Road traffic protection facility durability optimization method based on digital twinning

Abstract

A road traffic protection facility durability optimization method based on digital twinning relates to the field of electrical digital data processing, and comprises the following steps: standardizing environmental parameters, then carrying out weighted calculation on the environmental parameters and a damage contribution degree coefficient to obtain an environmental stress degree, analyzing environmental stress degree time sequence change characteristics to determine a migration path and an accumulation area, and calculating the environmental stress degree according to the migration path and the accumulation area; differentiated protection grades are divided based on stress intensity distribution of the accumulation area, and coating parameters are determined by adopting a numerical simulation method. By implementing the method, the service life of the road traffic protection facility can be prolonged.

Description

Technical Field

[0001] This application relates to the field of electronic digital data processing, and particularly to a method for optimizing the durability of highway traffic protection facilities based on digital twins. Background Art

[0002] With the rapid development of China's transportation infrastructure construction, highway traffic protection facilities play an increasingly important role in ensuring driving safety. These facilities need to be exposed to complex and variable natural environments for a long time, facing various environmental factors such as temperature, humidity, wind speed, and precipitation. Their durability is directly related to road operation safety and maintenance costs.

[0003] Currently, the anti-corrosion protection of highway traffic protection facilities mainly adopts anti-corrosion coatings with unified standards for treatment. This method coats an anti-corrosion coating with a certain thickness on the surface of the facilities and constructs it according to a fixed coating formula ratio in order to achieve the purpose of anti-corrosion and extending the service life.

[0004] However, due to the differences in geographical environment and meteorological conditions, the unified standard anti-corrosion treatment plan is difficult to meet the differentiated protection requirements brought by different regional environmental factors. Especially in areas with drastic changes in environmental conditions, the local performance of the anti-corrosion coating is prone to degradation, resulting in a significant reduction in the service life of the protection facilities and increasing the maintenance and replacement costs. Summary of the Invention

[0005] This application provides a method for optimizing the durability of highway traffic protection facilities based on digital twins, which is used to improve the service life of highway traffic protection facilities.

[0006] In a first aspect, this application provides a method for optimizing the durability of highway traffic protection facilities based on digital twins, which is applied to a durability optimization system for highway traffic protection facilities. The method includes: Obtaining real-time data of environmental parameters through multiple monitoring points. The real-time data of environmental parameters includes temperature, humidity, wind speed, and precipitation; calculating the environmental parameter gradient value between the monitoring points, and calculating the environmental stress degree according to the real-time data of environmental parameters. The environmental stress degree is obtained by weighted calculation of the standardized environmental parameters and their corresponding damage contribution coefficients, and the damage contribution coefficients are determined based on statistical analysis of historical damage data; analyzing the time-series change characteristics of the environmental stress degree of each adjacent monitoring point to determine the migration path and accumulation area of environmental stress. The time-series change characteristics of the environmental stress degree include the stress intensity change rate, migration speed, and accumulation duration; dividing the differentiated protection levels of the anti-corrosion coatings on the highway traffic protection facilities based on the stress intensity distribution in the accumulation area; determining the anti-corrosion coating thickness parameters and component ratio parameters in different protection level areas by using numerical simulation methods, and sending the anti-corrosion coating thickness parameters and the component ratio parameters to the target client.

[0007] In the above embodiments, after standardizing the environmental parameters, they are weighted and calculated with the damage contribution coefficient to obtain the environmental stress degree. The migration path and the accumulation area are determined by analyzing the temporal variation characteristics of the environmental stress degree. The differential protection levels are divided based on the stress intensity distribution in the accumulation area. The coating parameters are determined by using the numerical simulation method, forming a complete set of optimization processes for protection parameters, achieving the precise matching of the performance of the protective coating and the maximization of resource utilization, effectively extending the service life of the protection facilities, and reducing the maintenance cost.

[0008] Combined with some embodiments of the first aspect, in some embodiments, the steps of calculating the environmental parameter gradient value between the monitoring points and calculating the environmental stress degree according to the real-time data of the environmental parameters specifically include: calculating the environmental parameter gradient value of the real-time data of the environmental parameters between adjacent monitoring points; calculating the standardized environmental parameters according to the historical maximum and minimum values corresponding to the real-time data of the environmental parameters; extracting the corresponding relationship between each environmental parameter and the damage records of the protection facilities from the historical damage database, and obtaining the damage contribution coefficient of each environmental parameter based on the damage frequency statistics; multiplying the standardized environmental parameters by the corresponding damage contribution coefficients and summing them to obtain the environmental stress degree.

[0009] In the above embodiments, calculating the environmental parameter gradient value reflects the spatial variation characteristics of environmental factors. Using the historical maximum and minimum values for standardization eliminates the influence of dimensions. Obtaining the damage contribution coefficient based on the damage frequency statistics reflects the actual influence degree of each environmental factor. Combining the standardized parameters with the contribution coefficient to calculate the environmental stress degree establishes a quantitative evaluation model of environmental impact, improving the accuracy and reliability of the calculation of the environmental stress degree.

[0010] Combined with some embodiments of the first aspect, in some embodiments, the steps of dividing the differential protection levels of the anti-corrosion coating on the highway traffic protection facilities based on the stress intensity distribution in the accumulation area specifically include: calculating the average value and the coefficient of variation of the environmental stress degree at each point in the accumulation area; dividing the accumulation area into different stress intensity sub-areas according to the magnitude relationship of the average values of the environmental stress degree; analyzing the coefficient of variation of the environmental stress degree in each stress intensity sub-area, and merging the adjacent sub-areas with the coefficient of variation of the environmental stress degree within the same range to obtain the merged sub-areas; dividing the anti-corrosion coating of the highway traffic protection facilities into different protection level areas according to the distribution of the merged sub-areas.

[0011] In the above embodiments, calculating the average value and coefficient of variation of the environmental stress degree characterizes the overall level and fluctuation characteristics of the stress intensity. Dividing the stress intensity sub-regions according to the size of the average value realizes the preliminary zoning. Analyzing the coefficient of variation and merging similar sub-regions optimize the zoning results. The anti-corrosion coating is divided into different protection level regions, constructing a scientific and reasonable differential protection zoning system, and improving the pertinence and economy of the protection scheme.

[0012] Combined with some embodiments of the first aspect, in some embodiments, the steps of using the numerical simulation method to determine the anti-corrosion coating thickness parameters and component ratio parameters of different protection level regions specifically include: obtaining the environmental stress degree of different protection level regions and the service life requirements of the highway traffic protection facilities; calculating the coating corrosion rate of each protection level region according to the environmental stress degree; based on the coating corrosion rate and the service life requirements, calculating the anti-corrosion coating thickness parameters required for each protection level region; and determining the component ratio parameters according to the anti-corrosion coating thickness parameters.

[0013] In the above embodiments, calculating the coating corrosion rate based on the environmental stress degree reveals the loss law of the environment on the coating. Determining the anti-corrosion coating thickness parameters in combination with the service life requirements reflects the performance guarantee requirements during the service period. Optimizing the component ratio according to the coating thickness parameters ensures the matching of material properties, realizes the precise control of the protection performance and service life, and improves the coating protection effect.

[0014] Combined with some embodiments of the first aspect, in some embodiments, after the step of sending the anti-corrosion coating thickness parameters and the component ratio parameters to the target client, the method further includes: obtaining the terrain data and water system data of the area where the highway traffic protection facilities are located; calculating the surface runoff channels based on the terrain data, and calculating the pollutant migration paths based on the water system data and the surface runoff channels; calculating the pollutant cumulative concentration along the pollutant migration paths, converting the pollutant cumulative concentration into an environmental stress degree increment, and superimposing the environmental stress degree increment with the environmental stress degree to obtain the regional stress degree; dividing the protection level zoning according to the regional stress degree, calculating the coating technical parameters of the protection level zoning and sending them to the target client.

[0015] In the above embodiments, calculating the surface runoff channels using the terrain data and water system data reflects the characteristics of water flow movement. Determining the pollutant migration paths based on the runoff channels reflects the propagation law of environmental factors. Converting the pollutant cumulative concentration into an environmental stress degree increment and superimposing it to obtain the regional stress degree constructs a complete environmental impact propagation and evolution model, accurately predicting the dynamic changes of the environmental pressure on the protection facilities.

[0016] In some embodiments in combination with some embodiments of the first aspect, after the step of sending the anti-corrosion coating thickness parameter and the composition ratio parameter to the target client, the method further includes: receiving meteorological forecast data, and calculating a predicted environmental stress degree based on the meteorological forecast data; comparing the predicted environmental stress degree with the environmental stress degree to obtain a stress degree trend chart, and determining the boundary of the protection zone according to the stress degree trend chart; calculating the coating technical parameters within the boundary of the protection zone, and sending the coating technical parameters to the target client.

[0017] In the above embodiments, receiving meteorological forecast data to calculate the predicted environmental stress degree reflects the future environmental change trend, comparing and analyzing to obtain the stress degree trend chart shows the evolution law of environmental pressure, determining the boundary of the protection zone according to the trend chart and calculating the coating technical parameters, forming an active protection mechanism based on environmental prediction, and enhancing the adaptability and forward-looking of the protection scheme to environmental changes.

[0018] In some embodiments in combination with some embodiments of the first aspect, after the step of sending the anti-corrosion coating thickness parameter and the composition ratio parameter to the target client, the method further includes: extracting the usage environment data of the highway traffic protection facilities, and calculating the material fatigue index of the highway traffic protection facilities according to the usage environment data; analyzing the accelerating effect of environmental stress on material fatigue, and predicting the remaining service life of the highway traffic protection facilities according to the material fatigue index and the accelerating effect; determining the maintenance time window of the highway traffic protection facilities based on the remaining service life, and dividing the maintenance priority levels of the highway traffic protection facilities.

[0019] In the above embodiments, calculating the material fatigue index according to the usage environment data reflects the performance degradation state of the protection facilities, analyzing the accelerating effect of environmental stress on material fatigue reveals the influence mechanism of environmental factors, predicting the remaining service life based on the fatigue index and the accelerating effect, determining the maintenance time window and dividing the maintenance priority levels, optimizing the maintenance resource allocation, and ensuring the service performance of the protection facilities.

[0020] In a second aspect, an embodiment of the present application provides a durability optimization system for highway traffic protection facilities. The durability optimization system for highway traffic protection facilities includes: one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the durability optimization system for highway traffic protection facilities to execute the method described in the first aspect and any possible implementation manner in the first aspect.

[0021] In a third aspect, an embodiment of the present application provides a computer program product containing instructions. When the computer program product runs on the durability optimization system for highway traffic protection facilities, it causes the durability optimization system for highway traffic protection facilities to execute the method described in the first aspect and any possible implementation manner in the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium including instructions. When the instructions run on the durability optimization system for highway traffic protection facilities, it causes the durability optimization system for highway traffic protection facilities to execute the method described in the first aspect and any possible implementation manner in the first aspect.

[0023] It can be understood that the durability optimization system for highway traffic protection facilities provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the method provided in the embodiments of the present application. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method, which will not be elaborated here.

[0024] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. In the present application, by standardizing environmental parameters and performing weighted calculation with the damage contribution coefficient to obtain the environmental stress degree, analyzing the temporal variation characteristics of the environmental stress degree to determine the migration path and accumulation area, dividing different protection levels based on the stress intensity distribution in the accumulation area, and using numerical simulation methods to determine the coating parameters, a complete set of protection parameter optimization processes is formed, realizing the precise matching of the performance of the protective coating and the maximization of resource utilization, effectively extending the service life of the protection facilities and reducing the maintenance cost.

[0025] 2. In the present application, by calculating the environmental parameter gradient value, the spatial variation characteristics of environmental factors are reflected. Standardization processing using historical maximum and minimum values eliminates the influence of dimensions. The damage contribution coefficient obtained based on damage frequency statistics reflects the actual influence degree of each environmental factor. Combining the standardized parameters with the contribution coefficient to calculate the environmental stress degree, a quantitative evaluation model of environmental impact is established, improving the accuracy and reliability of environmental stress degree calculation.

[0026] 3. In the present application, by calculating the surface runoff channels using terrain data and water system data, the characteristics of water flow movement are reflected. Determining the pollutant migration path based on the runoff channels reflects the propagation law of environmental factors. Converting the pollutant cumulative concentration into an increment of environmental stress degree and superimposing it to obtain the regional stress degree, a complete environmental impact propagation and evolution model is constructed, accurately predicting the dynamic changes of the environmental pressure on the protection facilities. Description of the Drawings

[0027] Figure 1It is a schematic flowchart of a method for optimizing the durability of highway traffic protection facilities based on digital twin in an embodiment of the present application; Figure 2 It is another schematic flowchart of a method for optimizing the durability of highway traffic protection facilities based on digital twin in an embodiment of the present application; Figure 3 It is a schematic structural diagram of an entity device of a durability optimization system for highway traffic protection facilities in an embodiment of the present application. Detailed implementation manners

[0028] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. As used in the specification of the present application, the singular forms "a", "an", "the above", "the", and "this" are also intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations including one or more of the listed items.

[0029] Hereinafter, the terms "first" and "second" are only used for descriptive purposes, and cannot be construed as implying or indicating relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the embodiments of the present application, unless otherwise specified, the meaning of "a plurality" is two or more.

[0030] For ease of understanding, the application scenarios of the embodiments of the present application are introduced below.

[0031] A certain expressway is 120 kilometers long and spans three terrain regions: mountains, plains, and coastal areas. Among them, the mountainous section has frequent rain and fog, with an average annual precipitation of 1500 mm and a relative humidity of 85%; the plain section has relatively high temperatures, with an average annual temperature of 25 °C and a daily temperature difference of 15 °C; the coastal section has a high salt ion concentration and an average annual wind speed of 6 m / s. More than 3000 sets of guardrails are installed throughout the line, and a protection scheme of hot-dip galvanizing + anti-corrosion coating is adopted. During operation, it is found that the coating in the mountainous section often cracks and peels off, the coating surface in the plain section is severely powdered, and the bottom of the coastal section is significantly rusted. On-site inspections show that pitting corrosion has occurred on the base metal at the cracked part of the coating in the mountainous section, with a depth of 1.2 mm; the coating thickness loss in the plain section exceeds 45%; the rusted area in the coastal section accounts for more than 30% of the surface area. These local performance degradations have significantly shortened the service life of the protection facilities, and the average life is only 65% of the designed life. At the same time, due to the scattered damage locations, the maintenance and replacement costs are high, and the average annual maintenance cost exceeds 2 million yuan. This reflects that a unified standard anti-corrosion scheme is difficult to adapt to the environmental characteristics of different regions.

[0032] Existing technology employs an anti-corrosion coating with a fixed formulation and thickness applied to protective structures. For example, the guardrails on a certain highway are coated with a three-layer coating system consisting of an epoxy zinc-rich primer (80μm), an epoxy micaceous iron midcoat (120μm), and a polyurethane topcoat (50μm), for a total coating thickness of 250μm. The primer contains 75% zinc powder, the midcoat contains 35% iron mica, and the topcoat contains 60% polyurethane resin. Application is carried out according to standardized spraying procedures: surface rust removal grade Sa2.5, a single coat of primer, two coats of midcoat, and a single coat of topcoat, with a 24-hour interval between each coat. However, in actual use, the rainy environment in mountainous areas weakens the adhesion between the coating and the substrate, causing cracking; the high temperature in plains accelerates resin aging and causes coating powdering; and chloride ions in marine environments penetrate the coating and reach the substrate, causing corrosion. Because these environmental differences are not considered, the standardized coating system exhibits different failure modes in different regions and cannot be optimized based on environmental characteristics, resulting in suboptimal protection.

[0033] Following this proposed solution, environmental monitoring stations were first installed every 2 kilometers along the highway to collect real-time data on temperature, humidity, wind speed, and precipitation. Calculations revealed that environmental stress levels in mountainous areas increased by 50% during the rainy season, migrating at a rate of 3 km / day. Stress levels in plain areas fluctuated significantly during the day and night, peaking at 2 p.m. Coastal areas exhibited a decreasing stress gradient from sea to land, with the accumulation zone primarily located within 0.5 meters of the bottom of the guardrail. Based on these characteristics, the system divided the protective facilities into five protection levels, each receiving a different coating formulation: increasing the curing agent content in mountainous areas to improve crosslinking density; adding an anti-aging agent to improve thermal stability in plain areas; and increasing the zinc powder content in coastal areas to enhance cathodic protection. Coating thickness was also adjusted accordingly: increasing to 350μm in mountainous areas, maintaining 250μm in plain areas, and increasing to 400μm at the bottom of the coastal area. Follow-up testing one year after implementation showed that the coating integrity rate had increased to 95%, annual maintenance costs had decreased by 40%, and the projected service life was expected to exceed 90% of the design value, fully demonstrating the superiority of the differentiated protection solution.

[0034] For ease of understanding, the following describes the process of the method provided by this implementation in combination with the above scenario. Figure 1 , which is a flow chart of the durability optimization method of highway traffic protection facilities based on digital twins in an embodiment of the present application.

[0035] S101. Acquire real-time data of environmental parameters through multiple monitoring points. The real-time data of environmental parameters include temperature, humidity, wind speed, and precipitation.

[0036] Among them, the monitoring point represents the installation location of the environmental parameter acquisition device arranged around the highway traffic protection facilities. The real-time environmental parameter data refers to the physical quantity values representing the environmental state collected by the sensors. Temperature represents the degree of hotness or coldness of the air, in degrees Celsius or Kelvin. Humidity represents the water vapor content in the air, expressed as a percentage of relative humidity. Wind speed represents the air flow rate, in meters per second. Precipitation represents the precipitation volume per unit time, in millimeters per hour.

[0037] This step is executed when it is necessary to monitor and evaluate the environmental conditions of the highway traffic protection facilities. Specifically, the system collects environmental parameter data through multiple monitoring points distributed around the protection facilities. The layout of the monitoring points follows the representativeness principle to ensure that the regional environmental characteristics can be reflected. Each monitoring point is equipped with devices such as a temperature sensor, a humidity sensor, a wind speed sensor, and a rain gauge, and continuously collects data at a preset sampling frequency. The collected data is stored in the system database in the form of a time series after outlier processing and data completion.

[0038] In some embodiments, the real-time environmental parameter data can be obtained in multiple ways: Optionally, the system installs an integrated environmental monitoring station at each monitoring point, which includes a temperature and humidity composite sensor, an ultrasonic anemometer, and an automatic rain gauge, and transmits the collected data to the data center in real time through a wireless transmission module. The data center performs quality control and format conversion on the received data to form a standardized environmental parameter data set; Optionally, the system uses a mobile monitoring device to conduct patrol monitoring on a preset route. The mobile device is equipped with a GPS positioning module and an environmental sensor array, and continuously collects location information and environmental parameters during the movement. The collected data is uploaded to the server through the mobile communication network, and the server associates the data with the fixed monitoring point according to the location information. It can be understood that other methods can also be used to obtain the real-time environmental parameter data, such as through meteorological station data sharing, remote sensing monitoring, etc., which are not limited here.

[0039] S102. Calculate the environmental parameter gradient value between the monitoring points, and calculate the environmental stress degree based on the real-time environmental parameter data. The environmental stress degree is obtained by weighted calculation of the standardized environmental parameters and their corresponding damage contribution coefficient, and the damage contribution coefficient is determined based on the statistical analysis of historical damage data.

[0040] Among them, the environmental parameter gradient value represents the change rate of environmental parameters between adjacent monitoring points. The environmental stress degree refers to the comprehensive pressure intensity generated by environmental factors on the protection facilities. Standardization refers to the process of converting environmental parameters with different dimensions into a unified scale. The damage contribution coefficient represents the influence weight of each environmental parameter on the damage of the protection facilities. Historical damage data refers to the recorded damage cases of the protection facilities and their environmental condition information.

[0041] This step is executed when it is necessary to evaluate the impact of the environment on the protective facilities after obtaining the real-time data of the environmental parameters. Specifically, the system first calculates the environmental parameter gradient between adjacent monitoring points. For each environmental parameter, its measured value is processed by maximum-minimum normalization to obtain a normalized parameter value. The system extracts the damage records of the protective facilities from the historical database, statistically analyzes the correlation between each environmental parameter and the occurrence of damage, and determines the damage contribution coefficient. The normalized environmental parameters are multiplied by the corresponding damage contribution coefficients and summed to obtain a stress degree value reflecting the comprehensive environmental impact.

[0042] In some embodiments, the calculation of the environmental stress degree can be achieved in multiple ways: Optionally, the system adopts a linear superposition model. First, the environmental parameters are normalized, and the normalized value Z=(X-μ) / σ is calculated, where X is the measured value, μ is the historical average value, and σ is the standard deviation. Then, the principal component analysis method is used to determine the weight coefficients of each parameter. Finally, the normalized values are multiplied by the weight coefficients and summed to obtain the environmental stress degree. Optionally, the system establishes a non-linear neural network model. The normalized environmental parameters are used as the input layer, and the environmental stress degree output is obtained through the non-linear transformation of the hidden layer. The weight parameters of the model are obtained by training with historical data. It can be understood that other methods can also be used to calculate the environmental stress degree, such as fuzzy comprehensive evaluation, grey relational analysis, etc., which are not limited here.

[0043] This step specifically includes the following steps: Calculate the environmental parameter gradient value of the real-time data of the environmental parameters between adjacent monitoring points.

[0044] In this step, the real-time data of the environmental parameters refers to the instant measurement values of environmental indicators such as temperature, humidity, wind speed, and precipitation collected through the sensor network. Adjacent monitoring points refer to two adjacent environmental parameter acquisition points arranged at a specific interval around the protective facilities. The environmental parameter gradient value represents the change rate of the environmental parameter per unit distance and is used to characterize the spatial variation characteristics of the environmental parameter. The system uses the central difference method to calculate the environmental parameter gradient. For the environmental parameter x between adjacent monitoring points i and j, its gradient value calculation formula is: grad(x)=(xj-xi) / d, where d is the distance between the two points. In specific implementation, first obtain the three-dimensional coordinates (x, y, z) and environmental parameter measurement values of all monitoring points, and then calculate the gradient of each environmental parameter for each pair of adjacent points. Taking the temperature gradient as an example, if the temperature at monitoring point A is 25°C and the temperature at adjacent point B is 23°C, and the distance between the two points is 100 meters, then the temperature gradient is -0.02°C / m. The system calculates the gradient for all environmental parameters to form a complete gradient field data.

[0045] Calculate the normalized environmental parameters according to the historical maximum and minimum values corresponding to the real-time data of the environmental parameters.

[0046] In this step, the historical maximum and minimum values refer to the extreme values of environmental parameters recorded at a specific monitoring point during the historical observation period. The standardized environmental parameter refers to the dimensionless value obtained by converting environmental parameters with different dimensions to a unified scale. The system uses the range normalization method for parameter standardization. For an environmental parameter x, its standardized value calculation formula is: x' = (x - xmin) / (xmax - xmin), where xmax and xmin are the historical maximum and minimum values respectively. The system extracts the historical records of environmental parameters for each monitoring point from the database and determines the value range of each parameter. Then, it performs a standardized conversion on the real-time collected environmental parameters so that the values of all parameters are mapped to the interval [0, 1]. For example, if the temperature at a certain point is 25°C, the historical highest temperature is 35°C, and the lowest temperature is -5°C, then the standardized temperature value is 0.75.

[0047] Extract the corresponding relationship between each such environmental parameter and the protection facility damage record from the historical damage database, and obtain the damage contribution degree coefficient of each such environmental parameter based on the damage frequency statistics.

[0048] In this step, the historical damage database stores the damage event records of the protection facilities and the corresponding environmental condition data. The damage contribution degree coefficient represents the influence weight of each environmental parameter on the facility damage. The system determines the damage contribution degree coefficient through statistical analysis. First, group the historical damage records by the value range of the environmental parameter, and calculate the damage event frequency of each interval. The relative frequency method is used to calculate the contribution degree coefficient: w = fi / Σfi, where fi is the damage frequency caused by this environmental parameter. The system performs frequency statistics and coefficient calculation on each environmental parameter to obtain a complete set of contribution degree coefficients. For example, it is statistically found that the damage frequency under high temperature (>30°C) conditions accounts for 30% of the total damage events, then the damage contribution degree coefficient of the temperature parameter is 0.3.

[0049] Multiply the standardized environmental parameter by the corresponding damage contribution degree coefficient and sum them up to obtain the environmental stress degree.

[0050] In this step, the standardized environmental parameter is the dimensionless environmental index value after normalization processing. The damage contribution degree coefficient represents the influence weight of each environmental parameter. The environmental stress degree is a comprehensive index reflecting the influence degree of environmental conditions on the facility.

[0051] The system calculates the environmental stress degree using the weighted summation method. The calculation formula is: S = Σ(wi × xi'), where wi is the damage contribution coefficient of the i-th environmental parameter, and xi' is the corresponding standardized parameter value. In specific implementation, the system multiplies the standardized value of each environmental parameter by its contribution coefficient, and then sums the weighted values of all parameters to obtain the environmental stress degree of this monitoring point. For example, if the standardized temperature at a certain point is 0.75 and the standardized humidity is 0.6, and the corresponding contribution coefficients are 0.3 and 0.4 respectively, then the environmental stress degree S = 0.75 × 0.3 + 0.6 × 0.4 = 0.465. The system performs this calculation process for all monitoring points to generate the environmental stress degree distribution map.

[0052] S103. Analyze the temporal variation characteristics of the environmental stress degree of each adjacent monitoring point to determine the migration path and accumulation area of environmental stress. The temporal variation characteristics of the environmental stress degree include the stress intensity change rate, migration speed, and accumulation duration.

[0053] Among them, the temporal variation characteristics of the environmental stress degree represent the regular performance of the environmental stress degree changing with time. The migration path of environmental stress refers to the trajectory of the spread and diffusion of environmental stress in space. The accumulation area represents the spatial range where environmental stress gathers and accumulates. The stress intensity change rate refers to the change amount of the environmental stress degree per unit time. The migration speed represents the rate of the spread of environmental stress in space. The accumulation duration refers to the time when environmental stress continuously acts in a specific area. The monitoring point refers to the fixed location where the environmental parameter acquisition device is installed.

[0054] This step is executed when it is necessary to master the dynamic evolution law of environmental stress. Specifically, the system analyzes the time series data of the environmental stress degree of each pair of adjacent monitoring points, calculates the first derivative of the stress degree to obtain the change rate, calculates the migration speed through the time difference and spatial distance between the peak values of the stress degrees at adjacent points, and counts the duration when the stress degree exceeds the threshold to obtain the accumulation duration. By analyzing the change relationships of the stress degrees of multiple monitoring points, determine the propagation direction and path of the stress, and identify the area positions where the stress is likely to accumulate.

[0055] In some embodiments, the analysis of environmental stress migration and accumulation characteristics can be achieved in various ways: Optionally, the system adopts a spatio-temporal correlation analysis method. First, wavelet transform is performed on the stress degree time series of the monitoring points to extract periodic characteristics. Then, the cross-correlation function between adjacent points is calculated to determine the time delay. Finally, a migration field is constructed based on the delay time and spatial distance, and the accumulation area is identified through the divergence of the field. Optionally, the system establishes a stress propagation model, takes the stress degree as a scalar field, uses vector calculus methods to calculate the gradient and flux of the field, obtains the migration path by solving the propagation equation, and analyzes and determines the accumulation area in combination with the boundary conditions. It can be understood that other methods can also be used to achieve the analysis of environmental stress migration and accumulation characteristics, such as geostatistical methods, cellular automata models, etc., which are not limited herein.

[0056] S104. Divide the differential protection grades of the anti-corrosion coatings on the highway traffic protection facilities based on the stress intensity distribution in the accumulation area.

[0057] Among them, the accumulation area represents the spatial range where environmental stress significantly aggregates. The stress intensity distribution refers to the spatial distribution law of the environmental stress degree within the accumulation area. The anti-corrosion coating refers to the protective layer coated on the surface of the protection facilities to prevent corrosion. The differential protection grade refers to different protection requirement grades divided according to the environmental stress intensity. The highway traffic protection facilities refer to the facilities installed on the road to ensure traffic safety.

[0058] This step is executed when formulating the anti-corrosion protection plan for the protection facilities. Specifically, the system sets multiple stress intensity thresholds according to the spatial distribution characteristics of the stress intensity within the accumulation area, and divides the surface of the protection facilities into different protection areas. Statistical characteristic quantities are calculated for each area, including the average stress intensity, the maximum stress intensity, and the fluctuation amplitude, and the protection requirements of the area are comprehensively evaluated to determine the corresponding protection grade.

[0059] In some embodiments, the division of differential protection grades can be achieved in various ways: Optionally, the system adopts a clustering analysis method. First, the accumulation area is meshed, and the stress intensity feature vectors of each grid are extracted. Then, the K-means clustering algorithm is used to group the grids. Finally, the protection grades are determined according to the stress characteristics of each group, and the partition boundaries are smoothed. Optionally, the system establishes a multi-index evaluation system, combines indicators such as stress intensity, duration, and change frequency through weighting, calculates the comprehensive score, divides the protection grades according to the score interval, and optimizes the spatial continuity. It can be understood that other methods can also be used to achieve the division of differential protection grades, such as fuzzy classification, support vector machine and other methods, which are not limited herein.

[0060] This step specifically includes the following steps: Calculate the average value and coefficient of variation of the environmental stress degree of each point in the accumulation area.

[0061] In this step, the cumulative area refers to the spatial range where environmental stresses significantly aggregate, which is a continuous area composed of multiple discrete monitoring points. The average value of environmental stress degree represents the arithmetic average level of stress degrees of all monitoring points within the area. The coefficient of variation is the ratio of the standard deviation to the average value, and is used to measure the degree of data dispersion. The system uses statistical analysis methods to process the environmental stress degree data within the cumulative area. The formula for calculating the average value is: μ = (1 / n) × Σsi, where n is the number of monitoring points and si is the environmental stress degree of the i-th point. The formula for calculating the standard deviation is: σ = sqrt[(1 / n) × Σ(si - μ)²]. The formula for calculating the coefficient of variation is: CV = σ / μ. The system first determines the spatial positions and stress degree values of all monitoring points within the cumulative area, and then calculates the overall average value. Next, it calculates the sum of the squared deviations of the stress degree of each point from the average value to obtain the standard deviation. Finally, it divides the standard deviation by the average value to get the coefficient of variation. For example, a certain cumulative area contains 10 monitoring points, the average value of the stress degree is 0.6, and the standard deviation is 0.12, then the coefficient of variation is 0.2.

[0062] The cumulative area is divided into sub-regions of different stress intensities according to the magnitude relationship of the average value of the environmental stress degree.

[0063] In this step, the average value of the environmental stress degree reflects the overall level of environmental pressure within the area. The sub-region of stress intensity refers to a continuous spatial unit with a similar stress degree level. The system uses cluster analysis methods for regional division. First, a sequence of stress degree classification thresholds {T1, T2,..., Tn} is set, and the monitoring points within the cumulative area are grouped according to the magnitude of the average value of the stress degree. The minimum distance method is used to determine the sub-region to which each monitoring point belongs: when μi ∈ [Tk - 1, Tk], this point is classified into the k-th level sub-region. The system constructs a continuous distribution field of the stress degree through spatial interpolation methods, and then divides the continuous field into sub-regions of different levels according to the threshold sequence. For example, when the threshold sequence {0.3, 0.6, 0.9} is set, the area is divided into four sub-regions: low stress area (≤0.3), medium stress area (0.3 - 0.6), high stress area (0.6 - 0.9), and extremely high stress area (>0.9).

[0064] Analyze the coefficient of variation of the environmental stress degree within each sub-region of stress intensity, and merge adjacent sub-regions with the coefficient of variation of the environmental stress degree within the same range to obtain merged sub-regions.

[0065] In this step, the sub-region of stress intensity is a preliminarily divided regional unit with similar environmental pressure. The coefficient of variation of the environmental stress degree represents the degree of fluctuation of the stress degree within the sub-region. Adjacent sub-regions refer to two sub-regions that have a common boundary in space.

[0066] The system optimizes the initial partitioning result through the region merging algorithm. First, calculate the coefficient of variation of the environmental stress degree within each sub-region, and set the similarity threshold ε of the coefficient of variation. For any two adjacent sub-regions i and j, when |CVi - CVj| < ε, merge these two sub-regions. The system performs region merging in an iterative manner until the differences in the coefficient of variation of all adjacent regions are greater than the threshold. For example, the coefficients of variation of two adjacent sub-regions are 0.18 and 0.21 respectively, and the similarity threshold ε = 0.05. Since 0.21 - 0.18 < 0.05, the system merges these two sub-regions into a new regional unit.

[0067] According to the distribution of the merged sub-regions, divide the anti-corrosion coating of highway traffic protection facilities into different protection level regions.

[0068] In this step, the merged sub-regions are the environmental stress partitions optimized through the coefficient of variation analysis. The anti-corrosion coating is the protective material coated on the surface of the protection facilities. The protection level regions are different protection requirement regions determined according to the environmental stress intensity.

[0069] The system determines the protection level of the anti-corrosion coating based on the spatial distribution of the merged sub-regions. First, establish the mapping relationship between the stress degree and the protection requirement: determine the required protection intensity at different stress degree levels according to the material performance test data. Then, map each merged sub-region to the corresponding protection level to generate a protection zoning scheme. The system uses GIS tools for spatial analysis, identifies the boundary lines of the protection level regions, and smooths the boundaries to ensure the continuity and feasibility of the protection zoning. For example, divide the protection level into three levels. Regions with a stress degree < 0.4 adopt the first-level protection, 0.4 - 0.7 adopt the second-level protection, and > 0.7 adopt the third-level protection. The system generates a protection level zoning map accordingly.

[0070] S105. Use the numerical simulation method to determine the anti-corrosion coating thickness parameters and the component ratio parameters of different protection level regions, and send the anti-corrosion coating thickness parameters and the component ratio parameters to the target client.

[0071] Among them, the numerical simulation method refers to the method of simulating physical processes through mathematical models and computer simulation technologies. The protection level region refers to different protection requirement regions divided according to the environmental stress degree. The anti-corrosion coating thickness parameter represents the actual thickness value of the coating, in micrometers. The component ratio parameter refers to the weight or volume ratio of each component in the coating. The target client refers to the terminal device or system that receives the coating parameters. The anti-corrosion coating refers to the protective material coated on the surface of the facilities to prevent corrosion.

[0072] This step is executed when the division of the protection level areas is completed and the specific protection parameters for each area need to be determined. Specifically, the system establishes a numerical model of the anti-corrosion coating - environmental action, regarding the coating as a multi-layer composite structure, with each layer having different physical and chemical properties. For the environmental stress conditions in different protection level areas, the finite element method is used to calculate parameters such as the stress distribution and corrosion rate of the coating. By solving the coating damage evolution equation and the corrosion depth calculation formula, the minimum thickness of the anti-corrosion coating required for each area is determined. According to the thickness requirements, combined with the performance characteristics of the coating material, the ratio of each component is optimized to achieve the best protection effect.

[0073] In some embodiments, the determination of the anti-corrosion coating parameters can be achieved in various ways: Optionally, the system uses the finite element analysis method. First, a three-dimensional geometric model of the coating is established, the material properties and boundary conditions are defined, then the environmental load is applied for stress and strain analysis, the stress concentration areas and deformation amounts are calculated, and finally the thickness parameters are determined according to the strength and stiffness requirements, and the component ratio is optimized by the response surface method; Optionally, the system adopts a corrosion kinetics model, establishes a relationship equation between the corrosion rate and environmental factors, calculates the corrosion depth through numerical integration, determines the coating thickness, and optimizes the coating formulation in combination with the electrochemical impedance spectroscopy data. It can be understood that other ways can also be used to determine the anti-corrosion coating parameters, such as molecular dynamics simulation, artificial neural network and other methods, which are not limited here.

[0074] This step specifically includes the following steps: Obtain the environmental stress degrees of different protection level areas and the service life requirements of the highway traffic protection facilities.

[0075] In this step, the protection level area is a different protection requirement area divided according to the environmental stress intensity, including spatial partitions of multiple levels. The environmental stress degree is a comprehensive index representing the influence degree of environmental conditions on the facilities, which is obtained by weighted calculation of environmental parameters. The service life requirement refers to the time length that the protection facilities need to maintain good functions under normal use conditions, usually in years. The system obtains the protection level area information and related parameters through the data interface. First, the protection partition data is read, and the spatial range and environmental stress degree value of each area are extracted. The environmental stress degree data includes the average value, the maximum value and the fluctuation range. At the same time, the service life requirements of the protection facilities are extracted from the engineering design specifications, including the minimum service life and the design service life. For example, a certain protection facility is divided into three protection level areas, with environmental stress degrees of 0.3, 0.5 and 0.8 respectively, and the design service life requirement is 20 years. The system stores these data in the calculation parameter database for subsequent corrosion rate and coating parameter calculations.

[0076] Calculate the coating corrosion rate of each protection level area according to this environmental stress degree.

[0077] In this step, the coating corrosion rate represents the corrosion loss rate of the anti-corrosion coating material under specific environmental conditions, expressed as the thickness of material loss per year. The environmental stress degree is a comprehensive characterization of the corrosion effect of environmental conditions on materials. The system uses a corrosion kinetics model to calculate the coating corrosion rate. The corrosion rate calculation formula is: v = v0×exp(k×S), where v0 is the reference corrosion rate, k is the environmental sensitivity coefficient, and S is the environmental stress degree. The system first determines the reference corrosion rate and the environmental sensitivity coefficient through material test data, and then substitutes the environmental stress degree of each protection level area into the formula to calculate the actual corrosion rate. For the coupling effect of environmental factors such as temperature and humidity, a correction coefficient is used for correction: v' = v×Πfi, where fi is the correction coefficient of each environmental factor. For example, if the environmental stress degree of a certain area is 0.5, the reference corrosion rate is 0.1 mm / year, and the environmental sensitivity coefficient is 1.5, the calculated corrosion rate is 0.247 mm / year.

[0078] Based on this coating corrosion rate and this service life requirement, calculate the anti-corrosion coating thickness parameters required for each of these protection level areas.

[0079] In this step, the anti-corrosion coating thickness parameter refers to the actual thickness value of the coating, in micrometers. The coating corrosion rate represents the annual corrosion loss of the material. The service life requirement is the length of time the facility needs to maintain its function. The system determines the coating thickness parameter through numerical calculation. The thickness calculation formula is: d = v×t×(1 + α), where v is the corrosion rate, t is the designed service life, and α is the safety factor. The system performs calculations for each protection level area, considering the corrosion loss and safety margin of the coating. At the same time, a coating structure factor is introduced for correction: d' = d×β, where β is the structure correction coefficient, reflecting the influence of the coating structure on the protection performance. For example, if the corrosion rate of a certain area is 0.247 mm / year, the designed service life is 20 years, the safety factor is 0.2, and the structure correction coefficient is 1.1, the calculated coating thickness is 6.5 mm.

[0080] Determine the composition ratio parameters according to this anti-corrosion coating thickness parameter.

[0081] In this step, the component ratio parameter refers to the weight or volume ratio of each component of the anti-corrosion coating. The anti-corrosion coating thickness parameter is the designed thickness value of the coating. The system determines the coating formula through the material property optimization method. First, a relationship model between coating performance and composition is established: P = f(x1, x2,..., xn), where xi is the content of each component. The optimization objective function is set as: min{c(x)}, where c(x) is the cost function. The constraint conditions include: the component content range xi_min ≤ xi ≤ xi_max, and the performance index requirement P ≥ P0. The system uses a non-linear programming algorithm to solve the optimal ratio. For example, a certain coating contains three components: resin, curing agent, and filler, and the optimal ratio obtained through optimization calculation is 50:30:20. At the same time, the system generates coating formula process parameters, including process requirements such as mixing order and mixing time.

[0082] The following is a further and more specific process description of the method provided in this embodiment. Please refer to Figure 2 , which is another process schematic diagram of the durability optimization method for highway traffic protection facilities based on digital twin in the embodiments of the present application.

[0083] S201. Use the numerical simulation method to determine the anti-corrosion coating thickness parameter and the component ratio parameter of different protection level areas, and send the anti-corrosion coating thickness parameter and the component ratio parameter to the target client.

[0084] The numerical simulation method refers to the method of simulating and calculating the system through a mathematical model, including technical means such as finite element analysis and computational fluid dynamics. The protection level area is a different protection requirement area divided according to the degree of environmental stress, reflecting the corrosiveness intensity of the environment where the protection facilities are located. The anti-corrosion coating thickness parameter refers to the actual thickness value of the coating, usually measured in micrometers (μm). The component ratio parameter refers to the weight or volume ratio of each component in the coating, which directly determines the protection performance of the coating. The target client refers to the terminal device or system that receives the coating parameters and is used to specifically guide the construction of the coating.

[0085] First, establish a numerical model of the interaction between the anti-corrosion coating and the environment. Consider the coating as a multi-layer composite structure, with each layer having different physical and chemical properties. For the environmental stress conditions in different protection level areas, use the finite element method to calculate parameters such as the stress distribution and corrosion rate of the coating. By solving the coating damage evolution equation dD / dt = A•σα•exp(-Q / RT) (where D is the damage amount, σ is the stress, and T is the temperature), obtain the damage evolution law of the coating. Based on the corrosion depth calculation formula h = k•t^n (where k is the corrosion rate constant, t is the time, and n is the time exponent), determine the minimum thickness δ = h•SF (where SF is the safety factor) of the anti-corrosion coating required for each area. Then, according to the thickness requirements and combined with the performance characteristics of the coating material, optimize the proportion of each component to achieve the best protection effect. Finally, send the calculated specific coating thickness values and component ratio data to the target client through the network interface.

[0086] S202. Obtain the topographic data and water system data of the area where the highway traffic protection facilities are located.

[0087] Topographic data is a dataset that describes landform features such as surface elevation, slope, and aspect, containing detailed information about the undulation changes of the earth's surface. Water system data includes the spatial distribution and attribute information of water bodies such as rivers and lakes, reflecting the regional hydrological characteristics. Highway traffic protection facilities refer to road safety protection devices such as guardrails and anti-collision facilities, whose performance directly affects traffic safety.

[0088] This step is achieved in the following way: After determining the geographic coordinate range of the protection facilities, extract the digital elevation model (DEM) data of the area from the geographic information system (GIS) database, and obtain the longitude, latitude, and elevation values of each grid point. At the same time, extract the water system vector data, including attribute information such as water body type, flow direction, and width. Use remote sensing image interpretation technology to extract topographic features, establish a high-precision topographic model using survey data, and obtain real-time hydrological data through hydrological monitoring stations. All the obtained data is stored in a unified geographic coordinate system and data format to ensure data consistency and availability.

[0089] S203. Calculate the surface runoff channels based on the topographic data, and calculate the pollutant migration paths based on the water system data and the surface runoff channels.

[0090] Surface runoff channels refer to the water flow paths formed by the convergence of precipitation, reflecting the movement law of surface water. Pollutant migration paths refer to the trajectories of pollutants migrating and diffusing along with surface water flows, reflecting the diffusion process of pollutants in the environment.

[0091] This step is specifically implemented as follows: Use the D8 algorithm to perform hydrological analysis on DEM data and calculate the flow direction of each grid. Construct a flow path network based on the flow direction information to determine the main runoff channels. Superimpose and analyze the water system data, considering the confluence effect of rivers, to obtain a complete surface water flow network. Based on this network, use the convection-diffusion equation (where C is the pollutant concentration, v is the velocity vector, and D is the diffusion coefficient) to simulate the pollutant transport. By numerically solving this equation, trace the transport trajectory of the pollutant starting from the source point along the water flow path. The calculation process comprehensively considers the influence of factors such as terrain slope and surface roughness on the transport speed to achieve accurate prediction of the pollutant migration path.

[0092] S204. Calculate the cumulative concentration of the pollutant along this pollutant transport path, convert this cumulative concentration of the pollutant into an increment of environmental stress degree, and superimpose this increment of environmental stress degree with the environmental stress degree to obtain the regional stress degree.

[0093] The cumulative concentration of the pollutant refers to the degree of aggregation of pollutants at each point on the transport path, expressed in mg / L. The increment of environmental stress degree is the additional environmental pressure value caused by the pollutant concentration, and is processed by dimensionless. The regional stress degree is the overall environmental pressure index considering the basic environmental stress and the influence of pollutants.

[0094] The specific implementation process of this step is as follows: The system first calculates the cumulative concentration on the path according to the pollutant transport equation, specifically using the mass conservation equation for calculation, where M is the pollutant mass, v is the transport speed, and S is the source-sink term. At each calculation node, the cumulative concentration C = M / V (V is the control volume). Then convert the concentration value into an increment of stress degree, and the conversion formula is ΔS = k • (C / C0)^α, where k is the conversion coefficient, C0 is the reference concentration, and α is the nonlinear index. For n environmental factors, the total regional stress degree is calculated as St = S0 + Σ(wi • ΔSi), where S0 is the basic environmental stress degree and wi is the weight coefficient. The system performs calculations for each grid point to generate a regional stress degree distribution map.

[0095] S205. Divide the protection level zones according to this regional stress degree, calculate the coating technical parameters of this protection level zone and send them to the target client.

[0096] The regional stress degree is a comprehensive index characterizing the intensity of environmental pressure. The protection level zones refer to different protection requirement zones divided according to the stress degree level. The coating technical parameters include process indexes such as coating thickness and material ratio. The target client is the terminal device that receives the parameters.

[0097] The implementation process of this step is as follows: The system uses the clustering analysis method to classify the regional stress degree, and sets a threshold sequence {T1, T2,..., Tn} to divide the stress degree into n levels. For the stress degree value S, when Ti-1 < S ≤ Ti, it belongs to the i-th protection area. After determining the partition, the system calculates the coating parameters for each protection level. The coating thickness δ is determined by the corrosion life equation δ = V • t + δ0, where V is the corrosion rate, t is the design life, and δ0 is the process margin. The material ratio is solved by an optimization algorithm, and the objective function is min{f(x1, x2,..., xm)}, where xi is the content of each component, satisfying the constraint condition of Σxi = 1. After the calculation is completed, the system transmits the coating parameter data packets of each partition to the target client through the network.

[0098] S206. Receive meteorological forecast data and calculate the predicted environmental stress degree based on this meteorological forecast data.

[0099] The meteorological forecast data includes the predicted values of meteorological elements such as temperature, humidity, wind speed, and precipitation. The predicted environmental stress degree is a future environmental pressure index calculated based on the forecast data.

[0100] The specific implementation of this step is as follows: The system obtains meteorological forecast data through a data interface, including the hourly forecast values for the next 7 days. For each forecast time t, calculate the standardized value of each meteorological element zi(t) = (xi(t) - μi) / σi, where xi(t) is the forecast value, and μi and σi are the historical mean and standard deviation respectively. The predicted environmental stress degree is obtained by weighted summation: S(t) = Σ(wi • zi(t)), where wi is the weight coefficient of each element, determined by historical data regression analysis. The system calculates for all times within the forecast period to generate a stress degree time series for subsequent analysis. The coupling effect between meteorological elements is considered in the calculation, and cross-term correction is used: S'(t) = S(t) + Σ(kij • zi(t) • zj(t)), where kij is the coupling coefficient.

[0101] S207. Compare the predicted environmental stress degree with the environmental stress degree to obtain a stress degree trend graph, and determine the boundary of the protection partition according to this stress degree trend graph.

[0102] The stress degree trend graph is a two-dimensional curve graph representing the time variation law of the environmental stress degree, with the horizontal axis being time and the vertical axis being the stress degree value. The boundary of the protection partition refers to the dividing line between different protection level areas, determined by the gradient change of the stress degree. The predicted environmental stress degree and the environmental stress degree represent the future and current environmental pressure levels respectively.

[0103] The specific implementation process of this step is as follows: First, the system plots the predicted environmental stress degree sequence Sp(t) and the current environmental stress degree Sa(t) in the same coordinate system, and calculates the difference sequence ΔS(t) = Sp(t) - Sa(t). Analyze the periodic characteristics of the difference sequence through Fourier transform: F(ω) = ∫ΔS(t) • e^(-iωt)dt. According to the spectrum analysis results, identify the main periods and trends of the stress degree changes. Spatially, calculate the stress degree gradient vector , when the gradient value exceeds the threshold γ, it is determined as a partition boundary point. Fit all boundary points with a B-spline curve to form a continuous partition boundary line B(u) = ΣPi • Ni,k(u), where Pi is the coordinate of the control point and Ni,k(u) is the B-spline basis function.

[0104] S208. Calculate the coating technical parameters within the protection partition boundary and send the coating technical parameters to the target client.

[0105] The coating technical parameters include specific indicators such as coating thickness, material component ratio, construction process requirements, etc. The protection partition boundary defines the area range that requires differential protection treatment. The target client is a terminal device used to receive and display technical parameters.

[0106] The implementation process of this step is as follows: The system calculates the coating parameter combinations for each protection partition. The coating thickness is calculated through the corrosion life equation: d = v • t • f(S) + d0, where v is the reference corrosion rate, t is the design life, f(S) is the stress degree correction function, and d0 is the safety margin. The optimization of material components adopts the nonlinear programming method, and the objective function is min{c(x) + λ • p(x)}, where c(x) is the cost function, p(x) is the performance function, x is the component vector, and λ is the trade-off factor. The constraint conditions include: the component content range xi_min ≤ xi ≤ xi_max, and the performance index requirement gj(x) ≥ bj. The obtained optimal parameter combinations are sent to the target client through the data interface, and the data includes the coating structure parameter matrix D and the process parameter vector P.

[0107] S209. Extract the usage environment data of the highway traffic protection facilities and calculate the material fatigue index of the highway traffic protection facilities according to the usage environment data.

[0108] The usage environment data refers to the measured values of physical quantities such as temperature, humidity, and stress in the environment where the protection facilities are located. The material fatigue index is a quantitative index characterizing the degree of material performance degradation, including parameters such as fatigue damage degree and remaining strength. Highway traffic protection facilities refer to safety protection devices such as guardrails and anti-collision facilities on roads.

[0109] This step is specifically implemented as follows: The system collects the usage environment data of the protection facilities through the sensor network, including the environmental load sequence σ(t) and the environmental factor sequence E(t). Based on the Paris fatigue crack growth formula, the material damage evolution is calculated: da / dN = C•(ΔK)^m, where a is the crack length, N is the number of cycles, and ΔK is the stress intensity factor range. Considering the influence of environmental factors, the correction coefficient C = C0•exp(βE), where C0 is the reference value and β is the environmental sensitivity coefficient. The cumulative damage degree is calculated by the Miner criterion: D = Σ(ni / Ni), where ni is the actual number of cycles and Ni is the critical number of cycles. The system stores the calculated fatigue index in the database for subsequent life prediction.

[0110] S210. Analyze the acceleration effect of environmental stress on material fatigue, and predict the remaining service life of the highway traffic protection facilities based on the material fatigue index and this acceleration effect.

[0111] The acceleration effect of environmental stress refers to the promoting effect of environmental factors on the material fatigue process, which is quantitatively represented by the acceleration factor. The material fatigue index includes parameters such as damage degree and crack size that reflect the degradation of material properties. The remaining service life refers to the time length required for the protection facilities to reach the failure standard from the current state. Highway traffic protection facilities refer to the protection devices used to ensure road safety.

[0112] The specific implementation process of this step is as follows: The system first establishes an environment-fatigue coupling model and calculates the environmental acceleration factor AF = exp[Ea(1 / T0 - 1 / T)], where Ea is the apparent activation energy, T0 is the reference temperature, and T is the actual temperature. For the action of multiple environmental factors, the total acceleration factor AFt = ΠAFi. Based on the modified Manson-Coffin equation, the fatigue life is calculated: Nf = [εf'•exp(AF•kt)]^c, where εf' is the fatigue ductility coefficient, k is the time coefficient, and c is the material constant. Combining the current damage state D and the failure critical value Dc, the remaining life is solved by the integral equation: ∫[dD / (1 - D)] = ∫[A•σα•exp(-Q / RT)]dt, where A is the material constant, σ is the stress, Q is the activation energy, and R is the gas constant. The specific value of the remaining life tr is obtained through numerical integration.

[0113] S211. Determine the maintenance time window of the highway traffic protection facilities based on this remaining service life, and divide the maintenance priority levels of the highway traffic protection facilities.

[0114] The maintenance time window refers to the optimal time period for carrying out the maintenance of the protection facilities, which is determined by the remaining life and the maintenance duration. The maintenance priority level is the grading of the urgency degree for maintaining the protection facilities. The remaining service life is the remaining time before the protection facilities reach the failure state.

[0115] The implementation process of this step is as follows: The system sets the maintenance time interval [t1, t2] according to the remaining life tr, where t1 = tr - Δt1, t2 = tr - Δt2, and Δt1 and Δt2 are the safety margin and construction period respectively. For n protective facilities, a priority scoring function is constructed: P = w1•(1 / tr) + w2•D + w3•L, where w1, w2, and w3 are weight coefficients, D is the current damage degree, and L is the facility importance coefficient. The facilities are sorted according to the scoring value, and the priority intervals are divided: P > P1 is the first-level priority, P2 < P ≤ P1 is the second-level priority, and P ≤ P2 is the third-level priority. The system generates a maintenance schedule table including the maintenance time window [t1, t2] and the priority P, and stores it in the database for maintenance management. At the same time, the maintenance resource requirement R = Σ(ri•ni) for each priority interval is calculated, where ri is the resource requirement of a single facility and ni is the number of facilities in this priority.

[0116] The durability optimization system of highway traffic protection facilities in the embodiment of the present invention application will be described from the perspective of hardware processing. Please refer to Figure 3 , which is a schematic structural diagram of an entity device of the durability optimization system of highway traffic protection facilities in the embodiment of the present application.

[0117] It should be noted that Figure 3 the structure of the durability optimization system of highway traffic protection facilities shown is only an example, and should not bring any limitations to the functions and usage scopes of the embodiments of the present invention.

[0118] As Figure 3 shown, the durability optimization system of highway traffic protection facilities includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage part 308 into the random access memory (RAM) 303, such as executing the method described in the above embodiments. In the RAM 303, various programs and data required for system operation are also stored. The CPU 301, ROM 302, and RAM 303 are connected to each other through a bus 304. The input / output (I / O) interface 305 is also connected to the bus 304.

[0119] The following components are connected to the I / O interface 305: an input section 306 including an audio input device, a button switch, etc.; an output section 307 including a liquid crystal display (LCD), an audio output device, an indicator light, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. The drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc. is installed on the drive 310 as needed so that a computer program read from it can be installed into the storage section 308 as needed.

[0120] Specifically, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication section 309, and / or installed from the removable medium 311. When the computer program is executed by the central processing unit (CPU) 301, various functions defined in the present invention are executed.

[0121] It should be noted that specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, the computer-readable storage medium can be any tangible medium that contains or stores a program, and the program can be used by or combined with an instruction execution system, apparatus, or device.

[0122] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present invention. Among them, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, and the above-mentioned module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order from that marked in the accompanying drawings.

[0123] Specifically, the durability optimization system of highway traffic protection facilities in this embodiment includes a processor and a memory. A computer program is stored on the memory. When the computer program is executed by the processor, it implements the durability optimization method of highway traffic protection facilities based on digital twin provided in the above embodiment.

[0124] On the other hand, the present invention also provides a computer-readable storage medium, which may be included in the durability optimization system of highway traffic protection facilities described in the above embodiment; or it may exist alone and not be assembled into the durability optimization system of highway traffic protection facilities. The above storage medium carries one or more computer programs. When the above one or more computer programs are executed by a processor of the durability optimization system of highway traffic protection facilities, the durability optimization system of highway traffic protection facilities is enabled to implement the durability optimization method of highway traffic protection facilities based on digital twin provided in the above embodiment.

[0125] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the various embodiments of the present application.

[0126] As used in the above embodiments, depending on the context, the term "when..." may be interpreted to mean "if...", or "after...", or "in response to determining...", or "in response to detecting...". Similarly, depending on the context, the phrase "when determining..." or "if detecting (the stated condition or event)" may be interpreted to mean "if determining...", or "in response to determining...", or "when detecting (the stated condition or event)", or "in response to detecting (the stated condition or event)".

[0127] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by hardware instructed by a computer program. This program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above method embodiments. The foregoing storage medium includes: various media such as ROM, random access memory (RAM), magnetic disk, or optical disc that can store program codes.

Claims

1. A durability optimization method for highway traffic protection facilities based on digital twin, characterized in that Applied to the durability optimization system of highway traffic protection facilities, the method includes: Obtaining real-time environmental parameter data through multiple monitoring points, where the real-time environmental parameter data includes temperature, humidity, wind speed, and precipitation; Calculating the environmental parameter gradient values between the monitoring points, and calculating the environmental stress degree based on the real-time environmental parameter data. The environmental stress degree is obtained by weighted calculation after normalizing the environmental parameters and multiplying them by their corresponding damage contribution coefficient, and the damage contribution coefficient is determined based on statistical analysis of historical damage data; Analyzing the time-series change characteristics of the environmental stress degree of each adjacent monitoring point to determine the migration path and accumulation area of environmental stress. The time-series change characteristics of the environmental stress degree include the stress intensity change rate, migration speed, and accumulation duration; Based on the stress intensity distribution in the accumulation area, dividing the differential protection grades of the anti-corrosion coating on the highway traffic protection facilities; Using numerical simulation methods to determine the anti-corrosion coating thickness parameters and component ratio parameters in different protection grade areas, and sending the anti-corrosion coating thickness parameters and the component ratio parameters to the target client.

2. The method according to claim 1, characterized in that The step of calculating the environmental parameter gradient values between the monitoring points and calculating the environmental stress degree based on the real-time environmental parameter data specifically includes: Calculating the environmental parameter gradient values of the real-time environmental parameter data between adjacent monitoring points; Calculating the normalized environmental parameters according to the historical maximum and minimum values corresponding to the real-time environmental parameter data; Extracting the correspondence between each environmental parameter and the protection facility damage record from the historical damage database, and obtaining the damage contribution coefficient of each environmental parameter based on damage frequency statistics; Multiplying the normalized environmental parameters by their corresponding damage contribution coefficients and summing them to obtain the environmental stress degree.

3. The method according to claim 1, characterized in that The step of dividing the differential protection grades of the anti-corrosion coating on the highway traffic protection facilities based on the stress intensity distribution in the accumulation area specifically includes: Calculating the average value and coefficient of variation of the environmental stress degree of each point in the accumulation area; Dividing the accumulation area into different stress intensity sub-areas according to the magnitude relationship of the average environmental stress degree; Analyzing the coefficient of variation of the environmental stress degree in each stress intensity sub-area, and merging adjacent sub-areas with the coefficient of variation of the environmental stress degree within the same range to obtain merged sub-areas; Dividing the anti-corrosion coating of the highway traffic protection facilities into different protection grade areas according to the distribution of the merged sub-areas.

4. The method according to claim 1, characterized in that, The step of using numerical simulation methods to determine the anti-corrosion coating thickness parameters and component ratio parameters in different protection grade areas specifically includes: Obtaining the environmental stress degree of different protection grade areas and the service life requirements of the highway traffic protection facilities; Calculating the coating corrosion rate of each protection grade area according to the environmental stress degree; Based on the coating corrosion rate and the service life requirements, calculating the anti-corrosion coating thickness parameters required for each protection grade area; Determining the component ratio parameters according to the anti-corrosion coating thickness parameters.

5. The method according to claim 4, characterized in that After the step of sending the anti-corrosion coating thickness parameters and the component ratio parameters to the target client, the method further includes: Obtain the topographic data and water system data of the area where the highway traffic protection facilities are located; Calculate the surface runoff channels based on the topographic data, and calculate the pollutant migration paths based on the water system data and the surface runoff channels; Calculate the pollutant accumulation concentration along the pollutant migration path, convert the pollutant accumulation concentration into an environmental stress degree increment, and superimpose the environmental stress degree increment with the environmental stress degree to obtain the regional stress degree; Divide the protection level zoning according to the regional stress degree, calculate the coating technical parameters of the protection level zoning and send them to the target client.

6. The method according to claim 4, wherein After the step of sending the anti-corrosion coating thickness parameter and the component ratio parameter to the target client, the method further includes: Receive meteorological forecast data and calculate the predicted environmental stress degree based on the meteorological forecast data; Compare the predicted environmental stress degree with the environmental stress degree to obtain a stress degree trend chart, and determine the protection zoning boundary according to the stress degree trend chart; Calculate the coating technical parameters within the protection zoning boundary, and send the coating technical parameters to the target client.

7. The method according to claim 1, characterized in that After the step of sending the anti-corrosion coating thickness parameter and the component ratio parameter to the target client, the method further includes: Extract the usage environment data of the highway traffic protection facilities, and calculate the material fatigue index of the highway traffic protection facilities according to the usage environment data; Analyze the acceleration effect of environmental stress on material fatigue, and predict the remaining service life of the highway traffic protection facilities according to the material fatigue index and the acceleration effect; Determine the maintenance time window of the highway traffic protection facilities based on the remaining service life, and divide the maintenance priority levels of the highway traffic protection facilities.

8. A road traffic protection facility durability optimization system, characterized in that: The highway traffic protection facilities durability optimization system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the highway traffic protection facilities durability optimization system to execute the method according to any one of claims 1-7.

9. A computer-readable storage medium, comprising instructions, characterized in that, When the instruction runs on the highway traffic protection facilities durability optimization system, it enables the highway traffic protection facilities durability optimization system to execute the method according to any one of claims 1-7.

10. A computer program product, characterized in that, When the computer program product runs on the highway traffic protection facilities durability optimization system, it enables the highway traffic protection facilities durability optimization system to execute the method according to any one of claims 1-7.

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