Cable aging section state evaluation method, device, equipment, medium and product

Abstract

The invention relates to a cable aging section state evaluation method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring impedance spectrum data of a to-be-detected cable; dividing the to-be-tested cable into a plurality of initial aging sections according to the impedance spectrum data, and determining a complex dielectric constant of each initial aging section; constructing a target function according to the impedance spectrum data and the complex dielectric constants, and performing fitting calculation on the complex dielectric constants according to the target function to obtain a target complex dielectric constant; and correcting the section length of each initial aging section according to the target complex dielectric constant to obtain a target aging section. By adopting the method, the specific aging condition of the cable can be accurately evaluated.

Description

Technical Field

[0001] The present application relates to the field of automated detection technology, and in particular to a method, apparatus, computer equipment, storage medium, and computer program product for evaluating the status of a cable aging section. Background Art

[0002] Cross-linked polyethylene cables are widely used as high-voltage transmission carriers in modern power systems. The reliability of their insulation performance is directly related to the safe and stable operation of the power grid. Due to long-term exposure to multiple stresses, such as electrical, thermal, and mechanical stresses, the cable insulation gradually ages. Insulation degradation causes approximately 78% of cable failures in actual operation and maintenance statistics, becoming a major hidden danger that restricts power supply reliability.

[0003] In related technologies, Broadband Impedance Spectroscopy (BIS) is widely used for cable status detection. This method measures the broadband impedance response of the cable input end in an open-circuit state, identifying impedance change points and preliminarily inferring possible structural anomalies in the cable. However, due to the uneven aging of cables, that is, different areas in the same line may have different degrees of insulation degradation, traditional BIS detection is usually unable to accurately locate the location of the aging section. Even if it can find abnormal points with impedance discontinuity in the cable, it is difficult to further quantify and evaluate the specific degree of insulation degradation in the aging section, making it difficult to accurately assess the specific aging condition of the cable. Summary of the Invention

[0004] Based on this, it is necessary to provide a cable aging section status assessment method, device, computer equipment, computer-readable storage medium and computer program product that can accurately assess the specific aging conditions of the cable in order to address the above technical problems.

[0005] In a first aspect, the present application provides a method for evaluating the status of a cable aging section, comprising:

[0006] Obtain impedance spectrum data of the cable under test;

[0007] Dividing the cable to be tested into a plurality of initial aging sections according to the impedance spectrum data, and determining the complex dielectric constant of each of the initial aging sections;

[0008] Constructing a target function according to the impedance spectrum data and the complex dielectric constant, and performing fitting calculation on each of the complex dielectric constants according to the target function to obtain a target complex dielectric constant;

[0009] According to the target complex dielectric constant, the segment length of each initial aging segment is corrected to obtain a target aging segment.

[0010] In one embodiment, the impedance spectrum data includes measured impedance data and calculated impedance data; constructing a target function based on the impedance spectrum data and the complex dielectric constant, and performing fitting calculation on each of the complex dielectric constants according to the target function to obtain a target complex dielectric constant includes:

[0011] Constructing an objective function according to the complex dielectric constant, the measured impedance data and the impedance spectrum data;

[0012] Constructing a particle group according to the initial aging segment; wherein each initial aging segment corresponds to a particle in the particle group, and each particle is used to represent a set of complex dielectric constants;

[0013] The position data and velocity data of each particle are iteratively updated according to the objective function. When an iteration completion condition is met, a corresponding target complex dielectric constant is obtained based on each particle in the iteratively completed particle group.

[0014] In one embodiment, the step of correcting the segment length of each of the initial aging segments according to the target complex dielectric constant to obtain the target aging segment includes:

[0015] Calculating the electromagnetic wave velocity of each of the initial aging sections according to the target complex dielectric constant;

[0016] The length of the initial aging section is corrected according to the electromagnetic wave velocity to obtain a target aging section.

[0017] In one embodiment, after correcting the length of the initial aging section according to the electromagnetic wave velocity to obtain a target aging section, the method further includes:

[0018] Calculating fracture growth rate data of each target aging section according to the electromagnetic wave velocity;

[0019] The aging degree level of each target aging section is determined based on the fracture growth rate data.

[0020] In one embodiment, determining the aging level of each target aging segment based on the fracture growth rate data includes:

[0021] Normalizing the fracture growth rate data to obtain an aging degree score;

[0022] An aging degree grade is determined for each target aging segment according to a preset aging degree marking rule and the aging degree score.

[0023] In one embodiment, dividing the cable to be tested into a plurality of initial aging sections according to the impedance spectrum data includes:

[0024] Extracting at least one mutation peak according to the impedance spectrum data to obtain a mutation peak sequence;

[0025] The mutation peak sequence is traversed in sequence, and when two adjacent mutation peaks are of the same polarity, the section between the two mutation peaks is divided into an initial aging section.

[0026] In a second aspect, the present application further provides a device for evaluating the state of a cable aging section, comprising:

[0027] A data acquisition module is used to obtain impedance spectrum data of the cable to be tested;

[0028] a data processing module, configured to divide the cable to be tested into a plurality of initial aging sections according to the impedance spectrum data, and determine the complex dielectric constant of each of the initial aging sections;

[0029] a data calculation module, configured to construct a target function based on the impedance spectrum data and the complex dielectric constant, and perform fitting calculation on each of the complex dielectric constants according to the target function to obtain a target complex dielectric constant;

[0030] A data evaluation module is used to correct the segment length of each of the initial aging segments according to the target complex dielectric constant to obtain a target aging segment.

[0031] In a third aspect, the present application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0032] Obtain impedance spectrum data of the cable under test;

[0033] Dividing the cable to be tested into a plurality of initial aging sections according to the impedance spectrum data, and determining the complex dielectric constant of each of the initial aging sections;

[0034] Constructing a target function according to the impedance spectrum data and the complex dielectric constant, and performing fitting calculation on each of the complex dielectric constants according to the target function to obtain a target complex dielectric constant;

[0035] According to the target complex dielectric constant, the segment length of each initial aging segment is corrected to obtain a target aging segment.

[0036] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0037] Obtain impedance spectrum data of the cable under test;

[0038] Dividing the cable to be tested into a plurality of initial aging sections according to the impedance spectrum data, and determining the complex dielectric constant of each of the initial aging sections;

[0039] Constructing a target function according to the impedance spectrum data and the complex dielectric constant, and performing fitting calculation on each of the complex dielectric constants according to the target function to obtain a target complex dielectric constant;

[0040] According to the target complex dielectric constant, the segment length of each initial aging segment is corrected to obtain a target aging segment.

[0041] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, which, when executed by a processor, implements the following steps:

[0042] Obtain impedance spectrum data of the cable under test;

[0043] Dividing the cable to be tested into a plurality of initial aging sections according to the impedance spectrum data, and determining the complex dielectric constant of each of the initial aging sections;

[0044] Constructing a target function according to the impedance spectrum data and the complex dielectric constant, and performing fitting calculation on each of the complex dielectric constants according to the target function to obtain a target complex dielectric constant;

[0045] According to the target complex dielectric constant, the segment length of each initial aging segment is corrected to obtain a target aging segment.

[0046] The above-mentioned cable aging section status assessment method, device, computer equipment, storage medium and computer program product obtain the impedance spectrum data of the cable to be tested, use the input impedance spectrum of the cable as the basic data source for evaluation, and reflect the dielectric properties and internal structure changes of the cable through frequency domain response data, avoiding the traditional method's reliance on appearance or mechanical properties, thereby realizing non-destructive detection of the cable status. Then, based on the impedance spectrum data, the cable to be tested is divided into several initial aging sections, and the complex dielectric constant of each initial aging section is determined. A target function is constructed based on the impedance spectrum data and the complex dielectric constant, and each complex dielectric constant is fitted and calculated according to the target function to obtain the target complex dielectric constant. The introduced fitting mechanism can minimize the deviation between the model parameters and the actual cable status, thereby improving the physical accuracy fitting capability of the cable insulation aging degree. Next, the initially estimated segment length is corrected based on the target complex dielectric constant obtained by fitting, and the segment length of each initial aging segment is corrected to obtain the target aging segment. This effectively overcomes the problem of misjudgment of segment length caused by aging, significantly improves the spatial accuracy of aging segment positioning, and achieves accurate positioning of the aging segment length, thereby enabling accurate assessment of the specific aging condition of the cable. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0048] Figure 1 This is a diagram of an application environment of a cable aging section status assessment method according to an embodiment;

[0049] Figure 2 Schematic diagram of a process for evaluating the status of a cable aging section in one embodiment;

[0050] Figure 3 Schematic diagram of the process of step S206 of the cable aging section status assessment method in one embodiment;

[0051] Figure 4 This is a structural block diagram of a device for evaluating the state of a cable aging section in one embodiment;

[0052] Figure 5 is a diagram of the internal structure of a computer device in one embodiment;

[0053] Figure 6 FIG. 4 is a diagram showing the internal structure of a computer device in another embodiment. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0055] The cable aging section status assessment method provided in the embodiment of the present application can be applied to Figure 1In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network, and the terminal 102 can be used to collect the impedance spectrum data of the cable to be tested, and send the collected data to the server 104 for processing. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. The data storage system can be used to store data such as the impedance spectrum data of the cable to be tested. Among them, the terminal 102 can be an acquisition device for impedance spectrum data, and can also be but not limited to various personal computers, laptops, smart phones, tablet computers, Internet of Things devices and portable wearable devices, for obtaining the impedance measured data input by the user. The server 104 can be implemented with an independent server or a server cluster consisting of multiple servers.

[0056] In an exemplary embodiment, Figure 2 As shown in the figure, a cable aging section status assessment method is provided, which is applied to Figure 1 The server 104 in the example is used as an example to illustrate the method, which includes the following steps S202 to S208.

[0057] Step S202: Obtain impedance spectrum data of the cable to be tested.

[0058] Impedance spectrum data refers to the complex impedance response of the cable input end at different frequencies under broadband signal excitation, including the impedance amplitude and phase. The amplitude represents the overall reactance encountered when the signal is transmitted at different frequencies, while the phase reflects the relative delay and change in the cable's response to signals of different frequencies. The impedance spectrum constructed based on impedance spectrum data represents frequency on the horizontal axis and amplitude and phase on the vertical axis, respectively. This can be understood as the electrical response curve of the cable's internal structure to external signals, allowing for the detection of abnormal electromagnetic properties caused by aging, damage, or structural changes.

[0059] For example, server 104 can obtain complete broadband impedance spectrum data for the cable under test from terminal 102. Server 104 can remotely or locally control an on-site cable testing device serving as terminal 102. This device can have broadband input impedance measurement capabilities and be connected to the cable under test. In actual operation, server 104 can connect one end of the cable to the impedance tester and set the other end to an open circuit, generating a reflected signal within the cable. This amplifies the differences in the cable's response to electromagnetic excitation at different frequencies, facilitates interference enhancement of the reflected wave signal, and makes it easier for server 104 to detect subtle phase changes caused by changes in the cable's internal dielectric properties.

[0060] After starting the acquisition, server 104 can control the tester to inject a point-by-point scanning AC signal into the cable within a set frequency range. The frequency range can cover tens of kilohertz to several megahertz to ensure comprehensive coverage of the cable insulation performance. For example, for a 10kV cable that has been in operation for many years, its aging effect is particularly significant in the range of several hundred kilohertz to 1 MHz, so server 104 can pay special attention to impedance changes within this frequency band. For example, if a section of cable insulation experiences polarization delay due to moisture or thermal aging, the phase curve at that frequency point may show an upward mutation peak, reflecting the hysteresis of signal propagation in that section.

[0061] Furthermore, during the acquisition process, server 104 can cache the impedance spectrum data in real time and deconstruct the complex impedance corresponding to each frequency point, extracting its amplitude and phase. To prevent subsequent misjudgments caused by noise interference, server 104 can also enable a data smoothing module to pre-process the acquired data. For example, this module uses polynomial smoothing, window filtering, or wavelet noise reduction algorithms to eliminate high-frequency disturbances other than sudden changes, ensuring accurate identification of sudden change points.

[0062] After all data is collected, server 104 can organize the frequency points and corresponding impedance values ​​into a structured data file, which can be encapsulated in binary format and annotated with metadata such as timestamp, device number, and cable number. This impedance spectrum data can serve as direct input for subsequent aging segment identification and complex dielectric parameter fitting. Notably, compared to traditional methods that only measure cable capacitance or insulation resistance, the impedance spectrum data collected by server 104 contains more dimensional information, reflecting comprehensive characteristics such as material loss, dielectric polarization, and transmission delay.

[0063] Step S204 : dividing the cable to be tested into a number of initial aging sections according to the impedance spectrum data, and determining the complex dielectric constant of each initial aging section.

[0064] For example, server 104 can identify areas of electrical property mutation in the cable based on the frequency domain information in the impedance spectrum, and accordingly divide the entire cable into multiple initial aging sections with physical independence and electrical parameter consistency. The server 104 can first analyze the phase response curve in the impedance spectrum, extracting the locations in the curve that exhibit mutation behavior as mutation peaks, and then divide the cable under test into several initial aging sections based on the locations of the mutation peaks. A mutation peak refers to a point in the process of phase variation with frequency where the phase value near a certain point shows a significant jump or drop, manifested as a sudden peak or valley in a smooth curve, indicating a drastic change in physical parameters at a certain location in the cable. This change may be due to a mutation in the dielectric constant, dielectric loss, impedance structure, or geometric boundary, which are electrical indicators of an aging or defective section.

[0065] Illustratively, the server 104 may extract at least one mutation peak based on the impedance spectrum data to obtain a mutation peak sequence; sequentially traverse the mutation peak sequence, and when two adjacent mutation peaks have the same polarity, divide the section between the two mutation peaks into the initial aging section.

[0066] Furthermore, the server 104 can use the entire impedance spectrum curve as an input signal and call the mutation identification module. This module is based on the first-order derivative mutation detection algorithm, calculates the phase change rate between adjacent frequency points, filters out frequency points whose mutation amplitude exceeds the set threshold, and marks their index in the original curve to obtain at least one mutation peak and its position information. After the server 104 arranges these frequency points in order, it can form a mutation peak sequence, each element of which contains the mutation polarity (also known as the mutation direction, positive or negative) and the frequency position. At this point, the server 104 completes the identification of the mutation peak and constructs a logical skeleton for segmentation.

[0067] After obtaining the mutation peak sequence, server 104 can initiate traversal logic to sequentially compare the polarity relationships between two adjacent mutation peaks in the sequence. For example, if two adjacent mutation peaks are found to have the same polarity—that is, both are positive or both are negative—then the cable segment represented by them can be preliminarily determined to be a transitionally continuous aging region. Server 104 can map the frequency range corresponding to the two mutation peaks into an initial aging segment in the cable's spatial structure. In this case, this segment is not required to be completely uniform in physical properties; rather, it is treated as a continuous unit to be further parameterized, providing a basis for independent modeling.

[0068] If, during the traversal process, server 104 discovers two adjacent sudden change peaks with opposite polarity, for example, one positive peak and one negative peak, the frequency band between them can be determined to contain a potential concentrated defect. This defect may be caused by severe insulation breakdown, localized water tree penetration, or a break in the metal shielding layer at a specific point. These defects differ significantly from the electrical parameters of the surrounding materials and cannot be modeled as an aging segment. Therefore, they can be temporarily skipped in the current step and addressed in a subsequent step.

[0069] After completing the traversal of the entire mutation peak sequence, the server 104 constructs an initial aging segment set, which includes N initial aging segments. Each segment has a clear start and end frequency range, a position label, and a preliminary electrical structure identifier. Next, the server 104 can assign a set of initial values ​​of the complex dielectric constant to each initial aging segment. This set of parameters can be used to set the optimization starting point of the subsequent particle swarm algorithm. The complex dielectric constant is a key indicator that describes the electrical behavior of the cable insulation medium under frequency response. It usually includes the dielectric energy storage part (C), the dielectric loss part (D), and the nonlinear polarization characteristics or dispersion behavior (P). The server 104 can set the initial value range of each segment based on the non-aging parameter table provided by the cable manufacturer, the cable operating years, or the on-site environmental factors, and organize it into a unified data structure for iterative calculation. Through this step, the server 104 realizes a complete mapping from frequency domain mutation identification to spatial structure division, divides a section of cable in an overall unknown state into several initial aging units with modeling value, and gives each unit a parameter modeling basis.

[0070] Step S206 : constructing a target function based on the impedance spectrum data and the complex dielectric constant, and performing fitting calculation on each complex dielectric constant based on the target function to obtain a target complex dielectric constant.

[0071] For example, server 104 can first invoke a simulation modeling module, using the complex dielectric constants of each initial aging segment as input parameters. Combined with the lengths and arrangement order of the corresponding segments, this module constructs an equivalent transmission line model for the entire cable. In this model, different combinations of complex dielectric constants directly affect the propagation velocity, energy attenuation, and reflection characteristics of electromagnetic signals within each segment, ultimately determining the complex impedance response exhibited by the cable during a frequency sweep. By solving this equivalent model, server 104 can simulate a sequence of theoretical impedance values ​​corresponding to each frequency point, generating a set of simulation results that fully align with the measured impedance spectrum in the frequency domain.

[0072] After completing the impedance response simulation, server 104 compares the difference between the measured and simulated impedances at each frequency point. The difference is summarized as the absolute value or sum of squares to generate a single numerical indicator to quantify the degree of error between the current parameter combination and the actual cable state. The smaller this objective function, the closer the impedance spectrum output by the current model is to the measured data, and the more likely the current complex dielectric constant combination is to approximate the state of the actual cable material.

[0073] To enable the model to achieve adaptive optimization capabilities, server 104 can integrate the objective function structure and initiate a particle swarm optimization iteration module. Each set of complex permittivity values ​​is considered a particle, with the entire set of aging segments constituting the particle solution space. Each particle has its own position (i.e., the current complex permittivity value) and velocity (i.e., the update direction and amplitude), and adjusts its search behavior based on the objective function value. By continuously iterating the states of multiple particles and evaluating the changing trend of the objective function in each round, server 104 can dynamically adjust the search path between individual and swarm optimality, gradually converging the solution space to the optimal region.

[0074] During the iteration process, server 104 can also impose constraints on the parameter update results to ensure that the fitted complex dielectric constant is physically reasonable. For example, the dielectric constant C cannot be negative, and the loss factor D must increase monotonically with frequency. These constraints ensure that the optimization results are consistent with practical engineering applications while also improving the convergence stability of the algorithm. The iteration process continues until the objective function falls within the set error tolerance or the maximum number of iterations is reached.

[0075] Once the optimal particle is identified, server 104 extracts the complex permittivity combination represented by its position as the final target complex permittivity. Each initial aging segment will receive a set of three-tuple parameters corresponding to dielectric energy storage, dielectric loss, and frequency response characteristics, thereby reconstructing the electrical parameters of the segment's physical state. Through this fitting process, server 104 can convert the potential material aging characteristics in the impedance spectrum data into quantitative parameters that can be used in subsequent calculations, improving the model's ability to reproduce the actual cable state and providing a solid electrical foundation for the final aging assessment.

[0076] Step S208 : According to the target complex dielectric constant, the segment length of each initial aging segment is corrected to obtain the target aging segment.

[0077] After fitting the complex permittivity of each initial aging segment, each segment now possesses electrical parameters consistent with the measured response. However, its physical spatial location is still based on the initial division of the impedance discontinuity points, which may result in some error. Especially when the cable exhibits non-uniform aging, variations in signal propagation velocity within different aging segments can cause the frequency mapping position to deviate from the actual physical location. Therefore, server 104 can further correct the physical length of each segment based on the target complex permittivity to restore the cable's true spatial aging distribution and accurately determine the target aging segment division results.

[0078] For example, the server 104 can calculate the electromagnetic wave velocity of each initial aging section based on the target complex dielectric constant; and correct the section length of the initial aging section based on the electromagnetic wave velocity to obtain the target aging section. The server 104 can call the wave velocity calculation module to perform electromagnetic propagation characteristic analysis on each aging section that has been fitted. Based on the dielectric properties reflected by the complex dielectric constant, the server 104 can calculate the propagation velocity of the electromagnetic signal in the cable section. The larger the complex dielectric constant, the lower the signal propagation velocity, reflecting physical phenomena such as material aging, polarization hysteresis, or enhanced dielectric loss. For example, the dielectric constant of a section of XLPE cable in a moderate thermal aging state may have increased from the standard value of 2.3 to 2.8, and the corresponding signal wave velocity will drop from 200 meters per microsecond to 160 meters per microsecond. The server 104 can therefore infer the actual signal response lag of the section.

[0079] Next, the server 104 can combine the previously defined reference length of each initial aging segment with the calculated wave velocity. The original length is directly mapped based on the frequency interval of the impedance mutation point, without considering the difference in wave velocity within different segments. The server 104 can make an equivalent correction to the initial length based on the ratio between each segment and the standard wave velocity, and obtain a target segment length that is more consistent with the actual transmission characteristics of the material. For example, the formula for correcting the aging segment length using wave velocity difference can be: L i =l i ×v i / v0, where L i is the corrected length, l i is the positioning result before calibration, v i is the wave velocity of the segment to be calibrated, and v0 is the wave velocity of the unaged cable. For example, if the initial length of a segment is 60 meters, and the wave velocity of this segment is 25% lower than the unaged standard value, the server 104 can correct it to 45 meters to avoid the spatial position estimation being too long due to the slower speed.

[0080] After completing the correction of all segment lengths, the server 104 can rearrange the sequence of the segments to form a continuous target aging segment structure that covers the entire cable without overlap or gaps. At this point, each segment not only has a state description in the electrical parameter dimension, but also has accurate spatial location information, including the starting position, the end position, and the actual length. Through this step, the server 104 solves the one-to-one correspondence problem between frequency domain data and the physical structure, and realizes the precise transition from the frequency mutation point to the spatial aging segment. This correction process not only improves the accuracy of the aging assessment, but also provides a more valuable reference basis for operation and maintenance personnel in actual construction. For example, when a section of severely aged cable needs to be excavated and replaced, the target segment length and position provided by the server 104 can be directly used for construction drawing annotation to avoid problems such as mis-excavation and missed repairs.

[0081] Furthermore, the server 104 can calculate fracture growth rate data for each target aging segment based on the electromagnetic wave velocity and determine the aging severity level of each target aging segment based on the fracture growth rate data. For example, the server 104 can normalize the fracture growth rate data to obtain an aging severity score and determine the aging severity level for each target aging segment based on a preset aging severity labeling rule and the aging severity score. The server 104 can label each target aging segment based on the preset aging severity labeling rule and the aging severity score; the aging severity labeling rule includes a range of values ​​for the aging severity score corresponding to different aging severity levels.

[0082] The fracture growth rate is a key mechanical characteristic used to measure the ductility and aging resistance of cross-linked polyethylene insulation materials. A higher fracture growth rate indicates greater elasticity and ductility, and a lower degree of aging. Conversely, a lower fracture growth rate indicates significant damage to the material's internal microstructure, entering a brittle stage and making it more susceptible to failures such as cracking and breakdown. Therefore, server 104 can infer the fracture growth rate data for each target aging segment based on the wave velocity of that segment, serving as a key basis for subsequent aging level assessment.

[0083] For example, the server 104 can use the electromagnetic wave velocity information of each target aging section to call the built-in physical property mapping model. The model can establish a functional relationship between the electromagnetic wave velocity and the fracture growth rate through empirical fitting. The relationship can be derived from the statistical analysis of a large amount of material test data and cable measurement results, and has a clear physical basis and experimental support. After substituting the wave velocity of each section into the model, the server 104 can calculate the fracture growth rate data one by one, and organize it into a structured vector, marking the corresponding position of each section and the material ductility. Among them, the correlation formula between the wave velocity and the fracture elongation can be P EAB =420.1×e 0.1962×(v-128.5) -5.2, v represents the wave velocity, the length of each cable segment and the mechanical elongation at break of the insulation can be expressed as L i and P EAB-i (i=1,2,3...). i is the aging degree of the i-th cable segment, P EAB-unaged Represents the mechanical elongation at break of the non-aged cable insulation layer. The specific formula can be:

[0084]

[0085] The overall aging degree of the operable cable segment is between 0 and 1. The smaller the mechanical elongation at break of the cable segment insulation (the more serious the aging), the smaller the aging degree w value. For the unaged cable segment, the aging degree w value is 1. The aging degree w value of the cable segment that has just reached the end of its life (i.e., the elongation at break of the insulation layer is reduced to 50% of the original) is 0.

[0086] After completing the fracture growth rate calculation, the server 104 can then normalize the data to form a unified evaluation system. The purpose of normalization is to eliminate the interference caused by different cable models, factory standards or operating environment differences, so that the performance levels of all aging sections can be compared on the same numerical scale. The server 104 can use a linear mapping method to scale the fracture growth rate of each section according to the preset unaged reference value and critical degradation value. The normalized result is defined as an aging degree score, with a numerical range between 0 and 1, where 1 indicates completely unaged and 0 indicates completely aged to the limit state. For example, if the fracture growth rate of a section is 225%, the unaged value is 300%, and the critical value is 150%, the server 104 can calculate its aging degree score as approximately 0.5, indicating that the section has reached a moderate aging level.

[0087] After obtaining the aging degree score of each target aging segment, the server 104 can grade each segment according to the preset aging degree marking rule. The rule defines the correspondence between multiple scoring intervals and aging levels. For example, a score greater than 0.75 is "not aged", a score between 0.5 and 0.75 is "mildly aged", 0.25 to 0.5 is "moderately aged", and below 0.25 is "severely aged". The server 104 can compare the scoring results with the grade intervals section by section and add a grade mark to each segment. This marking information can include color codes (such as green, yellow, orange, red), text labels or numerical grades for subsequent risk visualization, construction scheduling or replacement recommendation generation.

[0088] Ultimately, server 104 can integrate the score, fracture growth rate, grade mark, and spatial location information for each target aging section into a complete aging status data table. This data table can be directly output to terminal 102 as a report, display chart, or be accessed by higher-level systems. Through this process, server 104 completes a closed-loop process, from frequency-domain impedance response to electrical parameter inversion, to material mechanical property evaluation, and finally to conversion into graded results. This not only provides engineers with an intuitive health index but also deepens their understanding of the overall aging structure of the cable, providing a scientific basis and precise support for inspection and maintenance strategies.

[0089] In the above-mentioned cable aging section status assessment method, the impedance spectrum data of the cable to be tested is obtained, and the input impedance spectrum of the cable is used as the basic data source for evaluation. The dielectric properties and internal structure changes of the cable are reflected through the frequency domain response data, avoiding the traditional method's reliance on appearance or mechanical properties, thereby realizing non-destructive detection of the cable status. Then, based on the impedance spectrum data, the cable to be tested is divided into several initial aging sections, and the complex dielectric constant of each initial aging section is determined. The target function is constructed based on the impedance spectrum data and the complex dielectric constant, and each complex dielectric constant is fitted and calculated according to the target function to obtain the target complex dielectric constant. The introduced fitting mechanism can minimize the deviation between the model parameters and the actual cable status, thereby improving the physical accuracy fitting capability of the cable insulation aging degree. Next, the initially estimated segment length is corrected based on the target complex dielectric constant obtained by fitting, and the segment length of each initial aging segment is corrected to obtain the target aging segment. This effectively overcomes the problem of misjudgment of segment length caused by aging, significantly improves the spatial accuracy of aging segment positioning, and achieves accurate positioning of the aging segment length, thereby enabling accurate assessment of the specific aging condition of the cable.

[0090] In an exemplary embodiment, Figure 3 As shown, the impedance spectrum data includes impedance measured data and impedance calculated data; step S206 includes steps S302 to S306.

[0091] Step S302: constructing an objective function based on the complex dielectric constant, the measured impedance data, and the impedance spectrum data.

[0092] For example, the server 104 can construct an objective function based on the impedance measurement data obtained in the early stage, the initial value of the complex dielectric constant corresponding to the divided aging section, and the preset cable equivalent transmission model. The server 104 can use the complex dielectric constant as the input variable, call the cable modeling module, simulate and calculate the impedance response at each frequency point, and generate a set of impedance calculation data. Each set of calculated data is compared one by one with the measured data at the corresponding frequency point. Next, the server 104 can accumulate the calculation error by point-by-point difference, and use the weighted or square sum of all errors as the numerical output of the objective function to form a clear optimization direction. The smaller the objective function value, the more the current complex dielectric constant combination can truly reflect the actual electrical response of the cable. For example, the server 104 can use the sum of the absolute values ​​of the difference between the measured value Zi and the calculated value Zc of the cable input impedance as the objective function g(X) = ∑|Zi(fi)-Zc(fi)|.

[0093] Step S304: constructing a particle swarm according to the initial aging segment.

[0094] Each initial aging segment corresponds to a particle in the particle population, and each particle is used to represent a set of complex dielectric constants.

[0095] For example, server 104 can construct a particle swarm structure based on the number of initial aging segments, assigning one particle to each initial aging segment. The number of particles in the entire particle swarm equals the number of aging segments. Each particle represents a set of complex dielectric constants for that segment, including dielectric storage coefficient, dielectric loss factor, and frequency response characteristic parameters. Server 104 can define the particle's position as the current parameter value combination, and its velocity as the direction and magnitude of change in parameter updates during each iteration. In addition, server 104 can initialize the current optimal position, global optimal position, and fitness record for each particle, preparing to enter the iterative optimization process.

[0096] Furthermore, during the particle swarm initialization process, the server 104 can use the complex dielectric constant parameters (C, D, P) of each aging segment as the optimization variables of the particle swarm to form a parameter matrix d = [C1, D1, P1, ..., CN, DN, PN], and set the inertia weight δ, acceleration constants c1 and c2 of the particle swarm to initialize the particle position and velocity. Among them, Ci, Di, Pi (1≤i≤N) are the high-frequency complex dielectric constant fitting values ​​corresponding to the i-th cable segment area. Among them, C, D, P need to meet the constraints:

[0097]

[0098] Step S306 , iteratively updating the position data and velocity data of each particle according to the objective function, and when the iteration completion condition is met, obtaining the corresponding target complex dielectric constant based on each particle in the iteratively completed particle group.

[0099] For example, during each iteration, server 104 can calculate the objective function value of a particle based on its current position, compare it with the current particle's historical optimal objective function value, and update its individual optimal position. Simultaneously, the optimal position among all particles is used as the global optimal position, serving as a reference target for the next round of movement for other particles. Server 104 can synchronously update the speed and position of each particle. Speed ​​updates are influenced by three factors: the inertia of the current speed, the attraction of the particle's own individual optimal point, and the guiding force of the entire particle swarm's global optimal point. Server 104 can adjust search behavior based on these factors to achieve a dynamic balance between local exploration and global jumping.

[0100] Next, the server 104 may continue to perform multiple rounds of iterations until a preset termination condition is met, including the objective function converging to a set threshold, the particle position change tending to be stable, or the number of iterations reaching an upper limit. For example, the speed update formula may be:

[0101] v i,d (k+1)=δvi,d (k)+c1r1(p i,d (k+1)-p i,d (k))+c2r2(g b (k+1)-g i,d (k))

[0102] The position update formula can be:

[0103] p i,d (k+1)=p i,d (k)+v i,d (k+1)

[0104] Among them, r1 and r2 are random numbers between 0 and 1, and p i，d (k) is the position of the d-th dimension of the i-th particle in the k-th iteration, g b (k) is the global optimal position for the kth iteration. Once the iteration is complete, server 104 can extract the final position coordinates of each particle in the particle swarm as the target complex dielectric constant for the corresponding initial aging segment. At this point, the complex dielectric parameters of each cable segment are no longer empirical estimates, but the result of repeated alignment of the optimization model with measured data. This highly reliable result can serve as a key basis for subsequent wave velocity calculations and fracture growth rate derivation. Through this process, server 104 completes the physical mapping of the cable from impedance response to dielectric properties, significantly improving the parameter accuracy and stability of aging assessments.

[0105] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0106] Based on the same inventive concept, embodiments of the present application also provide a device for implementing the aforementioned method for assessing the condition of a cable aging segment. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more embodiments of the device for assessing the condition of a cable aging segment can be found in the aforementioned definition of the method for assessing the condition of a cable aging segment, and are not further elaborated here.

[0107] In an exemplary embodiment, Figure 4 As shown, a device for evaluating the state of a cable aging section is provided, comprising: a data acquisition module 402, a data processing module 404, a data calculation module 406 and a data evaluation module 408, wherein:

[0108] The data acquisition module 402 is used to obtain impedance spectrum data of the cable to be tested;

[0109] The data processing module 404 is used to divide the cable to be tested into a number of initial aging sections according to the impedance spectrum data, and determine the complex dielectric constant of each initial aging section;

[0110] The data calculation module 406 is used to construct a target function based on the impedance spectrum data and the complex dielectric constant, and perform fitting calculations on the complex dielectric constants according to the target function to obtain a target complex dielectric constant;

[0111] The data evaluation module 408 is configured to modify the length of each initial aging segment according to the target complex dielectric constant to obtain a target aging segment.

[0112] In one embodiment, the impedance spectrum data includes measured impedance data and calculated impedance data; the data calculation module 406 is specifically used to: construct a target function based on the complex dielectric constant, the measured impedance data and the impedance spectrum data; construct a particle swarm based on the initial aging segment; wherein each initial aging segment corresponds to a particle in the particle swarm, and each particle is used to represent a set of complex dielectric constants; iteratively update the position data and velocity data of each particle according to the target function, and when the iteration completion condition is met, obtain the corresponding target complex dielectric constant based on each particle in the iteratively completed particle swarm.

[0113] In one embodiment, the data evaluation module 408 is specifically configured to: calculate the electromagnetic wave velocity of each initial aging segment according to the target complex dielectric constant; and correct the segment length of the initial aging segment according to the electromagnetic wave velocity to obtain the target aging segment.

[0114] In one embodiment, the data evaluation module 408 is further configured to: calculate fracture growth rate data of each target aging section based on the electromagnetic wave velocity; and determine the aging degree level of each target aging section based on the fracture growth rate data.

[0115] In one embodiment, the data evaluation module 408 is further configured to: normalize each fracture growth rate data to obtain an aging degree score; and determine an aging degree grade for each target aging segment according to a preset aging degree marking rule and the aging degree score.

[0116] In one embodiment, the data processing module 404 is specifically used to: extract at least one mutation peak based on the impedance spectrum data to obtain a mutation peak sequence; traverse the mutation peak sequence in sequence, and when two adjacent mutation peaks have the same polarity, divide the segment between the two mutation peaks into an initial aging segment.

[0117] Each module in the aforementioned device for assessing the condition of an aged cable section can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor within a computer device in the form of hardware, or can be stored in a computer device's memory in the form of software, allowing the processor to call and execute the corresponding operations of each module.

[0118] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 5 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data such as the impedance spectrum data of the cable to be tested. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for evaluating the status of a cable aging section is implemented.

[0119] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 6As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface, the display unit and the input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a method for evaluating the status of a cable aging section is implemented. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse.

[0120] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0121] In an exemplary embodiment, a computer device is provided, comprising a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented: obtaining impedance spectrum data of a cable to be tested; dividing the cable to be tested into a plurality of initial aging segments based on the impedance spectrum data, and determining the complex dielectric constant of each initial aging segment; constructing a target function based on the impedance spectrum data and the complex dielectric constant, and performing a fitting calculation on each complex dielectric constant based on the target function to obtain a target complex dielectric constant; and correcting the segment length of each initial aging segment based on the target complex dielectric constant to obtain a target aging segment.

[0122] In one embodiment, when the processor executes the computer program, it also implements the following steps: constructing a target function based on the complex dielectric constant, measured impedance data and impedance spectrum data; constructing a particle swarm based on the initial aging segment; wherein each initial aging segment corresponds to a particle in the particle swarm, and each particle is used to represent a set of complex dielectric constants; iteratively updating the position data and velocity data of each particle according to the target function, and when the iteration completion condition is met, obtaining the corresponding target complex dielectric constant based on each particle in the iteratively completed particle swarm.

[0123] In one embodiment, when the processor executes the computer program, the following steps are further implemented: calculating the electromagnetic wave velocity of each initial aging segment according to the target complex dielectric constant; and correcting the segment length of the initial aging segment according to the electromagnetic wave velocity to obtain the target aging segment.

[0124] In one embodiment, when the processor executes the computer program, the following steps are further implemented: calculating the fracture growth rate data of each target aging section according to the electromagnetic wave velocity; and determining the aging degree level of each target aging section according to the fracture growth rate data.

[0125] In one embodiment, when the processor executes the computer program, the following steps are further implemented: normalizing each fracture growth rate data to obtain an aging degree score; and determining an aging degree grade for each target aging segment according to a preset aging degree marking rule and the aging degree score.

[0126] In one embodiment, when the processor executes the computer program, the processor further implements the following steps: extracting at least one mutation peak based on the impedance spectrum data to obtain a mutation peak sequence; sequentially traversing the mutation peak sequence, and when two adjacent mutation peaks have the same polarity, dividing the segment between the two mutation peaks into an initial aging segment.

[0127] In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon. When executed by a processor, the computer program implements the following steps: obtaining impedance spectrum data of a cable to be tested; dividing the cable to be tested into a plurality of initial aging segments based on the impedance spectrum data, and determining the complex dielectric constant of each initial aging segment; constructing a target function based on the impedance spectrum data and the complex dielectric constant, and performing a fitting calculation on each complex dielectric constant based on the target function to obtain a target complex dielectric constant; and correcting the segment length of each initial aging segment based on the target complex dielectric constant to obtain a target aging segment.

[0128] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented: constructing a target function based on the complex dielectric constant, measured impedance data and impedance spectrum data; constructing a particle swarm based on the initial aging segment; wherein each initial aging segment corresponds to a particle in the particle swarm, and each particle is used to represent a set of complex dielectric constants; iteratively updating the position data and velocity data of each particle according to the target function, and when the iteration completion condition is met, obtaining the corresponding target complex dielectric constant based on each particle in the iteratively completed particle swarm.

[0129] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: calculating the electromagnetic wave velocity of each initial aging segment according to the target complex dielectric constant; and correcting the segment length of the initial aging segment according to the electromagnetic wave velocity to obtain the target aging segment.

[0130] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: calculating the fracture growth rate data of each target aging section based on the electromagnetic wave velocity; and determining the aging degree level of each target aging section based on the fracture growth rate data.

[0131] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: normalizing each fracture growth rate data to obtain an aging degree score; and determining an aging degree grade for each target aging segment according to a preset aging degree marking rule and the aging degree score.

[0132] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: extracting at least one mutation peak based on the impedance spectrum data to obtain a mutation peak sequence; sequentially traversing the mutation peak sequence, and when two adjacent mutation peaks have the same polarity, dividing the segment between the two mutation peaks into an initial aging segment.

[0133] In one embodiment, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the following steps: obtaining impedance spectrum data of a cable to be tested; dividing the cable to be tested into a plurality of initial aging segments based on the impedance spectrum data, and determining the complex dielectric constant of each initial aging segment; constructing a target function based on the impedance spectrum data and the complex dielectric constant, and performing a fitting calculation on each complex dielectric constant based on the target function to obtain a target complex dielectric constant; and correcting the segment length of each initial aging segment based on the target complex dielectric constant to obtain a target aging segment.

[0134] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented: constructing a target function based on the complex dielectric constant, measured impedance data and impedance spectrum data; constructing a particle swarm based on the initial aging segment; wherein each initial aging segment corresponds to a particle in the particle swarm, and each particle is used to represent a set of complex dielectric constants; iteratively updating the position data and velocity data of each particle according to the target function, and when the iteration completion condition is met, obtaining the corresponding target complex dielectric constant based on each particle in the iteratively completed particle swarm.

[0135] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: calculating the electromagnetic wave velocity of each initial aging segment according to the target complex dielectric constant; and correcting the segment length of the initial aging segment according to the electromagnetic wave velocity to obtain the target aging segment.

[0136] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: calculating the fracture growth rate data of each target aging section based on the electromagnetic wave velocity; and determining the aging degree level of each target aging section based on the fracture growth rate data.

[0137] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: normalizing each fracture growth rate data to obtain an aging degree score; and determining an aging degree grade for each target aging segment according to a preset aging degree marking rule and the aging degree score.

[0138] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: extracting at least one mutation peak based on the impedance spectrum data to obtain a mutation peak sequence; sequentially traversing the mutation peak sequence, and when two adjacent mutation peaks have the same polarity, dividing the segment between the two mutation peaks into an initial aging segment.

[0139] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0140] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processor involved in the various embodiments provided herein may be, but are not limited to, a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, and the like.

[0141] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0142] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for evaluating the status of a cable aging section, characterized in that: The method comprises: Obtain impedance spectrum data of the cable under test; Dividing the cable to be tested into a plurality of initial aging sections according to the impedance spectrum data, and determining the complex dielectric constant of each of the initial aging sections; Constructing a target function according to the impedance spectrum data and the complex dielectric constant, and performing fitting calculation on each of the complex dielectric constants according to the target function to obtain a target complex dielectric constant; According to the target complex dielectric constant, the segment length of each initial aging segment is corrected to obtain a target aging segment.

2. The method according to claim 1, characterized in that The impedance spectrum data includes measured impedance data and calculated impedance data; constructing a target function based on the impedance spectrum data and the complex dielectric constant, and performing fitting calculation on each of the complex dielectric constants according to the target function to obtain a target complex dielectric constant, including: Constructing an objective function according to the complex dielectric constant, the measured impedance data and the impedance spectrum data; Constructing a particle group according to the initial aging segment; wherein each initial aging segment corresponds to a particle in the particle group, and each particle is used to represent a set of complex dielectric constants; The position data and velocity data of each particle are iteratively updated according to the objective function. When an iteration completion condition is met, a corresponding target complex dielectric constant is obtained based on each particle in the iteratively completed particle group.

3. The method according to claim 1, characterized in that The step of correcting the segment length of each of the initial aging segments according to the target complex dielectric constant to obtain a target aging segment includes: Calculating the electromagnetic wave velocity of each of the initial aging sections according to the target complex dielectric constant; The length of the initial aging section is corrected according to the electromagnetic wave velocity to obtain a target aging section.

4. The method according to claim 3, characterized in that After the length of the initial aging section is corrected according to the electromagnetic wave velocity to obtain a target aging section, the method further includes: Calculating fracture growth rate data of each target aging section according to the electromagnetic wave velocity; The aging degree level of each target aging section is determined based on the fracture growth rate data.

5. The method according to claim 4, characterized in that Determining the aging degree level of each target aging section according to the fracture growth rate data includes: Normalizing the fracture growth rate data to obtain an aging degree score; An aging degree grade is determined for each target aging segment according to a preset aging degree marking rule and the aging degree score.

6. The method according to any one of claims 1 to 5, characterized in that The method of dividing the cable to be tested into a plurality of initial aging sections according to the impedance spectrum data includes: Extracting at least one mutation peak according to the impedance spectrum data to obtain a mutation peak sequence; The mutation peak sequence is traversed in sequence, and when two adjacent mutation peaks are of the same polarity, the section between the two mutation peaks is divided into an initial aging section.

7. A device for evaluating the status of a cable aging section, characterized in that: The device comprises: A data acquisition module is used to obtain impedance spectrum data of the cable to be tested; a data processing module, configured to divide the cable to be tested into a plurality of initial aging sections according to the impedance spectrum data, and determine the complex dielectric constant of each of the initial aging sections; a data calculation module, configured to construct a target function based on the impedance spectrum data and the complex dielectric constant, and perform fitting calculation on each of the complex dielectric constants according to the target function to obtain a target complex dielectric constant; A data evaluation module is used to correct the segment length of each of the initial aging segments according to the target complex dielectric constant to obtain a target aging segment.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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