A steel-cored aluminum stranded wire multi-field coupling aging simulation method based on actual operation data calibration

Abstract

The application discloses a kind of steel-cored aluminium strand multi-field coupling aging simulation methods based on actual operation data calibration, including establishing the three-dimensional structure model of target steel-cored aluminium strand on multi-physical field simulation platform, construct the multi-field coupling simulation model of electric field, thermal field, force field and environment field, and set material attribute and boundary condition to carry out coupling solution, obtain initial simulation result.Through constructing material and environmental parameter database, it is used as input condition to correct initial simulation result;Collect real-time operation data on site, and process data to obtain measured data for calibration;According to the deviation between measured data and simulation result, adjust parameters, iteratively correct material and environmental parameters, until the deviation between simulation result and measured data meets preset condition, finally output calibration model reflecting the actual aging state of steel-cored aluminium strand, and evaluate the aging state of the conductor based on the model, provide accurate life prediction and state evaluation.

Description

Technical Field

[0001] This invention belongs to the field of simulation technology for power transmission line operation and conductor aging, and specifically relates to a multi-field coupled aging simulation method for steel-cored aluminum stranded wire based on actual operation data calibration. Background Technology

[0002] Aluminum Conductor Steel Reinforced (ACSR) conductors, as a core component of overhead transmission lines, have long played a crucial role in high-capacity power transmission in global power grids due to their excellent conductivity, reliable mechanical strength, and economic advantages. However, during long-term service, these conductors are continuously exposed to complex natural environments and subjected to Joule heating caused by current, mechanical tension, and the effects of ambient temperature and humidity. This leads to aging phenomena in their internal materials, such as increased resistivity and decreased mechanical strength, thus affecting the current-carrying capacity and structural safety of the line. The aging of ACSR conductors is essentially a comprehensive result of the interaction of multiple physical fields, including electricity, heat, force, and the environment, involving changes in temperature distribution, stress-strain state, and vibration characteristics.

[0003] To accurately assess the health status of in-service steel-cored aluminum stranded wires and predict their remaining service life, academia and industry have conducted extensive research. Traditional simulation methods are mainly based on theoretical modeling or multiphysics coupling simulation to evaluate the aging process of conductors. However, these methods generally suffer from empirical assumptions about parameters and dynamic differences from actual operating conditions, leading to discrepancies between simulation results and the actual degradation patterns of conductors, making it difficult to provide a reliable basis for operation and maintenance decisions.

[0004] Currently, the multi-field coupled aging simulation technology for steel-cored aluminum stranded wire still has technical shortcomings in terms of model construction, material parameter selection, and data calibration. 1. Incomplete multi-field coupling: Most traditional conductor simulation models only consider two-field couplings, such as electro-thermal or thermo-mechanical couplings, and lack fully coupled models that cover electrical, thermal, mechanical, and environmental factors. Environmental factors are usually treated as constant boundary conditions, ignoring the region-specific environmental changes and their real-time interaction with the conductor.

[0005] 2. Insufficient authenticity of aging conditions: Traditional conductor life assessment relies on aging tests, but aging tests are time-consuming and costly, and the constant environmental conditions set by them are difficult to truly reproduce the actual operating environment on site, which easily underestimates the actual aging rate of conductors.

[0006] 3. Lack of data-driven calibration: The material parameters in existing simulation models are usually derived from the manufacturer's material manual or ideal conditions. They do not take into account the influence of material performance changes with aging during the service of the conductor, and lack a closed-loop calibration mechanism with real-time field operation data, resulting in a weak correlation between simulation results and actual aging patterns.

[0007] In the prior art, CN120493513A discloses a method and device for assessing the condition of transmission lines based on stress variation analysis of steel-cored aluminum stranded wire. This method uses simulation software to draw the steel-cored aluminum stranded wire and perform mesh generation to construct a three-dimensional stress mesh model. Under the coupling effect of a set physical field, the stress distribution is calculated, and the line operating condition is assessed based on the stress variation cloud map. This method has the following shortcomings: The analysis only focuses on stress changes and does not establish a multi-physics field fully coupled model that includes electrical, thermal, mechanical and environmental factors, so it cannot accurately reflect the thermal-mechanical-current-electric coupling effect of the conductor in the actual operating environment. The environmental conditions do not take into account actual changes and are usually only used as fixed boundary inputs, lacking real-time response simulation of the conductor's operating state in a dynamic environment; The simulation results failed to accurately reflect the actual aging state of the conductors because the model was not calibrated using real-time on-site data and the conductor material and environmental parameters were static or theoretical values.

[0008] Therefore, existing technologies are insufficient in terms of multi-field coupling integrity, operational condition reproduction accuracy, and data-driven calibration capabilities, making it difficult to achieve accurate assessment of the aging status of in-service conductors and prediction of their remaining life. Summary of the Invention

[0009] The purpose of this invention is to overcome the shortcomings of the existing technology and provide a multi-field coupling aging simulation method for steel-cored aluminum stranded wire based on actual operating data calibration.

[0010] The objective of this invention can be achieved through the following technical solutions: This invention provides a multi-field coupled aging simulation method for steel-cored aluminum stranded wire based on actual operating data calibration, comprising the following steps: Step S1: Establish a three-dimensional structural model of the target steel-cored aluminum stranded wire on a multiphysics simulation platform; Step S2: Based on the three-dimensional structural model, construct a multi-field coupled simulation model of electric field, thermal field, force field and environmental field, set material properties and boundary conditions, perform coupled solution, and obtain the initial simulation results of steel-cored aluminum stranded wire under current carrying and environmental action; Step S3: Construct a database of material parameters and environmental parameters, and use the material parameters and environmental parameters in the database as input conditions for the multi-field coupled simulation model to correct the initial simulation results; Step S4: Collect real-time on-site operating data of the target steel-cored aluminum stranded wire, and process the real-time operating data to obtain measured operating data for calibration; Step S5: Compare and analyze the measured running data with the corrected simulation results, and establish a parameter adjustment mechanism based on the deviation between the two. Step S6: Iteratively correct the material and environmental parameters in the multi-field coupled simulation model according to the parameter adjustment mechanism, and repeat steps S2 to S5 until the deviation between the simulation results and the measured running data meets the preset convergence condition, and obtain a calibration model that reflects the actual aging state of the steel-cored aluminum stranded wire. Step S7: Based on the calibration model, output the aging status evaluation results of steel-cored aluminum stranded wire under the multi-field coupling of electrothermal-mechanical and environmental effects.

[0011] Furthermore, the establishment of a three-dimensional structural model of the target steel-cored aluminum stranded wire on the multiphysics simulation platform specifically includes: Based on the specification manual and design requirements of the target steel-cored aluminum stranded wire, a three-dimensional geometric model including the steel core and aluminum strands is drawn. The parameters of the three-dimensional geometric model include the number of conductor strands, single diameter, strand diameter ratio, and pitch parameter. The three-dimensional geometric model is imported into a multiphysics simulation platform and meshed to obtain the three-dimensional structural model of the target steel-cored aluminum stranded wire.

[0012] Furthermore, the construction of a multi-field coupled simulation model of electric field, thermal field, force field, and environmental field based on the three-dimensional structural model specifically includes: In the three-dimensional structural model, current source boundary conditions are applied to define the current distribution in the conductor. Using the relationship between current density and electric field strength, the electric field control equation is established, the electric potential and electric field distribution are solved, and the heat source per unit volume is calculated according to Joule's law to construct the electric field model. Based on the heat source obtained from the electric field model, and combined with the ambient temperature boundary conditions, the heat conduction control equation is established, the temperature field distribution is solved, and a thermal field model is constructed. Based on the temperature field obtained from the thermal field model, a solid mechanics equilibrium equation is established, and constitutive relations are used to calculate the stress and strain distribution under the combined action of mechanical and thermal loads, thus constructing a force field model, wherein the strain is obtained by superimposing thermal expansion strain and mechanical load strain. An airflow region is established around the three-dimensional structural model. Environmental temperature, wind speed and external pressure boundary conditions are applied. Fluid continuity equation and momentum conservation equation are established to solve the flow field distribution around the conductor. The flow field and thermal field are coupled through convective heat transfer boundary conditions to construct an environmental field model. The electric field model, thermal field model, force field model, and environmental field model are coupled and solved simultaneously. The heat source generated by the electric field is used as the thermal field input, the temperature distribution of the thermal field is used as the thermal strain input of the force field, and the environmental field affects the thermal field distribution through convective heat transfer boundary conditions. The temperature field, stress field, and flow field distribution results of steel-cored aluminum stranded wire under the multi-field coupling of electrothermal-mechanical-environment are obtained, and a multi-field coupled simulation model is constructed.

[0013] Furthermore, the electric field control equation is as follows: in, For gradient operators, For electric potential, The electrical conductivity of the material; The governing equation for heat conduction is as follows: in, For material density, For specific heat capacity, For temperature, For time, Thermal conductivity, The heat source per unit volume obtained from the electric field model; The solid mechanics equilibrium equation is as follows: in, For stress tensor, Force per unit volume; The fluid continuity equation is as follows: in, It is the air velocity vector; The momentum conservation equation is as follows: in, air density, For pressure, Aerodynamic viscosity; The convective heat transfer boundary condition is expressed as follows: in, For heat exchange per unit area, The convective heat transfer coefficient is... The surface temperature of the conductor. The ambient temperature.

[0014] Furthermore, the material properties include: Electrical conductivity, thermal conductivity, density, specific heat capacity, elastic modulus, coefficient of thermal expansion, and Poisson's ratio of the steel core; Electrical conductivity, thermal conductivity, density, specific heat capacity, elastic modulus, coefficient of thermal expansion, and Poisson's ratio of aluminum stranded layers; The thermal contact coefficient between the aluminum stranded layer and the steel core contact surface; Environmental factors include air density, specific heat capacity, thermal conductivity, fluid dynamic viscosity, and wind speed. The boundary conditions include: Electric field boundary conditions, setting the current load on the conductor and the grounding potential; Thermal boundary conditions include convective heat transfer boundary conditions between the conductor surface and the air, with the convective heat transfer coefficient varying according to the conductor surface condition and ambient wind speed. Force field boundary conditions are set, and fixed supports and suspension methods are set at both ends of the conductor to simulate the stress and strain state caused by mechanical load and temperature changes; Environmental field boundary conditions, taking into account the influence of external meteorological factors on the conductor, set the inlet velocity and outlet pressure of the air flow domain.

[0015] Furthermore, the construction of the material and environmental parameter database specifically includes: Based on the material specification manual of the target steel-cored aluminum stranded wire, extract the material parameters of the steel core and aluminum stranded layer, including electrical conductivity, thermal conductivity, density, specific heat capacity, elastic modulus, coefficient of thermal expansion, Poisson's ratio and thermal contact coefficient. The environmental parameters of the area where the target steel-cored aluminum stranded wire is located over a recent period of time will be obtained. These environmental parameters include ambient temperature, relative humidity, wind speed, wind direction, and solar radiation intensity. The acquired material parameters are integrated with environmental parameters to construct a material and environmental parameter database.

[0016] Furthermore, the process of collecting real-time operational data of the target steel-cored aluminum stranded wire and processing the real-time operational data to obtain measured operational data for calibration specifically includes: By deploying an online monitoring system, including drones with multiple types of sensors, high-definition visible light and infrared thermal imagers, and communication modules, real-time operating data of the target steel-cored aluminum stranded wire is collected. The real-time operating data includes the wire's temperature, stress, current carrying capacity, vibration, wind speed, and ambient temperature. The real-time running data is transmitted to a cloud data center, which receives and stores multi-source heterogeneous data. The real-time operating data is preprocessed, including noise reduction, outlier removal, and data smoothing, to obtain measured operating data for calibration.

[0017] Furthermore, the step of comparing and analyzing the measured operating data with the corrected simulation results, and establishing a parameter adjustment mechanism based on the deviation between the two, specifically includes: The conductor temperature, stress, and current carrying capacity data obtained from the actual operation data are synchronized with the temperature field and stress field results output by the corrected multi-field coupled simulation model to construct a data matching sequence at the corresponding time. Based on the data matching sequence, the temperature deviation between the measured operating data and the simulation results is calculated respectively. and stress deviation The temperature deviation and stress deviation are expressed as follows: in, For temperature deviation, For the conductor temperature in the measured operating data, The output of the multi-field coupling simulation model shows the conductor temperature. For stress deviation, For the conductor stress in the measured operating data, The conductor stress output by the multi-field coupling simulation model; Based on temperature deviation and stress deviation Construct a comprehensive error function The formula is: in, , These are the weighting coefficients; With the error function With minimization as the goal, a parameter adjustment mechanism is established.

[0018] Furthermore, the parameter adjustment mechanism specifically includes: With minimizing the comprehensive error function J as the optimization objective, the material parameters and environmental parameters in the multi-field coupled simulation model are used as parameters to be corrected. Construct a parameter update model based on gradient iteration, with the parameter update formula expressed as: in, For any parameter to be corrected, For the number of iterations, For learning rate, For the comprehensive error function For parameters The partial derivatives; After each parameter update, the coupled solution of the multi-field coupled simulation model (electric field model, thermal field model, force field model, and environmental field model) is re-executed to obtain the updated temperature and stress field distribution results, and the comprehensive error function is recalculated. ; Determine the comprehensive error function Does it meet the preset convergence conditions?

[0019] Furthermore, the preset convergence conditions include: The comprehensive error function satisfies the threshold condition and is expressed as: in, This is the comprehensive error function. The preset error threshold is used; When the comprehensive error function meets the threshold condition, the multi-field coupled simulation model is determined to have reached the convergence state.

[0020] Compared with the prior art, the present invention has the following advantages: (1) In the prior art, the multi-field coupling simulation model of steel-cored aluminum stranded wire usually only considers electro-thermal coupling or thermo-mechanical coupling, and lacks full coupling modeling that covers electrical, thermal, mechanical and environmental factors, which makes it impossible to accurately reflect the multi-physics coupling effect of the conductor in actual operation. This invention establishes a three-dimensional structural model of steel-cored aluminum stranded wire on a multi-physics simulation platform, and constructs a multi-field coupling simulation model of electric field, thermal field, force field and environmental field. Combined with material properties and boundary conditions, the coupling solution is performed, realizing the full coupling analysis of conductor temperature field, stress field and flow field. This enables a more realistic simulation of the electro-thermal-mechanical-environmental coupling behavior of the conductor under current-carrying and complex environmental conditions, which significantly improves the accuracy of simulation results and engineering reference value.

[0021] (2) In the prior art, environmental conditions are usually treated as constant boundary inputs, ignoring the unique environmental changes in the region and the real-time interaction between the conductor and the environment. This results in the simulation results failing to reflect the temperature and stress fluctuations of the conductor under actual operating conditions. This invention collects historical meteorological data and real-time environmental data of the target conductor's area, including ambient temperature, relative humidity, wind speed, wind direction, and solar radiation intensity, and processes them into hourly variation curves for input into the simulation model. This enables the model to dynamically respond to environmental changes, achieving a high-precision reproduction of the conductor's operating environment, enhancing the correlation between simulation results and actual operating conditions, and supporting more reliable aging assessments and operational status predictions.

[0022] (3) In the prior art, the conductor material parameters are usually derived from the manufacturer's manual or theoretical design values, without considering the changes in conductor aging during service, and lacking closed-loop calibration with field data, resulting in poor correlation between simulation results and actual aging patterns. This invention collects conductor temperature, stress, current carrying capacity, vibration, and environmental data by deploying an online monitoring system, and performs noise reduction and outlier removal on the measured data. Combined with a closed-loop calibration mechanism, the measured operating data is compared with the simulation results, and the material and environmental parameters are iteratively updated, realizing dynamic correction of model parameters. This enables the simulation model to reflect the actual aging state of the conductor, thereby significantly improving simulation accuracy and prediction reliability.

[0023] (4) In the prior art, traditional aging assessment methods rely on aging tests, which are time-consuming, costly, and difficult to replicate the actual operating environment under experimental conditions, easily underestimating the actual aging rate of the conductor. This invention inputs measured operating data into a simulation model and performs iterative optimization of parameters based on an error function to form a real-time calibrated aging simulation model. This allows the simulation model to directly reflect the aging behavior of the conductor under complex current loads and environmental effects, thereby effectively compensating for the shortcomings of traditional test methods in terms of timeliness and environmental realism, and achieving efficient, low-cost, and realistic conductor aging assessment.

[0024] (5) In the prior art, existing simulation methods (such as CN120493513A) only focus on the stress distribution of the conductor, ignoring the comprehensive influence of temperature, current carrying capacity and environmental factors on aging, and lack data-driven closed-loop calibration, resulting in a large deviation between the evaluation results and the actual operating conditions. This invention establishes a comprehensive error function based on measured data for temperature deviation and stress deviation, and uses a gradient iterative algorithm to optimize and update material parameters and environmental parameters, thereby achieving closed-loop coupling calibration between the simulation model and actual operating data. This enables the simulation results to comprehensively reflect the temperature, stress and environmental conditions of the conductor, and achieves high-precision prediction of the conductor's operating conditions and assessment of aging trends under multi-physics fields. Attached Figure Description

[0025] Figure 1 This is a flowchart of the aging simulation method according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the overall logic of an embodiment of the present invention; Figure 3 This is a schematic diagram of the finite element model of an embodiment of the present invention; Figure 4 This is a schematic diagram of the electrothermal-mechanical multiphysics simulation results of an embodiment of the present invention; Figure 5 This is a schematic diagram of the electrothermal-environmental multiphysics simulation results of an embodiment of the present invention. Detailed Implementation

[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0027] Example 1: To address the shortcomings or improvement needs of existing technologies, this invention provides a multi-field coupled aging simulation method for steel-cored aluminum stranded wire based on actual operating data calibration, aiming to solve the problem of the disconnect between traditional simulation models and actual operating conditions. The multi-field coupled aging simulation method for steel-cored aluminum stranded wire based on actual operating data calibration mainly consists of three parts: a multi-field coupled calculation unit, a material environmental parameter integration unit, and a real-time data calibration unit. The multi-field coupled calculation unit is built based on CAD 3D design software and a finite element analysis platform. By coupling the control equations of electric field, thermal field, force field, and environmental field, it simultaneously calculates the temperature distribution, stress-strain, and velocity-pressure changes of the steel-cored aluminum stranded wire under the combined effects of current carrying capacity, mechanical load, heat source, and external environmental factors. The material environmental parameter integration unit integrates and analyzes company equipment ledgers, historical data, fault information, and regional environmental databases through a computer, and inputs this data into the multi-field coupled calculation unit to simulate the impact of regional environmental conditions and material parameter changes on aging. The real-time data calibration unit collects operational data such as conductor current and surface temperature from on-site monitoring devices through communication modules, sensors, infrared imaging, and drones. This data is then fed back to the material environment parameter integration unit for correction, reducing simulation deviations caused by the solidification of model parameters. This invention provides a reliable basis for transmission line condition assessment, lifespan prediction, and operation and maintenance strategy formulation through simulation.

[0028] This embodiment provides a multi-field coupled aging simulation method for steel-cored aluminum stranded wire based on actual operating data calibration, such as... Figure 1 As shown, it includes the following steps: Step S1: Establish a three-dimensional structural model of the target steel-cored aluminum stranded wire on a multiphysics simulation platform, specifically including: On a multiphysics simulation platform, the first step is to establish a three-dimensional structural model of the target steel-cored aluminum stranded wire. To this end, detailed geometric modeling is performed based on the specifications and design requirements of the target steel-cored aluminum stranded wire. This process includes drawing the three-dimensional geometric model of the steel core and aluminum strands, and setting parameters such as the number of conductor strands, the diameter of each strand, the pitch ratio, and the twist rate according to actual conditions. These geometric parameters are key factors affecting the electrical, thermal, and mechanical properties of the steel-cored aluminum stranded wire; therefore, the accuracy and rationality of these parameters must be ensured.

[0029] After completing the geometric modeling, the model is imported into a multiphysics simulation platform for mesh generation. Mesh generation is fundamental to the simulation model; fine meshing improves computational accuracy and ensures the reliability of simulation results. For each computational unit, the platform automatically generates the corresponding mesh based on the model's geometric features and physical properties. After mesh generation, a three-dimensional structural model of the target steel-cored aluminum stranded wire is obtained, providing accurate geometric data support for subsequent multi-field coupled simulations.

[0030] In this way, the geometry and material parameters of the conductor can be accurately reproduced, ensuring that subsequent simulation work can be based on a real physical model, thereby improving the credibility and application value of the simulation results.

[0031] Step S2: Based on the three-dimensional structural model, construct a multi-field coupled simulation model of electric field, thermal field, force field and environmental field, set material properties and boundary conditions, perform coupled solution, and obtain the initial simulation results of steel-cored aluminum stranded wire under current carrying and environmental action; This includes constructing a multi-field coupled simulation model of electric field, thermal field, force field, and environmental field based on the three-dimensional structural model, specifically including: In the three-dimensional structural model, current source boundary conditions are applied to define the current distribution in the conductor, and the relationship between current density and electric field strength is utilized. Establish the electric field control equations The electric potential and electric field distribution are solved, and the heat source per unit volume is calculated according to Joule's law to construct an electric field model; among which, For current density, For the electrical conductivity of the material, For electric field strength, For electric potential, This is the gradient operator.

[0032] Based on the heat source obtained from the electric field model, and combined with the ambient temperature boundary conditions, the heat conduction governing equation is established: in, For material density, For specific heat capacity, For temperature, For time, Thermal conductivity, A heat source per unit volume is obtained from the electric field model; the temperature field distribution is solved to construct a thermal field model; Based on the temperature field obtained from the thermal field model, the equilibrium equations of solid mechanics are established: in, For stress tensor, The force is the volumetric force per unit volume; and constitutive relations are used: in, For the elasticity matrix, For total strain, For thermal expansion strain, The coefficient of linear expansion is 1 / 3. Using the reference temperature, the stress and strain distribution under the combined action of mechanical and thermal loads is calculated, and a force field model is constructed, wherein the total strain is obtained by superimposing the thermal expansion strain and the mechanical load strain. An airflow region is established around the three-dimensional structural model, and boundary conditions of ambient temperature, wind speed, and external pressure are applied to establish the fluid continuity equation. And the momentum conservation equation: in, air density, For pressure, Given the aerodynamic viscosity; solve for the flow field distribution around the conductor, and couple the flow field and thermal field through convective heat transfer boundary conditions to construct an environmental field model; the convective heat transfer boundary conditions are expressed as: in, For heat exchange per unit area, The convective heat transfer coefficient is... The surface temperature of the conductor. The ambient temperature.

[0033] The electric field model, thermal field model, force field model, and environmental field model are coupled and solved simultaneously. The heat source generated by the electric field is used as the thermal field input, the temperature distribution of the thermal field is used as the thermal strain input of the force field, and the environmental field affects the thermal field distribution through convective heat transfer boundary conditions. The temperature field, stress field, and flow field distribution of steel-cored aluminum stranded wire under the multi-field coupling of electrothermal-mechanical-environment are obtained, and a multi-field coupled simulation model is constructed.

[0034] Step S3: Construct a database of material and environmental parameters, and use the material and environmental parameters in the database as input conditions for the multi-field coupled simulation model to correct the initial simulation results; In step S3, a database of material and environmental parameters is first constructed, and the data in this database is used as input conditions for the multi-field coupled simulation model to correct the initial simulation results. The accuracy of the material and environmental parameters is crucial to the accuracy of the simulation model; therefore, it is necessary to consider and collect relevant data in detail.

[0035] Specifically, material properties include various physical parameters of the steel core and aluminum stranded layers. The material properties of the steel core include electrical conductivity, thermal conductivity, density, specific heat capacity, elastic modulus, coefficient of thermal expansion, and Poisson's ratio; the material properties of the aluminum stranded layers include electrical conductivity, thermal conductivity, density, specific heat capacity, elastic modulus, coefficient of thermal expansion, and Poisson's ratio. The thermal contact coefficient at the interface between the aluminum stranded layers and the steel core should also be considered as a key parameter, as it has a significant impact on the heat transfer characteristics of the conductor.

[0036] Regarding environmental factors, parameters such as air density, specific heat capacity, thermal conductivity, fluid dynamic viscosity, and wind speed need to be collected and considered. These environmental parameters directly affect the heat exchange process, stress changes, and current distribution of the conductor, thus having a significant impact on the actual operation of the conductor.

[0037] By comprehensively considering the above material properties and environmental factors, the constructed database will provide accurate input conditions for the multi-field coupled simulation model. In this way, the initial simulation results, with corrections based on actual data, can more accurately reflect the aging of steel-cored aluminum stranded wire in actual operation, providing a reliable basis for subsequent aging assessment.

[0038] Step S4: Collect real-time on-site operating data of the target steel-cored aluminum stranded wire, and process the real-time operating data to obtain measured operating data for calibration; In step S4, an online monitoring system needs to be deployed to collect real-time operational data of the target steel-cored aluminum stranded wire. This system can include various types of sensors, drones equipped with high-definition visible light and infrared thermal imagers, and communication modules. These devices can monitor the conductor's operational status around the clock and from all angles. Through these monitoring devices, key data related to the conductor's condition can be acquired, including but not limited to conductor temperature, stress, current carrying capacity, vibration, wind speed, and ambient temperature.

[0039] Specifically, the monitoring system first collects real-time temperature data of the conductor. This data reflects the thermal state of the conductor under different operating conditions, thus predicting the aging trend of the conductor. Stress data helps assess the mechanical load on the conductor during operation and the thermal stress caused by temperature changes. Current-carrying capacity data can be used to calculate the conductor's load condition, further affecting the accumulation of Joule heat and the aging rate of the conductor. Vibration data provides information about the conductor's mechanical deformation and external disturbances, while wind speed and ambient temperature data help accurately describe the environmental conditions in which the conductor operates, thereby better predicting the aging of the conductor under different environments.

[0040] The collected real-time operational data is transmitted to a cloud data center for storage and management. To ensure the accuracy and validity of the data, it undergoes preprocessing, including noise reduction, outlier removal, and data smoothing. This preprocessed data serves as the actual operational data for calibration and will be used as the basis for subsequent model correction and optimization.

[0041] This process enables the acquisition of measured data that closely reflects the actual operating state of the conductor, providing a reliable basis for the subsequent calibration of the multi-field coupled simulation model and ensuring that the simulation results accurately reflect the aging state of the conductor under actual operating conditions. This process is a key step in the method of this invention, providing solid data support for achieving accurate condition assessment and life prediction.

[0042] Step S5: Compare and analyze the measured running data with the corrected simulation results, and establish a parameter adjustment mechanism based on the deviation between the two, specifically including: The conductor temperature, stress, and current carrying capacity data obtained from the actual operation data are synchronized with the temperature field and stress field results output by the corrected multi-field coupled simulation model to construct a data matching sequence at the corresponding time. Based on the data matching sequence, the temperature deviation between the measured operating data and the simulation results is calculated respectively. and stress deviation Temperature deviation and stress deviation are expressed as follows: in, For temperature deviation, For the conductor temperature in the measured operating data, The output of the multi-field coupling simulation model shows the conductor temperature. For stress deviation, For the conductor stress in the measured operating data, The conductor stress output by the multi-field coupling simulation model; Based on temperature deviation and stress deviation Construct a comprehensive error function The formula is: in, , These are the weighting coefficients; With error function With minimization as the goal, a parameter adjustment mechanism is established.

[0043] Step S6: Iteratively correct the material and environmental parameters in the multi-field coupled simulation model according to the parameter adjustment mechanism, and repeat steps S2 to S5 until the deviation between the simulation results and the measured running data meets the preset convergence condition, and obtain a calibration model that reflects the actual aging state of the steel-cored aluminum stranded wire. The parameter adjustment mechanism specifically includes: With minimizing the comprehensive error function J as the optimization objective, the material parameters and environmental parameters in the multi-field coupled simulation model are used as parameters to be corrected. Construct a parameter update model based on gradient iteration, with the parameter update formula expressed as: in, For any parameter to be corrected, For the number of iterations, For learning rate, For the comprehensive error function For parameters The partial derivatives; After each parameter update, the coupled solution of the multi-field coupled simulation model (electric field model, thermal field model, force field model, and environmental field model) is re-executed to obtain the updated temperature and stress field distribution results, and the comprehensive error function is recalculated. ; Determine the comprehensive error function Does it meet the preset convergence conditions?

[0044] The preset convergence conditions include: The comprehensive error function satisfies the threshold condition and is expressed as: in, This is the comprehensive error function. The preset error threshold is used; When the comprehensive error function meets the threshold condition, the multi-field coupled simulation model is determined to have reached the convergence state.

[0045] Step S7: Based on the calibration model, output the aging status assessment results of steel-cored aluminum stranded wire under the multi-field coupling of electrothermal-mechanical and environmental effects, specifically including: After completing closed-loop calibration with measured data, the calibration model possesses high accuracy and realism, capable of reflecting the aging characteristics of steel-cored aluminum stranded wire under different operating conditions. Based on this calibration model, the system will input real-time operating data of the target steel-cored aluminum stranded wire, including information such as conductor temperature, stress, current carrying capacity, wind speed, and ambient temperature. This input data not only includes static environmental parameters but also reflects multiple factors such as current load, mechanical stress, and environmental influences experienced by the conductor during actual operation.

[0046] The calibration model uses multiphysics coupling simulation to calculate the temperature, stress, strain, and other related physical field distributions of the conductor under the coupled effects of multiple fields, including electro-thermal, thermo-mechanical, and force-environmental factors. By comprehensively analyzing the changes in these fields, the model can provide a comprehensive assessment of the aging state of the steel-cored aluminum stranded wire. The assessment results mainly include the conductor's temperature changes, stress and strain states, decrease in mechanical strength, and damage to the conductor structure caused by Joule heating.

[0047] The assessment results will provide crucial information for the operation and maintenance of power systems. By analyzing the aging degree, remaining lifespan, and potential failure modes of conductors, the system can provide power companies with more accurate condition assessments, helping to determine whether repairs, reinforcement, or replacement of conductors are necessary. This real-time assessment and prediction capability can effectively improve the operational safety and economy of power systems, reduce sudden failures caused by aging power equipment, and ensure the long-term stable operation of transmission lines.

[0048] The aging status assessment results output by the calibration model of this invention not only improve the accuracy of traditional power line health monitoring, but also provide data support and scientific basis for future power line design, optimized operation strategies and fault early warning systems.

[0049] Example 2: This embodiment provides a multi-field coupled aging simulation method based on actual operating data calibration, which combines electrothermal-environmental data. Its core system architecture consists of a multi-field coupled calculation unit, a material and environmental parameter integration unit, and a real-time data calibration unit. The overall logical diagram is shown below. Figure 2 As shown. The specific implementation method includes the following steps: This implementation plan uses ACSR-720 / 50 steel-cored aluminum stranded wire as the object. The first step is to construct an accurate 3D geometric model of the steel-cored aluminum stranded wire using professional computer-aided design (CAD) 3D design software. The key to modeling is to accurately draw geometric parameters such as the number of conductor strands, single strand diameter, strand diameter ratio, and pitch. For ACSR-720 / 50, there is a manufacturer's datasheet available. Each aluminum strand and copper core needs to be modeled independently according to the datasheet to ensure the accuracy of subsequent multiphysics coupling simulation analysis. After completing the geometric modeling, the constructed 3D model needs to be exported in the STEP general format and imported into the finite element analysis platform. The high-precision model drawing will lay a solid foundation for subsequent mesh generation and boundary condition setting.

[0050] Secondly, the 3D model of the conductor, created using design software, is imported into the finite element simulation platform to efficiently handle and calculate the complex interactions between multiple physical fields. For example, based on the ACSR-720 / 50 specification manual, conductor ledger, and historical information, material parameters for the steel core and aluminum stranded layers are assigned, including electrical conductivity, thermal conductivity, density, specific heat capacity, elastic modulus, and thermal expansion characteristics. First, current loads are applied to the conductor ends at the selected terminals and grounding points, and the Joule heat distribution within the conductor is calculated by solving the current field. Next, a cuboid region is constructed outside the model to simulate the heat exchange between the external conductor surface and the surrounding air. Then, based on the suspension method of the conductor in actual line service, time-fixed constraints are applied at both ends of the model to calculate the stress and strain caused by the combined mechanical and thermal loads. To accurately simulate the impact of sea winds on conductors in special areas such as coastal areas, inlet and outlet wind velocities are set for the external airflow domain, and fluid-structure interaction simulation calculations are performed to accurately obtain the wind pressure distribution and convective heat transfer on the conductor surface. Figure 3 As shown, this is a finite element mesh generation model for a conductor based on multi-physics coupling analysis and coordinated optimization of geometric design parameters.

[0051] Next, the material and environmental parameter integration unit provides accurate data for the multi-field coupled simulation model. Through computer-programmed processing, the system integrates the company's equipment ledger, historical maintenance records, material manuals, and relevant technical standards to construct a complete material parameter database. Based on this, material parameters of the ACSR-720 / 50 conductor are extracted, including key properties such as resistivity, thermal conductivity, specific heat capacity, density, elastic modulus, Poisson's ratio, and coefficient of thermal expansion for both steel and aluminum cores. Simultaneously, regional meteorological databases or historical meteorological data are accessed to obtain long-term environmental data for the target line's location, covering multi-dimensional indicators such as ambient temperature, solar radiation intensity, wind speed, wind direction, and humidity. Furthermore, traditional static environmental parameters are processed into hourly variation curves over a day or month, thereby more accurately simulating the impact of the regional environment on conductor aging. All integrated material and environmental parameters are input into the multi-field coupled calculation unit as the initial and boundary conditions of the simulation model.

[0052] Finally, an online monitoring system was deployed on the transmission lines of the target substation. This system integrates multiple types of sensors, a drone equipped with a high-definition visible light and infrared thermal imager, and a communication module to achieve real-time acquisition and cloud transmission of conductor operation data. After receiving the multi-source heterogeneous data, the cloud data center initiates a dedicated data processing algorithm for preprocessing, including noise reduction and outlier removal, effectively improving data quality. Subsequently, a closed-loop calibration mechanism is implemented. The simulation system first calculates the theoretical temperature and stress of the conductor based on initial parameters and synchronous environmental data. Then, the simulation results are compared with the measured temperature from infrared imaging, and the temperature difference error is calculated. Subsequently, with minimizing the temperature error as the optimization objective, the system automatically iteratively adjusts parameters such as the thermal conductivity and resistivity of the conductor material. Calibration is completed when the error converges to within a preset threshold. Figure 4 The figure shows the results of ACSR-720 / 50 electrothermal multiphysics simulation. The intermediate expansion phenomenon is caused by the stress-deformation coupling effect resulting from the difference in thermal expansion coefficients between the aluminum strand and the steel core, and the squeezing effect of the aluminum strand on the steel core under axial constraint. Figure 5 The results of the electrothermal-environment multiphysics simulation explain the variation of convective heat transfer intensity with spatial location under wind speed. Its distribution characteristics are directly related to the temperature field gradient and the fluid velocity field, demonstrating the heat transfer mechanism under electrothermal-environment coupling. Following this process, the model parameters will be updated to equivalent parameters reflecting the actual aging state of the conductors, improving the consistency between the simulation model and actual operating conditions.

[0053] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0054] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A multi-field coupled aging simulation method for steel-cored aluminum stranded wire based on actual operating data calibration, characterized in that, Includes the following steps: Step S1: Establish a three-dimensional structural model of the target steel-cored aluminum stranded wire on a multiphysics simulation platform; Step S2: Based on the three-dimensional structural model, construct a multi-field coupled simulation model of electric field, thermal field, force field and environmental field, set material properties and boundary conditions, perform coupled solution, and obtain the initial simulation results of steel-cored aluminum stranded wire under current carrying and environmental action; Step S3: Construct a database of material parameters and environmental parameters, and use the material parameters and environmental parameters in the database as input conditions for the multi-field coupled simulation model to correct the initial simulation results; Step S4: Collect real-time on-site operating data of the target steel-cored aluminum stranded wire, and process the real-time operating data to obtain measured operating data for calibration; Step S5: Compare and analyze the measured running data with the corrected simulation results, and establish a parameter adjustment mechanism based on the deviation between the two. Step S6: Iteratively correct the material and environmental parameters in the multi-field coupled simulation model according to the parameter adjustment mechanism, and repeat steps S2 to S5 until the deviation between the simulation results and the measured running data meets the preset convergence condition, and obtain a calibration model that reflects the actual aging state of the steel-cored aluminum stranded wire. Step S7: Based on the calibration model, output the aging status evaluation results of steel-cored aluminum stranded wire under the multi-field coupling of electrothermal-mechanical and environmental effects.

2. The multi-field coupled aging simulation method for steel-cored aluminum stranded wire based on actual operating data calibration according to claim 1, characterized in that, The establishment of a three-dimensional structural model of the target steel-cored aluminum stranded wire on a multiphysics simulation platform specifically includes: Based on the specification manual and design requirements of the target steel-cored aluminum stranded wire, a three-dimensional geometric model including the steel core and aluminum strands is drawn. The parameters of the three-dimensional geometric model include the number of conductor strands, single diameter, strand diameter ratio, and pitch parameter. The three-dimensional geometric model is imported into a multiphysics simulation platform and meshed to obtain a three-dimensional structural model of the target steel-cored aluminum stranded wire.

3. The multi-field coupled aging simulation method for steel-cored aluminum stranded wire based on actual operating data calibration according to claim 1, characterized in that, The construction of a multi-field coupled simulation model of electric field, thermal field, force field and environmental field based on the three-dimensional structural model specifically includes: In the three-dimensional structural model, current source boundary conditions are applied to define the current distribution in the conductor. Using the relationship between current density and electric field strength, the electric field control equation is established, the electric potential and electric field distribution are solved, and the heat source per unit volume is calculated according to Joule's law to construct the electric field model. Based on the heat source obtained from the electric field model, and combined with the ambient temperature boundary conditions, the heat conduction control equation is established, the temperature field distribution is solved, and a thermal field model is constructed. Based on the temperature field obtained from the thermal field model, a solid mechanics equilibrium equation is established, and constitutive relations are used to calculate the stress and strain distribution under the combined action of mechanical and thermal loads, thus constructing a force field model, wherein the strain is obtained by superimposing thermal expansion strain and mechanical load strain. An airflow region is established around the three-dimensional structural model. Environmental temperature, wind speed and external pressure boundary conditions are applied. Fluid continuity equation and momentum conservation equation are established to solve the flow field distribution around the conductor. The flow field and thermal field are coupled through convective heat transfer boundary conditions to construct an environmental field model. The electric field model, thermal field model, force field model, and environmental field model are coupled and solved simultaneously. The heat source generated by the electric field is used as the thermal field input, the temperature distribution of the thermal field is used as the thermal strain input of the force field, and the environmental field affects the thermal field distribution through convective heat transfer boundary conditions. The temperature field, stress field, and flow field distribution of steel-cored aluminum stranded wire under the multi-field coupling of electrothermal-mechanical-environment are obtained, and a multi-field coupled simulation model is constructed.

4. The multi-field coupled aging simulation method for steel-cored aluminum stranded wire based on actual operating data calibration according to claim 3, characterized in that, The electric field control equation is as follows: in, For gradient operators, For electric potential, The electrical conductivity of the material; The governing equation for heat conduction is as follows: in, For material density, For specific heat capacity, For temperature, For time, Thermal conductivity, A heat source per unit volume obtained from an electric field model; The solid mechanics equilibrium equation is as follows: in, For stress tensor, Force per unit volume; The fluid continuity equation is as follows: in, It is the air velocity vector; The momentum conservation equation is as follows: in, air density, For pressure, Aerodynamic viscosity; The convective heat transfer boundary condition is expressed as follows: in, For heat exchange per unit area, The convective heat transfer coefficient is... The surface temperature of the conductor. The ambient temperature.

5. The multi-field coupled aging simulation method for steel-cored aluminum stranded wire based on actual operating data calibration according to claim 1, characterized in that, The material properties include: Electrical conductivity, thermal conductivity, density, specific heat capacity, elastic modulus, coefficient of thermal expansion, and Poisson's ratio of the steel core; Electrical conductivity, thermal conductivity, density, specific heat capacity, elastic modulus, coefficient of thermal expansion, and Poisson's ratio of aluminum stranded layers; The thermal contact coefficient between the aluminum stranded layer and the steel core contact surface; Environmental factors include air density, specific heat capacity, thermal conductivity, fluid dynamic viscosity, and wind speed. The boundary conditions include: Electric field boundary conditions, setting the current load on the conductor and the grounding potential; Thermal boundary conditions include convective heat transfer boundary conditions between the conductor surface and the air, with the convective heat transfer coefficient varying according to the conductor surface condition and ambient wind speed. Force field boundary conditions are set, and fixed supports and suspension methods are set at both ends of the conductor to simulate the stress and strain state caused by mechanical load and temperature changes; Environmental field boundary conditions, taking into account the influence of external meteorological factors on the conductor, set the inlet velocity and outlet pressure of the air flow domain.

6. The multi-field coupled aging simulation method for steel-cored aluminum stranded wire based on actual operating data calibration according to claim 1, characterized in that, The constructed material and environmental parameter database specifically includes: Based on the material specification manual of the target steel-cored aluminum stranded wire, extract the material parameters of the steel core and aluminum stranded layer, including electrical conductivity, thermal conductivity, density, specific heat capacity, elastic modulus, coefficient of thermal expansion, Poisson's ratio and thermal contact coefficient. The environmental parameters of the area where the target steel-cored aluminum stranded wire is located over a recent period of time will be obtained. These environmental parameters include ambient temperature, relative humidity, wind speed, wind direction, and solar radiation intensity. The acquired material parameters are integrated with environmental parameters to construct a material and environmental parameter database.

7. The multi-field coupled aging simulation method for steel-cored aluminum stranded wire based on actual operating data calibration according to claim 1, characterized in that, The process involves collecting real-time operational data of the target steel-cored aluminum stranded wire and processing this data to obtain measured operational data for calibration. Specifically, this includes: By deploying an online monitoring system, including drones with multiple types of sensors, high-definition visible light and infrared thermal imagers, and communication modules, real-time operating data of the target steel-cored aluminum stranded wire is collected. The real-time operating data includes the wire's temperature, stress, current carrying capacity, vibration, wind speed, and ambient temperature. The real-time running data is transmitted to a cloud data center, which receives and stores multi-source heterogeneous data. The real-time operating data is preprocessed, including noise reduction, outlier removal, and data smoothing, to obtain measured operating data for calibration.

8. The multi-field coupled aging simulation method for steel-cored aluminum stranded wire based on actual operating data calibration according to claim 1, characterized in that, The step of comparing and analyzing the measured operating data with the corrected simulation results, and establishing a parameter adjustment mechanism based on the deviation between the two, specifically includes: The conductor temperature, stress, and current carrying capacity data obtained from the actual operation data are synchronized with the temperature field and stress field results output by the corrected multi-field coupled simulation model to construct a data matching sequence at the corresponding time. Based on the data matching sequence, the temperature deviation between the measured operating data and the simulation results is calculated respectively. and stress deviation The temperature deviation and stress deviation are expressed as follows: in, For temperature deviation, For the conductor temperature in the measured operating data, The output of the multi-field coupling simulation model shows the conductor temperature. For stress deviation, For the conductor stress in the measured operating data, The conductor stress output by the multi-field coupling simulation model; Based on temperature deviation and stress deviation Construct a comprehensive error function The formula is: in, , These are the weighting coefficients; With the error function With minimization as the goal, a parameter adjustment mechanism is established.

9. The multi-field coupled aging simulation method for steel-cored aluminum stranded wire based on actual operating data calibration according to claim 8, characterized in that, The parameter adjustment mechanism specifically includes: With minimizing the comprehensive error function J as the optimization objective, the material parameters and environmental parameters in the multi-field coupled simulation model are used as parameters to be corrected. Construct a parameter update model based on gradient iteration, with the parameter update formula expressed as: in, For any parameter to be corrected, For the number of iterations, For learning rate, For the comprehensive error function For parameters The partial derivatives; After each parameter update, the coupled solution of the multi-field coupled simulation model (electric field model, thermal field model, force field model, and environmental field model) is re-executed to obtain the updated temperature and stress field distributions, and the comprehensive error function is recalculated. ; Determine the comprehensive error function Does it meet the preset convergence conditions? 10. The multi-field coupled aging simulation method for steel-cored aluminum stranded wire based on actual operating data calibration according to claim 1, characterized in that, The preset convergence conditions include: The comprehensive error function satisfies the threshold condition and is expressed as: in, This is the comprehensive error function. The preset error threshold is used; When the comprehensive error function meets the threshold condition, the multi-field coupled simulation model is determined to have reached the convergence state.

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