Digital cable modeling simulation system

Abstract

The invention relates to the technical field of digital twinning and system simulation, in particular to a digital cable modeling simulation system, which comprises a stress analysis unit used for acquiring real-time sensor data of a cable service environment to obtain main vibration frequency and amplitude; the coupling modeling unit is used for resolving to obtain mechanical stress; constructing equivalent coupling stress; the damage evolution unit is used for solving a microscopic damage accumulation variable through a damage accumulation model; the parameter correction unit is used for generating a simulation impedance value and a simulation modulus value; the closed loop verification unit is used for acquiring the real impedance value of the cable and calculating the fidelity of the degradation state; the self-adaptive correction unit is used for generating a first-stage correction signal or a second-stage correction signal, the first-stage correction signal is used for correcting a preset mapping coefficient, and the second-stage correction signal is used for correcting a preset material degradation characteristic coefficient; according to the method, unnecessary model reconstruction is avoided, and efficient, accurate and stable dynamic calibration is realized.

Description

Technical Field

[0001] This invention relates to the field of digital twin and system simulation technology, specifically a digital cable modeling and simulation system. Background Technology

[0002] In current cable health status simulations, traditional digital models typically rely on fixed material parameters. However, in actual service, cables are subjected to nonlinear coupling effects from various stresses, such as mechanical vibration, temperature cycling, and chemical corrosion. Existing models struggle to accurately quantify this multi-physics coupling effect, and model parameters cannot be dynamically updated as microscopic damage accumulates in the material. This open-loop simulation approach results in low long-term accuracy of model predictions, gradually deviating from the actual degradation state of the physical entity. Therefore, constructing a simulation model that integrates multi-physics coupling, dynamically tracks damage evolution, and achieves closed-loop adaptive correction to improve the prediction fidelity throughout the entire lifecycle is a key technical challenge. Summary of the Invention

[0003] To address the aforementioned technical problems, this invention provides a digital cable modeling and simulation system. Specifically, the technical solution of this invention includes: The stress analysis unit is used to collect real-time sensor data of the cable service environment and analyze the random vibration spectrum in the real-time sensor data to obtain the dominant frequency and amplitude. The coupling modeling unit is used to calculate the mechanical stress based on the dominant frequency and amplitude; and to construct the equivalent coupling stress by combining the mechanical stress with the temperature cycle and chemical corrosion concentration in real-time sensor data. The damage evolution unit is used to calculate the micro-damage accumulation variable based on the equivalent coupled stress, and based on the preset damage accumulation threshold and the preset material degradation characteristic coefficient through the damage accumulation model. The parameter correction unit is used to generate simulated impedance and simulated modulus values ​​based on the accumulated variables of micro-damage, combined with preset initial impedance, preset initial modulus and preset mapping coefficients. The closed-loop verification unit is used to obtain the actual impedance value and actual modulus value of the cable, and calculate the fidelity of the degradation state by combining the simulated impedance value and the preset initial impedance. An adaptive correction unit is used to compare the fidelity of the degradation state with a preset fidelity threshold and a preset significant deviation threshold to generate a first-level correction signal or a second-level correction signal. The first-level correction signal is used to correct the preset mapping coefficient, and the second-level correction signal is used to correct the preset material degradation characteristic coefficient.

[0004] Preferably, the analytical process of the stress analysis element is as follows: Real-time sensor data is collected, including vibration spectrum, temperature cycle, and concentration of chemical corrosive substances. Signal processing techniques were used to decompose the vibration spectrum and extract the main vibration frequency and corresponding amplitude that caused material damage.

[0005] Preferably, the coupled modeling unit is specifically used for: Mechanical stress is obtained by converting the dominant frequency and amplitude through finite element analysis; In addition, by combining mechanical stress, relative temperature difference caused by temperature cycling, concentration of chemical corrosive substances, and preset thermo-mechanical coupling coefficients and chemical-mechanical coupling coefficients, an equivalent coupled stress is constructed.

[0006] Preferably, the damage evolution unit is specifically used for: An evolutionary model incorporating a damage accumulation threshold and a damage saturation term is adopted. The damage accumulation rate is calculated by combining the portion of the equivalent coupled stress that is greater than the damage accumulation threshold with a preset material degradation characteristic coefficient. The damage accumulation rate is numerically integrated over time to calculate the microscopic damage accumulation variable in real time.

[0007] Preferably, the parameter correction unit is specifically used for: By combining the accumulated variable of micro-damage with the damage-impedance coupling coefficient in the preset mapping coefficient, the preset initial impedance is corrected to obtain the simulated impedance value.

[0008] Preferably, the parameter correction unit is also used for: By combining the accumulated variable of micro-damage with the damage-modulus coupling coefficient in the preset mapping coefficient, the preset initial modulus is corrected to obtain the simulated modulus value.

[0009] Preferably, the calculation process of the closed-loop verification unit is as follows: Obtain the simulated impedance value, and obtain the actual impedance value and actual modulus value measured on the physical entity; Calculate the absolute deviation between the simulated impedance value and the actual impedance value; The absolute deviation is normalized by dividing it by the preset initial impedance, and the normalized value is subtracted from 1 to obtain the fidelity of the degraded state.

[0010] Preferably, the adaptive correction unit is specifically used for: The fidelity of the degraded state is compared with a preset fidelity threshold and a preset significant deviation threshold. When the fidelity of the degraded state is greater than or equal to the preset fidelity threshold, it is determined that no correction is needed; When the fidelity of the degraded state is less than the preset fidelity threshold and greater than the difference between the preset fidelity threshold and the preset significant deviation threshold, it is determined to be a model mapping parameter drift, and a first-level correction signal is generated. When the fidelity of the degraded state is less than or equal to the difference between the preset fidelity threshold and the preset significant deviation threshold, the model evolution rate is determined to be in failure, and a secondary correction signal is generated.

[0011] Preferably, in response to a first-level correction signal: Calculate the normalized impedance error between the actual impedance value and the simulated impedance value; Obtain the true modulus value and calculate the normalized modulus error between the true modulus value and the simulated modulus value; Based on the normalized impedance error and the preset first-level correction feedback gain coefficient, the damage-impedance coupling coefficient in the preset mapping coefficient is corrected. Based on the normalized modulus error and the preset first-level correction feedback gain coefficient, the damage-modulus coupling coefficient in the preset mapping coefficient is corrected.

[0012] Preferably, in response to a second-level correction signal: Calculate the fidelity deviation between the preset fidelity threshold and the fidelity in the degraded state; Based on the fidelity deviation and the preset secondary correction feedback gain coefficient, the preset material degradation characteristic coefficient is corrected.

[0013] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention solves the quantification problem of nonlinear coupling of multiple physical fields by constructing an equivalent coupled stress model, which unifies the stresses of multiple physical fields such as mechanical vibration, temperature cycling and chemical corrosion into a single damage driving factor, thereby improving the physical fidelity of the stress model. 2. This invention constructs a dynamic mapping relationship from macroscopic stress to microscopic damage, and then to macroscopic simulation parameters; by solving the cumulative variables of microscopic damage and correcting the simulation impedance and modulus accordingly, the model can dynamically reflect the real degradation process of materials, overcoming the static limitations of traditional models. 3. This invention introduces a closed-loop verification and adaptive correction mechanism; by comparing the deviation between the simulated impedance and the actual impedance in real time, the fidelity of the degradation state is dynamically calculated, and the internal parameters of the model are corrected based on this, thereby realizing closed-loop control of the simulation and significantly reducing the accumulation of long-term prediction errors. 4. This invention employs a hierarchical adaptive correction strategy, which can intelligently diagnose the source of deviation. The system can distinguish between a slight drift in the model mapping parameters and a fundamental failure in the damage evolution rate, and trigger correction operations at different depths, avoiding unnecessary model reconstruction and achieving efficient, accurate and stable dynamic calibration. Attached Figure Description

[0014] The present invention will be further explained below with reference to the accompanying drawings and embodiments: Figure 1 This is a structural diagram of the system of the present invention. Detailed Implementation

[0015] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0016] Example 1: Please see Figure 1 A digital cable modeling and simulation system, comprising: The stress analysis unit is used to collect real-time sensor data of the cable service environment and analyze the random vibration spectrum in the real-time sensor data to obtain the main frequency and amplitude. The coupling modeling unit is used to calculate the mechanical stress based on the dominant frequency and amplitude; and to construct the equivalent coupling stress by combining the mechanical stress with the temperature cycle and chemical corrosion concentration in the real-time sensor data. The damage evolution unit is used to calculate the micro-damage accumulation variable based on the equivalent coupled stress, a preset damage accumulation threshold, and a preset material degradation characteristic coefficient through the damage accumulation model. The parameter correction unit is used to generate simulated impedance and simulated modulus values ​​based on the accumulated variables of micro-damage, combined with preset initial impedance, preset initial modulus and preset mapping coefficients. The closed-loop verification unit is used to obtain the actual impedance value and actual modulus value of the cable, and calculate the fidelity of the degradation state by combining the simulated impedance value and the preset initial impedance. An adaptive correction unit is used to compare the fidelity of the degradation state with a preset fidelity threshold and a preset significant deviation threshold to generate a first-level correction signal or a second-level correction signal. The first-level correction signal is used to correct the preset mapping coefficient, and the second-level correction signal is used to correct the preset material degradation characteristic coefficient.

[0017] This embodiment provides a digital cable modeling and simulation system. This system constructs a complete technical closed loop, encompassing macroscopic working condition perception, multi-physics coupled modeling, microscopic damage evolution, and macroscopic parameter correction, including closed-loop verification and adaptive correction. The system includes: The stress analysis unit aims to process raw, multi-source, and heterogeneous sensor data from the cable service environment into key driving factors required for subsequent stress modeling. In this embodiment, this unit is used to collect real-time sensor data from the cable service environment, which may specifically include vibration spectra. Temperature cycling and the concentration of chemical corrosive substances The stress analysis unit is also used to analyze the random vibration spectrum in real-time sensor data. Considering the randomness of the vibration spectrum under operating conditions, this embodiment preferably employs wavelet decomposition technology, for example, to decompose the vibration spectrum V(f) or its time domain V(t) to extract the dominant frequency that contributes most to material damage. and its corresponding amplitude ; The coupling modeling unit aims to solve the quantization problem of nonlinear coupling in multi-physics fields, mapping the stresses from different physical sources to a single, quantifiable damage driving factor. In this embodiment, this unit is used to model the dominant frequency output by the stress analysis unit. and amplitude The mechanical stress is obtained by solving; specifically, it can be obtained through the well-known finite element analysis method. and As a load input, it is converted into mechanical stress. Coupled modeling unit combined with this mechanical stress and temperature cycling in real-time sensor data. The relative temperature difference exhibited and concentration of chemical corrosive substances Construct equivalent coupled stress ; The damage evolution unit aims to establish a nonlinear mapping relationship from macroscopic stress to microscopic damage, and to simulate the complete nonlinear process of material damage from initiation, acceleration to saturation with high fidelity. In this embodiment, this unit is used to simulate the equivalent coupled stress output by the coupled modeling unit. And based on a preset damage accumulation threshold Based on the preset material degradation characteristic coefficients, the microscopic damage accumulation variable is calculated using a damage accumulation model. ; This refers to the minimum stress required for a material to begin accumulating damage. It is determined through stepped stress loading experiments, which involve gradually applying different levels of constant stress. And monitor whether damage occurs, the minimum stress that will lead to damage initiation. Calibrated as Material degradation characteristic coefficients, such as damage rate coefficients. Stress sensitivity index and damage saturation index , , , This refers to a coefficient characterizing the degradation properties of a material, derived from applying multiple different constant equivalent coupled stresses. Accelerated aging experiments were conducted at the horizontal level, and calibration data on the evolution of microscopic damage accumulation variables over time were measured and recorded. Using nonlinear fitting algorithms, such as the Levenberg-Marquardt algorithm, for... The solution is fitted, and the optimal solution is determined by inverse calibration. , and value; The parameter correction unit aims to correct abstract damage variables that are not directly measurable, calculated by the damage evolution unit. This is made explicit as specific, simulable macroscopic parameters in the digital twin; in this embodiment, this unit is used based on the cumulative variable of microscopic damage. And combined with the preset initial impedance Preset initial modulus And with preset mapping coefficients, generate simulated impedance values. and simulation modulus value ; and This refers to the initial characteristic impedance and initial elastic modulus of the cable, which are derived from the cable's factory specifications or initial measurements; preset mapping coefficients, such as the damage-impedance coupling coefficient. and damage-modulus coupling coefficient , and This refers to a coefficient characterizing the sensitivity of microscopic damage to macroscopic parameters. It is derived from calibration values ​​obtained by simultaneously measuring and recording the cumulative variable of microscopic damage at different times during accelerated aging experiments. and the corresponding macroscopic parameter measurements and Based on this set of calibration data Determined by linear regression The value is based on Data, through nonlinear fitting, for example, on The model is fitted and determined. The value; That is, in Module 3 , That is, in Module 3 ; The closed-loop verification unit aims to quantify the deviation between the simulation model and the physical entity, providing a basis for adaptive correction of the model. In this embodiment, this unit is used to obtain the actual impedance value of the cable. and true modulus value ; It refers to the actual impedance value obtained from physical entities through measurement or synchronous accelerated aging experiments, which serves as a verification benchmark. This refers to the actual modulus value of a physical entity obtained through synchronous experiments, such as dynamic mechanical analysis or tensile testing, which serves as the benchmark for modulus correction. The simulated impedance value is generated by the closed-loop verification unit in conjunction with the parameter correction unit. and the preset initial impedance Calculate the fidelity of the degradation state ; The adaptive correction unit aims to dynamically correct the core parameters of the simulation model based on the fidelity verification results, thereby reducing the long-term prediction error accumulation rate. In this embodiment, this unit is used to adjust the degradation state fidelity calculated by the closed-loop verification unit. Compared with the preset fidelity threshold and the preset significant deviation threshold Perform a comparison; and The threshold is preset based on the required model accuracy, for example, it can be set based on historical simulation data statistics or industry standards; based on the comparison results, the system generates a first-level correction signal or a second-level correction signal; the first-level correction signal is used to correct the preset mapping coefficients, i.e. and The secondary correction signal is used to correct the preset material degradation characteristic coefficient, i.e. ; This embodiment overcomes the problems of traditional simulation models failing to reflect the multi-physics coupling effect of real working conditions and long-term prediction failure caused by fixed model parameters by working collaboratively with the stress analysis, coupled modeling, damage evolution, parameter correction, closed-loop verification, and adaptive correction units. The invention constructs a multi-scale, multi-physics dynamic mapping model from macroscopic working conditions to microscopic damage and then to macroscopic parameters, and achieves high-fidelity, dynamic, and high-precision simulation and prediction of the health status of cables throughout their entire life cycle through simulation-real closed-loop verification and hierarchical adaptive correction.

[0018] Example 2: The analytical process of the stress analysis element is as follows: Real-time sensor data is collected, including vibration spectrum, temperature cycle, and concentration of chemical corrosive substances. Signal processing techniques were used to decompose the vibration spectrum and extract the main vibration frequency and corresponding amplitude that caused material damage.

[0019] Based on Example 1, this example optimizes and limits the specific implementation of the stress analysis unit; the analysis process of the stress analysis unit is as follows: Real-time sensor data is collected. As mentioned above, in this embodiment, the real-time sensor data preferably includes the vibration spectrum. Temperature cycling and the concentration of chemical corrosive substances ; Signal processing techniques are used to analyze the vibration spectrum. or its time domain The signal processing technology is not limited to a specific signal processing technique. In this embodiment, wavelet decomposition is preferred because it can effectively process non-stationary random vibration signals. Through decomposition, the dominant vibration frequency that causes material damage is extracted. and corresponding amplitude ; This embodiment, by clearly defining the specific composition of sensor data—namely vibration, temperature, and chemical data—and specifying the use of signal processing techniques, ensures that the stress analysis unit can accurately extract the key factors that determine damage from complex and random raw data. and This greatly improves the accuracy and relevance of inputs for subsequent multiphysics coupling modeling.

[0020] Example 3: The coupled modeling unit is specifically used for: Mechanical stress is obtained by converting the dominant frequency and amplitude through finite element analysis. In addition, by combining mechanical stress, relative temperature difference caused by temperature cycling, concentration of chemical corrosive substances, and preset thermo-mechanical coupling coefficients and chemical-mechanical coupling coefficients, an equivalent coupled stress is constructed.

[0021] Based on Example 1, this example provides a detailed definition of the specific method for constructing equivalent coupled stress using the coupling modeling unit; the coupling modeling unit is specifically used for: The dominant frequency extracted based on stress analysis unit and amplitude After conversion through finite element analysis, the mechanical stress was obtained. ; Combined with mechanical stress Temperature cycle The resulting relative temperature difference Concentration of chemical corrosive substances and the preset thermo-mechanical coupling coefficient and the preset chemical-mechanical coupling coefficient Construct equivalent coupled stress ; In this embodiment, the equivalent coupling stress The following empirical equivalent stress model was constructed: ; This refers to the thermo-mechanical coupling coefficient, whose dimensions are... The effect of temperature on mechanical damage sensitivity was characterized by accelerated aging tests; specifically, multiple cable samples were prepared and subjected to different constant relative temperature differences. and different constant chemical corrosive substance concentrations Vibration-accelerated aging was performed under combined operating conditions, and damage evolution data for each condition were recorded, such as the measured performance degradation rate. Based on this calibration dataset The optimal value was obtained through least squares regression analysis. and value; This refers to the chemical-mechanical coupling coefficient, with dimensions of stress / concentration, characterizing the equivalent stress induced by chemical substances. Its source and calibration method are the same as... ; This embodiment introduces a specific thermo-mechanical coupling coefficient. and chemical-mechanical coupling coefficient The equivalent coupled stress model innovatively unifies the originally independent and difficult-to-couple mechanical, thermal, and chemical physical stresses into a single damage driving force. This approach solves the quantification problem of nonlinear coupling of multiphysics fields, making it possible to map macroscopic working conditions to microscopic damage, and greatly improving the physical fidelity and accuracy of stress models.

[0022] Example 4: The damage evolution unit is specifically used for: An evolutionary model incorporating a damage accumulation threshold and a damage saturation term is adopted. The damage accumulation rate is calculated by combining the portion of the equivalent coupled stress that is greater than the damage accumulation threshold with a preset material degradation characteristic coefficient. The damage accumulation rate is numerically integrated over time to calculate the microscopic damage accumulation variable in real time.

[0023] Based on Example 1, this example optimizes and limits the specific process of the damage evolution unit in calculating the cumulative variable of microscopic damage; the damage evolution unit is specifically used for: Using damage accumulation threshold An evolution model for the damage saturation term is presented; this model originates from the theory of continuous damage mechanics and has been improved for the characteristics of cable polymer materials; in this embodiment, the model is as follows: ; in This represents the rate of damage accumulation. For the cumulative variable of microscopic damage, For no loss, Completely ineffective; This is a preset material degradation characteristic coefficient; It is a ramp function, i.e. when If true, then true; otherwise, true is 0. This unit will have equivalent coupled stress Medium greater than the damage accumulation threshold Part of Combined with the preset material degradation characteristic coefficient The damage accumulation rate was calculated. ; rate of damage accumulation Perform numerical integration over time, for example using the Runge-Kutta method, to calculate the cumulative variable of microscopic damage at the current moment in real time. ; This embodiment employs a method that includes a damage threshold. and saturation terms A specific nonlinear evolution model overcomes the failure problem of conventional linear extrapolation models in simulating material degradation; this model can simulate the complete nonlinear process of material damage from initiation, acceleration to saturation with high fidelity, realizing the simulation from macroscopic stress... To microscopic damage Precise quantitative tracking.

[0024] Example 5: The parameter correction unit is specifically used for: By combining the accumulated variable of micro-damage with the damage-impedance coupling coefficient in the preset mapping coefficient, the preset initial impedance is corrected to obtain the simulated impedance value.

[0025] Based on Example 1, this example specifies the method by which the parameter correction unit generates the simulated impedance value; the parameter correction unit is specifically used for: The micro-damage accumulation variable output by the damage evolution unit Combined with the damage-impedance coupling coefficient in the preset mapping coefficients For the preset initial impedance After correction, the simulated impedance value is obtained. ; In this embodiment, the correction process is implemented using the following first-order linear approximation model: ; in This is the output simulated impedance value. ; The initial impedance is preset. The cumulative variable for microscopic damage is the input. The damage-impedance coupling coefficient characterizes the sensitivity of microscopic damage to macroscopic impedance. This embodiment establishes... This specific mapping model will transform abstract, indirectly measurable microscopic damage variables. This is successfully transformed or made explicit into specific, simulable electrical core parameters in the digital twin, namely, the simulated impedance value. This provides a direct, quantitative input for subsequent signal integrity simulation and fidelity verification.

[0026] Example 6: The parameter correction unit is also used for: By combining the accumulated variable of micro-damage with the damage-modulus coupling coefficient in the preset mapping coefficient, the preset initial modulus is corrected to obtain the simulated modulus value.

[0027] Based on Embodiment 1, this embodiment further defines the function of the parameter correction unit, enabling it to correct not only electrical parameters but also mechanical parameters; the parameter correction unit is also used for: The micro-damage accumulation variable output by the damage evolution unit Combined with the damage-modulus coupling coefficient in the preset mapping coefficients For the preset initial modulus After correction, the simulated modulus value is obtained. ; In this embodiment, the correction process is preferably implemented using the following nonlinear model to ensure... Time modulus Approaching zero is more in line with physical reality: ; in This is the output simulation modulus value. ; The preset initial modulus; The cumulative variable for microscopic damage is the input. The damage-modulus coupling coefficient; This embodiment adds a core mechanical parameter, namely the equivalent elastic modulus. The dynamic correction enables the system to simulate not only the degradation of electrical performance, but also the degradation of mechanical properties such as cable flexibility, thus constructing a mechatronic digital twin model, which greatly expands the application scope and simulation dimensions of the model.

[0028] Example 7: The calculation process for the closed-loop verification unit is as follows: Obtain the simulated impedance value, and obtain the actual impedance value and actual modulus value measured on the physical entity; Calculate the absolute deviation between the simulated impedance value and the actual impedance value; The absolute deviation is normalized by dividing it by the preset initial impedance, and the normalized value is subtracted from 1 to obtain the fidelity of the degraded state.

[0029] Based on Example 1, this example provides a detailed description of the specific process for the closed-loop verification unit to calculate the fidelity of the degraded state; the calculation process of the closed-loop verification unit is as follows: Obtain the simulated impedance value output by the parameter correction unit. And obtain the actual impedance value measured on the physical entity. ; Calculate the simulated impedance value Compared with the true impedance value The absolute deviation between them, i.e. ; Divide the absolute deviation by the preset initial impedance. Perform normalization and subtract the normalized value from 1 to obtain the fidelity of the degenerate state. The calculation process is defined by the following formula: ; This embodiment is illustrated by... This standardized and normalized fidelity calculation formula provides an objective and quantitative standard for evaluating the consistency between simulation models and physical entities; The calculation results provide a clear and reliable triggering basis for subsequent adaptive corrections, which is a key step in realizing closed-loop control of the system and ensuring the long-term accuracy of the model.

[0030] Example 8: The adaptive correction unit is specifically used for: The fidelity of the degraded state is compared with a preset fidelity threshold and a preset significant deviation threshold. When the fidelity of the degraded state is greater than or equal to the preset fidelity threshold, it is determined that no correction is needed; When the fidelity of the degraded state is less than the preset fidelity threshold and greater than the difference between the preset fidelity threshold and the preset significant deviation threshold, it is determined to be a model mapping parameter drift, and a first-level correction signal is generated. When the fidelity of the degraded state is less than or equal to the difference between the preset fidelity threshold and the preset significant deviation threshold, the model evolution rate is determined to be in failure, and a secondary correction signal is generated.

[0031] Based on Example 1, this example provides a detailed definition of the specific logic for the adaptive correction unit to generate the correction signal; the adaptive correction unit is specifically used for: The fidelity of the degraded state calculated by the closed-loop verification unit Compared with the preset fidelity threshold and the preset significant deviation threshold Perform a comparison; The comparison logic, namely the hierarchical correction strategy, is as follows: When the fidelity of the degraded state Greater than or equal to the preset fidelity threshold Right now If the model is accurate, no correction is needed. When the fidelity of the degraded state Less than the preset fidelity threshold And greater than the preset fidelity threshold. Significant deviation threshold from the preset value When the difference is, that is When this occurs, it is determined to be a drift in the model mapping parameters, and a first-level correction signal is generated. When the fidelity of the degraded state Less than or equal to the preset fidelity threshold Significant deviation threshold from the preset value When the difference is, that is When the model evolution rate fails, a secondary correction signal is generated. This embodiment establishes a foundation based on and The hierarchical judgment logic enables intelligent diagnosis of model deviations. The system can distinguish between slight drift in the mapping layer, i.e., the first-level correction case, and fundamental failure in the evolution layer, i.e., the second-level correction case, thereby triggering correction operations at different depths, avoiding unnecessary model reconstruction, and achieving efficient, accurate and stable adaptive correction.

[0032] Example 9: In response to the first-level correction signal: Calculate the normalized impedance error between the actual impedance value and the simulated impedance value; Obtain the true modulus value and calculate the normalized modulus error between the true modulus value and the simulated modulus value; Based on the normalized impedance error and the preset first-level correction feedback gain coefficient, the damage-impedance coupling coefficient in the preset mapping coefficient is corrected. Based on the normalized modulus error and the preset first-level correction feedback gain coefficient, the damage-modulus coupling coefficient in the preset mapping coefficient is corrected.

[0033] Based on Example 8, this example specifies the specific correction actions in response to the first-level correction signal; when the adaptive correction unit generates the first-level correction signal, the system performs the following operations: Calculate the true impedance value With simulated impedance value Normalized impedance error between The calculation formula is as follows: ; Obtain the true modulus value And calculate the true modulus value. With simulation modulus value Normalized modulus error between The calculation formula is as follows: ; Based on normalized impedance error and the preset first-level correction feedback gain coefficient Correcting the damage-impedance coupling coefficient in the preset mapping coefficients Corrected coefficients The calculation is as follows: ; Based on normalized modulus error and the preset first-level correction feedback gain coefficient Correct the damage-modulus coupling coefficient in the preset mapping coefficients. Corrected coefficients The calculation is as follows: ; and It is the feedback gain coefficient that controls the correction rate and stability, and its source is determined through simulation control system tuning, such as PID parameter tuning methods; the corrected and Replace the parameter correction unit and ; This embodiment provides a specific algorithm for the first-level correction; when a slight drift in the mapping parameters is detected, the system calculates the normalization error. and and utilize feedback gain and For mapping coefficients and Fine-tuning is performed; this method allows the simulation output value to be adjusted. and Quickly and smoothly pull back to the true value. and This enables rapid calibration of the model's output layer.

[0034] Example 10: In response to the second-level correction signal: Calculate the fidelity deviation between the preset fidelity threshold and the fidelity in the degraded state; Based on the fidelity deviation and the preset secondary correction feedback gain coefficient, the preset material degradation characteristic coefficient is corrected.

[0035] Based on Example 8, this example specifies the specific correction actions in response to the secondary correction signal; when the adaptive correction unit generates the secondary correction signal, the system performs the following operations: Calculate the preset fidelity threshold fidelity with degradation state The fidelity deviation between them, i.e. ; Based on this fidelity deviation and the preset second-level correction feedback gain coefficient Correct the preset material degradation characteristic coefficient; In this embodiment, the correction targets the core evolution parameters in the damage evolution unit, such as the damage rate coefficient. Corrected coefficients The calculation is as follows: ; This is the feedback gain coefficient for the second-order correction, the source of which is determined through simulation debugging; the corrected... Will replace the damage evolution unit value; This embodiment provides a specific algorithm for secondary correction; when a significant fidelity deviation is detected, it indicates the basic damage accumulation rate of the model. When it has already failed, this embodiment corrects the core evolution parameters. This adjusts the rate of damage evolution; for example, when When it is a large positive value, This will be increased to speed up the model. The accumulation of these features allows the model to match real degradation more quickly; this correction, which goes deep into the core layer of the model, ensures that the model can still be corrected when deep failure occurs, guaranteeing the long-term effectiveness and robustness of the system.

[0036] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A digital cable modeling and simulation system, characterized in that... ,include: The stress analysis unit is used to collect real-time sensor data of the cable service environment and analyze the random vibration spectrum in the real-time sensor data to obtain the main frequency and amplitude. The coupling modeling unit is used to calculate the mechanical stress based on the dominant frequency and amplitude; and to construct the equivalent coupling stress by combining the mechanical stress with the temperature cycle and chemical corrosion concentration in the real-time sensor data. The damage evolution unit is used to calculate the micro-damage accumulation variable based on the equivalent coupled stress, a preset damage accumulation threshold, and a preset material degradation characteristic coefficient through the damage accumulation model. The parameter correction unit is used to generate simulated impedance and simulated modulus values ​​based on the accumulated variables of micro-damage, combined with preset initial impedance, preset initial modulus and preset mapping coefficients. The closed-loop verification unit is used to obtain the actual impedance value and actual modulus value of the cable, and calculate the fidelity of the degradation state by combining the simulated impedance value and the preset initial impedance. An adaptive correction unit is used to compare the fidelity of the degradation state with a preset fidelity threshold and a preset significant deviation threshold to generate a first-level correction signal or a second-level correction signal. The first-level correction signal is used to correct the preset mapping coefficient, and the second-level correction signal is used to correct the preset material degradation characteristic coefficient.

2. The digital cable modeling and simulation system according to claim 1, characterized in that... The analytical process of the stress analysis unit is as follows: Real-time sensor data is collected, including vibration spectrum, temperature cycle, and concentration of chemical corrosive substances. Signal processing techniques were used to decompose the vibration spectrum and extract the main vibration frequency and corresponding amplitude that caused material damage.

3. The digital cable modeling and simulation system according to claim 1, characterized in that... The coupling modeling unit is specifically used for: Mechanical stress is obtained by converting the dominant frequency and amplitude through finite element analysis. In addition, by combining mechanical stress, relative temperature difference caused by temperature cycling, concentration of chemical corrosive substances, and preset thermo-mechanical coupling coefficients and chemical-mechanical coupling coefficients, an equivalent coupled stress is constructed.

4. The digital cable modeling and simulation system according to claim 1, characterized in that... The damage evolution unit is specifically used for: An evolutionary model incorporating a damage accumulation threshold and a damage saturation term is adopted. The damage accumulation rate is calculated by combining the portion of the equivalent coupled stress that is greater than the damage accumulation threshold with a preset material degradation characteristic coefficient. The damage accumulation rate is numerically integrated over time to calculate the microscopic damage accumulation variable in real time.

5. A digital cable modeling and simulation system according to claim 1, characterized in that... The parameter correction unit is specifically used for: By combining the accumulated variable of micro-damage with the damage-impedance coupling coefficient in the preset mapping coefficient, the preset initial impedance is corrected to obtain the simulated impedance value.

6. A digital cable modeling and simulation system according to claim 5, characterized in that... The parameter correction unit is further used for: By combining the accumulated variable of micro-damage with the damage-modulus coupling coefficient in the preset mapping coefficient, the preset initial modulus is corrected to obtain the simulated modulus value.

7. The digital cable modeling and simulation system according to claim 1, characterized in that... The calculation process of the closed-loop verification unit is as follows: Obtain the simulated impedance value, and obtain the actual impedance value and actual modulus value measured on the physical entity; Calculate the absolute deviation between the simulated impedance value and the actual impedance value; The absolute deviation is normalized by dividing it by the preset initial impedance, and the normalized value is subtracted from 1 to obtain the fidelity of the degraded state.

8. A digital cable modeling and simulation system according to claim 1, characterized in that... The adaptive correction unit is specifically used for: The fidelity of the degraded state is compared with a preset fidelity threshold and a preset significant deviation threshold. When the fidelity of the degraded state is greater than or equal to the preset fidelity threshold, it is determined that no correction is needed; When the fidelity of the degraded state is less than the preset fidelity threshold and greater than the difference between the preset fidelity threshold and the preset significant deviation threshold, it is determined to be a model mapping parameter drift, and a first-level correction signal is generated. When the fidelity of the degraded state is less than or equal to the difference between the preset fidelity threshold and the preset significant deviation threshold, the model evolution rate is determined to be in failure, and a secondary correction signal is generated.

9. A digital cable modeling and simulation system according to claim 8, characterized in that... , in response to the first-level correction signal: Calculate the normalized impedance error between the actual impedance value and the simulated impedance value; Obtain the true modulus value and calculate the normalized modulus error between the true modulus value and the simulated modulus value; Based on the normalized impedance error and the preset first-level correction feedback gain coefficient, the damage-impedance coupling coefficient in the preset mapping coefficient is corrected. Based on the normalized modulus error and the preset first-level correction feedback gain coefficient, the damage-modulus coupling coefficient in the preset mapping coefficient is corrected.

10. A digital cable modeling and simulation system according to claim 8, characterized in that... , in response to the second-level correction signal: Calculate the fidelity deviation between the preset fidelity threshold and the fidelity in the degraded state; Based on the fidelity deviation and the preset secondary correction feedback gain coefficient, the preset material degradation characteristic coefficient is corrected.

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