresponds to the value of the sample in the corresponding dimension.

[0084] Cluster analysis can divide samples in a data set into multiple groups or clusters, so that the samples in the same cluster have a higher similarity, while the samples in different clusters have a lower similarity. The cluster center is an important concept in cluster analysis, representing the central position or typical characteristics of a cluster. The cluster center is usually the mean of all samples in the cluster, which is an actual sample point in the cluster, that is, the center point. In the analysis process of the intelligent cluster analysis function, different sample information will be assigned to different clusters, and the cluster center of this cluster represents the typical characteristics of the cluster.

[0085] Based on this, the second evaluation information set of the tire to be tested is obtained. For further processing flow of the second evaluation information set, please refer to Figure 2 , wherein S1, S2, and SN respectively represent information of different data sampling points in the first evaluation information of the tire to be tested, S1', S2', and SN' respectively represent information of different data sampling points in the first evaluation information of the tire to be tested after optimization using the sampling point data optimization function, S' represents the data set of the optimized sampling points, snhs represents the sampling point data optimization function, hhs represents the intelligent clustering analysis function, and h1', h2', h3', and hN' respectively represent information of different data sampling points after processing using the intelligent clustering analysis function.

[0086] Furthermore, in the present embodiment, the processing method of the tire evaluation information set to be tested is only an optional condition of the present invention. In one or some other embodiments, the processing method of the tire evaluation information set may be replaced according to the actual needs of the tire quality evaluation system and the characteristics of the evaluation information. Different evaluation methods may be based on different principles, algorithms or standards. In the embodiments, selecting an appropriate processing method according to the specific characteristics of the tire and the evaluation objectives can significantly improve the accuracy and reliability of the evaluation information set.

[0087] S3. Constructing a tire quality evaluation system according to the second evaluation information set in step S2. The tire quality evaluation system mainly includes primary evaluation indicators, secondary evaluation indicators and tertiary evaluation indicators. The specific implementation steps and contents are as follows:

[0088] In an optional embodiment, a first-level evaluation index is set according to the second evaluation information set, and the first-level evaluation index includes tire uniformity; a second-level evaluation index is set according to the second evaluation information set, and the second-level evaluation index includes tire physical and mechanical properties; a third-level evaluation index is set according to the second evaluation information set, and the third-level evaluation index includes tire chemical composition; and a tire quality evaluation system is constructed in combination with the above-mentioned tire uniformity, tire physical and mechanical properties and tire chemical composition.

[0089] Based on the second evaluation information set in step S2, the key quality dimensions of the tire are quickly extracted, mainly including chemical composition, physical and mechanical properties, and measurement uniformity, and a tire quality evaluation system is constructed based on the above information. For evaluation system information, please refer to Table 2.

[0090] Table 2 Tire quality evaluation index system

[0091]

[0092] Based on the tire quality evaluation system information in Table 2, it can be seen that the relevant indicators of the tire quality evaluation system cover the key quality dimensions of tires, including measurement uniformity, physical and mechanical properties, and chemical composition, providing a scientific basis for the comprehensive evaluation of tire quality.

[0093] The evaluation system uses three levels of indicators to evaluate tire quality from multiple perspectives. The first-level evaluation indicators focus on the consistency and stability of the tire manufacturing process, which can ensure that the tires to be tested meet the established quality standards; the second-level evaluation indicators focus on the physical and mechanical properties of the tires to be tested, which will directly affect the durability, safety and driving experience of the tires; the third-level evaluation indicators go deep into the chemical composition of the tires, analyzing the impact of the material composition on the performance of the tires to be tested. Through the tire quality evaluation system, the quality level of the tires to be tested can be comprehensively and objectively evaluated, providing strong support for subsequent production, inspection and use.

[0094] To further describe tire uniformity, its working principle and key component functions, so as to more clearly understand the measurement process of the first-level evaluation indicators, please refer to Figure 3 , where A and B represent vector orthogonal force sensor devices, Fj represents radial force, fc represents lateral force, fk represents tangential force, and x, y, z, and o represent coordinate axis directions.

[0095] In order to accurately extract the uniformity characteristic information of the tire to be tested, the tire quality evaluation system performs analysis by simulating the forces exerted on the tire under actual driving conditions. Figure 3 It can be seen that the load wheel preset in the embodiment is an idealized uniform rigid body, which can accurately apply a controllable load to the tire, thereby ensuring that the central axis of the load wheel remains parallel to the central axis of the tire, and the direction of the applied force is strictly perpendicular to the two central axes, thereby establishing a reference axis system of a two-dimensional force.

[0096] In order to obtain the force fluctuations generated by the tire to be tested during rotation, two vector orthogonal force sensor devices (marked as A and B respectively) are used in the embodiment. The above sensors are installed at both ends of the load wheel center axis as support points. The above layout helps the sensor to accurately capture the force changes caused by tire unevenness such as uneven weight distribution and material hardness differences.

[0097] During the measurement process, by adjusting the distance between the load wheel and the center axis of the tire, different fixed loads can be applied to the tire. As the tire rotates, its unevenness causes the load wheel to be subjected to periodic force changes. The force changes are captured in real time by the vector orthogonal force sensor and converted into electrical signals, which are then processed and analyzed through tire quality evaluation methods.

[0098] Among them, point O, as the midpoint of the load wheel axis, is the key reference point for force balance; and point C, that is, the center of the contact surface between the tire and the load wheel, is the direct point of force transmission and interaction. By collecting and processing the information collected from the two sensors A and B, the uniformity parameters of the tire to be tested can be calculated and analyzed, such as radial force fluctuation, lateral force fluctuation, dimensional tolerance, weight deviation, tread pattern depth consistency, dynamic balance and measurement variation coefficient, etc. The above parameters directly reflect the uniformity of the tire to be tested.

[0099] In this embodiment, by precisely controlling the load application, monitoring the force change in real time, and utilizing advanced sensor technology and data processing methods, efficient and accurate measurement of the uniformity of the tire to be tested is achieved.

[0100] Furthermore, in this embodiment, the tire uniformity needs to satisfy the following relationship:

[0101]

[0102] in, represents the lateral force, represents the first force of the component load cell, represents the second force of the component load cell, represents the spindle radius, Indicates tire radius;

[0103]

[0104] in, represents the radial force, represents the distance between sensors, represents the first force of the component load cell, represents the second force of the component load cell, Indicates tire width.

[0105] Next, the weight coefficients corresponding to different evaluation indicators in the tire quality evaluation system are analyzed based on the tire quality evaluation system and the second evaluation information set.

[0106] In the embodiment, the analytic hierarchy process is used to determine the weights and scores of uniformity, physical and mechanical properties, and chemical composition in the index system. Based on the analytic hierarchy process, a judgment matrix is ​​constructed. First, for the uniformity, physical and mechanical properties, and chemical composition in the index system, the importance of evaluation indicators at different levels is compared two by two, and quantitative scores are performed according to a 1-9 ratio scale. According to the above process, a judgment matrix is ​​constructed, in which the elements of the matrix reflect the relative importance between each pair of criteria.

[0107] In the embodiment, the survey results of uniformity, physical and mechanical properties and chemical composition in the index system are assigned values ​​based on the second evaluation information set, and the judgment matrix is ​​shown in Table 3 below.

[0108] In this embodiment, combined with the second evaluation information set, a systematic evaluation was conducted on the uniformity, physical and mechanical properties, and chemical composition in the index system, and data analysis and discussion were conducted in accordance with the 1-9 ratio scale principle, and the relative importance of evaluation indicators at different levels was quantitatively scored. Finally, a judgment matrix was constructed based on the evaluation results, as shown in Table 3. The above matrix clearly reflects the relative weight relationship between evaluation indicators at different levels.

[0109] Table 3 Judgment matrix

[0110]

[0111] Furthermore, in this embodiment, SPSSAU software is used to perform further hierarchical analysis on the above judgment matrix, which not only verifies the consistency of the judgment matrix, but also obtains the weights of the uniformity of each indicator, physical and mechanical properties, and chemical composition through scientific calculation methods. Please refer to Table 4 for details. Table 4 clearly shows the key information such as the weight values ​​and consistency ratios of evaluation indicators at different levels, providing solid data support for subsequent decision-making.

[0112] Table 4 Hierarchical analysis table of evaluation indicators at different levels

[0113]

[0114] Tables 3 and 4 provide quantitative tools for tire quality evaluation. By calculating the characteristic vectors and weight values ​​of evaluation indicators at different levels, the relative importance of chemical composition, physical and mechanical properties, and uniformity evaluation indicators in the evaluation system is further demonstrated. The above weight distribution not only provides an intuitive quantitative basis for decision makers, but also affects the final evaluation results of tire quality evaluation. In this embodiment, the weight of chemical composition is relatively low at 14.286%; the weight of physical and mechanical properties is 28.571%, which highlights its key role in ensuring the performance and durability of tire products; and the weight of uniformity is relatively high at 57.143%, which clearly points out the important role of uniformity in tire quality control.

[0115] In addition, the maximum eigenvalue of 3 is consistent with the number of tire quality evaluation indicators, indicating that the constructed hierarchical model is logically consistent. Furthermore, the embodiment finds the corresponding RI value of 0.525 according to the RI table. Since CR=CI / RI, it means that CR=0.0<0.1, indicating that the relative importance evaluation between the evaluation indicators is completely consistent, and there is no internal conflict or inconsistency, etc., which can further verify the reliability and effectiveness of evaluation indicators at different levels.

[0116] The tire quality evaluation method also includes weight analysis of specific contents corresponding to average indicators at different levels in the tire quality evaluation system. The specific implementation contents are as follows:

[0117] In an optional embodiment, the dimensional indicator weights corresponding to the third-level evaluation indicator - tire chemical composition are as follows: Please refer to Table 5 for details, the dimensional indicator weight analysis table of chemical composition.

[0118] Table 5 Chemical composition-dimensional index weight analysis table

[0119]

[0120] Furthermore, SPASSRO was used to perform hierarchical analysis on the matrix in Table 5 to obtain the hierarchical analysis results in the chemical composition, as shown in Table 6.

[0121] Table 6 Hierarchical analysis of chemical composition

[0122]

[0123] Combined with the second evaluation information set of the tire to be tested, the information in Table 5 and Table 6, the hierarchical analysis method is used to further reveal the relative importance of evaluation indicators at different levels. The information in Table 5 and Table 6 can intuitively analyze the mutual influence relationship and respective weight ratio of key elements such as natural rubber, carbon black, sulfur, zinc oxide and silicon dioxide.

[0124] Based on the above information, carbon black can improve the wear resistance, strength and anti-aging ability of tires, and is the key to ensuring the durability and safe driving of tires; sulfur, as a catalyst in the vulcanization process, can make the rubber molecules of the tires closely connected to form a tough network structure, so that the tires have good elasticity and sealing; and zinc oxide can improve the wear resistance and aging resistance of the tires to be tested during tire manufacturing.

[0125] In addition, the consistency ratio of the hierarchical analysis table of chemical composition was tested to ensure the accuracy and reliability of the relevant information in the hierarchical analysis table of chemical composition, providing strong data support for the effective implementation of the tire quality evaluation method.

[0126] In another optional embodiment, the dimensional indicator weights of the content corresponding to the secondary evaluation indicator - physical and mechanical properties are as follows: Please refer to Table 7 for details, the dimensional indicator weight analysis table of physical and mechanical properties.

[0127] Table 7 Physical and mechanical properties-dimensional index weight analysis table

[0128]

[0129] Similarly, SPASSRO is used to perform hierarchical analysis on the matrix in Table 7 to obtain the hierarchical analysis results in physical and mechanical properties. Please see Table 8 for details.

[0130] Table 8 Hierarchical analysis table of physical and mechanical properties

[0131]

[0132] Combined with the second evaluation information set of the tire to be tested, the information in Table 7 and Table 8, the physical and mechanical performance indicators are further analyzed.

[0133] 1. Wear

[0134] The wear weight is as high as 32.258%, which reveals the core position of wear resistance in the application of tire materials. It is not only directly related to the service life of the tire to be tested, but also a key indicator for measuring economic benefits.

[0135] 2. Elasticity

[0136] The elastic weight reaches 25.806%. The above weight value not only reflects the response ability of the tire material to be tested when subjected to external force, but also indicates the comfort and stability that the tire to be tested can provide during driving.

[0137] 3. Hardness and tear strength

[0138] The weight values ​​of hardness and tear strength rank third and fourth, respectively, at 19.355% and 12.9%. Hardness ensures the ability of the tire to be tested to resist wear, while tear strength ensures the ability of the tire to be tested to withstand sudden tearing force.

[0139] 4. Tensile strength and aging performance

[0140] Although the weights of tensile strength and tensile strength reduction rate after hot air aging at 100℃ for 4h are relatively low, namely 6.452% and 3.226% respectively, tensile strength is a direct reflection of the load-bearing capacity of the tire to be tested, while the change in tensile strength after aging reveals the stability and durability of the tire to be tested in long-term use.

[0141] Furthermore, based on the above contents, the weights of the evaluation indicators and their corresponding contents in the tire quality evaluation system were calculated respectively, as shown in Table 9.

[0142] Table 9 Tire quality evaluation system weight analysis table

[0143]

[0144] Furthermore, in the present embodiment, the tire quality evaluation system and the specific analysis methods and steps of different indicators are merely an optional condition of the present embodiment. In one or some other embodiments, the evaluation system and the analysis methods of indicators may be adjusted according to the actual conditions of the tire to be tested and the analysis objectives of the tire quality evaluation. Different types of tires have different usage environments and performance requirements. By adjusting the evaluation system and the analysis methods of indicators, the specific performance requirements of various types of tires may be more accurately reflected.

[0145] S4. Using the second evaluation information set and the tire quality evaluation system to evaluate the quality of the tire to be tested, and selecting high-quality tires based on the evaluation results. The specific implementation steps and contents are as follows:

[0146] In this embodiment, a preliminary quality assessment result of the tire to be tested is obtained through the tire quality assessment system; further, it is necessary to establish an assessment result standardization model based on the standard conditions of the tire quality assessment system; and the preliminary quality assessment result is standardized using the above-mentioned assessment result standardization model to obtain a standardized quality assessment result.

[0147] Based on the above standardized quality assessment results, the quality of the tire to be tested is analyzed to obtain a multi-dimensional quality assessment result. In the embodiment, the multi-dimensional quality assessment result mainly includes the uniformity assessment result, mechanical property assessment result and chemical composition assessment result of the tire to be tested, so as to screen out high-quality tires.

[0148] In an optional embodiment, relevant information of tires to be tested from different manufacturers is collected, calculated and analyzed.

[0149] The chemical composition evaluation results of the tires to be tested from different manufacturers are as follows. Please see Table 10 for details.

[0150] Table 10 Chemical composition evaluation results of tires to be tested from different manufacturers

[0151]

[0152] Furthermore, a score is given based on the evaluation results in Table 10. For specific score information, please refer to Table 11.

[0153] Table 11 Statistical table of chemical composition scores of tires to be tested from different manufacturers

[0154]

[0155] In another optional embodiment, relevant information of tires to be tested from different manufacturers is collected, calculated and analyzed.

[0156] The evaluation results of the physical and mechanical properties of the tires to be tested from different manufacturers are as follows. Please see Table 12 for details.

[0157] Table 12 Physical and mechanical performance evaluation results of tires to be tested from different manufacturers

[0158]

[0159] Furthermore, a score is given based on the evaluation results in Table 12. For specific score information, please refer to Table 13.

[0160] Table 13 Statistical table of physical and mechanical performance scores of tires to be tested from different manufacturers

[0161]

[0162] In another optional embodiment, relevant information of tires to be tested from different manufacturers is collected, calculated and analyzed.

[0163] The uniformity evaluation results of the tires to be tested from different manufacturers are as follows. Please see Table 14 for details.

[0164] Table 14 Uniformity evaluation results of tires to be tested from different manufacturers

[0165]

[0166] Furthermore, a score is given based on the evaluation results in Table 14. For specific score information, please refer to Table 15.

[0167] Table 15 Statistical table of uniformity scores of tires to be tested from different manufacturers

[0168]

[0169] Based on the evaluation result table and score statistical table of the chemical composition, physical and mechanical properties and uniformity of the tires to be tested from different manufacturers, the comprehensive scores of the quality of the tires to be tested from different manufacturers are calculated. Please see Table 16 for details.

[0170] Table 16 Comprehensive scoring table of tire quality of different manufacturers

[0171]

[0172] The tire quality evaluation method proposed in the present invention. First, a comprehensive quality inspection is performed on the target tire, and the basic performance data of the tire is collected to form a preliminary first evaluation information set; then, an evaluation information processing model is constructed based on the tire properties and quality evaluation requirements. The model uses advanced algorithms and logic to conduct in-depth analysis and processing on the first evaluation information set, thereby generating a second evaluation information set; based on the second evaluation information set, a tire quality evaluation system is further constructed, which is composed of a first-level evaluation index (uniformity), a second-level evaluation index (physical and mechanical properties), and a third-level evaluation index (chemical composition): Finally, the above tire quality evaluation system is used in combination with the specific data in the second evaluation information set to perform a quality evaluation on the target tire to be tested, and the tire to be tested is screened through a scientific scoring and sorting mechanism. The above process not only ensures the objectivity and accuracy of the evaluation results, but also provides strong data support for the subsequent use and promotion of tires.

[0173] In addition, the application of the present invention has further promoted the in-depth development of tire and road tribology research, not only focusing on the performance of the tire itself, but also providing more accurate data support for road design, vehicle dynamics analysis, and traffic safety assessment by improving the measurement accuracy of the lateral force friction coefficient. In summary, the present invention has shown important value and significance in improving tire quality, ensuring road safety, and promoting technological progress in related fields.

[0174] See also Figure 4In an optional embodiment, in order to efficiently execute the tire quality evaluation method provided by the present invention, the present invention further provides a tire quality evaluation system, in which an input device, a processor, an output device and a memory are interconnected, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the specific steps of the tire quality evaluation method provided by the present invention. The tire quality evaluation system of the present invention has a complete structure, is objective and stable, and can efficiently execute the tire quality evaluation method of the present invention, thereby improving the overall applicability and practical application ability of the present invention.

[0175] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A tire quality evaluation method, characterized in that: The steps include: Performing quality inspection on the tire to be inspected to obtain a first evaluation information set of the tire to be inspected; Establishing an evaluation information processing model, processing the first evaluation information set by the evaluation information processing model, and obtaining a second evaluation information set of the tire to be tested; Constructing a tire quality evaluation system according to the second evaluation information set, wherein the tire quality evaluation system includes a primary evaluation index, a secondary evaluation index, and a tertiary evaluation index; Using the second evaluation information set and the tire quality evaluation system to perform quality evaluation on the tire to be tested, and screening out high-quality tires based on the evaluation results; The step of establishing an evaluation information processing model, processing the first evaluation information set by means of the evaluation information processing model, and obtaining a second evaluation information set of the tire to be tested comprises: Establishing an evaluation information processing model based on the characteristics of the first evaluation information set and the evaluation target of tire quality, wherein the evaluation information processing model includes a sampling point data optimization function and an intelligent clustering analysis function; Obtaining a second evaluation information set of the tire to be tested through the sampling point data optimization function and the intelligent clustering analysis function; The sampling point data optimization function satisfies the following relationship: ， in, After optimization, The data of the sampling points, Indicates The number of data input layers of sampling points, Indicates the sampling point The received signal vector of the input layer, represents the channel matrix, Indicates the sampling point The noise coefficient of the received signal at the input layer, Indicates The matrix bias matrix corresponding to the sampling points, Indicates the sampling point The weight coefficient of the input layer; The intelligent clustering analysis function satisfies the following relationship: ， in, represents the discretized data set, represents the number of samples in the data set, Represents the first The coordinates of the samples, Represents the first The samples are in the cluster center of the cluster.

2. The tire quality evaluation method according to claim 1, characterized in that: The tire quality evaluation system is constructed according to the second evaluation information set, and the tire quality evaluation system includes primary evaluation indicators, secondary evaluation indicators and tertiary evaluation indicators including: Setting a primary evaluation index according to the second evaluation information set, wherein the primary evaluation index includes tire uniformity; Setting a secondary evaluation index according to the second evaluation information set, wherein the secondary evaluation index includes tire physical and mechanical properties; Setting a three-level evaluation index according to the second evaluation information set, wherein the three-level evaluation index includes tire chemical composition; A tire quality evaluation system is constructed by combining the tire uniformity, the tire physical and mechanical properties and the tire chemical composition.

3. The tire quality evaluation method according to claim 2, characterized in that: The tire quality evaluation system is constructed according to the second evaluation information set, and the tire quality evaluation system includes primary evaluation indicators, secondary evaluation indicators and tertiary evaluation indicators including: The weight coefficients corresponding to different evaluation indicators in the tire quality evaluation system are analyzed based on the tire quality evaluation system and the second evaluation information set.

4. The tire quality evaluation method according to claim 2, characterized in that: The tire uniformity satisfies the following relationship: ， in, represents the lateral force, represents the first force of the component load cell, represents the second force of the component load cell, represents the spindle radius, Indicates tire radius; ， in, represents the radial force, represents the distance between sensors, represents the first force of the component load cell, represents the second force of the component load cell, Indicates tire width.

5. The tire quality evaluation method according to claim 1, characterized in that: The using the second evaluation information set and the tire quality evaluation system to perform quality evaluation on the tire to be tested, and selecting high-quality tires based on the evaluation results comprises: Obtaining preliminary quality evaluation results of the tire to be tested through the tire quality evaluation system; Establish a standardized model for evaluation results based on the standard conditions of the tire quality evaluation system; The preliminary quality assessment result is standardized using the assessment result standardization model to obtain a standardized quality assessment result.

6. The tire quality evaluation method according to claim 5, characterized in that: The using the second evaluation information set and the tire quality evaluation system to perform quality evaluation on the tire to be tested, and selecting high-quality tires based on the evaluation results comprises: Based on the standardized quality assessment results, a quality analysis is performed on the tire to be tested to obtain a multi-dimensional quality assessment result, which includes a uniformity assessment result, a mechanical property assessment result, and a chemical composition assessment result of the tire to be tested, so as to screen out high-quality tires.

7. A tire quality evaluation system, characterized in that: The system includes a processor, an input device, an output device and a memory, wherein the processor, the input device, the output device and the memory are interconnected, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the tire quality evaluation method according to any one of claims 1 to 6.

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