Tire pressure-temperature coupling anomaly analysis method and system for engineering tire

Abstract

The invention relates to the field of engineering tire analysis, in particular to an engineering tire-oriented tire pressure-temperature coupling anomaly analysis method and system. The method comprises the following steps: acquiring a multi-source temperature data set, and based on the multi-source temperature data set, analyzing the superposition effect of a basic temperature field and an asphalt persistent heat source to generate a multi-source temperature influence feature set; a basic tire pressure data set is obtained, the abnormal fluctuation trend and local pressure distortion of the overall tire pressure of the tire are recognized based on the basic tire pressure data set and the multi-source temperature influence feature set, and a tire pressure abnormal feature set is generated; based on the temperature influence factor set and the tire pressure anomaly feature set, positioning and coupling a thermal aging acceleration area and a mechanical fatigue hot spot area of the tire, and generating a coupling anomaly degradation information set; and based on this, carrying out fusion analysis in combination with tire material performance parameters and historical working load data, and generating a tire pressure-temperature coupling anomaly report. In the engineering tire analysis process, the maintenance efficiency is improved, and the operation and maintenance cost is reduced.

Description

Technical Field

[0001] This application relates to the field of engineering tire analysis, and in particular to a method and system for analyzing tire pressure-temperature coupling anomalies in engineering tires. Background Technology

[0002] In the field of tire safety for large construction machinery such as road rollers, the health of engineering tires, as core load-bearing and execution components, directly determines the construction quality, equipment uptime and operational economy, and is a key foundation for ensuring continuous and efficient operation of large-scale infrastructure projects.

[0003] However, existing tire anomaly monitoring methods generally view tire pressure and temperature parameters in isolation when dealing with special working conditions such as road rollers crushing high-temperature asphalt. They lack in-depth analysis of the complex thermodynamic coupling effects inside the tire. This not only makes it difficult to warn of potential structural damage caused by the superposition of local thermal aging and mechanical fatigue, but may also mask the risk of rapidly deteriorating local failure due to the false normality of the overall tire pressure, thus posing a serious operational safety hazard. Summary of the Invention

[0004] This application provides a method and system for analyzing tire pressure-temperature coupling anomalies in engineering tires to solve the aforementioned technical problems.

[0005] In a first aspect, this application provides a method for analyzing tire pressure-temperature coupling anomalies in engineering tires. The method includes: acquiring a multi-source temperature dataset; analyzing the superposition effect of the base temperature field and the continuous heat source of asphalt based on the multi-source temperature dataset to generate a multi-source temperature influence feature set; acquiring a base tire pressure dataset; identifying the abnormal fluctuation trend of the overall tire pressure and local pressure distortion based on the base tire pressure dataset and the multi-source temperature influence feature set to generate a tire pressure anomaly feature set; locating and coupling the tire's thermal aging acceleration zone and mechanical fatigue hotspot zone based on the multi-source temperature influence feature set and the tire pressure anomaly feature set to generate a coupled anomaly degradation information set; and performing a fusion analysis based on the coupled anomaly degradation information set, combined with tire material performance parameters and historical working load data, to generate a tire pressure-temperature coupling anomaly report.

[0006] The above technical solutions enable accurate early warning and location of abnormal coupling between tire pressure and temperature in engineering tires, effectively avoiding sudden failures caused by misjudgment or missed reporting due to a single factor; by revealing the synergistic degradation mechanism of thermal aging and mechanical fatigue, a scientific basis is provided for preventive maintenance, significantly extending tire lifespan; at the same time, the automatically generated comprehensive diagnostic report greatly improves maintenance efficiency, reduces operation and maintenance costs, and comprehensively enhances the operational safety and reliability of engineering vehicles under harsh working conditions.

[0007] Optionally, the step of analyzing the superposition effect of the base temperature field and the continuous heat source of asphalt based on the multi-source temperature dataset to generate a multi-source temperature influence feature set includes: the multi-source temperature dataset includes a base temperature field dataset and asphalt temperature field data, wherein the base temperature field dataset includes ambient temperature, tire internal temperature, and road surface temperature; based on the asphalt temperature field dataset, analyzing the instantaneous thermal shock caused by the high temperature asphalt to the tire tread when the tire rolls over fresh asphalt, generating an instantaneous thermal shock influence temperature; analyzing the local heat preservation effect formed in the tire due to the poor thermal conductivity of asphalt after the asphalt is embedded in the tire tread, generating a local heat preservation effect influence temperature; and generating the multi-source temperature influence feature set based on the instantaneous thermal shock influence temperature and the local heat preservation effect influence temperature.

[0008] Optionally, the analysis of the instantaneous thermal shock caused by high-temperature asphalt to the tire tread when the tire rolls over fresh asphalt, and the generation of the instantaneous thermal shock effect temperature, includes: establishing a dynamic thermal contact model of the asphalt-tire interface, wherein the dynamic thermal contact model determines a time-varying equivalent thermal contact coefficient based on the viscoelastic state of the asphalt, the geometry of the tire tread, and the rolling speed of the tire; analyzing the dynamic heat flux density distribution of the tire tread during the contact period based on the equivalent thermal contact coefficient and the instantaneous temperature difference between the asphalt and the tire; identifying each independent contact event between the roller and the high-temperature asphalt pavement in a continuous working cycle based on the roller's working path and the number of compaction passes; performing a double integration of the dynamic heat flux density distribution in the contact time domain and the tire tread spatial domain to generate an instantaneous thermal shock accumulation factor characterizing the intensity of the single thermal shock generated by each independent contact event; and summing multiple instantaneous thermal shock accumulation factors generated by consecutive independent contact events based on the identified independent contact events to generate the instantaneous thermal shock effect temperature used to evaluate periodic thermal fatigue.

[0009] Optionally, the analysis of the local insulation effect formed in the tire after asphalt is embedded in the tire tread, due to the poor thermal conductivity of asphalt, and the generation of the temperature affected by the local insulation effect, includes: constructing an asphalt filling model of the tire tread; based on the asphalt filling model, identifying the tread area substantially covered and filled by asphalt and defining it as a heat-shielding zone; analyzing the effective heat dissipation area reduction coefficient of the heat-shielding zone relative to the exposed surface of the tire, and establishing an equivalent additional thermal resistance model of the heat-shielding zone in combination with the thermal conductivity of the asphalt material; based on the equivalent additional thermal resistance model and the convective heat dissipation field of the tire as a whole, analyzing the real-time heat accumulation rate in the heat-shielding zone due to the obstruction of the heat dissipation path; integrating the real-time heat accumulation rate over the tire's working time domain to generate the temperature affected by the local insulation effect, which characterizes the historical total heat accumulation in the heat-shielding zone.

[0010] Optionally, the step of identifying abnormal fluctuation trends and local pressure distortions in the overall tire pressure based on the baseline tire pressure dataset and the multi-source temperature influence feature set, and generating a tire pressure anomaly feature set, includes: reconstructing the non-uniform temperature field of the gas inside the tire based on the baseline tire pressure dataset and the multi-source temperature influence feature set, and calculating and generating a quasi-static pressure field driven by the temperature field according to the ideal gas law; analyzing the pressure homogenization effect of the internal gas due to forced convection during tire rolling, establishing a dynamic balance relationship between the quasi-static pressure field and the overall measured tire pressure, so as to identify the periodic fluctuation trend of the overall tire pressure and the degree of thermal deviation of the baseline tire pressure dominated by the temperature affected by the local heat insulation effect; in the quasi-static pressure field, eliminating the influence of the pressure homogenization effect, identifying residual pressure peaks that are spatially locked below the heat shielding area and cannot be effectively homogenized, defining them as local pressure distortions; and constructing the tire pressure anomaly feature set according to the periodic fluctuation trend, the degree of thermal deviation of the baseline tire pressure, and the local pressure distortions.

[0011] Optionally, the step of locating and coupling the thermal aging acceleration zone and the mechanical fatigue hotspot zone of the tire based on the multi-source temperature influence feature set and the tire pressure anomaly feature set to generate a coupled abnormal degradation information set includes: locating, based on the multi-source temperature influence feature set, regions where the material performance degradation rate exceeds the average level due to the continuous superposition of the temperature affected by the instantaneous thermal shock and the temperature affected by the local heat preservation effect, defining these as thermal aging acceleration zones; locating, based on the tire pressure anomaly feature set, regions where the dynamic stress concentration and the risk of microcrack initiation in the tire skeleton material significantly increase due to the continuous effect of the local pressure distortion, defining these as mechanical fatigue hotspot zones; establishing a spatiotemporal mapping relationship between the thermal aging acceleration zone and the mechanical fatigue hotspot zone, and analyzing the coupling effect between the two in spatial overlap and temporal evolution; and generating the coupled abnormal degradation information set to characterize the overall degradation state and failure risk of the tire based on the spatiotemporal mapping relationship and coupling effect.

[0012] Optionally, establishing the spatiotemporal mapping relationship between the accelerated thermal aging zone and the mechanical fatigue hotspot zone, and analyzing their coupling effect in spatial overlap and temporal evolution, includes: analyzing the local modal stiffness variation in the accelerated thermal aging zone caused by the hardening / softening of the rubber compound, quantifying its modulation gain on the dynamic stress amplitude of the mechanical fatigue hotspot zone, and constructing a first energizing channel; analyzing the mechanical strain energy dissipated by the mechanical fatigue hotspot zone due to cyclic deformation, quantifying its catalytic effect on the microscopic molecular chain breakage reaction rate of the accelerated thermal aging zone, and constructing a second energizing channel; and based on the first energizing channel and the second energizing channel, identifying and defining the coupling core region that forms a positive feedback loop in the spatiotemporal dimension.

[0013] Optionally, the step of identifying and defining the coupling core region forming a positive feedback loop in the spatiotemporal dimension based on the first and second empowering channels includes: the coupling core region being characterized as the most dangerous area where the degradation rate of thermal aging and mechanical fatigue is continuously amplified under the interaction; quantifying the interaction strength between the first and second empowering channels, and analyzing and generating a spatially distributed thermo-mechanical coupling strength factor; the thermo-mechanical coupling strength factor being the equivalent degradation increment jointly contributed by the thermal stress gain and the mechanical aging catalytic effect per unit time; within the spatiotemporal evolution domain of the tire, tracking the strengthening trajectory of the thermo-mechanical coupling strength factor as the number of rolling passes increases, and iteratively converging and locking the final range and danger level of the coupling core region from the initial thermal aging acceleration zone and the mechanical fatigue hotspot zone by setting a dynamic threshold.

[0014] Optionally, the step of generating a tire pressure-temperature coupling anomaly report by fusing analysis based on the coupled anomaly degradation information set and tire material performance parameters with historical working load data includes: comparing the final extent and hazard level of the coupled core area with the tire material performance parameters to generate a risk level classification for each region of the tire; fusing the historical working load data to predict the damage evolution of the coupled core area within a predetermined working cycle to generate an estimated remaining service life of the critical area; and generating the tire pressure-temperature coupling anomaly report containing graded early warning information, maintenance priority suggestions, and targeted operation guidance based on the risk level classification and the estimated remaining service life.

[0015] Secondly, this application provides a tire pressure-temperature coupling anomaly analysis system for engineering tires. The system includes: a temperature analysis module for acquiring a multi-source temperature dataset, analyzing the superposition effect of the base temperature field and the continuous heat source of asphalt based on the multi-source temperature dataset, and generating a multi-source temperature influence feature set; a tire pressure analysis module for acquiring a base tire pressure dataset, identifying the abnormal fluctuation trend and local pressure distortion of the overall tire pressure based on the base tire pressure dataset and the multi-source temperature influence feature set, and generating a tire pressure anomaly feature set; a coupling analysis module for locating and coupling the thermal aging acceleration zone and mechanical fatigue hotspot zone of the tire based on the multi-source temperature influence feature set and the tire pressure anomaly feature set, and generating a coupled anomaly degradation information set; and a report generation module for performing a fusion analysis based on the coupled anomaly degradation information set, combined with tire material performance parameters and historical working load data, to generate a tire pressure-temperature coupling anomaly report. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram illustrating an application scenario provided in one embodiment of this application;

[0018] Figure 2 A flowchart of a tire pressure-temperature coupling anomaly analysis method for engineering tires provided in an embodiment of this application;

[0019] Figure 3 This is a schematic diagram of a tire pressure-temperature coupling anomaly analysis system for engineering tires, provided as an embodiment of this application. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0021] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article, unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship.

[0022] The embodiments of this application will now be described in further detail with reference to the accompanying drawings.

[0023] Existing tire anomaly monitoring methods, when dealing with special working conditions such as road rollers compacting high-temperature asphalt, generally view tire pressure and temperature parameters in isolation, lacking in-depth analysis of the complex thermodynamic coupling effects inside the tire. This not only makes it difficult to warn of potential structural damage caused by the superposition of local thermal aging and mechanical fatigue, but may also mask rapidly deteriorating local failure risks due to the false normality of overall tire pressure, posing serious operational safety hazards.

[0024] Based on this, this application provides a method and system for analyzing tire pressure-temperature coupling anomalies in engineering tires. First, multi-source sensors deployed on the tire collect temperature and tire pressure data in real time. Next, the superposition effect of the tire's base temperature field and the continuous heat source from the asphalt pavement is analyzed to generate a temperature feature set that accurately reflects local thermal effects. Based on this, combined with real-time tire pressure data, abnormal fluctuations in overall tire pressure and local pressure distortions caused by uneven heating are identified, forming a tire pressure anomaly feature set. Then, through spatial matching and correlation analysis, the identified accelerated thermal aging zone and mechanical fatigue hotspot zone are coupled and located, generating a coupled anomaly information set revealing the synergistic degradation mechanism. Finally, by integrating tire material performance parameters and historical working load data, the coupled degradation information is comprehensively evaluated and risk predicted, automatically generating a tire pressure-temperature coupling anomaly report containing specific anomaly areas, severity, and maintenance recommendations, which is then output to maintenance personnel. This method enables accurate early warning and location of abnormal coupling between tire pressure and temperature in engineering tires, effectively avoiding sudden failures caused by misjudgment or missed reporting due to a single factor. By revealing the synergistic degradation mechanism of thermal aging and mechanical fatigue, it provides a scientific basis for preventive maintenance and significantly extends tire life. At the same time, the automatically generated comprehensive diagnostic report greatly improves maintenance efficiency, reduces operation and maintenance costs, and comprehensively enhances the operational safety and reliability of engineering vehicles under harsh conditions.

[0025] Figure 1 This is a schematic diagram illustrating an application scenario provided by this application. In the process of analyzing engineering tires, the method provided in this application improves maintenance efficiency, reduces operation and maintenance costs, and comprehensively enhances the operational safety and reliability of engineering vehicles under harsh working conditions.

[0026] Specifically, the method of this application can be applied to any server. First, multi-source sensors deployed on the tire collect temperature and tire pressure data in real time. Then, the superposition effect of the tire's base temperature field and the continuous heat source from the asphalt pavement is analyzed to generate a temperature feature set that accurately reflects the local thermal effects. Based on this, combined with real-time tire pressure data, abnormal fluctuation trends in the overall tire pressure and local pressure distortion caused by uneven heating are identified, forming a tire pressure anomaly feature set. Then, through spatial matching and correlation analysis, the identified thermal aging acceleration zone and mechanical fatigue hotspot zone are coupled and located to generate a coupled anomaly information set that reveals the synergistic degradation mechanism. Finally, by integrating tire material performance parameters and historical working load data, the coupled degradation information is comprehensively evaluated and risk predicted, automatically generating a tire pressure-temperature coupled anomaly report containing specific anomaly areas, severity, and maintenance recommendations, which is then output to maintenance personnel.

[0027] For specific implementation details, please refer to the following examples.

[0028] Figure 2 This is a flowchart illustrating a tire pressure-temperature coupling anomaly analysis method for engineering tires, provided as an embodiment of this application. The method of this embodiment can be applied to servers in the above-mentioned scenarios. Figure 2 As shown, the method includes:

[0029] S201. Obtain a multi-source temperature dataset. Based on the multi-source temperature dataset, analyze the superposition effect of the basic temperature field and the continuous heat source of asphalt, and generate a multi-source temperature influence feature set.

[0030] A multi-source temperature dataset can be a comprehensive set of multi-dimensional parameters characterizing the temperature state of engineering tires during operation. It includes data on ambient temperature, tire internal temperature, road surface temperature, and asphalt temperature field, sourced from temperature sensors embedded in the tire surface. The baseline temperature field represents the stable temperature distribution region formed by natural physical processes when there are no external continuous heat sources, serving as the reference background for tire temperature. The continuous asphalt heat source refers to the asphalt pavement in contact with the engineering tire during operation, which continuously transfers heat to the tire under the influence of solar radiation, accumulated ambient temperature, and rolling heat. The multi-source temperature influence feature set is a set of characteristic parameters extracted by analyzing the superposition of the baseline temperature field and the continuous asphalt heat source, quantifying the influence of temperature on the tire. This includes the temperature affected by instantaneous thermal shock and the temperature affected by local insulation effects.

[0031] Specifically, engineering tires are widely used in heavy vehicles such as construction machinery, trucks, and mining equipment, often operating in harsh environments with high temperatures and heavy loads. Especially when in prolonged contact with asphalt pavements, tire temperature management becomes a critical factor for safe operation. While the base temperature field reflects the external ambient temperature, the continuous heat source of the asphalt pavement introduces external heat input, leading to abnormally high local temperatures, accelerating tire material aging and structural damage. Existing tire temperature monitoring technologies are mostly limited to overall temperature monitoring, neglecting the analysis of the cumulative effects of local heat sources, making it difficult to accurately identify abnormal temperature areas and thus predict thermal aging risks. This step first collects temperature data in real time using multi-source temperature sensors deployed on the tires, forming a multi-source temperature dataset. Then, the data processing module analyzes the base temperature field, combining it with the heat source data from the asphalt pavement, and analyzes the heating effect of the continuous heat source of asphalt on the tire through heat conduction simulation, identifying the superimposed abnormal temperature areas. Finally, key features such as temperature change rate, hotspot location, and heat distribution uniformity are extracted and integrated to generate a multi-source temperature influence feature set. This step improves the accuracy and real-time performance of tire temperature monitoring, provides early warning of thermal aging tendencies, reduces the risk of tire blowouts or wear caused by abnormal temperatures, extends tire lifespan, and enhances the operational safety of engineering vehicles in high-temperature environments.

[0032] S202. Obtain the basic tire pressure dataset. Based on the basic tire pressure dataset and the multi-source temperature influence feature set, identify the abnormal fluctuation trend of the overall tire pressure and the local pressure distortion, and generate a tire pressure abnormality feature set.

[0033] The baseline tire pressure dataset can be a set of parameters characterizing the tire pressure benchmark and dynamic changes under normal operating conditions of an engineering tire. The data comes from the tire pressure monitoring sensor built into the tire. Abnormal fluctuation trends can be the overall tire pressure deviating from the normal fluctuation range, exhibiting a continuous increase, decrease, or irregular and drastic fluctuation trend. Local pressure distortion can be the phenomenon where the tire pressure in a local area inside the tire differs significantly from the overall tire pressure, forming local high-pressure or low-pressure areas. The tire pressure anomaly feature set can be a set of feature parameters extracted by identifying abnormal fluctuation trends and local pressure distortions to quantify the abnormal tire pressure state.

[0034] Specifically, the tire pressure of engineering tires directly affects vehicle stability, fuel efficiency, and safety. Especially under heavy loads, abnormal tire pressure can lead to tire blowouts, loss of handling, or accelerated wear. Existing tire pressure monitoring systems often only focus on the overall tire pressure value, lacking in-depth analysis of abnormal fluctuation trends and local pressure distortions, and rarely correlate with temperature effects, resulting in a high risk of missed or false alarms. For example, in high-temperature environments, tire pressure may increase due to gas expansion, but localized high temperatures can cause pressure distortion, leading to mechanical fatigue. This step first obtains a basic tire pressure dataset and, combined with a multi-source temperature influence feature set, analyzes the mechanism by which temperature affects tire pressure. Then, a trend analysis algorithm is used to detect abnormal fluctuations in overall tire pressure, such as identifying a continuous upward trend that may indicate overheating risk, or a sudden downward trend that may indicate leakage. Simultaneously, based on the pressure distribution map, local pressure distortion areas are detected, for example, by comparing data from adjacent sensors to find pressure anomalies. Finally, these analytical results are integrated to generate a tire pressure anomaly feature set. This step improves the comprehensiveness and accuracy of tire pressure monitoring, effectively prevents safety accidents caused by abnormal tire pressure, optimizes tire maintenance strategies, reduces operating costs, and enhances the overall reliability and efficiency of engineering vehicles.

[0035] S203. Based on the temperature influencing factor set and the tire pressure abnormality feature set, locate and couple the tire's thermal aging acceleration zone and mechanical fatigue hot spot zone to generate a coupled abnormal degradation information set.

[0036] The accelerated thermal aging zone is an area on the tire where the temperature is consistently high or fluctuates drastically, causing a significant acceleration in the thermal aging rate of materials (rubber, cord). Material properties in this area deteriorate rapidly (rubber hardens, cord strength decreases), making it the core area of ​​tire degradation. The mechanical fatigue hotspot is an area where uneven stress caused by abnormal tire pressure leads to a significant concentration of mechanical stress in the tire structure. Under repeated loading, fatigue damage accumulates rapidly, easily causing bulges, cord breakage, and other failures. The coupled abnormal degradation information set is a comprehensive set of information reflecting the abnormal degradation state of the tire, generated by coupling the accelerated thermal aging zone and the mechanical fatigue hotspot.

[0037] Specifically, the failure of engineering tires often stems from the synergistic effect of thermal aging and mechanical fatigue: high temperatures soften rubber materials, accelerating oxidative aging, while mechanical stress triggers crack propagation. The combined effect of these two factors can significantly shorten tire life. Existing analytical methods typically treat thermal aging and mechanical fatigue as independent factors, lacking coupled analysis and failing to accurately predict the overall degradation path of the tire. For example, in high-temperature and high-pressure regions, thermal aging may exacerbate mechanical fatigue, leading to early damage. This step first identifies accelerated thermal aging zones based on a set of temperature influence factors using threshold analysis or clustering algorithms, such as marking areas where the temperature consistently exceeds the safety threshold. Simultaneously, based on a set of abnormal tire pressure features, mechanical fatigue hotspots are identified using a stress distribution model, such as locating areas with frequent pressure distortion. Then, spatial matching or correlation analysis is used to couple the accelerated thermal aging zones with the mechanical fatigue hotspots, for example, by detecting overlapping regions or calculating correlations to identify areas where both factors interact. Finally, the degree of degradation in the coupled regions is assessed, for example, by predicting the rate of material performance degradation based on a thermomechanical model, generating a set of coupled abnormal degradation information. This step improves the accuracy of tire failure prediction, avoids unexpected downtime due to coupling degradation, extends tire replacement cycles, reduces maintenance costs, and enhances the durability and safety of engineering vehicles under harsh operating conditions.

[0038] S204. Based on the coupled abnormal degradation information set, a tire pressure-temperature coupled abnormality report is generated by combining tire material performance parameters with historical working load data for fusion analysis.

[0039] Tire material performance parameters can be a set of parameters characterizing the physical and mechanical properties of the materials used in the tire (tread rubber, cords, belt layers, etc.). Historical working load data can be a set of load-related data that the tire has experienced during past operation, including driving loads (fully loaded, half-loaded, unloaded) at different time periods, load distribution, mileage, road conditions (mining, construction roads), etc. Tire pressure-temperature coupling anomaly reports can be reports generated based on fusion analysis results that contain detailed information on tire coupling anomalies, including the location of the anomaly area, its severity, and maintenance recommendations.

[0040] Specifically, abnormal degradation of engineering tires depends not only on their current condition but also on material tolerance limits and historical usage. Material performance parameters define the tire's physical boundaries; for example, the heat resistance threshold determines the safe range at high temperatures. Historical workload data reflects cumulative tire damage; for instance, a history of high loads may exacerbate fatigue. Existing report generation methods often rely on real-time data, lacking a comprehensive consideration of material properties and historical context, leading to incomplete risk assessments. This step first acquires tire material performance parameters and historical workload data based on a coupled abnormal degradation information set. Then, through data fusion techniques, such as rule-based engines or machine learning models, the severity of current abnormal degradation is assessed, for example, by calculating risk scores or predicting remaining service life. Simultaneously, patterns are identified by combining historical data, such as degradation acceleration trends under high-frequency loads. Finally, the analysis results are integrated to generate a structured tire pressure-temperature coupled anomaly report. This step generates comprehensive and accurate anomaly reports, helping users take timely preventative measures, reduce tire failure rates, improve vehicle availability, lower overall operating costs, and promote the scientific management of tire lifecycles.

[0041] The method provided in this embodiment firstly collects temperature and tire pressure data in real time using multi-source sensors deployed on the tire. Next, it analyzes the superposition effect of the tire's base temperature field and the continuous heat source from the asphalt pavement to generate a temperature feature set that accurately reflects local thermal effects. Based on this, combined with real-time tire pressure data, it identifies abnormal fluctuations in overall tire pressure and local pressure distortions caused by uneven heating, forming a tire pressure anomaly feature set. Then, through spatial matching and correlation analysis, it couples and locates the identified accelerated thermal aging zone and mechanical fatigue hotspot zone, generating a coupled anomaly information set that reveals the synergistic degradation mechanism. Finally, by integrating tire material performance parameters and historical workload data, it comprehensively assesses and predicts risks related to the coupled degradation information, automatically generating a tire pressure-temperature coupled anomaly report containing specific anomaly areas, severity, and maintenance recommendations, which is then output to maintenance personnel. This method enables accurate early warning and location of abnormal coupling between tire pressure and temperature in engineering tires, effectively avoiding sudden failures caused by misjudgment or missed reporting due to a single factor. By revealing the synergistic degradation mechanism of thermal aging and mechanical fatigue, it provides a scientific basis for preventive maintenance and significantly extends tire life. At the same time, the automatically generated comprehensive diagnostic report greatly improves maintenance efficiency, reduces operation and maintenance costs, and comprehensively enhances the operational safety and reliability of engineering vehicles under harsh conditions.

[0042] In some embodiments, the multi-source temperature dataset includes a base temperature field dataset and asphalt temperature field data, wherein the base temperature field dataset includes ambient temperature, tire interior temperature, and road surface temperature; based on the asphalt temperature field dataset, the instantaneous thermal shock caused by the high-temperature asphalt to the tire tread when the tire rolls over fresh asphalt is analyzed to generate the instantaneous thermal shock effect temperature; the local insulation effect formed in the tire due to the poor thermal conductivity of asphalt after the asphalt is embedded in the tire tread is analyzed to generate the local insulation effect temperature; based on the instantaneous thermal shock effect temperature and the local insulation effect temperature, a multi-source temperature effect feature set is generated.

[0043] The basic temperature field dataset is a collection of temperature data generated by natural physical processes when engineering tires are driving on non-fresh asphalt roads. It serves as a benchmark reference for tire temperature and includes three core dimensions: ambient temperature, tire internal temperature, and road surface temperature. The asphalt temperature field data is a set of parameters specifically characterizing the temperature state of fresh asphalt roads, focusing on the temperature characteristics of this unique heat source. Ambient temperature refers to the temperature of the atmosphere surrounding the engineering tire's operation. It is a fundamental environmental parameter affecting tire heat dissipation efficiency, exhibiting no significant spatial differences and providing an environmental background reference for tire temperature analysis. Tire internal temperature refers to the temperature inside the engineering tire (carcass layers, tire cavity), directly reflecting the balance between frictional heat generation and dissipation, and is a core parameter characterizing the tire's thermal state. Road surface temperature refers to the temperature of the tire in contact with the road surface, divided into conventional road surface temperature (a component of the basic temperature field) and fresh asphalt road surface temperature (the core of the asphalt temperature field data), representing the primary temperature source of external heat for the tire. The instantaneous thermal shock effect temperature is a set of characteristic parameters obtained by quantifying the instantaneous thermal shock, including the amplitude, peak value, and duration of tread temperature changes during the impact process. It is used to accurately characterize the degree of impact of instantaneous thermal effects on the tire. Localized heat insulation can occur when fresh asphalt embeds into the tire tread pattern under tire pressure. Due to the low thermal conductivity and slow heat dissipation of asphalt, a localized "insulating layer" forms in the tread gaps, making it difficult for heat to dissipate in certain areas and maintaining a higher temperature in those areas. The impact of localized heat insulation on temperature can be characterized by analyzing the rate of temperature decrease in the tread pattern area, the duration of high temperature maintenance, and the temperature difference between the tread pattern area and the non-tread area. These parameters represent the sustained effect of heat insulation on the local temperature of the tire.

[0044] Specifically, engineering tires frequently come into contact with high-temperature asphalt during operation, especially on paved or maintained roads. This contact not only brings instantaneous thermal shock but also causes localized temperature anomalies due to asphalt residue. Traditional temperature monitoring methods often only focus on the basic temperature field (such as ambient or tire internal temperature) and ignore the cumulative effect of asphalt as a continuous heat source. This may lead to misjudgments of tire thermal aging or mechanical fatigue. For example, in road construction areas, the temperature of fresh asphalt can be much higher than the ambient temperature. When a tire rolls over it, the tread absorbs a large amount of heat within milliseconds, causing instantaneous thermal shock. This shock may trigger micro-cracks or softening of the tread rubber, accelerating wear. At the same time, asphalt particles are easily embedded in the tire tread. Due to the low thermal conductivity of asphalt (usually in the range of 0.5-1.0 W / m·K), it acts like an insulation layer, preventing heat from dissipating to the surroundings and forming a "heat insulation layer" in the local area of ​​the tire. This results in a persistently high temperature in that area, which in turn promotes rubber aging and weakens the tire structure. To address the above issues, this step first involves activating multiple temperature acquisition devices to simultaneously acquire data and construct a multi-source temperature dataset: ambient temperature is collected via an onboard vehicle temperature sensor; temperatures at different locations within the tire are collected via a tire-embedded temperature measurement module; and conventional road surface temperatures (e.g., 25°C) are collected via sensors embedded in non-asphalt areas of the road surface. These three data points are integrated into a basic temperature field dataset. Next, the surface temperature of fresh asphalt (e.g., 120-180°C) is collected via a mobile road surface temperature measurement device, and internal temperatures and temperature decay data at different depths of asphalt are collected via sensors embedded in the asphalt layer, forming asphalt temperature field data. Subsequently, the time periods during which the tire rolled over fresh asphalt are selected based on the asphalt temperature field data. The system captures dynamic changes in tire tread temperature, recording the start time of a sudden temperature rise, the peak temperature (e.g., 80℃), and the duration of a rapid temperature drop (e.g., 10 seconds), generating the instantaneous thermal shock effect temperature. Next, it extracts temperature data from the tread pattern area after the tire has rolled over asphalt, compares the temperature changes between the asphalt-embedded tread area and the non-asphalt-adhered area, records the temperature drop rate of the tread area (e.g., 2℃ per minute), the duration of high temperature maintenance (e.g., 30 minutes), and the temperature difference between the tread area and the non-tread area (e.g., 5℃), generating the local insulation effect temperature. Finally, it integrates the key characteristic parameters of the two types of temperatures, supplements the temperature influence differences of different areas of the tread (e.g., the middle and the edge), forming a multi-source temperature influence feature set.

[0045] The method provided in this embodiment generates a multi-source temperature influence feature set, which can accurately capture temperature anomalies of engineering tires under real road conditions, effectively identify potential risks brought about by instantaneous thermal shock and local heat preservation effects, and make subsequent tire pressure anomaly analysis and coupled degradation positioning more targeted and reliable.

[0046] In some embodiments, a dynamic thermal contact model of the asphalt-tire interface is established. This model determines a time-varying equivalent thermal contact coefficient based on the viscoelastic state of the asphalt, the geometry of the tire tread pattern, and the rolling speed of the tire. Based on the equivalent thermal contact coefficient and the instantaneous temperature difference between the asphalt and tire, the dynamic heat flux density distribution of the tire tread during the contact period is analyzed. Based on the roller's operating path and number of compaction passes, each independent contact event between the roller and the high-temperature asphalt pavement within a continuous working cycle is identified. The dynamic heat flux density distribution is double-integrated in both the contact time domain and the tire tread spatial domain to generate an instantaneous thermal shock accumulation factor characterizing the intensity of a single thermal shock generated by each independent contact event. Based on the identified independent contact events, multiple instantaneous thermal shock accumulation factors generated by consecutive independent contact events are summed to generate an instantaneous thermal shock influence temperature for evaluating periodic thermal fatigue.

[0047] A dynamic thermal contact model is a heat transfer analysis model built based on the dynamic physical properties of asphalt-tire contact. It can reflect changes in heat transfer efficiency at the contact interface in real time, overcoming the limitations of traditional fixed-parameter models. The viscoelastic state of asphalt can be the physical state of fresh asphalt at high temperatures, exhibiting both viscous flow and elastic recovery characteristics. The geometry of the tire tread pattern can be the structural parameters of the tire tread pattern, including tread depth, tread width, tread spacing, and tread block shape, which determine the actual contact area, contact pressure distribution, and contact time between the tire and the asphalt pavement. The tire's rolling speed can be the instantaneous linear velocity of the tire traveling on the asphalt pavement, directly affecting the contact time between the tire and the asphalt interface, thus altering the heat transfer time window. The equivalent thermal contact coefficient is a dynamic parameter that quantifies the heat transfer capacity of the asphalt-tire interface, comprehensively reflecting the combined effects of interface contact pressure, contact area, and material thermal conductivity, changing in real time with the tire's rolling state. Dynamic heat flux density distribution describes the heat distribution per unit time through a unit contact area during asphalt-tire contact, dynamically changing with contact time and location. It accurately characterizes the spatial transmission pattern of thermal shock on the tire tread. An independent contact event is the complete process of a tire rolling over a specific asphalt area in a continuous working cycle. The initial contact between the tire and the asphalt in that area, until complete separation, constitutes an independent event, with each event corresponding to a transient thermal shock. The transient thermal shock accumulation factor is a parameter obtained by standardizing the accumulated temperature of each transient thermal shock. It is used to quantify the relative magnitude of the thermal shock intensity of different independent contact events, facilitating cumulative calculations.

[0048] Specifically, when engineering tires are used on heavy equipment such as road rollers, they frequently roll over hot asphalt pavements, causing the tire tread to experience severe instantaneous thermal shocks. These shocks not only cause a sudden rise in tread temperature but may also accelerate rubber aging and structural fatigue. Traditional temperature monitoring methods often ignore the dynamic and cumulative effects of thermal shocks, relying solely on average temperature or point measurements for judgment, making it impossible to accurately predict tire life and failure risks. For example, during road construction, road rollers repeatedly roll over the same area, generating thermal shocks with each contact. These shocks accumulate in specific areas of the tread (such as tread grooves), forming local hot spots, which can then lead to microcracks or delamination. The problem is that the intensity of thermal shocks is affected by various factors, such as the viscoelastic state of the asphalt (asphalt is softer at higher temperatures, resulting in tighter contact and enhanced heat conduction), the geometry of the tire tread pattern (complex patterns may increase the area of ​​heat accumulation), and the rolling speed (slower speeds result in longer contact time and greater heat input). These factors interact, making the thermal shock process highly nonlinear. To address the above issues, this step first constructs a dynamic thermal contact model of the asphalt-tire interface by combining asphalt viscoelastic parameters (e.g., elastic modulus 2.5 MPa, viscosity coefficient 0.8 Pa·s), tire tread geometry data (e.g., tread depth 18 mm, width 20 mm, spacing 30 mm), and real-time tire rolling speed (e.g., 5 km / h), and calculates the equivalent thermal contact coefficient as the contact state changes. Subsequently, instantaneous temperature differences (e.g., 100 °C) are simultaneously acquired using an asphalt surface temperature sensor (e.g., collecting data from a fresh asphalt surface at 160 °C) and a tire tread embedded sensor (e.g., collecting data from the initial tire tread at 60 °C), and these differences are analyzed in conjunction with the equivalent thermal contact coefficient. The dynamic heat flux density distribution of the tire tread is obtained. Then, based on the operation path (e.g., circular construction trajectory) and number of compaction passes (e.g., 8 passes) recorded by the GPS of the road roller, independent contact events between the tire and the same asphalt area are identified within a continuous working cycle (e.g., 2 hours) (e.g., each contact lasts for 2 seconds). Subsequently, the dynamic heat flux density distribution of each event is double-integrated in the contact time domain (e.g., 2 seconds) and the tire tread spatial domain (e.g., the middle tread block area) to obtain the cumulative temperature of a single thermal shock. Finally, the instantaneous thermal shock accumulation factors of 10 consecutive independent contact events are summed to generate the instantaneous thermal shock effect temperature for evaluating periodic thermal fatigue.

[0049] The method provided in this embodiment generates instantaneous thermal shock impact temperature, which can accurately quantify the cumulative thermal shock effect of engineering tires in rolling contact, effectively identify the risk of periodic thermal fatigue, and make subsequent tire pressure anomaly analysis and coupled degradation positioning more scientific and reliable. At the same time, through dynamic thermal contact model and dual integration method, the accuracy and real-time performance of thermal shock assessment are improved, which helps to prevent early tire failure, extend service life, and thus improve the safety and operational efficiency of engineering equipment.

[0050] In some embodiments, an asphalt-filled model of the tire tread is constructed. Based on the asphalt-filled model, the tread area substantially covered and filled by asphalt is identified and defined as the heat-shielding zone. The effective heat dissipation area reduction coefficient of the heat-shielding zone relative to the exposed surface of the tire is analyzed, and combined with the thermal conductivity of the asphalt material, an equivalent additional thermal resistance model of the heat-shielding zone is established. Based on the equivalent additional thermal resistance model and the convective heat dissipation field of the tire as a whole, the real-time heat accumulation rate caused by the obstruction of the heat dissipation path in the heat-shielding zone is analyzed. The real-time heat accumulation rate is integrated over the tire's working time domain to generate the temperature representing the local heat preservation effect that characterizes the historical total heat accumulation in the heat-shielding zone.

[0051] The asphalt filling model is a simulation analysis model based on the tire tread structure and asphalt filling patterns. It is used to accurately identify the filling area and coverage state of asphalt in the tread gaps. The heat-shielded area is a localized region of the tire tread where asphalt is substantially covered and filled in the tread gaps, obstructing the heat dissipation path. This is the core area of ​​the heat insulation effect, distinct from the bare tread area without asphalt. The effective heat dissipation area reduction factor is the ratio of the actual usable heat dissipation area of ​​the heat-shielded area to the theoretical heat dissipation area of ​​that area. It quantifies the degree to which asphalt coverage obstructs heat dissipation; a smaller factor indicates a more severe loss of heat dissipation area. The thermal conductivity of asphalt material is a physical parameter characterizing the thermal conductivity of asphalt, reflecting the efficiency of heat transfer. Its low thermal conductivity is the core reason for the heat insulation effect. The equivalent additional thermal resistance model is an analytical model that quantifies the heat dissipation resistance of the heat-shielded area. It comprehensively considers the synergistic effect of the effective heat dissipation area reduction factor and the thermal conductivity of asphalt material, reflecting the degree to which asphalt filling hinders tread heat dissipation. The real-time heat accumulation rate can be the amount of heat accumulated per unit time in the heat shielded area, reflecting the balance between heat generation and heat dissipation obstruction, and it changes dynamically with the working status.

[0052] Specifically, during the construction or operation of engineering tires, asphalt embedded in the tire tread creates a localized heat-insulating effect due to the poor thermal conductivity of asphalt. This effect causes heat to accumulate in specific areas of the tread, accelerating rubber thermal aging, hardening, or cracking. Traditional temperature monitoring methods often only focus on the overall average temperature or point measurements, ignoring the dynamic accumulation of the localized heat-insulating effect. This makes it impossible to accurately assess the risk of localized overheating and predict tire lifespan. For example, during the operation of road rollers or heavy engineering vehicles, high-temperature asphalt particles can easily embed in the tire tread grooves, forming heat-shielded areas. These areas have reduced effective heat dissipation area due to asphalt coverage, and the low thermal conductivity of asphalt (typically in the range of 0.5-1.5 W / m·K) increases additional thermal resistance, hindering heat dissipation to the surrounding air. This results in persistently higher local temperatures, sometimes even several degrees Celsius higher than exposed areas. Over time, this heat accumulation promotes the breakage of rubber molecular chains and accelerates oxidation reactions, leading to tread peeling, uneven wear, or the risk of tire blowout. To address the above issues, this step, based on tire surface scanning data (such as 3D images of the tire tread obtained through a laser scanner), first constructs an asphalt-filled model of the tire tread pattern, identifying the heat-shielding areas covered by asphalt (e.g., areas with a groove depth of 8mm and a coverage rate exceeding 60%). Next, it analyzes the effective heat dissipation area reduction factor of this area relative to the exposed tire tread (e.g., 0.3), and establishes an equivalent additional thermal resistance model based on the thermal conductivity of asphalt material (e.g., 0.8 W / m·K). Then, based on this model and the tire's convective heat dissipation field (e.g., airflow at a vehicle speed of 5 km / h), it calculates the real-time heat accumulation rate (e.g., a temperature increase of 1.2℃ per minute) caused by heat dissipation obstruction within the heat-shielding area. Finally, it integrates the real-time heat accumulation rate over a continuous working time domain (e.g., a 4-hour work cycle) to generate a temperature representing the local insulation effect that characterizes the total historical heat accumulation.

[0053] The method provided in this embodiment can accurately quantify the local heat accumulation effect of engineering tires after asphalt embedding, effectively identify the thermal aging risk and structural damage caused by the heat insulation effect, and make subsequent tire pressure anomaly analysis and coupled degradation positioning more scientific and reliable. At the same time, by using an equivalent additional thermal resistance model and integral method, the accuracy and real-time performance of local temperature assessment are improved, which helps to prevent local overheating and early failure of tires.

[0054] In some embodiments, based on a baseline tire pressure dataset and a multi-source temperature influence feature set, the non-uniform temperature field of the gas inside the tire is reconstructed, and a quasi-static pressure field driven by the temperature field is calculated and generated according to the ideal gas law. The pressure homogenization effect of the internal gas due to forced convection during tire rolling is analyzed, and a dynamic balance relationship between the quasi-static pressure field and the overall measured tire pressure is established to identify the periodic fluctuation trend of the overall tire pressure and the degree of thermal deviation of the baseline tire pressure, which is dominated by the temperature affected by the local heat insulation effect. In the quasi-static pressure field, the influence of the pressure homogenization effect is eliminated, and residual pressure peaks that are spatially locked below the heat shield and cannot be effectively homogenized are identified and defined as local pressure distortion. Based on the periodic fluctuation trend, overall thermal drift, and local pressure distortion, a tire pressure anomaly feature set is constructed.

[0055] A non-uniform temperature field can be a spatially uneven temperature distribution field formed by the gas inside an engineering tire due to local insulation effects, instantaneous thermal shocks, etc. The ideal gas law (PV=nRT) is a physical equation describing the relationship between pressure, volume, and temperature of an ideal gas. It is used to quantify the driving effect of temperature changes on tire pressure and is the theoretical basis for calculating the quasi-static pressure field. The quasi-static pressure field of a tire can be a field characterizing the spatial distribution of gas pressure inside the tire, calculated based on the non-uniform temperature field using the ideal gas law. The pressure homogenization effect can be a physical effect where forced convection of gas inside the tire gradually reduces local pressure differences and makes the overall tire pressure tend to be uniform. This effect can mask some local pressure distortions and is a key interfering factor affecting the identification of abnormal tire pressure. The degree of thermal deviation of the base tire pressure can be the degree to which the base tire pressure deviates from the standard value due to an increase in overall temperature (such as accumulated ambient temperature or multiple thermal shocks). This is a normal thermal response and not an anomaly caused by structural failure. Residual pressure peaks can be localized high-pressure regions that persist below the heat shield in a quasi-static pressure field after the pressure homogenization effect has been eliminated. These are pressure distortions that cannot be eliminated by gas convection. Localized pressure distortions, characterized by residual pressure peaks, are tire pressure anomalies confined to below the heat shield. They differ from overall tire pressure fluctuations and are often caused by localized tire structural damage (such as bulges or cord breakage) or impeded heat dissipation due to asphalt filling.

[0056] Specifically, abnormal tire pressure is one of the main factors leading to tire failure during operation. However, traditional tire pressure monitoring methods are usually based on overall average values ​​or simple thresholds, which cannot capture complex pressure changes caused by temperature non-uniformity. For example, during the operation of road rollers or heavy vehicles, the temperature of the gas inside the tire is non-uniform due to thermal shock and insulation effects, resulting in local pressure distortion and overall fluctuations. These problems may cause uneven tread wear, tire blowout risk, or operational instability. Traditional methods ignore the driving effect of the temperature field on the pressure field and the influence of forced convection during rolling, relying solely on measured tire pressure for judgment, which makes it impossible to distinguish between normal fluctuations and abnormal distortions, resulting in low accuracy of early warning. To address the above issues, this step, based on a basic tire pressure dataset (such as a real-time pressure value of 2.5 Bar obtained through a tire pressure monitoring system) and a multi-source temperature influence feature set (such as the temperature of the 65°C heat-shrouded area caused by local heat insulation effects), first reconstructs the non-uniform temperature field of the gas inside the tire (e.g., the spatial distribution of a tread temperature of 70°C while the sidewall temperature is only 50°C); then, it calculates and generates a quasi-static pressure field driven by this temperature field based on the ideal gas law (e.g., the theoretical pressure of 2.8 Bar corresponding to the heat-shrouded area); finally, it analyzes the pressure homogenization effect of the internal gas due to forced convection during tire rolling (e.g., rolling...). The dynamic balance between the quasi-static pressure field and the overall measured tire pressure (e.g., 2.6 Bar) is established by reducing the pressure difference by 0.15 Bar. This allows for the identification of periodic fluctuation trends (e.g., 0.1 Bar fluctuation per work cycle) and the degree of thermal deviation of the basic tire pressure (e.g., an overall deviation of 0.3 Bar). Subsequently, the homogenization effect is eliminated in the quasi-static pressure field, and residual pressure peaks (e.g., a local high-pressure area of ​​2.75 Bar) locked below the thermally shielded area are identified and defined as local pressure distortion. Finally, the periodic fluctuations, overall thermal deviation, and local pressure distortion are integrated to construct a tire pressure anomaly feature set.

[0057] The method provided in this embodiment can accurately identify abnormal fluctuations in overall tire pressure and local pressure distortions, effectively distinguishing between temperature-driven pressure changes and mechanical anomalies, making subsequent coupled degradation analysis more scientific and reliable. At the same time, through non-uniform temperature field reconstruction and pressure homogenization effect analysis, the accuracy and real-time performance of tire pressure anomaly detection are improved, which helps prevent tire failure and extend service life.

[0058] In some embodiments, based on the multi-source temperature influence feature set, regions where the material performance degradation rate exceeds the average level due to the continuous superposition of the temperature affected by instantaneous thermal shock and the temperature affected by local heat preservation effect are located and defined as the thermal aging acceleration zone; based on the tire pressure anomaly feature set, regions where the dynamic stress concentration and risk of microcrack initiation in the tire skeleton material are significantly increased due to the continuous effect of local pressure distortion are located and defined as the mechanical fatigue hot spot zone; a spatiotemporal mapping relationship between the thermal aging acceleration zone and the mechanical fatigue hot spot zone is established, and the coupling effect between the two in spatial overlap and temporal evolution is analyzed; based on the spatiotemporal mapping relationship and coupling effect, a coupled abnormal degradation information set for characterizing the overall degradation state and failure risk of the tire is generated.

[0059] Material performance degradation rate can characterize the rate at which the properties (such as elasticity and strength) of tire materials (rubber, cords, etc.) deteriorate due to temperature. Exceeding the average level indicates the onset of accelerated aging. Accelerated thermal aging zones are localized areas on the tire where the rate of material performance degradation significantly exceeds the overall average due to the combined effects of instantaneous thermal shock and localized insulation. These are the core areas of thermal damage accumulation, distinct from normal aging areas. Tire carcass materials are the core structural materials that provide support within engineering tires, mainly including cords (such as steel cords and polyester cords) and belt layers. Their fatigue resistance directly determines the tire's service life. Mechanical fatigue hotspots are localized areas where continuous localized pressure distortion leads to dynamic stress concentration in the carcass material and a significantly higher risk of microcrack initiation compared to other areas. These are the core areas of mechanical damage accumulation.

[0060] Specifically, during the operation of engineering tires, thermal aging and mechanical fatigue are the two main factors leading to failure. However, traditional analysis methods usually treat temperature and pressure anomalies independently, failing to capture the coupling effect between the two. For example, during the operation of road rollers or heavy vehicles, the thermal shock and insulation effect caused by high-temperature asphalt may lead to hardening and embrittlement of the tread rubber. At the same time, local pressure distortion causes stress concentration in the skeleton material. However, if only temperature or pressure is analyzed separately, the accelerated degradation caused by thermo-mechanical coupling will be ignored, thus missing potential failure risks. Traditional methods lack precise positioning of the thermal aging acceleration zone and mechanical fatigue hotspot zone, as well as analysis of the spatiotemporal relationship between the two, resulting in delayed warnings or misjudgments, and failing to provide a comprehensive degradation assessment. To address the above issues, this step first obtains a multi-source temperature influence feature set, extracts the temperature affected by instantaneous thermal shock and the temperature affected by local insulation effects, and combines tire material performance parameters (such as the rubber thermal aging rate threshold). If the cumulative instantaneous thermal shock value of a certain area exceeds the short-term thermal aging threshold of the material, and the local insulation effect causes its degradation rate to exceed the overall average level by 1.5 times (such as the tire shoulder area), it is defined as a thermal aging acceleration zone and its coordinates are recorded. Next, a tire pressure anomaly feature set is obtained. Based on local pressure distortion and combined with skeleton material parameters (such as the dynamic fatigue limit of the cord), if a certain area has a dynamic stress ultra-microcrack initiation threshold and a duration exceeding the standard (such as the tread block in the middle), it is defined as a mechanical fatigue hotspot area. Subsequently, the coordinates of the two types of areas are superimposed to identify overlapping areas (such as an overlap ratio of 60%), and time-series data are compared (such as the synchronous increase in stress 1.5 hours after thermal aging) to quantify the coupling level (such as strong coupling). Finally, the area location, coupling relationship, and risk assessment (such as marking strong coupling areas as "high risk") are integrated to generate a coupling anomaly degradation information set.

[0061] The method provided in this embodiment can accurately locate the accelerated thermal aging zone and the hot spot zone of mechanical fatigue in tires, and scientifically couple their spatiotemporal relationship, effectively revealing the interaction mechanism between temperature and pressure anomalies, making subsequent anomaly reports more comprehensive and accurate; at the same time, by establishing spatiotemporal mapping relationship and coupling effect analysis, the real-time and early warning capabilities of degradation risk identification are improved, which helps to prevent early tire failure and extend service life.

[0062] In some embodiments, the local modal stiffness variation caused by the hardening / softening of the rubber compound in the accelerated thermal aging zone is analyzed, and its modulation gain on the dynamic stress amplitude of the mechanical fatigue hot spot is quantified to construct a first energizing channel; the mechanical strain energy dissipated by cyclic deformation in the mechanical fatigue hot spot is analyzed, and its catalytic effect on the microscopic molecular chain breakage reaction rate in the accelerated thermal aging zone is quantified to construct a second energizing channel; based on the first and second energizing channels, the coupling core region that forms a positive feedback loop in the spatiotemporal dimension is identified and defined.

[0063] Local modal stiffness variation can refer to the difference in modal stiffness (resistance to deformation under vibration or stress) between the tire rubber compound and the surrounding normal area caused by hardening or softening due to thermal aging within the accelerated thermal aging zone. This is the core physical quantity affecting the distribution of mechanical stress during thermal aging. Modulation gain can be a coefficient quantifying the influence of "local modal stiffness variation" on the "dynamic stress amplitude of the mechanical fatigue hotspot," and is the core quantitative indicator of the first energizing channel. The first energizing channel can be the "reinforcing effect" channel generated by the accelerated thermal aging zone on the mechanical fatigue hotspot through the path of "rubber compound hardening / softening → local modal stiffness variation → adjustment of dynamic stress amplitude in the mechanical fatigue hotspot," reflecting the active driving mechanism of thermal aging on mechanical fatigue. Mechanical strain energy can be the energy consumed by the skeleton material (such as cord or belt layer) of the mechanical fatigue hotspot during cyclic deformation. This energy is converted into local heat energy or directly acts on the material's molecular structure, and is the key energy source driving accelerated thermal aging. The rate of microscopic molecular chain breakage reaction can be the rate at which the molecular chains of tire rubber or skeleton materials break due to heat and force within the accelerated thermal aging zone. This directly determines the thermal aging process; the faster the rate, the more rapidly the material properties degrade. The catalytic effect can be the accelerating effect of mechanical strain energy on the "microscopic molecular chain breakage reaction rate," meaning the greater the strain energy, the faster the molecular chain breaks, and the more rapid the thermal aging process. This is the core mechanism of the second energizing channel. The second energizing channel can be the "reinforcing effect" channel generated by the mechanical fatigue hotspot zone on the accelerated thermal aging zone through the path of "cyclic deformation → accumulation of mechanical strain energy → increased molecular chain breakage reaction rate in the accelerated thermal aging zone," reflecting the reverse driving mechanism of mechanical fatigue on thermal aging. The coupling core region can be a local area with a significant positive feedback loop within the overlap range of the accelerated thermal aging zone and the mechanical fatigue hotspot zone. This is the "critical trigger point" with the fastest overall tire degradation rate and the highest failure risk.

[0064] Specifically, during the operation of engineering tires, the coupling effect of thermal aging and mechanical fatigue is a key factor leading to failure. However, traditional analysis methods often treat the temperature field and pressure field independently, failing to reveal the dynamic interaction mechanism between the two. For example, in the operation of road rollers or heavy vehicles, the local stiffness changes in the accelerated thermal aging zone due to the hardening or softening of the rubber compound may exacerbate the stress concentration in the mechanical fatigue hot spot. The strain energy generated by mechanical fatigue may catalyze the molecular chain breakage in the thermal aging zone, forming a vicious cycle that exacerbates each other. Traditional methods lack quantitative analysis of this coupling channel, providing only isolated abnormal information, which makes it impossible to identify positive feedback loops, thus missing the risk of accelerated degradation, resulting in delayed early warning or failure of maintenance strategies. To address the above issues, this step first obtains the spatial coordinates of the accelerated thermal aging zone and the rubber compound performance data (such as hardness and elastic modulus). By comparing these with the baseline parameters of fresh rubber compound, the local modal stiffness variation is obtained (e.g., rubber hardening increases stiffness by 12% compared to the baseline value). This data is then substituted into the tire structural mechanics model to simulate the stress distribution under rolling conditions, and the modulation gain is calculated (e.g., a gain of 1.15 is obtained when the stress amplitude increases from 200 MPa to 230 MPa). This constructs the first enabling channel of "thermal aging → stiffness variation → stress amplification." Next, cyclic stress-strain data for the mechanical fatigue hotspot area are obtained. The mechanical strain energy (e.g., 50 J consumed per cycle) was calculated. The catalytic effect (e.g., the molecular chain breakage rate of the experimental group was 1.2 times that of the baseline group) was quantified through a control experiment (the experimental group was subjected to both heat and strain energy, while the baseline group was subjected to only heat energy). A second energizing channel of "mechanical fatigue → strain energy accumulation → accelerated thermal aging" was constructed. Finally, the potential coupling region was obtained by superimposing the ranges of the two channels. The coupling core region was defined and its coordinates and positive feedback cycle period (e.g., the degradation rate increased by 5% every 30 minutes) were recorded by screening according to the positive feedback intensity threshold (e.g., modulation gain × catalytic effect coefficient > 1.3).

[0065] By establishing the spatiotemporal mapping relationship between the thermal aging acceleration zone and the mechanical fatigue hotspot zone and analyzing the coupling effect through the method provided in this embodiment, the positive feedback loop and coupling core area can be accurately identified, revealing the synergistic degradation mechanism of temperature and pressure anomalies, making tire failure risk assessment more accurate and forward-looking. By constructing the first and second empowerment channels, the quantitative analysis of the thermo-mechanical coupling effect is realized, which helps to optimize maintenance strategies and focus intervention measures, extend tire service life and improve the safety of engineering equipment.

[0066] In some embodiments, the coupling core region is characterized as the most dangerous area where the degradation rate of thermal aging and mechanical fatigue is continuously amplified under the interaction; the interaction strength between the first and second energizing channels is quantified, and the spatially distributed thermo-mechanical coupling strength factor is analyzed; the thermo-mechanical coupling strength factor is the equivalent degradation increment contributed by the thermal stress gain and the mechanical aging catalytic effect per unit time; within the spatiotemporal evolution domain of the tire, the strengthening trajectory of the thermo-mechanical coupling strength factor with the increase of the number of rolling passes is tracked, and by setting a dynamic threshold, the final range and danger level of the coupling core region are iteratively converged and locked from the initial thermal aging acceleration zone and mechanical fatigue hotspot zone.

[0067] The thermo-mechanical coupling strength factor can be the equivalent degradation increment contributed by the "thermal stress gain" of the first energizing channel and the "mechanical aging catalytic effect" of the second energizing channel per unit time. It is a core indicator for quantifying the degradation rate of the coupling core area; a larger value indicates faster regional degradation and higher risk. The thermal stress gain can be the increment in the dynamic stress amplitude of the mechanical fatigue hotspot area caused by the local modal stiffness variation due to rubber hardening / softening in the thermal aging acceleration zone of the first energizing channel, which is a direct quantitative result of thermal aging driving mechanical fatigue. The mechanical aging catalytic effect can be the increment in the microscopic molecular chain breakage reaction rate of the thermal aging acceleration zone caused by the mechanical strain energy dissipated by cyclic deformation in the mechanical fatigue hotspot area of ​​the second energizing channel, which is a direct quantitative result of mechanical fatigue driving thermal aging. The equivalent degradation increment can be the range boundary of the coupling core area dynamically changing with "time (increased rolling passes) - space (expansion of degradation area)" during the operation of the engineering tire. It includes the cumulative effect in the time dimension and the diffusion effect in the spatial dimension, and is an analytical framework for tracking the evolution trajectory of the coupling core area.

[0068] Specifically, in the analysis of tire pressure-temperature coupling anomalies in engineering tires, accurately defining the coupling core area is a key link in achieving efficient risk management. However, traditional methods can only identify the thermal aging acceleration zone and the mechanical fatigue hotspot zone, but cannot capture the positive feedback loop formed by their interaction and its spatial evolution. This leads to scattered maintenance strategies and delayed early warnings. For example, in the operation of road rollers or heavy vehicles, the stiffness variation (first energizing channel) caused by the hardening or softening of rubber in the thermal aging acceleration zone will amplify the dynamic stress amplitude of the mechanical fatigue hotspot zone. Meanwhile, the strain energy dissipated by cyclic deformation in the mechanical fatigue hotspot zone (second energizing channel) will catalyze the molecular chain breakage in the thermal aging zone. If this mutually reinforcing cycle is not quantitatively tracked, the highest risk area with an exponentially increasing degradation rate will be missed, thus causing early tire failure or safety accidents. Traditional analysis lacks the spatial distribution assessment of the thermal-mechanical coupling strength and the dynamic definition of its evolution over time. It cannot converge and lock the most dangerous core area from the initial anomaly area, resulting in wasted resources or insufficient protection. To address the above issues, this step first determines the characteristics of the coupling core region, extracts the modulation gain of the first enabling channel (e.g., 1.15) and the catalytic effect coefficient of the second enabling channel (e.g., 1.18), and calculates the interaction strength (e.g., 1.357) using a correlation model. Next, the modulation gain is multiplied by the initial dynamic stress amplitude (e.g., 200 MPa) to obtain the thermally induced stress gain (e.g., 30 MPa), and the catalytic effect coefficient is multiplied by the initial molecular chain breakage rate (e.g., 0.02 times / hour) to obtain the mechano-aging catalytic effect (e.g., 0. The process involves rolling 0.036 times per hour, then converting it into an equivalent degradation increment (e.g., 0.035% per hour) using a material model, which is the thermo-mechanical coupling strength factor. Subsequently, a spatiotemporal evolution domain is constructed with the number of rolling passes (e.g., 1-10 passes) as the time dimension and the tire coordinates as the spatial dimension, and the reinforcement trajectory is fitted (e.g., 0.035 for 1 roll, 0.05 for 3 rolls). Finally, a dynamic threshold is set (e.g., 0.06 for 1 roll, 0.05 for 5 rolls), and the coupling core area is locked through iterative comparison (e.g., a 5cm×8cm area, high risk).

[0069] The method provided in this embodiment can accurately identify and define the coupling core area that forms a positive feedback loop in the tire, scientifically reveal the degradation mechanism of mutual aggravation of thermal aging and mechanical fatigue, and make the failure risk assessment more targeted and forward-looking. By generating a thermo-mechanical coupling strength factor and tracking its reinforcement trajectory, dynamic monitoring and quantitative analysis of the coupling degradation process are realized, which helps to take targeted maintenance measures in a timely manner.

[0070] In some embodiments, the final extent and hazard level of the coupled core area are compared with the tire material performance parameters to generate a risk level classification for each region of the tire; historical working load data are integrated to predict the damage evolution of the coupled core area within a predetermined working cycle, generating an estimated remaining service life of the critical area; based on the risk level classification and the estimated remaining service life, a tire pressure-temperature coupling anomaly report is generated, which includes graded early warning information, maintenance priority suggestions, and targeted operation guidance.

[0071] The remaining service life estimate can be the remaining working time or number of operations (such as 50 remaining compaction passes or 15 remaining service life) of the coupled core area from its current state until it can no longer meet the usage requirements (material performance drops to a critical value). It is a core indicator for planning maintenance timing.

[0072] Specifically, in the analysis of tire pressure-temperature coupling anomalies in engineering tires, generating a comprehensive and accurate anomaly report is the final step in achieving risk management and maintenance decisions. However, traditional report generation methods are often based on single-dimensional data or static analysis, which cannot integrate coupled degradation information, material properties, and historical loads. This results in one-sided report content, untimely warnings, or maintenance recommendations that lack specificity. For example, in the operation of road rollers or heavy vehicles, even if the coupling core area and hazard level are identified through the aforementioned examples, without combining tire material performance parameters (such as the resistance of rubber hardness to thermal aging) and historical working load data (such as the impact of past pressure fluctuations on fatigue accumulation), it is impossible to scientifically classify risk levels, predict damage evolution, or estimate remaining lifespan. This may lead to missed detection of high-risk areas, misjudgment of maintenance timing, or provision of ineffective operational guidance, resulting in sudden tire failure or waste of resources. To address the above issues, this step first retrieves the final range of the coupling core area (e.g., the three tread blocks in the middle of the tire, 5cm×8cm) and its hazard level (extremely high risk). Combined with tire material performance parameters (e.g., rubber thermal aging limit of 120℃), and compared with the current state of the core area (e.g., rubber temperature of 115℃), the risk level of the entire tire is classified (e.g., the tire shoulder area is medium risk), and a risk map is drawn. Next, based on historical working load data (e.g., average rolling load of 10t over the past 30 days, degradation rate of 0.02% / pass), the damage evolution within a predetermined period (e.g., 100 rolling passes) is simulated to obtain an estimated remaining service life (e.g., 15 days / 50 rolling passes). Finally, the graded early warning (extremely high risk → red warning), maintenance priority (maintenance within 24 hours), and operational guidance (e.g., removing 5mm of degraded rubber, replacing with rubber resistant to 130℃) are integrated to generate a multi-module tire pressure-temperature coupling anomaly report.

[0073] The method provided in this embodiment enables the scientific integration and coupling of degradation information, material properties, and historical loads, achieving precise risk level classification and dynamic prediction of remaining life, making the report comprehensive, accurate, and forward-looking. By providing tiered early warning information, maintenance priority suggestions, and targeted operational guidance, the operability and decision support capabilities of the report are enhanced.

[0074] Figure 3 A schematic diagram of a tire pressure-temperature coupled anomaly analysis system for engineering tires, provided in an embodiment of this application, is shown below. Figure 3 As shown, a tire pressure-temperature coupling anomaly analysis system 300 for engineering tires in this embodiment includes: a temperature analysis module 301, a tire pressure analysis module 302, a coupling analysis module 303, and a report generation module 304;

[0075] Temperature analysis module 301 is used to acquire a multi-source temperature dataset, and based on the multi-source temperature dataset, analyze the superposition effect of the basic temperature field and the continuous heat source of asphalt to generate a multi-source temperature influence feature set; tire pressure analysis module 302 is used to acquire a basic tire pressure dataset, and based on the basic tire pressure dataset and the multi-source temperature influence feature set, identify the abnormal fluctuation trend of the overall tire pressure and local pressure distortion, and generate a tire pressure anomaly feature set; coupling analysis module 303 is used to locate and couple the thermal aging acceleration zone and mechanical fatigue hot spot zone of the tire based on the multi-source temperature influence feature set and the tire pressure anomaly feature set, and generate a coupled abnormal degradation information set; report generation module 304 is used to perform fusion analysis based on the coupled abnormal degradation information set, combined with tire material performance parameters and historical working load data, to generate a tire pressure-temperature coupled anomaly report.

[0076] Optionally, when the temperature analysis module 301 analyzes the superposition of the base temperature field and the continuous heat source of asphalt based on the multi-source temperature dataset to generate a multi-source temperature influence feature set, it is specifically used for: the multi-source temperature dataset including a base temperature field dataset and asphalt temperature field data, wherein the base temperature field dataset includes ambient temperature, tire internal temperature, and road surface temperature; based on the asphalt temperature field dataset, analyzing the instantaneous thermal shock caused by high-temperature asphalt to the tire tread when the tire rolls over fresh asphalt, generating an instantaneous thermal shock influence temperature; analyzing the insulation effect formed locally in the tire due to the poor thermal conductivity of asphalt after it is embedded in the tire tread, generating a local insulation effect influence temperature; and generating the multi-source temperature influence feature set based on the instantaneous thermal shock influence temperature and the local insulation effect influence temperature.

[0077] Optionally, when the temperature analysis module 301 generates an instantaneous thermal shock effect temperature based on the instantaneous thermal shock caused by the high-temperature asphalt to the tire tread when the tire rolls over fresh asphalt, it specifically performs the following: Establishing a dynamic thermal contact model of the asphalt-tire interface, wherein the dynamic thermal contact model determines a time-varying equivalent thermal contact coefficient based on the viscoelastic state of the asphalt, the geometry of the tire tread, and the rolling speed of the tire; analyzing the dynamic heat flux density distribution of the tire tread during the contact period based on the equivalent thermal contact coefficient and the instantaneous temperature difference between the asphalt and the tire; identifying each independent contact event between the roller and the high-temperature asphalt pavement within a continuous working cycle based on the roller's working path and the number of compaction passes; performing a double integration of the dynamic heat flux density distribution in the contact time domain and the tire tread spatial domain to generate an instantaneous thermal shock accumulation factor characterizing the intensity of the single thermal shock generated by each independent contact event; and summing multiple instantaneous thermal shock accumulation factors generated by consecutive independent contact events based on the identified independent contact events to generate the instantaneous thermal shock effect temperature used to evaluate periodic thermal fatigue.

[0078] Optionally, when the temperature analysis module 301 generates a temperature effect influenced by the local insulation effect of asphalt embedded in the tire tread due to the poor thermal conductivity of asphalt, it is specifically used to: construct an asphalt filling model of the tire tread; based on the asphalt filling model, identify the tread area substantially covered and filled by asphalt and define it as a heat-shielding zone; analyze the effective heat dissipation area reduction coefficient of the heat-shielding zone relative to the exposed surface of the tire, and establish an equivalent additional thermal resistance model of the heat-shielding zone in combination with the thermal conductivity of asphalt material; based on the equivalent additional thermal resistance model and the convective heat dissipation field of the tire as a whole, analyze the real-time heat accumulation rate caused by the obstruction of the heat dissipation path in the heat-shielding zone; integrate the real-time heat accumulation rate over the tire's working time domain to generate the temperature effect influenced by the local insulation effect, which characterizes the historical total heat accumulation in the heat-shielding zone.

[0079] Optionally, the tire pressure analysis module 302 is specifically used for: reconstructing the non-uniform temperature field of the gas inside the tire based on the basic tire pressure dataset and the multi-source temperature influence feature set, and calculating and generating a quasi-static pressure field of the tire driven by the temperature field according to the ideal gas law; analyzing the pressure homogenization effect of the internal gas due to forced convection during tire rolling, establishing a dynamic balance relationship between the quasi-static pressure field and the overall measured tire pressure, so as to identify the periodic fluctuation trend of the overall tire pressure and the degree of thermal deviation of the basic tire pressure dominated by the temperature affected by the local heat insulation effect; in the quasi-static pressure field, eliminating the influence of the pressure homogenization effect, identifying the residual pressure peaks that are spatially locked below the heat shielding area and cannot be effectively homogenized, defining them as local pressure distortion; and constructing the tire pressure anomaly feature set according to the periodic fluctuation trend, the degree of thermal deviation of the basic tire pressure and the local pressure distortion.

[0080] Optionally, when the coupling analysis module 303 locates and couples the thermal aging acceleration zone and the mechanical fatigue hotspot zone of the tire based on the multi-source temperature influence feature set and the tire pressure anomaly feature set to generate a coupled abnormal degradation information set, it is specifically used for: locating, based on the multi-source temperature influence feature set, areas where the material performance degradation rate exceeds the average level due to the continuous superposition of the instantaneous thermal shock influence temperature and the local insulation effect influence temperature, defining these as thermal aging acceleration zones; locating, based on the tire pressure anomaly feature set, areas where the dynamic stress concentration and the risk of microcrack initiation in the tire skeleton material significantly increase due to the continuous effect of the local pressure distortion, defining these as mechanical fatigue hotspot zones; establishing a spatiotemporal mapping relationship between the thermal aging acceleration zone and the mechanical fatigue hotspot zone, and analyzing the coupling effect between the two in spatial overlap and temporal evolution; and generating the coupled abnormal degradation information set to characterize the overall degradation state and failure risk of the tire based on the spatiotemporal mapping relationship and coupling effect.

[0081] Optionally, when establishing the spatiotemporal mapping relationship between the accelerated thermal aging zone and the mechanical fatigue hotspot zone, and analyzing their coupling effects in spatial overlap and temporal evolution, the coupling analysis module 303 is specifically used for: analyzing the local modal stiffness variation in the accelerated thermal aging zone caused by the hardening / softening of the rubber compound, quantifying its modulation gain on the dynamic stress amplitude of the mechanical fatigue hotspot zone, and constructing a first energizing channel; analyzing the mechanical strain energy dissipated by the mechanical fatigue hotspot zone due to cyclic deformation, quantifying its catalytic effect on the microscopic molecular chain breakage reaction rate of the accelerated thermal aging zone, and constructing a second energizing channel; and identifying and defining the coupling core region that forms a positive feedback loop in the spatiotemporal dimension based on the first energizing channel and the second energizing channel.

[0082] Optionally, when the coupling analysis module 303 identifies and defines the coupling core region forming a positive feedback loop in the spatiotemporal dimension based on the first empowerment channel and the second empowerment channel, it is specifically used for: the coupling core region being characterized as the most dangerous area where the degradation rate of thermal aging and mechanical fatigue is continuously amplified under the interaction; quantifying the interaction strength between the first empowerment channel and the second empowerment channel, and analyzing and generating a spatially distributed thermo-mechanical coupling strength factor; the thermo-mechanical coupling strength factor being the equivalent degradation increment jointly contributed by the thermal stress gain and the mechanical aging catalytic effect per unit time; within the spatiotemporal evolution domain of the tire, tracking the strengthening trajectory of the thermo-mechanical coupling strength factor as the number of rolling passes increases, and iteratively converging and locking the final range and danger level of the coupling core region from the initial thermal aging acceleration zone and the mechanical fatigue hotspot zone by setting a dynamic threshold.

[0083] Optionally, the report generation module 304 is specifically used to: compare the final range and hazard level of the coupling core area with the tire material performance parameters to generate a risk level classification for each region of the tire; integrate the historical working load data to predict the damage evolution of the coupling core area within a predetermined working cycle and generate an estimated remaining service life of the key area; and based on the risk level classification and the estimated remaining service life, generate a tire pressure-temperature coupling anomaly report containing graded early warning information, maintenance priority suggestions, and targeted operation guidance.

[0084] The system in this embodiment can be used to execute the methods of any of the above embodiments, and its implementation principle and technical effect are similar, so they will not be described again here.

Claims

1. A method for analyzing tire pressure-temperature coupled anomalies in engineering tires, characterized in that, include: A multi-source temperature dataset is obtained. Based on the multi-source temperature dataset, the superposition effect of the basic temperature field and the continuous heat source of asphalt is analyzed to generate a multi-source temperature influence feature set. Obtain a baseline tire pressure dataset. Based on the baseline tire pressure dataset and the multi-source temperature influence feature set, identify the abnormal fluctuation trend of the overall tire pressure and local pressure distortion, and generate a tire pressure anomaly feature set. Based on the multi-source temperature influence feature set and the tire pressure anomaly feature set, the thermal aging acceleration zone and mechanical fatigue hot spot zone of the tire are located and coupled to generate a coupled abnormal degradation information set. Based on the aforementioned set of coupled abnormal degradation information, a tire pressure-temperature coupled abnormality report is generated by combining tire material performance parameters with historical working load data for fusion analysis.

2. The method according to claim 1, characterized in that, Based on the multi-source temperature dataset, the superposition effect of the base temperature field and the persistent heat source of asphalt is analyzed to generate a multi-source temperature influence feature set, including: The multi-source temperature dataset includes a basic temperature field dataset and asphalt temperature field data, wherein the basic temperature field dataset includes ambient temperature, tire temperature and pavement temperature. Based on the asphalt temperature field dataset, the instantaneous thermal shock caused by high-temperature asphalt to the tire tread when the tire rolls over fresh asphalt is analyzed, and the instantaneous thermal shock effect temperature is generated. Analysis of the local heat insulation effect formed in the tire after asphalt is embedded in the tire tread, due to the poor thermal conductivity of asphalt, shows that the local heat insulation effect affects the temperature. Based on the temperature affected by the instantaneous thermal shock and the temperature affected by the local heat preservation effect, the multi-source temperature influence feature set is generated.

3. The method according to claim 2, characterized in that, The analysis describes the instantaneous thermal shock caused by the high-temperature asphalt to the tire tread when the tire rolls over fresh asphalt, and the resulting instantaneous thermal shock affects the temperature, including: A dynamic thermal contact model for the asphalt-tire interface is established, wherein the dynamic thermal contact model is based on the viscoelastic state of asphalt, the geometry of the tire tread, and the rolling speed of the tire to determine the time-varying equivalent thermal contact coefficient. Based on the equivalent thermal contact coefficient and the instantaneous temperature difference between asphalt and tire, the dynamic heat flux density distribution of the tire tread during the contact period is analyzed. Based on the working path and number of compaction passes of the road roller, the independent contact events between the roller and the high-temperature asphalt pavement during the continuous working cycle were identified. The dynamic heat flux density distribution is double-integrated in the contact time domain and the tire tread space domain to generate an instantaneous thermal shock accumulation factor characterizing the intensity of a single thermal shock generated by each independent contact event. Based on the identified independent contact events, the cumulative factors of the instantaneous thermal shock generated by the consecutive independent contact events are summed to generate the instantaneous thermal shock effect temperature for evaluating periodic thermal fatigue.

4. The method according to claim 3, characterized in that, The analysis describes the localized heat insulation effect formed in the tire after asphalt is embedded in the tire tread, due to the poor thermal conductivity of asphalt. This localized heat insulation effect affects the temperature, including: Construct an asphalt filling model of tire tread, and based on the asphalt filling model, identify the tread area that is substantially covered and filled by asphalt, and define it as the heat shielding area; The effective heat dissipation area reduction factor of the heat shielding zone relative to the exposed surface of the tire is analyzed, and an equivalent additional thermal resistance model of the heat shielding zone is established in combination with the thermal conductivity of asphalt material. Based on the equivalent additional thermal resistance model and the overall convective heat dissipation field of the tire, the real-time heat accumulation rate caused by the obstruction of the heat dissipation path in the heat shielding area is analyzed. The real-time heat accumulation rate is integrated over the tire's operating time domain to generate the local insulation effect temperature, which characterizes the historical total heat accumulation in the heat-shielding area.

5. The method according to claim 4, characterized in that, Based on the basic tire pressure dataset and the multi-source temperature influence feature set, the abnormal fluctuation trend of the overall tire pressure and local pressure distortion are identified, and a tire pressure anomaly feature set is generated, including: Based on the basic tire pressure dataset and the multi-source temperature influence feature set, the non-uniform temperature field of the gas inside the tire is reconstructed, and the quasi-static pressure field of the tire driven by the temperature field is calculated and generated according to the ideal gas law. The pressure homogenization effect of internal gas due to forced convection during tire rolling is analyzed, and the dynamic balance relationship between the quasi-static pressure field and the overall measured tire pressure is established to identify the periodic fluctuation trend of the overall tire pressure and the degree of thermal deviation of the base tire pressure, which is dominated by the temperature affected by the local heat preservation effect. In the quasi-static pressure field, the influence of the pressure homogenization effect is eliminated, and the residual pressure peak that is spatially locked below the heat shielding area and cannot be effectively homogenized is identified and defined as local pressure distortion. Based on the periodic fluctuation trend, the degree of thermal deviation of the baseline tire pressure, and the local pressure distortion, the tire pressure abnormality feature set is constructed.

6. The method according to claim 5, characterized in that, Based on the multi-source temperature influence feature set and the tire pressure anomaly feature set, the tire's thermal aging acceleration zone and mechanical fatigue hotspot zone are located and coupled to generate a coupled abnormal degradation information set, including: Based on the multi-source temperature influence feature set, the region where the material performance degradation rate exceeds the average level due to the continuous superposition of the temperature affected by the instantaneous thermal shock and the temperature affected by the local heat preservation effect is located and defined as the thermal aging acceleration zone. Based on the aforementioned abnormal tire pressure feature set, the region where dynamic stress concentration and the risk of microcrack initiation in the tire skeleton material are significantly increased due to the continuous effect of the local pressure distortion is located, and this region is defined as a mechanical fatigue hotspot. Establish the spatiotemporal mapping relationship between the thermal aging acceleration zone and the mechanical fatigue hot spot zone, and analyze the coupling effect between the two in terms of spatial overlap and temporal evolution; Based on the spatiotemporal mapping relationship and coupling effect, a set of coupled abnormal degradation information is generated to characterize the overall degradation state and failure risk of tires.

7. The method according to claim 6, characterized in that, The process of establishing a spatiotemporal mapping relationship between the accelerated thermal aging region and the mechanical fatigue hotspot region, and analyzing their coupling effects in spatial overlap and temporal evolution, includes: The local modal stiffness variation caused by the hardening / softening of the rubber in the accelerated thermal aging zone is analyzed, and its modulation gain on the dynamic stress amplitude of the mechanical fatigue hot spot is quantified to construct the first energy channel. The mechanical strain energy dissipated by cyclic deformation in the mechanical fatigue hotspot is analyzed, and its catalytic effect on the microscopic molecular chain breakage reaction rate in the thermal aging accelerated zone is quantified to construct a second energy-enabling channel. Based on the first and second empowerment channels, the coupling core area that forms a positive feedback loop in the spatiotemporal dimension is identified and defined.

8. The method according to claim 7, characterized in that, The process of identifying and defining the coupling core region that forms a positive feedback loop in the spatiotemporal dimension based on the first and second empowerment channels includes: The coupled core region is characterized as the most dangerous area where the degradation rate of thermal aging and mechanical fatigue is continuously amplified under the interaction. The interaction strength between the first and second empowerment channels is quantified, and the thermal-mechanical coupling strength factor of the spatial distribution is analyzed. The thermo-mechanical coupling strength factor is the equivalent degradation increment contributed by the thermo-induced stress gain and the mechanical aging catalytic effect per unit time. Within the spatiotemporal evolution domain of the tire, the strengthening trajectory of the thermo-mechanical coupling strength factor as the number of rolling passes increases is tracked, and by setting a dynamic threshold, the final range and danger level of the coupling core area are iteratively converged and locked from the initial thermal aging acceleration zone and the mechanical fatigue hot spot zone.

9. The method according to claim 8, characterized in that, The tire pressure-temperature coupling anomaly report is generated by fusing and analyzing the coupled anomaly information set with tire material performance parameters and historical working load data, including: The final range and hazard level of the coupling core area are compared with the tire material performance parameters to generate a risk level classification for each region of the tire. By integrating the historical workload data, the damage evolution of the coupled core area within a predetermined working cycle is predicted, and an estimated remaining service life of the key area is generated. Based on the risk level classification and the estimated remaining service life, a tire pressure-temperature coupling anomaly report is generated, which includes graded early warning information, maintenance priority suggestions, and targeted operation guidance.

10. A tire pressure-temperature coupled anomaly analysis system for engineering tires, characterized in that, The method applied to any one of claims 1-9 includes: The temperature analysis module is used to acquire a multi-source temperature dataset, and based on the multi-source temperature dataset, analyze the superposition effect of the basic temperature field and the continuous heat source of asphalt to generate a multi-source temperature influence feature set. The tire pressure analysis module is used to acquire a basic tire pressure dataset, and based on the basic tire pressure dataset and the multi-source temperature influence feature set, to identify the abnormal fluctuation trend of the overall tire pressure and local pressure distortion, and generate a tire pressure abnormality feature set. The coupling analysis module is used to locate and couple the thermal aging acceleration zone and mechanical fatigue hot spot zone of the tire based on the multi-source temperature influence feature set and the tire pressure anomaly feature set, and generate a coupled abnormal degradation information set. The report generation module is used to generate a tire pressure-temperature coupling anomaly report by combining the coupling anomaly degradation information set with tire material performance parameters and historical working load data for fusion analysis.

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