High-voltage switch cabinet contact service life management system based on digital twinning

Abstract

The invention relates to the technical field of life prediction, in particular to a high-voltage switch cabinet contact life management system based on digital twinning, which comprises a thermal behavior acquisition module, a conductive state construction module, a thermal loss dynamic evaluation module, a thermal disturbance response regulation and control module and a life mapping driving module. According to the method, temperature difference and time interval in an on-off period are collected, thermal stress change is calculated in combination with current density, thermal characteristics of materials are correlated, thermal behaviors of a contact are dynamically reflected, a conductive path boundary is reconstructed based on contact area and pressure offset, a through-flow state is accurately described, and heat accumulation and arc energy input are extracted. The method comprises the steps of analyzing a temperature trend under thermal diffusion lag, constructing a heat loss evolution curve, adjusting thermal conductivity distribution through a ratio of temperature rise to mass migration rate, improving local adaptability of thermal disturbance response, generating a life attenuation layer in combination with equivalent thermal mechanical load and fatigue tolerance, and enhancing dynamic nature and precision of evaluation. And accurate judgment and management of the degradation area are realized.

Description

Technical Field

[0001] This invention relates to the field of life prediction technology, and in particular to a high-voltage switchgear contact life management system based on digital twins. Background Technology

[0002] The field of life prediction technology involves modeling, assessing the condition, and estimating the remaining service life of key components in mechanical and electrical equipment during operation. Its core aspects include fault mechanism modeling, operational data acquisition, life modeling method construction, and life prediction mechanisms based on historical data and real-time conditions. The overall technology utilizes statistical analysis, physical models, and machine learning to perform multi-source fusion and evolutionary reasoning on the state parameters of equipment under different operating conditions, thereby enabling the prediction of the future state of key components. Specifically, the traditional high-voltage switchgear contact life management system relies on periodic manual inspections or statistical data based on a single environment and number of operations to determine contact wear status. This technology primarily addresses the mechanical wear and electro-corrosion problems caused by frequent operations, contact arcs, and environmental stress during the operation of high-voltage switchgear. Traditional methods use timed inspections to record the number of operations or collect single parameters such as contact resistance, judging the degradation state and lifespan of the contacts based on their threshold changes.

[0003] Traditional life management methods generally rely on periodic manual inspections or condition assessments based on single parameters such as the number of operations or contact resistance. These methods struggle to dynamically monitor complex thermodynamic behaviors during operation. Because the heat accumulation, mechanical wear, and electro-corrosion processes caused by the frequency of operation, arc impact, and environmental stress on the contacts are highly coupled, a single parameter threshold cannot fully reflect the true degradation process. For example, in the early stages of contact surface oxidation, this parameter changes only slightly, failing to trigger timely warnings and easily leading to the omission of early degradation. While the number of operations provides a frequency reference, it ignores the coupling effect of current carrying capacity and thermal disturbance, easily causing life assessment biases. Without feedback mechanisms for thermal stress distribution and localized degradation, it is difficult to grasp the evolution trajectory of the actual conductive area of ​​the contacts, further limiting the intelligence and precision of life management and easily creating blind spots in management, such as over-maintenance or misjudgment of fault risks. Summary of the Invention

[0004] To address the technical problems existing in the prior art, this invention provides a high-voltage switchgear contact life management system based on digital twins. The technical solution is as follows:

[0005] On the one hand, a digital twin-based high-voltage switchgear contact life management system is provided, which includes:

[0006] The thermal behavior acquisition module monitors the temperature change of the contact surface of the contact, records the temperature difference and time interval of the on / off cycle, calculates the ratio of temperature change rate to current density, and generates thermal behavior response data by combining the thermal expansion coefficient of the material.

[0007] The conductivity state construction module calls the thermal behavior response data, calculates the contact area change, combines the pressure offset to calculate the shrinkage amplitude of the conductive region, reconstructs the flow path boundary of the twin model, and generates a conductivity mapping structure.

[0008] The thermal loss dynamic assessment module extracts the changes in heat accumulation based on the conductive mapping structure, calculates the energy input rate by combining the arc duration, and compares it with the heat diffusion time constant to generate a thermal loss evolution trend line.

[0009] The thermal disturbance response control module calls the thermal loss evolution trend line to obtain the temperature rise rate, compares it with the mass migration rate, calculates the proportional relationship, adjusts the model thermal conductivity, updates the thermal diffusion distribution, forms a thermal disturbance response spectrum, and generates a control value spectrum.

[0010] The life mapping driving module calls the control value map, selects the point with the highest control coefficient, extracts the heat loss distribution, calculates the equivalent thermomechanical load by combining it with the contact pressure, compares it with the thermal fatigue tolerance, assigns a life decay coefficient, and generates a life mapping layer.

[0011] As a further aspect of the present invention, the thermal behavior response data includes temperature change rate, current density ratio, thermal stress change law per unit time, and thermal expansion coefficient related parameters; the conductive mapping structure includes contact area change value, contact pressure offset, flow path boundary, and conductive region boundary range; the thermal loss evolution trend line includes heat accumulation change value, arc energy input rate, temperature distribution trend, and thermal loss change curve; the control value spectrum includes temperature rise change rate, mass migration rate ratio, thermal conductivity adjustment coefficient, and thermal diffusion distribution spectrum; and the lifetime mapping layer includes thermal loss distribution, contact pressure distribution value, equivalent thermomechanical load parameters, and lifetime decay coefficient.

[0012] As a further aspect of the present invention, the thermal behavior acquisition module includes:

[0013] The temperature monitoring submodule monitors the temperature change of the contact surface between the moving contact and the stationary contact in each on-off cycle, collects the temperature values ​​at the corresponding moments of on and off, records the temperature difference and time interval within the cycle, and generates a set of data on the cycle temperature difference and time interval.

[0014] The rate calculation submodule calculates the temperature change rate value corresponding to a unit current density based on the periodic temperature difference and time interval group data, combined with the current density within the on / off cycle, and generates a current density to temperature change rate value sequence.

[0015] The thermal stress correlation submodule calls the current density to temperature change rate sequence and the thermal expansion coefficient of the contact material to calculate the thermal stress change amplitude in each cycle, summarizes the cycle results, and generates thermal behavior response data.

[0016] As a further aspect of the present invention, the conductivity state construction module includes:

[0017] The area calculation submodule calls the thermal behavior response data to obtain the temperature gradient and boundary change parameters of the contact area of ​​the conductive main circuit contact assembly. Combined with the deformation characteristics of the contact surface during the switching cycle, it calculates the contact area change value of the contact assembly in the conductive state and generates the contact area change amount.

[0018] The pressure offset submodule acquires the contact pressure sensing signal during the conduction process based on the change in the contact area of ​​the contact, extracts the contact pressure change trend within the on / off cycle, calculates the degree of difference between the contact pressure and the area change trend, and obtains the shrinkage amplitude value of the conductive area.

[0019] The path construction submodule calls the contraction amplitude value of the conductive region and the boundary conditions of the flow path in the twin model to identify the variation range of the path boundary within the on / off cycle, extract the correspondence between the flow point position and the boundary point, calculate the boundary range of the conductive region, and generate the conductive mapping structure.

[0020] As a further aspect of the present invention, the dynamic heat loss assessment module includes:

[0021] The heat extraction submodule extracts the heat flux time series of the flow region based on the conductive mapping structure, identifies the heat flux fluctuation segment by combining the conduction duration, judges the heat accumulation trend in the region within the period, and generates heat accumulation change value.

[0022] The energy rate submodule calls the heat accumulation change value and the arc duration to calculate the energy input rate per unit time, identifies the diffusion response state based on the thermal diffusion time constant, judges the relationship between the input rate and the diffusion rate, and obtains the temperature distribution trend coefficient.

[0023] The trend generation submodule extracts the temperature rise value change segment within the cycle based on the temperature distribution trend coefficient and the on / off cycle number, filters the change sequence with consistent trend direction, establishes the correspondence between the cycle number and the temperature rise value, and generates the heat loss evolution trend line.

[0024] As a further aspect of the present invention, the thermal disturbance response control module includes:

[0025] The rate extraction submodule extracts the temperature rise change value and time series of the corresponding time period based on the change segment in the heat loss evolution trend line, obtains the temperature rise change rate in the segment, and collects the mass migration rate data in the contact material migration area, calculates the numerical ratio between the two, and generates the thermo-mass ratio coefficient.

[0026] The parameter adjustment submodule calls the thermo-mass ratio coefficient and the initial thermal conductivity value of the contact area, corrects the thermal conductivity parameter in the twin model according to the ratio relationship, updates the thermal diffusion distribution state in the correction area, and obtains the thermal diffusion distribution value.

[0027] The map generation submodule constructs a local thermal disturbance response matrix based on the thermal diffusion distribution value and the region number, determines the gradient relationship of diffusion values ​​between different regions, filters the region numbers whose diffusion value differences exceed the thermal disturbance response benchmark value, establishes a mapping relationship between the number and the thermal disturbance response value, and generates a control value map.

[0028] As a further aspect of the present invention, the lifetime mapping driving module includes:

[0029] The point selection submodule, based on the control value map, filters and sorts the control coefficient values ​​in the map, determines the map point number with the largest value, extracts the heat loss distribution area index and value set corresponding to the number in the twin space, and generates a heat loss area index set.

[0030] The parameter calculation submodule calls the heat loss value and the contact pressure distribution value of the contact pressure system at each location in the heat loss area index set, performs weighted average processing on the corresponding values, obtains the total thermomechanical value of the location and normalizes it to generate the equivalent thermomechanical load value.

[0031] The attenuation assignment submodule compares the equivalent thermomechanical load value with the thermal fatigue tolerance threshold set in the model, selects the thermomechanical value location index that exceeds the threshold and marks it as the region to be attenuated, assigns attenuation coefficient value to the location in the region, and obtains the life mapping layer.

[0032] As a further aspect of the present invention, the current density refers to the current value per unit area through the conductive cross section of the contact, which is derived from the standard definition of current density in electrical engineering;

[0033] The coefficient of thermal expansion refers to the proportionality of the change in length or volume of the contact material when the temperature changes, and it is derived from the table of material mechanical and thermal properties parameters.

[0034] As a further aspect of the present invention, the pressure offset refers to the difference between the actual contact pressure and the design rated contact pressure of the contact under mechanical operation or thermal stress, which is derived from the standard for measuring the mechanical parameters of electrical contact.

[0035] The twin model refers to a virtual digital model formed by real-time operating data of physical devices, which originates from the construction principle of digital twin systems;

[0036] The arc duration refers to the time interval from the generation to the extinction of the arc during the circuit breaking process, which is derived from the definition of physical experimental data on arc discharge.

[0037] The thermal diffusion time constant refers to the time parameter required for heat to be conducted in the contact material and reach a steady-state distribution. It is determined by the material's thermal diffusivity and characteristic length, and is derived from the heat transfer parameter model.

[0038] As a further aspect of the present invention, the mass migration rate refers to the speed at which contact material particles or atoms migrate per unit area per unit time due to thermal or electrical effects, which is derived from the definition of material migration dynamics under an electric arc.

[0039] Thermal conductivity refers to the ability of a contact material to conduct heat energy under a unit temperature gradient. It is a fundamental physical quantity for heat conduction calculations and is derived from a thermal property parameter database.

[0040] The contact pressure refers to the loading mechanism in the high-voltage switchgear that maintains the contact pressure between the moving and stationary contacts. It consists of springs, levers, or hydraulic devices and originates from the mechanical structure design of high-voltage electrical appliances.

[0041] The equivalent thermomechanical load refers to the composite load strength parameter obtained after the action of thermal stress and mechanical stress in the contact life calculation, which comes from the thermo-mechanical coupling analysis theory.

[0042] The thermal fatigue tolerance refers to the maximum range of thermal stress that the contact material can withstand under cyclic temperature changes, which is derived from the thermal fatigue test standard for metallic materials.

[0043] The life decay coefficient refers to the contact performance decay rate parameter derived from the changes in thermal, mechanical and material parameters, which is derived from the calculation parameters of the life prediction model.

[0044] The lifetime mapping layer refers to a virtual layer structure used in a digital twin system to visualize the spatial distribution of the remaining lifetime of contacts. It reflects the mapping result of the lifetime status in the three-dimensional model and originates from the digital twin visualization display system.

[0045] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0046] In this invention, by collecting the temperature difference and time interval within the switching cycle, calculating the thermal stress change in conjunction with the current density, and correlating it with the thermal properties of the material, the thermal behavior of the contact is dynamically reflected. Based on the contact area and pressure offset, the boundary of the conductive path is reconstructed to accurately characterize the current flow state. Heat accumulation and arc energy input are extracted, the temperature trend under thermal diffusion hysteresis is analyzed, and a thermal loss evolution curve is constructed. The thermal conductivity distribution is adjusted by the ratio of temperature rise to mass migration rate to improve the local adaptability of thermal disturbance response. Combined with equivalent thermomechanical load and fatigue tolerance, a life decay layer is generated to enhance the dynamics and accuracy of the assessment, and to achieve accurate determination and management of the degradation area. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] Figure 1 This is a system flowchart of the present invention;

[0049] Figure 2 This is a system block diagram of the present invention;

[0050] Figure 3 This is a flowchart of the thermal behavior acquisition module of the present invention;

[0051] Figure 4 This is a flowchart of the conductive state construction module of the present invention;

[0052] Figure 5 This is a flowchart of the dynamic heat loss assessment module of the present invention;

[0053] Figure 6 This is a flowchart of the thermal disturbance response control module of the present invention;

[0054] Figure 7 This is a flowchart of the lifetime mapping driving module of the present invention. Detailed Implementation

[0055] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0056] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0057] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, their intended meanings are consistent. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, their intended meanings are consistent.

[0058] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0059] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0060] This invention provides a high-voltage switchgear contact life management system based on digital twins, such as... Figure 1-2 The diagram shown illustrates a digital twin-based contact life management system for high-voltage switchgear. The system includes:

[0061] The thermal behavior acquisition module monitors the temperature change of the contact surface between the moving contact and the stationary contact, records the temperature difference and time interval in each switching cycle, calculates the ratio of the temperature change rate to the current density, obtains the thermal stress change law per unit time, and correlates the law with the thermal expansion coefficient of the contact material to generate thermal behavior response data.

[0062] The contact surface between the moving contact and the stationary contact refers to the electrical contact area formed between the moving contact and the stationary contact in a high-voltage switchgear when current is switched on or off. This area is a key location for current conduction and arc generation, and it originates from the standard structural design specifications of power switchgear.

[0063] Current density refers to the current per unit area passing through the conductive cross section of a contact. It is used to characterize the intensity of current distribution in a conductive path and is derived from the standard definition of current density in electrical engineering.

[0064] The coefficient of thermal expansion is a proportionality coefficient of the length or volume change of a contact material when the temperature changes. It is used to reflect the thermal deformation characteristics of the material and is derived from the table of mechanical and thermal properties of materials.

[0065] The conductive state construction module calls thermal behavior response data to calculate the change in contact area of ​​the conductive main circuit contact assembly, calculates the shrinkage amplitude of the conductive region in combination with the contact pressure offset, reconstructs the flow path boundary in the twin model based on the amplitude, and identifies the boundary range as the conductive region to generate a conductive mapping structure.

[0066] The conductive main circuit contact assembly refers to the collection of conductive components that perform switching functions in high-voltage switchgear. It mainly consists of moving contacts, stationary contacts, and connecting conductive rods, and is derived from the structural definition of the conductive system of switchgear.

[0067] Contact pressure offset refers to the difference between the actual contact pressure and the design rated contact pressure of the contact under mechanical operation or thermal stress. It is used to measure the change in the tightness of the contact and is derived from the standard for measuring the mechanical parameters of electrical contact.

[0068] A twin model is a virtual digital model driven by real-time operating data of physical equipment, used to synchronously reflect the status of equipment in virtual space, and originates from the construction principle of digital twin systems;

[0069] The heat loss dynamic assessment module is based on the conductive mapping structure. It extracts the heat accumulation change value in the flow region, calculates the energy input rate per unit time by combining the arc duration, compares the rate with the heat diffusion time constant, analyzes the temperature distribution trend under heat diffusion lag, establishes the heat loss change curve in the continuous on-off cycle, and generates the heat loss evolution trend line.

[0070] Arc duration refers to the time interval from the generation to the extinction of the arc during the circuit breaking process. It is used to evaluate the energy release characteristics of the arc and is derived from the definition of physical experimental data on arc discharge.

[0071] The thermal diffusion time constant refers to the time parameter required for heat to be conducted in the contact material and reach a steady-state distribution. It is determined by the material's thermal diffusivity and characteristic length, and is derived from the heat transfer parameter model.

[0072] The thermal disturbance response control module calls the changing segment in the thermal loss evolution trend line, obtains the temperature rise rate of the corresponding segment, compares it with the mass migration rate in the contact material migration area, calculates the ratio between the two, adjusts the thermal conductivity in the twin model according to the ratio, updates the thermal diffusion distribution in the local area of ​​the contact, forms the overall thermal disturbance response control spectrum, and generates the control value spectrum.

[0073] The contact material migration zone refers to the local area on the contact surface where the material vaporizes, splashes, migrates, and redeposits under the action of an electric arc. It reflects the changes in the morphology and performance of the contact and originates from research on electrical contact wear and migration.

[0074] Mass migration rate refers to the speed at which contact material particles or atoms migrate per unit area per unit time due to thermal or electrical effects. It is used to assess the intensity of the material migration process and is derived from the definition of material migration kinetics under an electric arc.

[0075] Thermal conductivity refers to the ability of a contact material to conduct heat energy under a unit temperature gradient. The commonly used unit is watts per meter per Kelvin. It is a fundamental physical quantity for heat conduction calculations and is derived from a thermal property parameter database.

[0076] The life mapping drive module calls the control value map, selects the point with the highest control coefficient, extracts the heat loss distribution of the location in the twin space, combines the contact pressure distribution value of the contact pressure system, calculates the equivalent thermomechanical load parameters, compares the parameters with the thermal fatigue tolerance value set in the model, assigns the corresponding area a life decay coefficient, and generates a life mapping layer.

[0077] The contact pressure system refers to the loading mechanism in a high-voltage switchgear that maintains the contact pressure between the moving and stationary contacts. It consists of springs, levers, or hydraulic devices and originates from the mechanical structure design of high-voltage electrical appliances.

[0078] The contact pressure distribution value refers to the distribution of contact pressure at the contact surface location. It is used to characterize the uniformity of force on the contact surface and is derived from the contact force distribution measurement standard.

[0079] The equivalent thermomechanical load parameter refers to the composite load strength parameter obtained after the action of thermal stress and mechanical stress in the contact life calculation. It is used to reflect the overall stress level of the contact and comes from the thermo-mechanical coupling analysis theory.

[0080] The thermal fatigue tolerance value refers to the maximum range of thermal stress that a contact material can withstand under cyclic temperature changes. It is used to determine the critical condition for thermal fatigue failure of a material and is derived from the thermal fatigue test standard for metallic materials.

[0081] The life decay coefficient is a parameter derived from the changes in thermal, mechanical and material parameters to describe the rate of decay of contact performance. It is used to describe the life decline trend and is derived from the calculation parameters of the life prediction model.

[0082] The lifetime mapping layer refers to a virtual layer structure in a digital twin system used to visualize the spatial distribution of the remaining lifetime of contacts. It reflects the mapping result of the lifetime status in the three-dimensional model and originates from the digital twin visualization display system.

[0083] The thermal behavior response data includes the rate of temperature change, the ratio of current density to current flow, the change law of thermal stress per unit time, and the associated parameters of the coefficient of thermal expansion. The conductive mapping structure includes the change value of contact area, the offset of contact pressure, the boundary of the flow path, and the boundary range of the conductive region. The thermal loss evolution trend line includes the change value of heat accumulation, the rate of arc energy input, the temperature distribution trend, and the thermal loss change curve. The control value spectrum includes the rate of temperature rise, the ratio of mass migration rate, the thermal conductivity adjustment coefficient, and the thermal diffusion distribution spectrum. The lifetime mapping layer includes the thermal loss distribution, the contact pressure distribution value, the equivalent thermomechanical load parameters, and the lifetime decay coefficient.

[0084] Specifically, such as Figure 2 , 3 As shown, the thermal behavior acquisition module includes:

[0085] The temperature monitoring submodule monitors the temperature change of the contact surface between the moving contact and the stationary contact in each on-off cycle, collects the temperature values ​​at the corresponding moments of on and off, records the temperature difference and time interval within the cycle, and generates a set of data on the cycle temperature difference and time interval.

[0086] In temperature monitoring of the contact surface between the moving and stationary contacts, multiple temperature measurement points are first set up in the contact area. Temperature data is continuously acquired using thermocouples or infrared sensors at a sampling frequency of 100 milliseconds. Each on / off cycle is set to 5 seconds, with the on state lasting 3 seconds and the off state lasting 2 seconds. The on / off state is identified by a sudden change in current. The on start point is defined as the current increasing from 0 to the rated value, and the off start point is defined as the current decreasing from the rated value to 0. The temperature recording point is the average of multiple temperature values ​​within 0.1 seconds before and after the on / off state to eliminate interference. The system extracts two key time points—the end of conduction and the end of disconnection—within a single on / off cycle. For example, if the end of conduction is 1.8 seconds and the temperature is 45.3℃, and the end of disconnection is 4.3 seconds and the temperature is 50.7℃, the temperature difference is calculated to be 5.4℃ and the time difference is 2.5 seconds. This forms a set of periodic temperature difference and time interval data. If the on / off behavior is repeated at 10-second intervals, 6 sets of data will be generated per minute. This continuous recording provides the original basis for subsequent use and is suitable for application scenarios with frequent on / off cycles in power equipment such as circuit breakers and contactors.

[0087] The rate calculation submodule calculates the temperature change rate value corresponding to the unit current density based on the periodic temperature difference and time interval group data, combined with the current density within the on / off cycle, and generates a sequence of current density to temperature change rate values.

[0088] Based on the acquired periodic temperature difference and time interval data, combined with the current density within that period, the rate of temperature change per unit current density is calculated. First, the current density is calculated using the current and the conductor cross-sectional area. For example, if the current is 100A and the conductor area is 40mm²... 2 The current density is then 2.5 A / mm². 2With a periodic temperature difference of 5.4℃ and a time interval of 2.5s, the temperature change rate is 2.16℃ / s. Dividing this rate by the current density yields a temperature rise rate of 0.864℃·s⁻¹·(A / mm)⁻¹ per unit current density. Continuous cycles are processed in the same way; for example, five cycles yield rates of 0.862, 0.870, 0.864, 0.859, and 0.868 respectively. The mean value is approximately 0.864, and the fluctuation is approximately 0.004 based on the standard deviation. This sequence reflects the regularity and intensity of thermal changes during switching. In practical devices, current, temperature, and time data can be read by a microcontroller's timed task, processed according to the corresponding cycle, and the sequence data can be output. This is suitable for current characteristic identification and analysis in typical scenarios such as medium-voltage distribution cabinets and switchgear where frequent load switching occurs.

[0089] The thermal stress correlation submodule calls the current density to temperature change rate sequence and the thermal expansion coefficient of the contact material to calculate the thermal stress change amplitude in each cycle, summarizes the cycle results, and generates thermal behavior response data.

[0090] Based on existing data series on temperature rise rate per unit current density, the thermal stress variation amplitude is calculated by combining the thermal expansion parameters of the contact material. Taking copper as an example, the coefficient of thermal expansion is 16.5 × 10⁻⁶. -6 / ℃, Young's modulus is taken as 110,000 MPa, when the temperature difference in a certain period is 5.4℃, the thermal strain is 16.5 × 10 -6 Multiplying by 5.4 yields approximately 89 microstrain, corresponding to a thermal stress of 89 microstrain multiplied by 110,000 MPa, resulting in approximately 9.8 MPa. This process is repeated for five cycles with temperature differences of 5.4, 5.6, 5.2, 5.5, and 5.3°C, yielding thermal stresses of approximately 9.8, 10.2, 9.5, 10.0, and 9.7 MPa, respectively. The cycle number, temperature difference, time interval, current density, temperature rise rate, thermal strain, and thermal stress are recorded for each cycle. These data are then compiled to form a thermal behavior response data structure, used to express the thermal response capability of the equipment under repeated switching conditions. This structure is suitable for scenarios with specific requirements for contact reliability and lifespan assessment, such as high-voltage circuit breakers, contactor wear assessment, and monitoring of frequent switching processes in railway traction circuits.

[0091] Specifically, such as Figure 2 , 4 As shown, the conductivity state construction module includes:

[0092] The area calculation submodule calls thermal behavior response data to obtain the temperature gradient and boundary change parameters of the contact area of ​​the conductive main circuit contact assembly. Combined with the deformation characteristics of the contact surface during the switching cycle, it calculates the contact area change value of the contact assembly in the conductive state and generates the contact area change amount.

[0093] Area calculation is based on thermal behavior response data. By analyzing the temperature gradient distribution and boundary change parameters of the conductive main circuit contact assembly in each switching cycle, the temperature values ​​and spatial coordinates of each measuring point are first extracted to construct a two-dimensional or three-dimensional temperature field map. Then, the temperature difference between each measuring point is calculated to form a temperature gradient vector field. Combined with the time synchronization signal, the spatial boundary is reconstructed for each sampling cycle. The deformation characteristics of the contact area are judged by the curvature boundary change. For example, if the distance between measuring points A and B is 2 mm and the temperature difference is 8℃, then the temperature gradient in this direction is 4℃ per millimeter. If the boundary coordinate change Δx is 0.3 mm, the deformation rate is approximately 15%. This is further combined with the elastic deformation range, such as the linear expansion coefficient of copper material under heating being 16.5 × 10⁻⁶. -6 / ℃, under a temperature rise of 50℃, the theoretical deformation per unit length is 0.000825 mm / mm. This allows for the estimation of the actual contact profile deformation surface. Multi-point projection analysis is used to calculate the surface fit of the contact area, and further estimates are made for the change in contact area, assuming the original contact area is 80 mm². 2 After deformation, the raised edges reduce the effective contact area by approximately 5%, resulting in a contact area of ​​76 mm² for this cycle. 2 The area change is a decrease of 4 mm2. This process is suitable for quantitative analysis of the contact wear process of high voltage circuit breaker contacts under long-term switching conditions.

[0094] The pressure offset submodule acquires the contact pressure sensing signal during the conduction process based on the change in the contact area of ​​the contact, extracts the contact pressure change trend within the on / off cycle, calculates the degree of difference between the contact pressure and the area change trend, and obtains the shrinkage amplitude value of the conductive area.

[0095] Pressure offset is based on the change in contact area. It utilizes synchronously acquired contact pressure sensor data to extract pressure value sequences within the current conduction and disconnection cycles. Pressure curve fitting analysis is performed for each cycle, and combined with area data, area-pressure comparison data sets are formed periodically. The consistency of the physical response of the contact area is assessed by the difference between the rate of area change and the rate of pressure change. For example, if the area decreases from 78 mm² to 74 mm² in a certain cycle, and the pressure decreases from 320 N to 250 N, the area change rate is 5.1%, and the pressure change rate is 21.9%, with a difference of 16.8%. If this difference exceeds a set threshold of 15%, it is marked as abnormal compression behavior. The contraction amplitude is calculated by multiplying the difference percentage by the area change. For example, if the area change is 4 mm²... 2 Therefore, the shrinkage amplitude is 0.168 × 4 = 0.672 mm. 2It should be noted that the threshold setting is based on the statistical results of multiple periods. For example, the average fluctuation range of the area-pressure change ratio is calculated within 100 consecutive periods, and the standard deviation range is set as the judgment limit. If it exceeds the range, it is marked as abnormal contraction behavior. This method is suitable for the performance monitoring scenario of switchgear with sluggish contact pressure response.

[0096] The path construction submodule calls the contraction amplitude value of the conductive region and the boundary conditions of the flow path in the twin model to identify the variation range of the path boundary within the on-off cycle, extract the correspondence between the flow point position and the boundary point, calculate the boundary range of the conductive region, and generate the conductive mapping structure.

[0097] The path construction uses the aforementioned contraction amplitude as the core input, combined with the pre-set flow path boundary conditions in the twin model. It dynamically adjusts the coordinates of the path boundary points within each cycle based on the contraction amplitude, identifying the boundary variation range. For example, if the original path boundary is a rectangular area of ​​100mm × 20mm, the contraction amplitude is 1.2mm. 2 The system determines whether the compression is longitudinal or lateral, and determines which dimension of the path to adjust based on the direction of thermal deformation. If it is longitudinal compression, the boundary length is compressed from 100mm to approximately 99.88mm. In each cycle, the mapping relationship between the current flow point and the boundary point is extracted. If there are 5 key current flow points in the current flow path, their coordinates and the distance to the boundary point are calculated using Euclidean distance. For example, if the distance from the origin A(20,5) to the boundary point B(100,5) is 80mm, and the boundary after compression is 99.88mm, then the new distance is 79.88mm. This change is recorded, and a periodic path boundary list is generated. In the conductive mapping structure, the coordinates of the current flow point, the coordinates of the boundary point, the mapping distance value, and the region number are recorded in each on / off cycle to form a spatial topology table. This table is suitable for scenarios such as circuit breaker structure simulation and contact mechanism wear trend analysis, facilitating subsequent design stages such as current path evolution modeling and current carrying uniformity adjustment.

[0098] Specifically, such as Figure 2 , 5 As shown, the dynamic heat loss assessment module includes:

[0099] The heat extraction submodule is based on the conductive mapping structure to extract the heat flux time series of the flow region, identify the heat flux fluctuation segment by combining the conduction duration, determine the heat accumulation trend in the region within the period, and generate heat accumulation change value.

[0100] Based on the conductive mapping structure, the spatial boundary of the current-carrying region is first determined, an array of equidistant heat flux sampling points is set up, and heat flux values ​​at each moment are collected at a fixed frequency to form a complete time series. This is achieved under typical conditions of a conduction period of 5 seconds, a sampling frequency of 100 Hz, and a sampling area of ​​20 mm². 2During this process, 500 sets of heat flux data for the flow path were accumulated. By calculating the variation in heat flux between adjacent time points, sections with significant heat flux fluctuations were identified; for example, sections with a variation rate greater than 500 W / m / s were identified as abnormal fluctuation sections. Based on this, the heat flux value within the fluctuation section was multiplied by the sampling time interval, and the accumulated values ​​were summed to obtain the heat accumulation value for that section. For example, if the average heat flux was 1000 W / m... 2 The area is 20mm. 2 The duration is 5 seconds, corresponding to a heat accumulation of 0.1 J. The heat accumulation results in consecutive cycles are compared, and the difference is taken to obtain the change in heat accumulation. For example, if the previous cycle was 0.08 J and the current cycle is 0.1 J, the change is 0.02 J. This value forms the basis for subsequent judgment of the heat transfer status of the conductive area.

[0101] The energy rate submodule calls the heat accumulation change value and the arc duration to calculate the energy input rate per unit time, identifies the diffusion response state based on the thermal diffusion time constant, judges the relationship between the input rate and the diffusion rate, and obtains the temperature distribution trend coefficient.

[0102] The specific calculation formula for identifying the diffusion response state based on the thermal diffusion time constant is as follows:

[0103]

[0104] Calculate the diffusion difference value, determine the relationship between the input rate and the diffusion rate, and obtain the temperature distribution trend coefficient;

[0105] Among them, E i Q represents the total energy input accumulated during the i-th arcing phase. j This represents the actual heat absorbed by material j in this stage, n represents the total number of energy input records, and m represents the total number of material types.

[0106] Total energy value of electric arc input E i Calculations are performed using current density, voltage, and duration. In actual data acquisition, the current density is J. i =3.5×10 7 A / m 2 The current waveform acquired by an oscilloscope is used to determine the area of ​​the unit electrode, which is A = 5 × 10⁻⁶. -6 m 2 Instantaneous voltage U i =35V, recorded in real time by the voltage monitoring node, duration τ i =0.15s is obtained by triggering the synchronization timing of the arc light metering system.

[0107] Through formula

[0108] E i =Ji ·A·U i ·τ i ;

[0109] Substitute:

[0110] E1 = 3.5 × 10 7 ·5×10 -6 ·35·0.15=918.75J;

[0111] Heat absorption value Q j The temperature difference before and after is recorded by a temperature measurement system, and combined with thermophysical parameters for calculation. The temperature measurement points are located in three different material regions, and the following parameters are monitored for each material:

[0112] Category 1 material (copper block): density ρ1 = 8960 kg / m³ 3 Specific heat capacity c1 = 385 J / (kg·K), volume V1 = 2.5 × 10 -5 m 3 The infrared thermometer recorded a temperature rise of ΔT1 = 12.3 K.

[0113] Category 2 material (aluminum block): density ρ2 = 2700 kg / m³ 3 Specific heat capacity c2 = 900 J / (kg·K), volume V2 = 4.0 × 10 -5 m 3 The temperature rise ΔT2 = 8.7K;

[0114] Category 3 materials (carbon steel): density ρ3 = 7850 kg / m³ 3 Specific heat capacity c3 = 490 J / (kg·K), volume V3 = 3.0 × 10 -5 m 3 The temperature rise ΔT3 = 10.4K;

[0115] The formula for heat absorption is:

[0116] Q j =ρ j ·c j ·ΔT j ·V j ;

[0117] Calculate Q for each type of material j :

[0118] Q1 = 8960·385·12.3·2.5×10 -5 =1062.348J;

[0119] Q2 = 2700·900·8.7·4.0×10 -5 =844.92J;

[0120] Q3 = 7850 · 490 · 10.4 · 3.0 × 10 -5 =1200.012J;

[0121] All Q j The sum is obtained as follows:

[0122]

[0123] Substitute into the formula to calculate:

[0124]

[0125] The results indicate that the total energy input per unit time is significantly lower than the heat required for the material to absorb and induce a temperature rise, suggesting that the arc heat input is insufficient to form a balanced diffusion state. The temperature distribution trend coefficient shows a negative shift, resulting in diffusion lag. This characteristic of the energy deficiency in the diffusion-dominated process provides a basis for subsequent control of the heat source input frequency.

[0126] The operational logic of this formula is based on the relationship between energy conservation and thermal conduction response. The electric arc input energy term is represented by the multiplication of current density, voltage, time and area, which represents the total amount of energy injected per unit time, reflecting the heat source intensity of the electric arc. The material endothermic term is expressed by multiplying density, specific heat capacity, temperature rise and volume, which represents the actual heat accumulation change that occurs per unit area under the action of energy. The difference between the two is used to measure the degree of deviation between input and response. The absolute value ensures that the deviation is positive, which is convenient for determining the trend. The summation of the denominator with respect to the material endothermic term is used as a normalization standard, so that the deviation is expressed as a relative energy difference, which is convenient for horizontal comparison under different working conditions. This structure uses multiplication to realize the combination of physical quantity dimensions, uses addition and subtraction to highlight the difference between input and absorption, and uses ratio normalization to form a standard output. The overall logic follows the quantitative path of thermal energy conduction and physical response.

[0127] The diffusion difference value represents the relative deviation between the thermal energy input by the electric arc and the actual thermal diffusion response induced by the material per unit time or under unit operating conditions. It is an important parameter for measuring the matching relationship between the intensity of the heat source and the material's diffusion capacity. When the diffusion difference value is close to 0, it indicates that the input energy and absorbed heat are basically consistent, and the system is in a state of thermal diffusion equilibrium. When the value is large, it indicates insufficient heat input or lag in the material's thermal response, which may lead to phenomena such as concentrated temperature gradients or local overheating. This value comprehensively reflects the coupling degree between heat input and diffusion absorption, and can be used to dynamically monitor response lag, energy excess or deficiency in the heat conduction process, and provide a basis for adjusting thermal control strategies.

[0128] The trend generation submodule extracts the temperature rise value change segment within the cycle based on the temperature distribution trend coefficient and the on / off cycle number, filters the change sequence with the same trend direction, establishes the correspondence between the cycle number and the temperature rise value, and generates the heat loss evolution trend line.

[0129] Based on the aforementioned trend factors and on / off cycle numbers, the temperature rise change value within each cycle is extracted to form a temperature rise change sequence. By judging the positive or negative direction of the temperature rise change value, time periods with consistent trend directions are selected. For example, if the temperature rise in a certain sequence is 62℃, 65℃, 67℃, 68℃, 70℃, and 72℃, then its change direction is consistently positive, and it is identified as a temperature rise upward trend segment. When there are individual values ​​in a downward direction but not exceeding the tolerance, they are still classified as a consistent trend sequence, with a trend tolerance of 1, allowing a maximum of one downward jump within 5 cycles. Further, trend factors are introduced for cross-judgment. If the trend factors in this stage are all greater than 1.5, then the consistency with the temperature rise change trend is confirmed. After extracting the effective trend segments, the cycle number and the corresponding temperature rise value are paired to form a temperature rise trend mapping relationship. Trend change curves are plotted sequentially to describe the heat loss evolution trajectory and its expansion state over time. This curve constitutes the main basis for the quantitative expression of thermal evolution behavior and serves the temperature evolution assessment of the long-term working state of the flow structure.

[0130] Specifically, such as Figure 2 , 6 As shown, the thermal disturbance response control module includes:

[0131] The rate extraction submodule extracts the temperature rise change value and time series of the corresponding time period based on the change segment in the thermal loss evolution trend line, obtains the temperature rise change rate in the segment, and collects the mass migration rate data in the contact material migration area, calculates the numerical ratio between the two, and generates the thermo-mass ratio coefficient.

[0132] Based on the identified change segments in the thermal loss evolution trend line, the temperature rise data corresponding to these time periods are extracted to form a temperature rise time series. Assuming the segment duration is 10 seconds, with sampling once per second, a total of 11 data sets are obtained. The temperature rise gradually increases from 50℃ to 68℃. The temperature rise difference between adjacent time points is differentially processed and then divided by the sampling interval to obtain the temperature rise rate per second. For example, if the temperature rise in the first two seconds is 50℃ and 52℃, the temperature rise rate is 2℃ / s, and so on to form a rate series. Subsequently, the contact material migration region is entered, and the mass change data of the material per unit time is obtained using electronic weighing. The mass migration is calculated by measuring the mass difference before and after weighing and combining it with the migration time. The rate of mass migration is calculated as follows: if the mass migration rate is 0.5 mg within 10 seconds, then the rate is 0.05 mg / s. The ratio of the temperature rise rate to the mass migration rate is then calculated to obtain the calorific value. For example, if the temperature rise rate is 2℃ / s and the corresponding mass migration rate is 0.05 mg / s, then the calorific value for that period is 40℃·s / mg. After collecting data from multiple segments or periods, all ratio values ​​are averaged to form a stable calorific value coefficient sequence, which lays the data foundation for subsequent adjustments to the thermal diffusion parameters. During this process, the temperature rise data and the mass migration rate data must be collected from the same time period to ensure the timeliness and regional consistency of the calculation results.

[0133] The parameter adjustment submodule calls the thermal mass ratio coefficient and the initial thermal conductivity value of the contact area, corrects the thermal conductivity parameter in the twin model according to the ratio relationship, updates the thermal diffusion distribution state in the correction area, and obtains the thermal diffusion distribution value.

[0134] The obtained thermogravimetric ratio is used as a correction factor. Combined with the initial thermal conductivity value of the contact area, thermal parameters are adjusted. If the original thermal conductivity is set to 400 W / (m·K), the thermogravimetric ratio is 40℃·s / mg, and the reference thermogravimetric ratio is 35℃·s / mg, then a correction factor of approximately 1.14 is formed. This correction factor is used to numerically adjust the thermal conductivity, updating it to 456 W / (m·K). The corrected value is embedded into the digital model of the contact structure area. The thermal conductivity parameter values ​​are replaced sequentially in the model mesh according to their numbers. The thermal diffusion simulation environment is reconstructed based on the corrected thermal conductivity. The heat flux density intensity is reassessed within the grid cells based on the existing temperature gradient. The heat flux density will increase accordingly due to the increase in thermal conductivity compared to the original state. The adjusted heat flux density data is input into the thermal diffusion simulation process to form a new steady-state heat distribution map. The simulation time range can be set to 20s with a time step of 0.1s. At the steady-state moment, the temperature values ​​of each numbered cell are extracted to form a thermal diffusion dataset. The dataset is output with a one-to-one correspondence between the number and the temperature, providing a data source for the next step of constructing the thermal disturbance response map. This process requires high simulation accuracy and reasonable mesh division to ensure that the corrected thermal conductivity accurately reflects the changes in thermal diffusion behavior.

[0135] The map generation submodule constructs a local thermal disturbance response matrix based on the thermal diffusion distribution value and the region number, determines the gradient relationship of diffusion values ​​between different regions, filters the region numbers whose diffusion value differences exceed the thermal disturbance response benchmark value, establishes a mapping relationship between the number and the thermal disturbance response value, and generates a control value map.

[0136] Based on the thermal diffusion dataset, each grid cell is paired with its thermal diffusion value according to its number, constructing a local thermal disturbance response matrix. This matrix reflects the distribution of thermal diffusion values ​​between different regions. The difference in thermal diffusion values ​​between adjacent numbered cells is compared one by one, and the magnitude of the diffusion value change is calculated. The corresponding thermal disturbance response difference is used as the judgment criterion. If the thermal diffusion values ​​of adjacent cells are 95 W / m² and 65 W / m², respectively, the difference is 30 W / m². The baseline judgment value is set to 20 W / m², and this numbered pair is then classified as a region with significant thermal disturbance response. This method is used to classify the entire numbered area. A comprehensive analysis was conducted, collecting and recording all numbers exceeding the baseline value and their corresponding thermal disturbance response differences. A table mapping numbers to differences was created, and then a graph was plotted in numerical order, with the horizontal axis representing the number and the vertical axis representing the thermal disturbance response value. The response intensity of each local region can be directly observed on the graph. Steep changes in the graph correspond to high thermal disturbance areas within the structure. This graph is suitable for identifying local response anomalies in materials. The baseline judgment value used must be determined in conjunction with the material's allowable temperature variation range. For example, if a material specifies that temperature fluctuations should not exceed 25% and the maximum thermal diffusivity is 100 W / m², then... 2 Therefore, setting the baseline value to 25W / m2 is more reasonable. During the analysis process, it should be ensured that all numbers correspond one-to-one with the physical spatial location to facilitate the accurate positioning of the spectral results in the actual structure.

[0137] Specifically, such as Figure 2 , 7 As shown, the lifetime mapping driver module includes:

[0138] The point selection submodule is based on the control value map, filters and sorts the control coefficient values ​​in the map, determines the map point number with the largest value, extracts the heat loss distribution area index and value set in the twin space corresponding to the number, and generates a heat loss area index set.

[0139] Based on the existing control coefficient information for each point in the control value map, we first extract all map point numbers and their corresponding values, establishing a correspondence between numbers and values. We then sort all control coefficients in descending order of magnitude, identifying the point number with the largest value. Assuming the highest control coefficient is 78, the number is 1056. After selecting this number, we retrieve its mapped location region in the twin space model, extracting the three-dimensional spatial coordinates corresponding to number 1056 within the twin space. For example, its location might be a node region with x = 25, y = 12, and z = 8. Finally, we extract the heat loss record for this region from historical heat loss data. The heat loss values ​​are sampled over time to obtain continuous data within 10 seconds. For example, the values ​​from the 1st to the 10th second are 40, 42, 44, 45, 47, 48, 50, 52, 54, and 55 respectively. These values ​​are then uniformly numbered and summarized to form the heat loss distribution subset corresponding to number 1056. This process is repeated to perform mapping and extraction operations on all numbers with higher control coefficient values. Finally, these numbers are combined with their spatial locations and heat loss data to form a heat loss area index set. All data is classified and organized by number, including number index, coordinate location, historical heat loss sequence, etc., as the basic information for the next stage of thermomechanical assessment calculation.

[0140] The parameter calculation submodule calls the heat loss value and the contact pressure distribution value of the contact pressure system at each location in the heat loss area index set, performs weighted average processing on the corresponding values, obtains the total thermomechanical value of the location and normalizes it to generate the equivalent thermomechanical load value.

[0141] The heat loss data corresponding to each number in the heat loss area index set is retrieved, and combined with the contact pressure distribution of each area provided by the contact pressure system, a correspondence is established between the area number and the heat loss value and contact pressure value. A weighted average is then calculated for each set of data, multiplying the heat loss value by its corresponding contact pressure, and summing all products. Simultaneously, all contact pressure values ​​are summed to obtain a weighted average. For example, number 1056 has a heat loss value of 44 and a corresponding contact pressure of 3; number 1062 has a heat loss value of 48 and a contact pressure of 4; and number 1075 has a heat loss value of 42 and a contact pressure of 2.5. After processing these data, the heat engine... The total thermomechanical value is approximately 45.16. This value is used as the initial thermomechanical intensity corresponding to number 1056. After repeatedly calculating the weighted total thermomechanical value for each numbered region, a normalization transformation is performed on all results to unify the numerical range to between 0 and 1. A linear scaling method between the minimum and maximum values ​​is used. If the minimum value in all regions is 30 and the maximum value is 60, then the normalized value of number 1056 is approximately 0.505. A matching list of numbers and normalized thermomechanical values ​​is formed and arranged in sequence into a mapping dataset, representing the distribution of equivalent thermomechanical load values. The data structure contains three parts: number, total thermomechanical value, and normalized load value.

[0142] The attenuation assignment submodule compares the equivalent thermomechanical load value with the thermal fatigue tolerance threshold set in the model, selects the thermomechanical value location index that exceeds the threshold and marks it as the region to be attenuated, assigns attenuation coefficient value to the location in the region, and obtains the lifetime mapping layer.

[0143] All equivalent thermomechanical load values ​​are compared with preset thermal fatigue tolerance thresholds. Regions exceeding the threshold are identified and categorized into attenuation zones. The threshold is set based on material thermal fatigue experimental data, with a maximum acceptable normalized thermomechanical load value of 0.6 determined through multi-cycle thermal stress loading tests. When the normalized load value corresponding to a certain numbered region exceeds this threshold, it is marked as a potential risk point. For example, region number 1062 has a normalized load value of 0.75 and is therefore included in the attenuation zone. Subsequently, an attenuation coefficient is set according to the normalized value, and an attenuation level is generated using linear interpolation. Assuming the normalized value is... The attenuation coefficient is 0.8 when the value is 0.6 and 1.0 when the normalized value is 0.9. Therefore, the attenuation coefficient that can be assigned to number 1062 is approximately 0.9. All numbered regions exceeding the threshold are assigned corresponding attenuation coefficients according to their respective thermomechanical strengths, forming a set of corresponding numbers and attenuation values. Finally, a lifetime mapping layer is constructed. This layer uses three-dimensional spatial regions as units, embedding the attenuation coefficient of each point. Combined with the twin model structure, it achieves a one-to-one mapping with spatial entities. The data is output in point cloud or grid format for visualization. The complete structure includes three key fields: number, coordinate position, and attenuation coefficient.

[0144] 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 variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included 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 digital-twin based high voltage switchgear contact life management system, characterized in that, The system comprises: The thermal behavior acquisition module monitors the temperature change of the contact surface, records the temperature difference and time interval of the on-off cycle, calculates the temperature change rate and current density ratio, combines the thermal expansion coefficient of the material, and generates thermal behavior response data; The conductive state construction module calls the thermal behavior response data, calculates the contact area change, combines the pressure offset, calculates the shrinkage amplitude of the conductive area, reconstructs the through-flow path boundary of the twin model, and generates a conductive mapping structure; The thermal damage dynamic evaluation module extracts the heat accumulation change based on the conductive mapping structure, combines the arc duration, calculates the energy input rate, compares it with the thermal diffusion time constant, and generates a thermal damage evolution trend line; The thermal disturbance response regulation module calls the thermal damage evolution trend line to obtain the temperature rise change rate, compares it with the mass migration rate, calculates the proportion, adjusts the model thermal conductivity, updates the thermal diffusion distribution, forms a thermal disturbance response map, and generates a regulation value map; The life mapping driving module calls the regulation value map, selects the highest point of the regulation coefficient, extracts the thermal damage distribution, combines the contact pressure, calculates the equivalent thermal mechanical load, compares it with the thermal fatigue tolerance, assigns a life attenuation coefficient, and generates a life mapping layer.

2. The digital-twin-based contact life management system for a high-voltage switchgear cabinet of claim 1, characterized in that: The thermal behavior response data includes temperature change rate, through-flow current density ratio, unit time thermal stress change rule, and thermal expansion coefficient correlation parameters. The conductive mapping structure includes contact area change value, contact pressure offset, through-flow path boundary, and conductive area boundary range. The thermal damage evolution trend line includes heat accumulation change value, arc energy input rate, temperature distribution trend, and thermal damage change curve. The regulation value map includes temperature rise change rate, mass migration rate ratio, thermal conductivity adjustment coefficient, and thermal diffusion distribution map. The life mapping layer includes thermal damage distribution, contact pressure distribution value, equivalent thermal mechanical load parameter, and life attenuation coefficient.

3. The digital twin based high voltage switchgear contact life management system according to claim 1, characterized in that, The thermal behavior acquisition module comprises: The temperature monitoring submodule monitors the temperature change of the contact surface between the moving contact and the stationary contact in each on-off cycle, collects the temperature values at the corresponding time of conduction and disconnection, records the temperature difference and time interval in the cycle, and generates cycle temperature difference and time interval group data; The rate calculation submodule calculates the temperature change rate value corresponding to the unit through-flow current density according to the cycle temperature difference and time interval group data, in combination with the through-flow current density in the on-off cycle, and generates a current density to temperature change rate value sequence; The thermal stress correlation submodule calls the current density to temperature change rate value sequence and the thermal expansion coefficient of the contact material, calculates the thermal stress change amplitude in each cycle, aggregates the cycle results, and generates thermal behavior response data.

4. The digital-twin-based contact life management system for a high-voltage switchgear cabinet of claim 3, wherein, The conductive state construction module comprises: The area calculation submodule calls the thermal behavior response data, obtains the contact area temperature gradient and boundary change parameter of the conductive main loop contact assembly, combines the deformation characteristics of the contact surface in the on-off cycle, calculates the contact area change value of the contact assembly in the conductive state, and generates the contact area change amount; The pressure offset sub-module obtains a contact pressure sensing signal in a conduction process according to the contact area change amount of the contact, extracts a contact pressure change trend in an on-off cycle, calculates a difference degree between the contact pressure change trend and the area change trend, and obtains a conduction area shrinkage amplitude value; The path construction sub-module calls the conduction area shrinkage amplitude value and a boundary condition of a flow path in a twin model, identifies a variation interval of a path boundary in the on-off cycle, extracts a corresponding relationship between a flow point position and a boundary point, calculates a boundary range of the conduction area, and generates a conduction mapping structure.

5. The digital twin based contact life management system for high voltage switchgear as claimed in claim 4, wherein, The thermal damage dynamic evaluation module comprises: The heat extraction sub-module extracts a heat flux time sequence of a flow area based on the conduction mapping structure, identifies a heat flux fluctuation section in combination with a conduction duration, judges an accumulation trend of heat in the area in the cycle, and generates a heat accumulation change value; The energy rate sub-module calls the heat accumulation change value and an arc duration, calculates an energy input rate per unit time, identifies a diffusion response state according to a thermal diffusion time constant, judges a change relationship between the input rate and the diffusion rate, and obtains a temperature distribution trend coefficient; The trend generation sub-module extracts a temperature rise value change section in the cycle according to the temperature distribution trend coefficient and a cycle number, screens change sequences with the same trend direction, establishes a corresponding relationship between the cycle number and the temperature rise value, and generates a thermal damage evolution trend line.

6. The digital twin based contact life management system for high voltage switchgear according to claim 5, characterized in that, The thermal disturbance response regulation module comprises: The rate extraction sub-module extracts a temperature rise change value and a time sequence of a corresponding period based on a change section in the thermal damage evolution trend line, obtains a temperature rise change rate in the section, collects mass migration rate data in a contact material migration area, calculates a numerical proportion relationship between the two, and generates a thermal mass proportion coefficient; The parameter adjustment sub-module calls the thermal mass proportion coefficient and an initial thermal conductivity value of the contact area, corrects a thermal conductivity parameter in the twin model according to the proportion relationship, updates a thermal diffusion numerical distribution state in a corrected area, and obtains a thermal diffusion distribution value; The atlas generation sub-module constructs a local thermal disturbance response matrix according to the thermal diffusion distribution value and an area number, judges a gradient relationship of diffusion values between difference areas, screens area numbers with a diffusion value difference exceeding a thermal disturbance response reference value, establishes a mapping relationship between the numbers and thermal disturbance response values, and generates a regulation value atlas.

7. The digital-twin-based contact life management system of a high-voltage switchgear according to claim 6, characterized in that, The life mapping driving module comprises: The point screening sub-module screens regulation coefficient values in the regulation value atlas and sorts them based on the regulation value atlas, determines a maximum value atlas point number, extracts a thermal damage distribution area index and a numerical set corresponding to the number in the twin space, and generates a thermal damage area index set; The parameter calculation sub-module calls a thermal damage numerical value of each position in the thermal damage area index set and a contact pressure distribution value of a contact pressure system, performs numerical weighted average processing correspondingly, obtains a thermal mechanical total value of the position and unifies normalization, and generates an equivalent thermal mechanical load value; The attenuation assignment sub-module performs numerical comparison on the equivalent thermal mechanical load value and a thermal fatigue tolerance threshold value set in the model, selects a thermal mechanical value position index exceeding the threshold value and marks it as a to-be-attenuated area, assigns an attenuation coefficient value to positions in the area, and obtains a life mapping layer.

8. The digital twin based high voltage switchgear contact life management system as claimed in claim 1, wherein: The current density refers to the current value per unit area through the contact conductive section, derived from the standard definition of current density in electrical engineering; The thermal expansion coefficient refers to the proportional coefficient of length or volume change of the contact material when the temperature changes, derived from the material mechanics and thermal properties parameter table.

9. The digital twin based high voltage switchgear contact life management system as claimed in claim 1, wherein: The pressure offset refers to the difference between the actual contact pressure and the design rated contact pressure of the contact under the action of mechanical operation or thermal stress, derived from the standard of electrical contact mechanics parameter measurement; The twin model refers to a virtual digital model formed by real-time running data of physical equipment, derived from the principle of digital twin system construction; The arc duration refers to the time interval from the generation to the extinction of the arc during the circuit breaking process of the contact, derived from the definition of arc discharge physical experimental data; The thermal diffusion time constant refers to the time parameter required for heat to conduct and reach a steady state distribution in the contact material, determined by the material thermal diffusion coefficient and characteristic length, derived from the heat transfer parameter model.

10. The digital twin based high voltage switchgear contact life management system as claimed in claim 1, wherein: The mass migration rate refers to the speed of contact material particles or atoms per unit area per unit time due to heat and electricity, derived from the definition of material migration mechanics under arc; The thermal conductivity refers to the ability parameter of the contact material to conduct heat energy under a unit temperature gradient, which is the basic physical quantity for heat conduction calculation, derived from the thermal physical property parameter database; The contact pressure refers to the loading mechanism that maintains the contact pressure of the moving and static contacts in the high-voltage switch cabinet, composed of springs, levers or hydraulic devices, derived from the mechanical structure design of high-voltage electrical appliances; The equivalent thermal-mechanical load refers to the composite load strength parameter obtained after the action of thermal stress and mechanical stress in the contact life calculation, derived from the thermal-mechanical coupling analysis theory; The thermal fatigue tolerance refers to the maximum thermal stress range that the contact material can withstand under the action of cyclic temperature change, derived from the standard of thermal fatigue test of metal materials; The life attenuation coefficient refers to the contact performance attenuation rate parameter derived from the changes of thermal, mechanical and material parameters, derived from the calculation parameters of life prediction model; The life mapping layer refers to a virtual layer structure used to visually present the spatial distribution of the remaining life of the contact in the digital twin system, reflecting the mapping results of the life state in the three-dimensional model, derived from the digital twin visualization display system.

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