High-voltage cable degradation state live evaluation method based on current harmonics

Abstract

The invention relates to the technical field of electronic data processing, and provides a high-voltage cable degradation state electrification evaluation method based on current harmonics. The method comprises the following steps: acquiring a line current signal during operation of a high-voltage cable, decomposing the line current signal through an adaptive filter bank to generate a high-frequency first harmonic component and an ultrahigh-frequency second harmonic component, and determining energy parameters respectively corresponding to the first harmonic component and the second harmonic component; correcting the energy parameters according to the environment temperature and the load current of the high-voltage cable to obtain corrected parameters; and quantifying the degradation risk level of the current high-voltage cable based on the corrected parameters and the historical data set of the degradation of the high-voltage cable, generating an energy risk assessment report and sending the report to the power management terminal to manage the scheduling operation of the cable infrastructure project. Dynamic and accurate live evaluation of the degradation state of the high-voltage cable is realized, and the accuracy and the anti-interference performance of the degradation risk state evaluation of the high-voltage cable infrastructure project are improved.

Description

Technical Field

[0001] This application relates to the field of electronic data processing technology, and more specifically, to a live assessment method for the deterioration state of high-voltage cables based on current harmonics. Background Technology

[0002] High-voltage cables, as the core carrier of power transmission, directly affect the safe and stable operation of the power grid due to their insulation condition. With the acceleration of urbanization and the continuous growth of electricity demand, the safety and reliability of high-voltage cables, as the main means of power transmission, are crucial to the stable operation of the entire power system. The assessment of the degradation status of high-voltage cables is an important component of cable infrastructure projects, and their quality and safety directly affect the stable operation of the power system. As the scale and quantity of cable infrastructure projects and high-voltage cables continue to increase, the requirements for assessing the degradation status of high-voltage cables are also becoming increasingly stringent. However, because high-voltage cables are typically located in complex environments, their insulation condition is easily affected by various factors such as temperature, humidity, and electrical stress, gradually leading to degradation and even failure.

[0003] Traditional methods for assessing the condition of high-voltage cables often require power outages for testing. This not only disrupts power supply and the continuity of cable infrastructure operations but also makes it difficult to reflect the cable's operational status in real time. Furthermore, traditional methods lack the accuracy to detect early insulation degradation, easily missing optimal maintenance opportunities and reducing the operational efficiency of cable infrastructure projects. Summary of the Invention

[0004] This application provides a live assessment method for the degradation state of high-voltage cables based on current harmonics, which can at least partially solve the problem of insufficient detection accuracy of traditional methods for assessing the condition of high-voltage cables.

[0005] Other features and advantages of this application will become apparent from the following detailed description, or may be learned in part from practice of this application.

[0006] According to one aspect of this application, a live assessment method for the degradation state of high-voltage cables based on current harmonics is provided, comprising: acquiring the line current signal of the high-voltage cable during operation; decomposing the line current signal using an adaptive filter bank to generate a high-frequency first harmonic component and an ultra-high-frequency second harmonic component, and determining the energy parameters corresponding to the first harmonic component and the second harmonic component respectively; acquiring the ambient temperature of the current cable infrastructure project and the load current of the high-voltage cable, and correcting the energy parameters according to the ambient temperature and the load current to obtain corrected parameters; predicting the degradation risk level of the current high-voltage cable based on the corrected parameters and a historical dataset of high-voltage cable degradation, and generating an energy risk assessment report based on the degradation risk level.

[0007] In this application, based on the aforementioned scheme, the step of decomposing the line current signal using an adaptive filter bank to generate a high-frequency first harmonic component and an ultra-high-frequency second harmonic component includes: decomposing the line current signal using an adaptive filter bank to generate a fundamental frequency and a sum of harmonics; and extracting the high-frequency first harmonic component and the ultra-high-frequency second harmonic component from the sum of harmonics using a bandpass filter.

[0008] In this application, based on the aforementioned scheme, the step of decomposing the line current signal using an adaptive filter bank to generate a fundamental frequency and harmonic sum includes: determining the center frequency of the adaptive filter bank based on a preset fundamental frequency; and decomposing the line current signal based on the center frequency of the adaptive filter bank to generate a fundamental frequency and harmonic sum.

[0009] In this application, based on the aforementioned scheme, the step of performing short-time Fourier transforms on the first harmonic component and the second harmonic component respectively to determine the energy parameters corresponding to the first harmonic component and the second harmonic component includes: performing short-time Fourier transforms on the first harmonic component and the second harmonic component respectively to generate a first time-frequency matrix and a second time-frequency matrix; and determining the first energy parameter and the second energy parameter corresponding to the first harmonic component and the second harmonic component respectively based on the first time-frequency matrix and the second time-frequency matrix.

[0010] In this application, based on the aforementioned scheme, determining the first energy parameter and the second energy parameter corresponding to the first harmonic component and the second harmonic component based on the first time-frequency matrix and the second time-frequency matrix respectively includes: determining the first distribution probability and the second distribution probability corresponding to the first harmonic component and the second harmonic component based on the first time-frequency matrix and the second time-frequency matrix respectively; and determining the first energy parameter and the second energy parameter corresponding to the first harmonic component and the second harmonic component based on the first distribution probability and the second distribution probability respectively.

[0011] In this application, based on the aforementioned scheme, the step of obtaining the ambient temperature of the current cable infrastructure project and the load current of the high-voltage cable, and correcting the energy parameters according to the ambient temperature and the load current to obtain corrected parameters, includes: obtaining the ambient temperature of the current cable infrastructure project and the load current of the high-voltage cable; generating dielectric parameters based on the material parameters of the high-voltage cable and the ambient temperature; generating loss parameters according to the dielectric parameters and the load current of the high-voltage cable; and correcting the energy parameters according to the loss parameters to obtain corrected parameters.

[0012] In this application, based on the aforementioned scheme, the step of obtaining the ambient temperature of the current cable infrastructure project and the load current of the high-voltage cable, and generating dielectric parameters based on the material parameters of the high-voltage cable and the ambient temperature, includes: obtaining the current ambient temperature and the load current of the high-voltage cable; and generating a frequency of [missing information] based on the material parameters of the high-voltage cable and the ambient temperature. f The ambient temperature is T dielectric parameters at time for:

[0013] in, These represent the static dielectric constant and the dielectric constant at the high-frequency limit, respectively. Indicates the ambient temperature is T The relaxation time of the high-voltage cable These represent the distribution parameter and frequency, respectively.

[0014] In this application, based on the aforementioned scheme, generating loss parameters according to the dielectric parameters and the load current of the high-voltage cable includes: generating loss parameters according to the dielectric parameters. and the load current of the high-voltage cable The generation frequency is f The ambient temperature is T Loss parameters at time for:

[0015] in, Indicates taking the complex number The imaginary part, Represents the dielectric constant under vacuum conditions. This indicates the preset load factor.

[0016] In this application, based on the aforementioned scheme, the step of correcting the energy parameters according to the loss parameters to obtain correction parameters includes: correcting the energy parameters according to the loss parameters to obtain correction parameters corresponding to the first harmonic component and the second harmonic component respectively.

[0017]

[0018] in, Indicates the first energy parameter. This represents the second energy parameter.

[0019] In this application, based on the aforementioned scheme, the step of predicting the current degradation risk level of the high-voltage cable based on the correction parameters and historical data of high-voltage cable degradation, and generating an energy risk assessment report based on the degradation risk level, includes: constructing a dynamic coupling function and aging model based on the correction parameters and historical data of high-voltage cable degradation; predicting the current degradation risk level of the high-voltage cable based on the coupling function and aging model, and generating an energy risk assessment report based on the degradation risk level.

[0020] According to one aspect of this application, a computer-readable medium is provided having a computer program stored thereon, which, when executed by a processor, implements the live-line assessment method for the deterioration state of high-voltage cables based on current harmonics as described in the above embodiments.

[0021] According to one aspect of this application, an electronic device is provided, comprising: one or more processors; and a storage device for storing one or more programs, which, when executed by the one or more processors, cause the one or more processors to implement the live assessment method for high-voltage cable degradation status based on current harmonics as described in the above embodiments.

[0022] According to one aspect of this application, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the live-line assessment method for high-voltage cable degradation status based on current harmonics provided in the various alternative implementations described above.

[0023] The technical solution of this application involves acquiring the line current signal of a high-voltage cable during operation, decomposing the line current signal using an adaptive filter bank to generate a high-frequency first harmonic component and an ultra-high-frequency second harmonic component, and determining the energy parameters corresponding to the first and second harmonic components respectively; acquiring the ambient temperature and load current of the current cable infrastructure project, and correcting the energy parameters according to the ambient temperature and load current to obtain corrected parameters; predicting the current degradation risk level of the high-voltage cable based on the corrected parameters and historical data on high-voltage cable degradation, generating an energy risk assessment report based on the degradation risk level, sending the energy risk assessment report to the power management terminal, and managing the scheduling and operation of the cable infrastructure project based on the energy risk assessment report. By acquiring high-voltage cable current signals in real time, high-frequency and ultra-high-frequency harmonic components are dynamically decomposed to capture degradation-related characteristics; energy parameters are obtained through short-time Fourier transform to reflect the time-frequency distribution characteristics of harmonics; external interference is eliminated by combining ambient temperature and load current correction parameters; finally, the degree of degradation is quantified based on the correction parameters and historical data, realizing dynamic and accurate live assessment of the degradation status of high-voltage cables, thus improving the accuracy and anti-interference capability of degradation risk assessment for high-voltage cable infrastructure projects.

[0024] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0025] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0026] Figure 1 The flowchart of a live assessment method for the degradation state of high-voltage cables based on current harmonics is illustrated in one embodiment of this application.

[0027] Figure 2 The flowchart illustrating the generation of correction parameters is shown in one embodiment of this application.

[0028] Figure 3 The illustration shows a schematic diagram of a live assessment system for the degradation status of high-voltage cables based on current harmonics in one embodiment of this application.

[0029] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown. Detailed Implementation

[0030] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided to make this application more comprehensive and complete, and to fully convey the concept of the exemplary embodiments to those skilled in the art.

[0031] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this application. However, those skilled in the art will recognize that the technical solutions of this application can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this application.

[0032] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0033] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0034] The implementation details of the technical solution of this application are described below: Figure 1 A flowchart of a live-line assessment method for the degradation state of high-voltage cables based on current harmonics, according to an embodiment of this application, is shown. (Refer to...) Figure 1 As shown, the live-line assessment method for the degradation state of high-voltage cables based on current harmonics includes at least steps S110 to S150, which are described in detail below: S110 acquires the line current signal of the high-voltage cable during operation.

[0035] In one embodiment of this application, a suitable current transformer or Rogowski coil sensor is selected based on the voltage level and operating environment of the high-voltage cable. The sensor possesses high accuracy, wide bandwidth, and anti-interference capabilities to ensure accurate capture of current changes during cable operation. During installation, good coupling between the sensor and the cable is ensured to avoid signal distortion due to poor contact. The core principle at this stage is to convert the current signal in the cable into a measurable electrical signal through physical coupling, providing a reliable input for subsequent data acquisition. Optionally, a wireless network can be constructed based on Z-wave technology to build a sensor network among the sensors. This sensor network collects the line current signal of the high-voltage cable during operation and feeds the current signal back to the high-voltage cable management platform, such as an industrial cloud platform.

[0036] The raw signals output by sensors often contain high-frequency noise and power frequency interference. To address this, edge computing nodes deployed near the sensors filter and amplify the acquired signals. The filtering stage uses bandpass filters to retain characteristic frequency bands related to insulation degradation while suppressing irrelevant frequency components. The amplification stage adjusts the gain according to the signal amplitude to ensure the signal remains within the measurement range of the acquisition device. The technical effect of this stage is to improve signal quality, laying the foundation for digital acquisition.

[0037] The conditioned analog signal is converted into a digital signal by a high-precision analog-to-digital converter. The acquisition equipment has sufficient sampling rate and resolution to capture subtle changes in the current signal. The acquired digital signal is transmitted to the processing unit via optical fiber or shielded cable. Electromagnetic interference protection measures are taken during transmission to prevent signal contamination. The core principle of this stage is to discretize the continuous signal through digital means, facilitating subsequent algorithm processing.

[0038] Optionally, the acquired digital signals can be stored in real time to a cache or hard drive, with timestamps added for traceability. Preliminary verification is performed during storage to check signal integrity and for any abnormal abrupt changes. If abnormal data is found, the anomaly type is marked and recorded for future analysis.

[0039] Optionally, after acquiring the photothermal data, the acquired photothermal data can be organized and archived by edge computing nodes deployed near the sensor.

[0040] By acquiring line current signals from high-voltage cables in real time during operation, a raw data foundation is provided for subsequent analysis, ensuring that the evaluation process can be based on actual operating conditions, avoiding the limitations of static testing, and achieving real-time dynamic monitoring. This ensures data integrity and availability, forming a complete technical closed loop from signal acquisition to storage, supporting the subsequent insulation condition assessment process.

[0041] S120, the line current signal is decomposed by an adaptive filter bank to generate a high-frequency first harmonic component and an ultra-high-frequency second harmonic component, and the energy parameters corresponding to the first harmonic component and the second harmonic component are determined respectively.

[0042] In one embodiment of this application, the line current signal of a high-voltage cable under energized operation is processed to separate high-frequency harmonic components and ultra-high-frequency harmonic components. This avoids the loss of features due to the aliasing of harmonic energy in different frequency bands, providing an accurate data basis for subsequent degradation status assessment. The entire processing is divided into two sub-steps: first, an adaptive filter bank is used to decompose the line current signal into a fundamental frequency and a sum of harmonics; then, the sum of harmonics is decomposed into two frequency bands to extract the high-frequency and ultra-high-frequency components respectively.

[0043] In one embodiment of this application, the line current signal is decomposed using an adaptive filter bank to generate a high-frequency first harmonic component and an ultra-high-frequency second harmonic component, including: The line current signal is decomposed by an adaptive filter bank to generate a fundamental frequency and a sum of harmonics. The high-frequency first harmonic component and the ultra-high-frequency second harmonic component are extracted from the sum of harmonics using a bandpass filter.

[0044] In one embodiment of this application, the line current signal is decomposed using an adaptive filter bank to generate a fundamental frequency and a sum of harmonics, including: The center frequency of the adaptive filter bank is determined based on the preset fundamental frequency. Based on the center frequency of the adaptive filter bank, the line current signal is decomposed to generate the fundamental frequency and harmonic sum.

[0045] In one embodiment of this application, the adaptive filter bank can automatically adjust its parameters according to the characteristics of the input signal to better separate the fundamental frequency and harmonics. Based on the preset fundamental frequency, the center frequency of the adaptive filter bank is determined as follows:

[0046] in, Let represent the center frequency of the k-th filter. Indicates the fundamental frequency. This represents the bandwidth spread factor, with a value ranging from 0.1 to 0.3. k, N These represent the identifier and total number of filters in the filter bank, respectively.

[0047] In one embodiment of this application, after determining the center frequency, the line current signal is decomposed based on the center frequency of the adaptive filter bank to generate a fundamental frequency and a sum of harmonics. The adaptive filter bank is used to process the line current signal. The signal is processed and decomposed into fundamental frequency. Harmonic sum During this process, the center frequency of the filter bank is dynamically adjusted according to a specific formula. By adaptively adjusting the filter center frequency, the fundamental and harmonic frequencies can be separated more accurately, reducing the interference of the fundamental frequency on harmonic analysis and laying the foundation for the subsequent accurate extraction of harmonic components in different frequency bands.

[0048] In one embodiment of this application, the input is the sum of harmonics obtained through adaptive filter bank decomposition, and high-frequency and ultra-high-frequency components are extracted from the sum of harmonics. For example, in the high-frequency band, a bandpass filter is used to extract components from the sum of harmonics. Extracting the frequency range in The component, as the first harmonic component of the high frequency. In the ultra-high frequency band, a bandpass filter is also used to extract the total harmonics. Extracting the frequency range in The component, as the second harmonic component of ultra-high frequency. A bandpass filter allows signals within a specific frequency range to pass through while blocking signals of other frequencies. By appropriately setting the passband frequency range of the bandpass filter, the harmonic components of the desired frequency band can be accurately extracted.

[0049] In this embodiment, the first harmonic component of high frequency and the second harmonic component of ultra-high frequency are separated by the synergistic effect of adaptive filter banks and bandpass filters. This avoids the aliasing of harmonic energy in different frequency bands, achieves effective separation of harmonic components in high-voltage cable current signals, preserves the independent characteristics of each harmonic band, enhances the adaptability of the decomposition process, ensures the accurate extraction of different frequency components, provides a clear frequency component basis for subsequent energy analysis, and provides clear and accurate data for subsequent assessment of high-voltage cable degradation based on these components. This helps to more accurately analyze the degradation of the cable.

[0050] In one embodiment of this application, short-time Fourier transforms are performed on the first harmonic component and the second harmonic component respectively to determine the energy parameters corresponding to the first harmonic component and the second harmonic component respectively. Short-time Fourier transform operations are performed on the separated first harmonic component and the second harmonic component respectively. By sliding a window function of a certain length on the time axis, Fourier analysis is performed on the harmonic component segment within each window, converting the time-domain signal into a time-frequency domain representation. This obtains the energy distribution of each harmonic component at different times and frequencies, thereby determining their corresponding energy parameters and providing energy characteristic information based on time-frequency characteristics for subsequent analysis.

[0051] In one embodiment of this application, short-time Fourier transforms are performed on the first harmonic component and the second harmonic component respectively to determine the energy parameters corresponding to the first harmonic component and the second harmonic component, including: Short-time Fourier transforms are performed on the first harmonic component and the second harmonic component respectively to generate a first time-frequency matrix and a second time-frequency matrix; Based on the first time-frequency matrix and the second time-frequency matrix, the first energy parameter and the second energy parameter corresponding to the first harmonic component and the second harmonic component are determined respectively.

[0052] In one embodiment of this application, the first harmonic component Second harmonic component Short-time Fourier transforms are performed separately, and signal segments are extracted using a sliding window function. Each segment is then processed using Fourier transform-based segmentation. Specifically, the choice of the Fourier transform window function balances time and frequency resolution. The division between high-frequency and ultra-high-frequency bands is determined based on the characteristics of insulation degradation-sensitive frequency bands. For example, a longer window length is used in the high-frequency band to capture stable features, while a shorter window length is used in the ultra-high-frequency band to adapt to rapid changes, ensuring that the time-frequency analysis focuses on key energy distribution regions. The first time-frequency matrix is ​​then generated. Second time-frequency matrix ,in t and f These represent time and frequency, respectively. This process transforms the time-domain signal into a time-frequency matrix, visually demonstrating the distribution of energy in time and frequency, and providing data support for energy probability normalization.

[0053] In addition, the window length of the short-time Fourier transform can be dynamically adjusted according to the signal characteristics. For example, a 20ms window length can be used to capture rapid changes in the high-frequency band, while a 5ms window length can be used in the ultra-high-frequency band to adapt to higher frequency characteristics.

[0054] In one embodiment of this application, based on the first time-frequency matrix Second time-frequency matrix The first harmonic component is determined respectively. and the second harmonic component The corresponding first distribution probability Second distribution probability They are respectively:

[0055]

[0056] in, Indicates the frequency band range of the integral. The time window representing the integration. t andf These represent time and frequency, respectively. By converting the energy at each point in the time-frequency matrix into a probability value, the energy distribution satisfies the basic requirements of a probability distribution. The normalized probability distribution accurately reflects the relative strength of energy at different time and frequency locations, providing standardized input for subsequent energy parameter calculations.

[0057] In one embodiment of this application, based on the first distribution probability Second distribution probability The first harmonic component is determined respectively. and the second harmonic component The corresponding first energy parameter Second energy parameter for:

[0058]

[0059] in, t and f Representing time and frequency respectively, This represents the preset energy factor. Through the above calculations, a higher energy parameter value indicates a more dispersed energy distribution, corresponding to a more severe deterioration of the microstructure of the insulating material.

[0060] Optionally, the above calculation results are used to generate energy parameters and time curves using visualization tools. The energy parameters of normal insulation samples should be lower than those of degraded samples, and the trend of energy parameter changes should be positively correlated with the insulation life decay curve. For example, when partial discharge occurs in the insulation material, the energy parameters in the ultra-high frequency band will increase significantly, forming identifiable degradation characteristic peaks. Time-frequency analysis of harmonic components using short-time Fourier transform can capture the local characteristics of the signal in both time and frequency dimensions. The determination of energy parameters focuses on the intensity performance of harmonic components in a specific time-frequency region, providing key indicators for quantitative analysis, reflecting the actual impact of harmonic components on cable operation, and ensuring that the quantitative results of energy parameters are strongly correlated with the actual insulation state.

[0061] S130: Obtain the ambient temperature and load current of the current cable infrastructure project and the high-voltage cable, and correct the energy parameters according to the ambient temperature and the load current to obtain the corrected parameters.

[0062] In one embodiment of this application, the current ambient temperature is obtained by a temperature sensor, and the real-time load current of the high-voltage cable is obtained by a current measuring device. Then, based on the specific conditions of the obtained ambient temperature and load current, the energy parameters corresponding to the previously determined first harmonic component and second harmonic component are corrected respectively, so as to eliminate the influence of ambient temperature changes and load current fluctuations on the energy parameters, and finally obtain more accurate and reliable corrected parameters.

[0063] like Figure 2 As shown, in one embodiment of this application, the ambient temperature of the current cable infrastructure project and the load current of the high-voltage cable are obtained. The energy parameters are then corrected based on the ambient temperature and the load current to obtain corrected parameters, including: S210, Obtain the ambient temperature and load current of the current cable infrastructure project, and generate dielectric parameters based on the material parameters of the high-voltage cable and the ambient temperature; S220, generate loss parameters based on the dielectric parameters and the load current of the high-voltage cable; S230, the energy parameters are corrected according to the loss parameters to obtain the corrected parameters.

[0064] In one embodiment of this application, the ambient temperature of the current cable infrastructure project and the load current of the high-voltage cable are obtained. Based on the material parameters of the high-voltage cable and the ambient temperature, the polarization behavior of the material in the electric field is analyzed, considering how the dielectric parameters change with frequency and temperature, and generating a frequency of... f The ambient temperature is T dielectric parameters at time for:

[0065] in, These represent the static dielectric constant and the dielectric constant at the high-frequency limit, respectively. Indicates the ambient temperature is T The relaxation time of the high-voltage cable These represent the distributed parameters and frequency, respectively. The dielectric response characteristics of the insulating material under different conditions were obtained experimentally, and a model that accurately describes its nonlinear polarization characteristics was established. This model forms the basis for subsequent correction work, ensuring that the correction process truly reflects the material properties and improves the accuracy of the correction.

[0066] In one embodiment of this application, a dynamic loss parameter is generated based on a dielectric property model and considering the ambient temperature and load conditions during actual operation. Specifically, based on the dielectric parameter... and the load current of the high-voltage cable The generation frequency is fThe ambient temperature is T Loss parameters at time for:

[0067] in, Indicates taking the complex number The imaginary part, Represents the dielectric constant under vacuum conditions. This represents the preset load factor. By calculating loss parameters, the influence of temperature and load on energy parameters can be effectively captured. By quantifying the effects of these external factors, it is ensured that the correction process can specifically eliminate interference and retain the degradation characteristics of the insulation material itself.

[0068] In one embodiment of this application, based on the loss parameters The energy parameters are corrected respectively to obtain the correction parameters corresponding to the first harmonic component and the second harmonic component:

[0069]

[0070] in, Indicates the first energy parameter. This represents the second energy parameter.

[0071] By utilizing the loss parameters calculated earlier, the original high-frequency and ultra-high-frequency energy parameters are normalized. This process removes the interference of temperature and load on the energy parameters, allowing the corrected energy parameters to more purely reflect the microstructural changes of the insulating material. Through this process, the energy entropy assessment results will more closely approximate the actual degradation state of the insulating material.

[0072] In the above calculation process, the first energy parameter is adjusted using a correction factor. Second energy parameter Normalization was performed separately. This was done by normalizing the loss parameters within a specified frequency band. Integrating the original energy parameters yields corrected parameters. This process considers the impact of external environment and operating conditions on the cable's electrical characteristics. By eliminating the interference effects of temperature and load, it ensures that the obtained corrected parameters accurately reflect the cable's degradation state, thus improving the accuracy of the evaluation results.

[0073] S140, Based on the correction parameters and historical dataset of high-voltage cable degradation, predict the current degradation risk level of the high-voltage cable, and generate an energy risk assessment report based on the degradation risk level.

[0074] In one embodiment of this application, by using previously obtained correction parameters and simultaneously retrieving historical datasets of high-voltage cable degradation, the current corrected parameter information is comprehensively compared and analyzed with data from different degradation stages in the historical data. By finding the correlation and differences between the two, and based on the degradation patterns reflected in the historical data, the current parameter characteristics are mapped to the corresponding degradation level category, thereby quantifying the current degradation risk level of the high-voltage cable. Based on the degradation risk level, an energy risk assessment report is generated, providing a key basis for assessing the cable condition.

[0075] In one embodiment of this application, based on the correction parameters and historical datasets of high-voltage cable degradation, the current degradation risk level of the high-voltage cable is predicted, and an energy risk assessment report is generated based on the degradation risk level, including: Based on the aforementioned correction parameters and historical datasets of high-voltage cable degradation, a dynamic coupling function and aging model are constructed. Based on the coupling function and aging model, the current degradation risk level of the high-voltage cable is predicted, and an energy risk assessment report is generated based on the degradation risk level.

[0076] In one embodiment of this application, a dynamic coupling function is constructed based on the correction parameters and historical datasets of high-voltage cable degradation. Specifically, the dynamic coupling function is constructed by weighted combination of high-frequency and ultra-high-frequency correction parameters and their rates of change. The weighting coefficients and nonlinear exponents in the weighting process are obtained from historical data using a particle swarm optimization algorithm, ensuring that the model can accurately capture the complex nonlinear relationship between energy entropy and degradation degree. The core principle of the function in this embodiment lies in fusing multi-source feature information and achieving a comprehensive characterization of degradation features through dynamic weight adjustment, providing a basic model for real-time assessment.

[0077] In one embodiment of this application, an aging model is constructed based on the corrected parameters and historical datasets of high-voltage cable degradation. Specifically, an aging model is introduced to describe the long-term aging effect of the insulation material. Corrected parameters for high-frequency and ultra-high-frequency energy are integrated in an integral form, and an exponential decay model is used to simulate the cumulative effect of the aging process. The decay coefficient in the aging model is determined by fitting historical degradation data to ensure that the trend term accurately reflects the gradual degradation of material performance over time. The technical effect of this stage is to establish a time-related degradation baseline, providing a dynamic reference benchmark for real-time evaluation.

[0078] After quantifying the risk level of high-voltage cable degradation, the quantified degradation risk level is encapsulated according to a preset communication protocol to ensure that the data format matches the receiving standard of the power management terminal. Then, the encapsulated data is transmitted securely and reliably to the terminal through wired or wireless communication links. After receiving the data, the power management terminal parses and verifies it. After confirming that the data is complete and error-free, it displays it on the monitoring interface, allowing maintenance personnel to monitor the degradation status of the high-voltage cable in real time and providing a basis for subsequent maintenance decisions.

[0079] In one embodiment of this application, by coupling the coupling function and the aging model, the current degradation risk level of the high-voltage cable is predicted, realizing dynamic modeling of the high-voltage cable's operating state, and generating an energy risk assessment report based on the degradation risk level. Optionally, the degradation risk level, along with preset corresponding processing methods, risk levels, and other information, are written into a preset report template to generate an energy risk assessment report.

[0080] S150, the energy risk assessment report is sent to the power management terminal, and the scheduling operation of the cable infrastructure project is managed based on the energy risk assessment report.

[0081] After the energy risk assessment report is generated, an efficient and stable information transmission system ensures that the report is accurately and promptly transmitted to the power management terminal. Optionally, encryption technology is used to ensure data security during transmission, preventing information leakage or tampering. Once the report is successfully delivered to the power management terminal, subsequent processing is automatically triggered, providing a scientific basis for the scheduling and operation of cable infrastructure projects.

[0082] Upon receiving the energy risk assessment report, the power management terminal initiates a data analysis and processing mechanism to thoroughly analyze the various risk indicators and their potential impacts. Based on these detailed risk assessment results, managers can use industrial control software to develop more precise and reasonable scheduling plans for cable infrastructure projects, including optimizing construction sequences, adjusting resource allocation, and improving emergency response plans. In this way, the energy risk assessment report not only provides strong support for the safe operation of cable infrastructure projects but also promotes the efficient and stable operation of the entire power system.

[0083] The above process, from static feature extraction to dynamic evaluation, optimizes weighting and attenuation coefficients to ensure the model adapts to the different characteristics of various insulation materials, and introduces periodic fluctuation terms to improve evaluation stability under load variations. The final energy risk assessment report displays the degradation degree over time through a visual interface, providing intuitive and quantitative decision-making basis for insulation condition monitoring, forming a complete technical closed loop from data input to condition output. Parameters at each stage are derived from historical data training or physical characteristic analysis, ensuring the model's engineering applicability and physical interpretability.

[0084] This application's technical solution acquires the line current signal of a high-voltage cable during operation, decomposes the line current signal using an adaptive filter bank to generate a high-frequency first harmonic component and an ultra-high-frequency second harmonic component, and determines the energy parameters corresponding to the first and second harmonic components respectively; acquires the ambient temperature and load current of the current cable infrastructure project, and corrects the energy parameters according to the ambient temperature and load current to obtain corrected parameters; based on the corrected parameters and historical data of high-voltage cable degradation, predicts the current degradation risk level of the high-voltage cable, and generates an energy risk assessment report based on the degradation risk level, sending the energy risk assessment report to the power management terminal, and managing the scheduling and operation of the cable infrastructure project based on the energy risk assessment report. By acquiring the high-voltage cable line current signal in real time, dynamically decomposing high-frequency and ultra-high-frequency harmonic components, and capturing degradation-related characteristics; combining ambient temperature and load current correction parameters to eliminate external interference; and finally quantifying the degradation degree based on the corrected parameters and historical data, a dynamic and accurate live-line assessment of the degradation state of the high-voltage cable is achieved, improving the accuracy and anti-interference capability of the degradation risk state assessment of high-voltage cable infrastructure projects.

[0085] The following describes embodiments of the live-line assessment system for the degradation state of high-voltage cables based on current harmonics, which can be used to execute the live-line assessment method for the degradation state of high-voltage cables based on current harmonics described in the above embodiments of this application. It is understood that the live-line assessment system for the degradation state of high-voltage cables based on current harmonics can be a computer program (including program code) running on a computer device; for example, the live-line assessment system for the degradation state of high-voltage cables based on current harmonics is an application software. This live-line assessment system for the degradation state of high-voltage cables based on current harmonics can be used to execute the corresponding steps in the methods provided in the embodiments of this application. For details not disclosed in the embodiments of the live-line assessment system for the degradation state of high-voltage cables based on current harmonics of this application, please refer to the embodiments of the live-line assessment method for the degradation state of high-voltage cables based on current harmonics described above.

[0086] Figure 3A block diagram of a live-line assessment system for the degradation status of high-voltage cables based on current harmonics, according to an embodiment of this application, is shown.

[0087] Reference Figure 3 As shown, a live-line assessment system for the degradation status of high-voltage cables based on current harmonics according to an embodiment of this application includes: The acquisition module 310 is used to acquire the line current signal of the high-voltage cable during operation; The decomposition module 320 is used to decompose the line current signal through an adaptive filter bank to generate a high-frequency first harmonic component and an ultra-high-frequency second harmonic component, and to determine the energy parameters corresponding to the first harmonic component and the second harmonic component respectively. The correction module 330 is used to obtain the ambient temperature and the load current of the high-voltage cable in the current cable infrastructure project, and correct the energy parameters according to the ambient temperature and the load current to obtain the correction parameters. The quantization module 340 is used to predict the current degradation risk level of the high-voltage cable based on the correction parameters and the historical dataset of high-voltage cable degradation, and to generate an energy risk assessment report based on the degradation risk level. The management module 340 is used to send the energy risk assessment report to the power management terminal and manage the scheduling and operation of the cable infrastructure project based on the energy risk assessment report.

[0088] In this application, based on the aforementioned scheme, the step of decomposing the line current signal using an adaptive filter bank to generate a high-frequency first harmonic component and an ultra-high-frequency second harmonic component includes: decomposing the line current signal using an adaptive filter bank to generate a fundamental frequency and a sum of harmonics; and extracting the high-frequency first harmonic component and the ultra-high-frequency second harmonic component from the sum of harmonics using a bandpass filter.

[0089] In this application, based on the aforementioned scheme, the step of decomposing the line current signal using an adaptive filter bank to generate a fundamental frequency and harmonic sum includes: determining the center frequency of the adaptive filter bank based on a preset fundamental frequency; and decomposing the line current signal based on the center frequency of the adaptive filter bank to generate a fundamental frequency and harmonic sum.

[0090] In this application, based on the aforementioned scheme, determining the energy parameters corresponding to the first harmonic component and the second harmonic component respectively includes: performing short-time Fourier transform on the first harmonic component and the second harmonic component respectively to generate a first time-frequency matrix and a second time-frequency matrix; and determining the first energy parameter and the second energy parameter corresponding to the first harmonic component and the second harmonic component respectively based on the first time-frequency matrix and the second time-frequency matrix.

[0091] In this application, based on the aforementioned scheme, determining the first energy parameter and the second energy parameter corresponding to the first harmonic component and the second harmonic component based on the first time-frequency matrix and the second time-frequency matrix respectively includes: determining the first distribution probability and the second distribution probability corresponding to the first harmonic component and the second harmonic component based on the first time-frequency matrix and the second time-frequency matrix respectively; and determining the first energy parameter and the second energy parameter corresponding to the first harmonic component and the second harmonic component based on the first distribution probability and the second distribution probability respectively.

[0092] In this application, based on the aforementioned scheme, the step of obtaining the ambient temperature of the current cable infrastructure project and the load current of the high-voltage cable, and correcting the energy parameters according to the ambient temperature and the load current to obtain corrected parameters, includes: obtaining the ambient temperature of the current cable infrastructure project and the load current of the high-voltage cable; generating dielectric parameters based on the material parameters of the high-voltage cable and the ambient temperature; generating loss parameters according to the dielectric parameters and the load current of the high-voltage cable; and correcting the energy parameters according to the loss parameters to obtain corrected parameters.

[0093] In this application, based on the aforementioned scheme, the step of obtaining the ambient temperature of the current cable infrastructure project and the load current of the high-voltage cable, and generating dielectric parameters based on the material parameters of the high-voltage cable and the ambient temperature, includes: obtaining the current ambient temperature and the load current of the high-voltage cable; and generating a frequency of [missing information] based on the material parameters of the high-voltage cable and the ambient temperature. f The ambient temperature is T dielectric parameters at time for:

[0094] in, These represent the static dielectric constant and the dielectric constant at the high-frequency limit, respectively. Indicates the ambient temperature is T The relaxation time of the high-voltage cable These represent the distribution parameter and frequency, respectively.

[0095] In this application, based on the aforementioned scheme, generating loss parameters according to the dielectric parameters and the load current of the high-voltage cable includes: generating loss parameters according to the dielectric parameters. and the load current of the high-voltage cable The generation frequency is f The ambient temperature is T Loss parameters at time for:

[0096] in, Indicates taking the complex number The imaginary part, Represents the dielectric constant under vacuum conditions. This indicates the preset load factor.

[0097] In this application, based on the aforementioned scheme, the step of correcting the energy parameters according to the loss parameters to obtain correction parameters includes: correcting the energy parameters according to the loss parameters to obtain correction parameters corresponding to the first harmonic component and the second harmonic component respectively.

[0098]

[0099] in, Indicates the first energy parameter. This represents the second energy parameter.

[0100] In this application, based on the aforementioned scheme, the step of predicting the current degradation risk level of the high-voltage cable based on the correction parameters and historical data of high-voltage cable degradation, and generating an energy risk assessment report based on the degradation risk level, includes: constructing a dynamic coupling function and aging model based on the correction parameters and historical data of high-voltage cable degradation; predicting the current degradation risk level of the high-voltage cable based on the coupling function and aging model, and generating an energy risk assessment report based on the degradation risk level.

[0101] The technical solution of this application involves acquiring the line current signal of a high-voltage cable during operation, decomposing the line current signal using an adaptive filter bank to generate a high-frequency first harmonic component and an ultra-high-frequency second harmonic component, and determining the energy parameters corresponding to the first and second harmonic components respectively; acquiring the ambient temperature and load current of the current cable infrastructure project, and correcting the energy parameters according to the ambient temperature and load current to obtain corrected parameters; predicting the current degradation risk level of the high-voltage cable based on the corrected parameters and historical data on high-voltage cable degradation, generating an energy risk assessment report based on the degradation risk level, sending the energy risk assessment report to the power management terminal, and managing the scheduling and operation of the cable infrastructure project based on the energy risk assessment report. By acquiring high-voltage cable current signals in real time, high-frequency and ultra-high-frequency harmonic components are dynamically decomposed to capture degradation-related characteristics; energy parameters are obtained through short-time Fourier transform to reflect the time-frequency distribution characteristics of harmonics; external interference is eliminated by combining ambient temperature and load current correction parameters; finally, the degree of degradation is quantified based on the correction parameters and historical data, realizing dynamic and accurate live assessment of the degradation status of high-voltage cables, thus improving the accuracy and anti-interference capability of degradation risk assessment for high-voltage cable infrastructure projects.

[0102] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown.

[0103] It should be noted that the computer system of the electronic device in this embodiment is only an example and should not impose any limitations on the function and scope of use of the embodiments of this application.

[0104] In this embodiment, the computer system includes a central processing unit 401, which can perform various appropriate actions and processes based on a program stored in the read-only memory 402 or a program loaded from the storage section 408 into the random access memory 403, such as executing the live assessment method for high-voltage cable degradation status based on current harmonics described in the above embodiment. The random access memory 403 also stores various programs and data required for system operation. The central processing unit 401, the read-only memory 402, and the random access memory 403 are interconnected via a bus 404. An input / output interface 405 is also connected to the bus 404.

[0105] The following components are connected to the input / output interface 405: an input section 406 including a keyboard, mouse, etc.; an output section 407 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the input / output interface 405 as needed. A removable medium 411, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 410 as needed so that computer programs read from it can be installed into the storage section 408 as needed.

[0106] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 409, and / or installed from removable medium 411. When the computer program is executed by central processing unit 401, it performs various functions defined in the system of this application.

[0107] It should be noted that the computer-readable medium shown in the embodiments of this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying a computer-readable computer program. The transmitted data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0108] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0109] The units described in the embodiments of this application can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0110] According to one aspect of this application, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the methods provided in the various alternative implementations described above.

[0111] In another aspect, this application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiments; or it may exist independently and not assembled into the electronic device. The computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to implement the live-line assessment method for high-voltage cable degradation status based on current harmonics described in the above embodiments.

[0112] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0113] Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, touch terminal, or network device, etc.) to execute the method according to the embodiments of this application.

[0114] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein.

[0115] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A live-line assessment method for the degradation state of high-voltage cables based on current harmonics, characterized in that, include: Acquire the line current signal of the high-voltage cable during operation; The line current signal is decomposed by an adaptive filter bank to generate a high-frequency first harmonic component and an ultra-high-frequency second harmonic component, and the energy parameters corresponding to the first harmonic component and the second harmonic component are determined respectively. The ambient temperature and load current of the high-voltage cable in the current cable infrastructure project are obtained, and the energy parameters are corrected according to the ambient temperature and the load current to obtain the corrected parameters. Based on the corrected parameters and historical datasets of high-voltage cable degradation, the current degradation risk level of the high-voltage cable is predicted, and an energy risk assessment report is generated based on the degradation risk level. The energy risk assessment report is sent to the power management terminal, and the scheduling and operation of the cable infrastructure project are managed based on the energy risk assessment report.

2. The live-line assessment method for the degradation state of high-voltage cables based on current harmonics according to claim 1, characterized in that, The line current signal is decomposed using an adaptive filter bank to generate a high-frequency first harmonic component and an ultra-high-frequency second harmonic component, including: The line current signal is decomposed by an adaptive filter bank to generate a fundamental frequency and a sum of harmonics. The high-frequency first harmonic component and the ultra-high-frequency second harmonic component are extracted from the sum of harmonics using a bandpass filter.

3. The live-line assessment method for the degradation state of high-voltage cables based on current harmonics according to claim 2, characterized in that, The line current signal is decomposed using an adaptive filter bank to generate a fundamental frequency and a sum of harmonics, including: The center frequency of the adaptive filter bank is determined based on the preset fundamental frequency. Based on the center frequency of the adaptive filter bank, the line current signal is decomposed to generate the fundamental frequency and harmonic sum.

4. The live-line assessment method for the degradation state of high-voltage cables based on current harmonics according to claim 1, characterized in that, Determining the energy parameters corresponding to the first harmonic component and the second harmonic component respectively includes: Short-time Fourier transforms are performed on the first harmonic component and the second harmonic component respectively to generate a first time-frequency matrix and a second time-frequency matrix; Based on the first time-frequency matrix and the second time-frequency matrix, the first energy parameter and the second energy parameter corresponding to the first harmonic component and the second harmonic component are determined respectively.

5. The live-line assessment method for the degradation state of high-voltage cables based on current harmonics according to claim 4, characterized in that, Based on the first time-frequency matrix and the second time-frequency matrix, the first energy parameter and the second energy parameter corresponding to the first harmonic component and the second harmonic component are determined respectively, including: Based on the first time-frequency matrix and the second time-frequency matrix, the first distribution probability and the second distribution probability corresponding to the first harmonic component and the second harmonic component are determined respectively; Based on the first distribution probability and the second distribution probability, the first energy parameter and the second energy parameter corresponding to the first harmonic component and the second harmonic component are determined respectively.

6. The live-line assessment method for the degradation state of high-voltage cables based on current harmonics according to claim 1, characterized in that, The ambient temperature and load current of the high-voltage cable in the current cable infrastructure project are obtained. The energy parameters are then corrected based on the ambient temperature and load current to obtain corrected parameters, including: The ambient temperature and load current of the high-voltage cable in the current cable infrastructure project are obtained, and dielectric parameters are generated based on the material parameters of the high-voltage cable and the ambient temperature. Based on the dielectric parameters and the load current of the high-voltage cable, loss parameters are generated; The energy parameters are corrected according to the loss parameters to obtain the corrected parameters.

7. The live-line assessment method for the degradation state of high-voltage cables based on current harmonics according to claim 6, characterized in that, Obtain the ambient temperature and load current of the current cable infrastructure project, and generate dielectric parameters based on the material parameters of the high-voltage cable and the ambient temperature, including: Obtain the current ambient temperature and the load current of the high-voltage cable; Based on the material parameters of the high-voltage cable and the ambient temperature, the generation frequency is... f The ambient temperature is T dielectric parameters at time for: in, These represent the static dielectric constant and the dielectric constant at the high-frequency limit, respectively. Indicates the ambient temperature is T The relaxation time of the high-voltage cable These represent the distribution parameter and frequency, respectively.

8. The live-line assessment method for the degradation state of high-voltage cables based on current harmonics according to claim 7, characterized in that, Based on the dielectric parameters and the load current of the high-voltage cable, loss parameters are generated, including: According to the dielectric parameters and the load current of the high-voltage cable The generation frequency is f The ambient temperature is T Loss parameters at time for: in, Indicates taking the complex number The imaginary part, Represents the dielectric constant under vacuum conditions. This indicates the preset load factor.

9. The live-line assessment method for the degradation state of high-voltage cables based on current harmonics according to claim 8, characterized in that, The energy parameters are corrected according to the loss parameters to obtain the corrected parameters, including: The energy parameters are corrected based on the loss parameters to obtain the correction parameters corresponding to the first harmonic component and the second harmonic component, respectively: in, Indicates the first energy parameter. This represents the second energy parameter.

10. The live-line assessment method for the degradation state of high-voltage cables based on current harmonics according to claim 1, characterized in that, Based on the corrected parameters and historical data on high-voltage cable degradation, the current degradation risk level of the high-voltage cable is predicted, and an energy risk assessment report is generated based on the degradation risk level, including: Based on the aforementioned correction parameters and historical datasets of high-voltage cable degradation, a dynamic coupling function and aging model are constructed. Based on the coupling function and aging model, the current degradation risk level of the high-voltage cable is predicted, and an energy risk assessment report is generated based on the degradation risk level.

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