Power cable insulation state evaluation method and system based on broadband impedance spectroscopy

Abstract

The invention discloses a power cable insulation state evaluation method and system based on a broadband impedance spectrum, relates to the technical field of cable insulation, and is used for solving the problem that a defect grading result deviates from a real aging process of a cable. The method comprises the following steps: extracting broadband reflection data, calling a corresponding insulation aging type, converting a phase sequence in the broadband reflection data into a phase deviation coefficient for region screening, extracting a reflection peak value based on a reflection coefficient amplitude sequence, calling a corresponding impedance variation reference according to the insulation aging type, and performing region screening. The method comprises the following steps: generating impedance variation characteristics in combination with a reflection coefficient peak value, judging whether a defect grading mechanism is entered, detecting discharge pulse count and insulation recovery time of a marked division region, generating marked division defect grades according to a detection result, and distinguishing impedance variation modes corresponding to different aging forms in judgment. And the defect grading result better conforms to the actual aging process of the cable.

Description

Technical Field

[0001] This invention relates to the field of cable insulation technology, and more specifically, to a method and system for evaluating the insulation condition of power cables based on broadband impedance spectrum. Background Technology

[0002] As a critical power transmission and distribution channel in the power system, the insulation integrity of power cables is directly related to the safety and stability of the power grid operation. With the increase in laying years and the increasing complexity of the operating environment, cable insulation materials will undergo different forms of dielectric degradation under the influence of multiple factors such as thermal aging, electric field stress, moisture intrusion and external medium corrosion. These degradations include enhanced interface polarization, dielectric constant drift, local resistivity decrease, and partial discharge activity induced by microcracks. This makes the assessment of cable insulation condition and the location of potential faults highly complex.

[0003] The existing technology has the following shortcomings: Currently, existing technologies lack a correlation model between insulation aging types and broadband impedance response, lack phase sequence transformation and region screening mechanisms based on aging mechanisms, and fail to introduce differentiated impedance benchmarks for dielectric degradation morphologies during feature extraction. As a result, broadband reflection data remains at the general analysis level and cannot effectively distinguish impedance change patterns caused by different aging morphologies. This further causes the defect classification results to deviate from the actual aging process of the cable. Therefore, a method and system for evaluating the insulation status of power cables based on broadband impedance spectra are proposed. Summary of the Invention

[0004] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide a method and system for evaluating the insulation status of power cables based on broadband impedance spectrum. This method addresses the problems mentioned in the background art by employing an insulation aging type identification model driven by aging levels, a region screening method constructed using phase sequence offset coefficients, and an impedance variation feature generation mechanism oriented towards different media degradation mechanisms.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for evaluating the insulation status of power cables based on broadband impedance spectrum, comprising the following steps: Step S1: Obtain historical operating data of the cable under test and analyze the cable insulation status, detect the laying medium data of the cable under test, calculate the aging level in combination with the cable insulation status, and access the preset database to match the insulation aging type corresponding to the aging level. Step S2: Divide the cable under test into regions. Obtain broadband reflection data of each region by inputting a high-frequency signal at the beginning of the cable under test. Use the broadband reflection data to filter and mark the regions. Step S3: Extract the peak reflection coefficient of the marked area, retrieve the corresponding impedance variation benchmark according to the insulation aging type, fuse the impedance variation benchmark and the peak reflection coefficient to generate impedance variation characteristics and determine whether to enter the defect classification mechanism. Step S4: When entering the defect grading mechanism, the discharge pulse count and insulation recovery time of the marked area are detected, and a defect grading index for the marked area is generated and the defect level is classified according to the detection results.

[0006] In a preferred embodiment, in step S1, the historical operating data of the cable under test is obtained through the historical operating database. The historical operating data includes the historical operating current and the number of historical power outages and restorations. The product of the historical operating current and the number of historical power outages and restorations, after standardization, is used as the cable insulation status. The environment of the area where the cable to be tested is laid is tested to obtain data on the laying medium of the cable, including soil moisture and soil conductivity. The soil moisture in the laying medium is detected by a soil moisture sensor, and the soil conductivity in the laying medium is detected by a soil conductivity sensor. The environmental driving index is calculated by combining soil moisture and soil electrical conductivity.

[0007] In a preferred embodiment, in step S1, the cable insulation state and the environmental driving index are used as two-dimensional state points, and the aging level is calculated by the distance from the preset health benchmark point. The aging level is used as an index parameter to query the preset database. Different insulation aging types correspond to different preset aging level ranges. If the aging level falls within a certain preset aging level range, then the insulation aging type corresponding to the aging level range is determined as the insulation aging type of the cable under test.

[0008] In a preferred embodiment, in step S2, the cable under test is divided into regions according to the structural nodes of the cable under test. A high-frequency signal is input to the first end of the cable under test, and the reflected signals returned from each divided area are processed by the terminal acquisition device in the frequency domain to obtain broadband reflection data. The broadband reflection data includes a phase sequence arranged in frequency order and a reflection coefficient amplitude sequence.

[0009] In a preferred embodiment, in step S2, the phase offset coefficient of the divided region is calculated by the phase sequence of the divided region; The preset phase offset threshold is compared with the phase offset coefficient of the divided regions to filter and mark the divided regions: If the phase offset coefficient is greater than the preset phase offset threshold, the divided region is marked. Conversely, no marking is made for the divided areas.

[0010] In a preferred embodiment, in step S3, the frequency index of the reflection coefficient amplitude sequence is mapped to the distance index corresponding to the cable length, and the maximum value of the reflection coefficient amplitude within the distance interval corresponding to each marked division area is extracted as the peak value of the reflection coefficient of the marked division area. Retrieve the impedance variation reference corresponding to the insulation aging type from the preset database. The impedance variation reference refers to the characteristic deviation value of broadband impedance caused by different insulation aging types. The maximum value of the reflection coefficient peak in all marked regions is taken as the peak reference. The standard reflection coefficient peak value is obtained by dividing the reflection coefficient peak value of each marked region by the peak reference value.

[0011] In a preferred embodiment, in step S3, the peak value of the standard reflection coefficient and the impedance variation reference are multiplied to obtain the impedance variation characteristics; When the impedance variation characteristic is greater than or equal to the preset amplitude threshold, it indicates that the impedance change of the corresponding marked area has exceeded the normal fluctuation range under the corresponding insulation aging type, which means that there is a potential defect risk and it is necessary to further implement the defect classification mechanism. Conversely, if the impedance variation characteristics are less than the preset amplitude threshold, the corresponding marked area is considered to exhibit normal structural reflection or regular fluctuations caused by slight insulation aging, and it is determined that there is no need to enter the defect classification mechanism.

[0012] In a preferred embodiment, in step S4, when entering the defect classification mechanism, within the set measurement time window, the total number of discharge pulses in the marked and divided areas is identified and recorded by the partial discharge detection device as the discharge pulse count. A step voltage of predetermined amplitude is applied to the marked area to induce the insulating medium to enter the polarization response stage. The applied voltage is then removed and the time points are recorded. The leakage current monitoring device is used to monitor the decay process of the dielectric current in the marked area over time in real time, and to identify the time point when the leakage current drops from the polarization peak and finally stabilizes at the reference leakage current. The difference between the time when the applied voltage is removed and the time when the reference leakage current is reached is taken as the insulation recovery time.

[0013] In a preferred embodiment, in step S4, after standardizing the discharge pulse count and insulation recovery time, the discharge pulse factor and insulation recovery factor are obtained. The defect classification index is obtained by comprehensively calculating the discharge pulse factor and insulation recovery factor using a weighted summation method. The threshold for classifying defects is set using a three-part method, which divides the range of defect classification index values ​​into three intervals according to the principle of equal intervals. Each interval corresponds to a different defect level, including low-level defects, medium-level defects, and high-level defects.

[0014] The power cable insulation condition evaluation system based on broadband impedance spectrum includes an aging identification module, a reflection acquisition module, an anomaly detection module, and a grading and location module. The functions of each module are as follows: The aging identification module is used to acquire historical operating data and laying medium data of the cable under test, calculate the cable insulation status and environmental driving index, generate aging levels, and match the insulation aging type corresponding to the aging level. The reflection acquisition module divides the cable under test into regions according to the cable structure, injects a high-frequency signal at the beginning and acquires the reflection response, completes the frequency domain analysis of the phase sequence and the amplitude sequence of the reflection coefficient, and marks the divided regions according to the phase offset coefficient. The anomaly determination module is used to extract the peak value of the reflection coefficient within the marked area, retrieve the impedance anomaly benchmark corresponding to the insulation aging type, generate impedance anomaly characteristics, and determine whether to enter the defect classification mechanism. The grading and positioning module, when entering the defect grading mechanism, detects the discharge pulse count and insulation recovery time of the marked area, generates a defect grading index for the marked area based on the detection results, and classifies the defect level.

[0015] The technical effects and advantages of this invention are as follows: This invention analyzes the aging levels of the cable under test by acquiring historical operating data and laying medium data, and retrieves the corresponding insulation aging type. It converts the phase sequence in the broadband reflection data into a phase offset coefficient for region screening, extracts the reflection peak value based on the reflection coefficient amplitude sequence, retrieves the corresponding impedance variation benchmark according to the insulation aging type, generates impedance variation characteristics by combining the reflection coefficient peak value, and determines whether a defect grading mechanism has been entered. It detects the discharge pulse count and insulation recovery time of the marked regions, and generates markers to classify defect levels based on the detection results. By introducing the insulation aging type as a prerequisite in the diagnostic link, the feature extraction of broadband reflection data is transformed from general analysis to targeted analysis corresponding to the medium degradation mechanism. This allows the impedance change patterns corresponding to different aging forms to be distinguished in the judgment, making the defect grading results more consistent with the actual aging process of the cable. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating the implementation of the power cable insulation condition evaluation method based on broadband impedance spectrum according to the present invention.

[0017] Figure 2 This is a data processing flowchart of the power cable insulation condition evaluation method based on broadband impedance spectrum according to the present invention.

[0018] Figure 3 This is a module framework diagram of the power cable insulation condition evaluation system based on broadband impedance spectrum according to the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] This invention analyzes the aging levels of the cable under test by acquiring historical operating data and laying medium data, and retrieves the corresponding insulation aging type. It converts the phase sequence in the broadband reflection data into a phase offset coefficient for region screening, extracts the reflection peak value based on the reflection coefficient amplitude sequence, retrieves the corresponding impedance variation benchmark according to the insulation aging type, generates impedance variation characteristics by combining the reflection coefficient peak value, and determines whether a defect grading mechanism has been entered. It detects the discharge pulse count and insulation recovery time of the marked regions, generates markers to classify defect levels based on the detection results, and introduces the insulation aging type as a prerequisite in the diagnostic link. This transforms the feature extraction of broadband reflection data from general analysis to targeted analysis corresponding to the medium degradation mechanism, enabling the impedance change patterns corresponding to different aging forms to be distinguished during the judgment process.

[0021] Example 1, such as Figures 1 to 2 As shown, the method for evaluating the insulation condition of power cables based on broadband impedance spectrum includes the following steps: Step S1: Obtain historical operating data of the cable under test and analyze the cable insulation status, detect the laying medium data of the cable under test, calculate the aging level in combination with the cable insulation status, and access the preset database to match the insulation aging type corresponding to the aging level. Step S2: Divide the cable under test into regions. Obtain broadband reflection data of each region by inputting a high-frequency signal at the beginning of the cable under test. Use the broadband reflection data to filter and mark the regions. Step S3: Extract the peak reflection coefficient of the marked area, retrieve the corresponding impedance variation benchmark according to the insulation aging type, fuse the impedance variation benchmark and the peak reflection coefficient to generate impedance variation characteristics and determine whether to enter the defect classification mechanism. Step S4: When entering the defect grading mechanism, the discharge pulse count and insulation recovery time of the marked area are detected, and a defect grading index for the marked area is generated and the defect level is classified according to the detection results.

[0022] The specific implementation is as follows: In step S1, when assessing the insulation status of the cable under test, the historical operating data of the cable under test is obtained through the historical operating database. The historical operating data includes the historical operating current and the number of historical power outages and restorations. Frequent power outages and restorations cause insulation materials to repeatedly experience electrical shocks and thermal cycles, thereby accelerating the degradation of insulation performance. The more power outages and restorations in the past, the more likely the cable insulation condition will show signs of aging and deepening. Historical operating current refers to the current value that the cable under test withstands under normal load conditions. The larger the historical operating current, the faster the insulation's ability to withstand electric field strength and temperature rise cycles decays, and the more the cable insulation condition tends to deteriorate. The product of the historical operating current and the number of historical power outages and restorations, after standardization, is used as the cable insulation status. The higher the insulation condition of the cable, the stronger the current load impact and start-stop impact that the cable under test has experienced in the past operating cycle, the faster its insulation degradation rate, and the higher the corresponding aging level. The environment of the area where the cable under test is laid is tested to obtain the laying medium data of the cable under test. The laying medium data refers to the environmental parameters that affect the insulation material of the cable under test in the long term, including soil moisture and soil conductivity. Soil moisture in the laying medium is detected by a soil moisture sensor laid around the cable under test. Soil moisture is used to reflect the degree of influence of external moisture penetration on insulation moisture. The higher the soil moisture, the easier it is for external moisture to penetrate into the insulation layer through the micropores of the sheath, causing a decrease in insulation resistance and a higher aging level. The soil conductivity in the laying medium is detected by a soil conductivity sensor laid around the cable to be tested. Soil conductivity reflects the content of dissolved salts and electrolyte ions in the soil. The higher the soil conductivity, the richer the corrosive ions in the soil, the greater the chemical erosion intensity that the outer sheath and insulation interface can withstand, the faster the insulation degradation rate, and the higher the corresponding aging level.

[0023] It should be explained that the historical operation database is a collection of various operation data generated by the cable in each operation cycle; the standardization processing methods include, but are not limited to, standard linear transformation based on interval scaling, Z-Score standardization method based on statistics, or normalization method based on nonlinear mapping function. The application methods of standardization processing will not be elaborated here; the soil moisture sensor is a sensing element used to detect the soil moisture content in the cable laying area; the soil conductivity sensor is a detection device used to measure the conductivity of the soil solution around the cable.

[0024] Soil moisture content and soil electrical conductivity were standardized to obtain soil moisture index and soil electrical conductivity coefficient, respectively. Calculation of environmental driving index based on soil moisture coefficient and soil electrical conductivity coefficient: , in, , and The preset adjustment coefficient, Soil moisture coefficient, Let be the soil electrical conductivity, and e be the natural constant. It is an environmentally driven index.

[0025] It should be explained that the preset adjustment coefficient can be set according to the statistical contribution of the historical laying environment to the degradation of cable insulation. For example, when there is a significant risk of salt erosion in the laying area, a preset adjustment coefficient corresponding to the soil conductivity coefficient can be set.

[0026] The aging level is calculated based on the cable insulation condition and environmental driving index. The cable insulation condition and environmental driving index are used as two-dimensional state points, and the aging level is calculated by the distance from the preset health benchmark point. , in, and To preset the balance coefficient, The cable is in insulation condition. This is the default reference value for the preset health baseline in the cable insulation condition dimension. This sets the default reference value for the predefined health baseline under the environmentally driven index dimension. This is the aging level; It should be explained that the preset health benchmark point refers to the parameter point where the insulation performance of the cable is normal during long-term operation. It is obtained by statistical analysis of a large sample of historical healthy cables and may include the default reference value under the dimension of cable insulation status and the default reference value under the dimension of environmental driving index. The preset balance coefficient can be set according to the cable model and the type of laying environment. For example, for direct-buried cables in humid areas, the balance coefficient corresponding to the environmental driving index can be increased.

[0027] After obtaining the current aging level of the cable under test, the aging level is used as an index parameter to query the corresponding insulation aging type in the preset database. Different insulation aging types correspond to different preset aging level ranges. If the aging level falls into a certain preset aging level range, the insulation aging type corresponding to that aging level range is determined as the insulation aging type of the cable under test. Among them, insulation aging type refers to the insulation degradation mode formed by the long-term effects of historical operating data and laying medium data on the cable in actual operation. For example, thermal aging type, water tree type, electrical tree type, moisture intrusion type or interface corrosion type, etc. Different insulation aging modes have different load conditions and aging trends.

[0028] It should be explained that the pre-built database is a pre-constructed database of insulation degradation characteristics, which consists of different types of cable insulation aging samples, operating history, experimental data under multiple environmental conditions, and field defect records. Corresponding aging level ranges are set for each type of insulation aging.

[0029] This step involves matching the external environment and historical operating stress with the insulation degradation mechanism to identify the causes of insulation aging in advance, providing a targeted reference for subsequent impedance characteristic analysis and defect classification mechanism.

[0030] In step S2, the cable under test is divided into regions according to the structural nodes of the cable under test. The structural nodes refer to the physical locations along the path of the cable under test that cause changes in the cable's geometry or characteristic impedance, such as cable joints, branch points, and sheath repair sections.

[0031] A high-frequency signal is input to the first end of the cable under test, and the reflected signals returned from each divided area are processed by the terminal acquisition device in the frequency domain to obtain broadband reflection data. The broadband reflection data includes a phase sequence arranged in frequency order and a reflection coefficient amplitude sequence. Among them, high-frequency signals refer to a type of high-frequency excitation signal that excites broadband electromagnetic wave propagation at the interface between conductor and insulation. It consists of multiple discrete frequency points, which makes the reflected signal form a distinguishable reflection phase value and reflection coefficient at each frequency point. By inputting a high-frequency signal to the beginning of the cable under test, the reflection characteristics caused by impedance discontinuity or local structural abnormalities along the cable under test can be distinguished in different frequency ranges.

[0032] Broadband reflection data refers to the response information formed during the propagation and reflection of different frequencies inside the cable under test under high frequency signal excitation; the phase sequence refers to the sequence formed by arranging the frequencies from low to high, including the reflection phase value corresponding to each frequency point, reflecting the propagation phase response characteristics of each divided region of the cable under test at different frequencies; the reflection coefficient amplitude sequence is used to reflect the impedance discontinuity and reflection intensity of each divided region at different frequency points. Calculate the phase offset coefficient of the divided region using the phase sequence of the divided region: , in, The phase offset coefficient for dividing the region. The number of frequency points, The index takes values ​​of 1, 2, 3... , For the first The reflection phase value corresponding to each frequency point For the preset number Phase thresholds corresponding to each frequency point; The preset phase offset threshold is compared with the phase offset coefficient of the divided regions to filter and mark the divided regions: If the phase offset coefficient is greater than the preset phase offset threshold, the divided region is marked. Conversely, no marking is made for the divided areas.

[0033] When the phase offset coefficient is greater than the preset phase offset threshold, it indicates that there may be abnormal propagation characteristics caused by factors such as impedance discontinuity, changes in dielectric parameters, or local structural anomalies within the divided region.

[0034] It should be explained that frequency domain analysis processing is used to convert the reflection time-domain waveform acquired by the terminal acquisition device into frequency domain response data with frequency as the horizontal axis, to obtain the phase value and reflection coefficient amplitude of the reflected signal at different frequency points; the phase threshold corresponding to the preset frequency point can be set according to the phase statistical results of the cable in a healthy state at different frequency points. For example, by collecting broadband reflection data of multiple normal cables, the phase value of each frequency point is averaged to obtain the phase threshold; the preset phase offset threshold can be set according to the phase offset distribution characteristics of healthy cables. For example, the preset phase offset threshold can be calculated by statistical analysis of the phase offset coefficients of multiple normal cables.

[0035] In step S3, the peak value of the reflection coefficient is extracted from the broadband reflection data of the marked division area. The peak value of the reflection coefficient is the point of maximum amplitude of the reflection coefficient in each marked division area, which reflects the maximum reflection intensity of the external excitation signal in the marked division area. The larger the value, the greater the degree of local impedance change in the corresponding marked division area.

[0036] Specifically, an equivalent distance transformation is performed on the reflection coefficient amplitude sequence, that is, the frequency index is mapped to the distance index corresponding to the cable length, so that the reflection coefficient amplitude sequence is converted from the frequency domain to the distance domain. Based on the interval range of the marked division area, the maximum value of the reflection coefficient amplitude within the distance interval corresponding to each marked division area is extracted as the peak value of the reflection coefficient of the marked division area.

[0037] Different insulation aging types exhibit different characteristics in broadband response. To suppress misjudgments caused by normal reflection fluctuations, impedance variation benchmarks corresponding to the insulation aging type are retrieved from a pre-set database. The impedance variation benchmarks are standard impedance variation parameters uniformly formed through long-term historical samples and experimental samples. Their meaning is the characteristic deviation value of broadband impedance caused by factors such as cable structure, dielectric loss, conductor shielding, or insulation molecular chain breakage under a specific insulation aging type, reflecting the typical impedance frequency response characteristics of similar cables under the corresponding aging type.

[0038] The maximum value of the reflection coefficient peak in all marked regions is taken as the peak reference. The standard reflection coefficient peak is obtained by dividing the reflection coefficient peak of each marked region by the peak reference, thereby achieving the standardization of the reflection coefficient peak.

[0039] Multiplying the peak value of the standard reflection coefficient with the impedance variation reference yields the impedance variation characteristics. The above process uses the peak value of the standard reflection coefficient to correct the amplitude of the impedance variation reference, so that the characteristics of the insulation aging type represented by the impedance variation reference match the actual reflection intensity of the marked area. Thus, while preserving the inherent impedance deviation law of the insulation aging type in broadband response, the reflection amplitude information of the marked area itself is introduced, thereby accurately reflecting the true impedance change degree of the marked area under the current insulation aging type.

[0040] Based on impedance variation characteristics, it is determined whether the marked and divided region has entered the defect classification mechanism by comparing the impedance variation characteristics with a preset amplitude threshold. When the impedance variation characteristic is greater than or equal to the preset amplitude threshold, it indicates that the impedance change of the corresponding marked area has exceeded the normal fluctuation range under the corresponding insulation aging type, which means that there is a potential defect risk and it is necessary to further implement the defect classification mechanism. Conversely, if the impedance variation characteristics are less than the preset amplitude threshold, the corresponding marked area is considered to exhibit normal structural reflection or regular fluctuations caused by slight insulation aging, and it is determined that there is no need to enter the defect classification mechanism.

[0041] It should be noted that the preset amplitude threshold is used to distinguish between normal reflection fluctuations and abnormal impedance deviations. In the specific setting process, a large number of cable samples under different insulation aging types but without defects are collected, and the upper limit of impedance variation characteristics is statistically analyzed. The upper limit value is used as the normal fluctuation boundary of this aging type. Then, combined with the minimum trigger value of impedance variation characteristics of known defect samples under experimental conditions, the middle value between the two is taken as the amplitude threshold.

[0042] Through the above process, while maintaining the consistency of insulation aging type, impedance anomaly characteristics are constructed based on the peak value of the reflection coefficient and the impedance anomaly benchmark, so as to accurately identify the impedance anomaly in the marked and divided area and ensure that the area entering the defect classification mechanism has clear anomaly basis.

[0043] In step S4, when entering the defect classification mechanism, the discharge pulse count and insulation recovery time of the marked division area are detected.

[0044] Discharge pulse counting is the process by which a partial discharge detection device identifies and records the total number of discharge pulses in a marked area within a set measurement time window. This count is used to characterize the frequency of processes such as micro-local breakdown, dendritic discharge channel expansion, or charge accumulation and release within the insulating medium.

[0045] To obtain the discharge pulse count, a predetermined test voltage condition is applied to the marked area, and the transient electrical pulses generated by partial discharge activity within the marked area are counted. Specifically, a stable and controllable test voltage is applied to the marked area to excite the electric field distortion points within the marked area. Then, the transient current signal of the marked area is collected by a partial discharge detection device, and the discharge events are distinguished from background noise based on a preset current threshold. Finally, all pulses determined to be discharge events are counted within the measurement time window to form the discharge pulse count. The discharge pulse count directly reflects the activity level of potential defects in the insulation structure of the marked area. The higher the value, the higher the degree of insulation degradation.

[0046] It should be noted that the partial discharge detection device is an electrical measurement device used to identify transient discharge behavior in insulating media. It can capture the rapid current changes generated in the marked area under the action of test voltage and output the captured signal in the form of a time series for discharge event determination. In order to ensure that the detection results are not affected by background noise, weak disturbances or equipment background signals, a current threshold is set as the lower limit for the discrimination of discharge events. The current threshold is obtained by statistically analyzing the reference noise level of the normal operation sample and the no-load test sample of the same type of cable. Its value is the maximum background current amplitude that occurs when the cable has no discharge activity.

[0047] Insulation recovery time is the time required for the insulating medium in the marked area to recover from a polarized state to a stable leakage current state after the applied electric field is removed. In the specific acquisition process, a step voltage of a predetermined amplitude is applied to the marked area to induce the insulating medium to enter the polarization response stage. Subsequently, the applied voltage is removed and the time point is recorded. The decay process of the dielectric current in the marked area over time is monitored in real time using a leakage current monitoring device. The time point at which the leakage current decreases from the polarization peak and finally stabilizes at the reference leakage current is identified. The difference between the time point at which the applied voltage is removed and the time point at which the reference leakage current is reached is taken as the insulation recovery time. The insulation recovery time reflects the polarization relaxation of the insulating material. The larger the value, the more obvious the polarization residue of the insulating material in the marked area and the higher the dielectric loss.

[0048] It should be noted that the leakage current monitoring device is a measuring device used to record the weak current changes in the insulating medium during the energization and de-energization process. It can continuously monitor the attenuation trajectory of the leakage current in the marked area after the applied voltage is removed, and output the current change over time in a continuous sampling manner. The reference leakage current is the stable leakage current level of the same type of cable under healthy conditions without obvious residual polarization effects. It is obtained by measuring the steady-state leakage current of a large number of healthy samples under conditions without applying a step polarization voltage, and taking the average value of its statistically stable interval as the reference leakage current.

[0049] After standardizing the discharge pulse count and insulation recovery time, the discharge pulse factor and insulation recovery factor are obtained. The defect classification index is obtained by comprehensively calculating the discharge pulse factor and insulation recovery factor using a weighted summation method. The specific calculation formula is as follows: ; in, This is a defect grading index. The discharge pulse factor. For insulation recovery factor, and The preset weighting coefficients satisfy... .

[0050] It should be noted that the weighting coefficients were set by statistically analyzing the discharge pulse counts and insulation recovery times of a large number of cable samples under different insulation aging types and different defect degrees, calculating the sensitivity and range of variation of each index to the severity of insulation degradation; then the weighting coefficients were assigned based on the sensitivity and dimensional normalization results.

[0051] The defect levels of the marked regions are classified based on the defect grading index. A three-part method is used to set the grading thresholds, including a first grading threshold and a second grading threshold, where the first grading threshold is lower than the second grading threshold. This divides the range of defect grading index values ​​into three intervals according to the principle of equal intervals. The first zone is the low value range, with the value range being the defect classification index below the first classification threshold. The corresponding defect level is low-level defect, indicating that the discharge pulse activity and insulation recovery delay in the marked area are at a low level, the insulation structure is basically intact, and there is no need to take immediate repair measures. The second zone is the middle zone, with values ​​ranging from a defect grading index that is higher than or equal to the first grading threshold but lower than the second grading threshold. The corresponding defect level is medium-level defect, indicating that there is significant discharge pulse activity or prolonged insulation recovery time in the marked area, and that the insulation medium is deteriorating. Monitoring needs to be strengthened and a targeted maintenance plan needs to be developed. The third zone is the high-value range, with values ​​ranging from the defect grading index that is higher than or equal to the second grading threshold. The corresponding defect level is high-level defect, indicating that the discharge pulse count is significantly increased and the insulation recovery time is significantly prolonged. The insulation medium polarization is severe, and the local impedance disturbance is prominent, indicating that there is a significant potential risk of breakdown, and timely maintenance, replacement or other protective measures are required.

[0052] Furthermore, after confirming that the zoning defect level is a high-level defect, a more refined location is performed based on impedance reflection time delay characteristics. Specifically, by analyzing the group time delay variation curve of the reflection coefficient over a wide frequency range, the time delay offset corresponding to the anomaly point is extracted, and the distance location of the suspected defect point is calculated in conjunction with the propagation speed of the cable medium. At the same time, this location is compared with the joint points, branch points, and historical maintenance records in the cable structure file, and a secondary convergence calibration is performed on the location area, thereby achieving the precise determination of the location of the high-level defect and providing clear guidance for subsequent maintenance, excavation, or replacement operations.

[0053] Example 2, as Figure 3 As shown, the power cable insulation condition evaluation system based on broadband impedance spectrum includes an aging identification module, a reflection acquisition module, an anomaly detection module, and a grading and location module. The functions of each module are as follows: The aging identification module is used to acquire historical operating data and laying medium data of the cable under test, calculate the cable insulation status and environmental driving index, generate aging levels, and match the insulation aging type corresponding to the aging level. The reflection acquisition module divides the cable under test into regions according to the cable structure, injects a high-frequency signal at the beginning and acquires the reflection response, completes the frequency domain analysis of the phase sequence and the amplitude sequence of the reflection coefficient, and marks the divided regions according to the phase offset coefficient. The anomaly determination module is used to extract the peak value of the reflection coefficient within the marked area, retrieve the impedance anomaly benchmark corresponding to the insulation aging type, generate impedance anomaly characteristics, and determine whether to enter the defect classification mechanism. The grading and positioning module, when entering the defect grading mechanism, detects the discharge pulse count and insulation recovery time of the marked area, generates a defect grading index for the marked area based on the detection results, and classifies the defect level.

[0054] Finally, it should be noted that in this paper, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0055] Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0056] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0057] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means (e.g., infrared, wireless, microwave, etc.).

[0058] The above description of the disclosed embodiments will enable those skilled in the art to make or use various modifications to these embodiments. It will be readily apparent to those skilled in the art that the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for evaluating the insulation condition of power cables based on broadband impedance spectrum, characterized in that: Includes the following steps: Step S1: Obtain historical operating data of the cable under test and analyze the cable insulation status, detect the laying medium data of the cable under test, calculate the aging level by combining the laying medium data with the cable insulation status, and access the preset database to match the insulation aging type corresponding to the aging level. Step S2: Divide the cable under test into regions. Obtain broadband reflection data of each region by inputting a high-frequency signal at the beginning of the cable under test. Use the broadband reflection data to filter and mark the regions. Step S3: Extract the peak reflection coefficient of the marked area, retrieve the corresponding impedance variation benchmark according to the insulation aging type, fuse the impedance variation benchmark and the peak reflection coefficient to generate impedance variation characteristics and determine whether to enter the defect classification mechanism. Step S4: When entering the defect grading mechanism, the discharge pulse count and insulation recovery time of the marked area are detected, and a defect grading index for the marked area is generated and the defect level is classified according to the detection results.

2. The method for evaluating the insulation status of power cables based on broadband impedance spectrum according to claim 1, characterized in that: In step S1, historical operating data of the cable under test is obtained and the cable insulation status is analyzed. The laying medium data of the cable under test is detected. Historical operating data of the cable under test is obtained through the historical operating database. The historical operating data includes historical operating current and historical power outages and restorations. The product of the historical operating current and the number of historical power outages and restorations after standardization is used as the cable insulation status. The environment of the area where the cable to be tested is laid is tested to obtain data on the laying medium of the cable, including soil moisture and soil conductivity. The soil moisture in the laying medium is detected by a soil moisture sensor, and the soil conductivity in the laying medium is detected by a soil conductivity sensor. The environmental driving index is calculated by combining soil moisture and soil electrical conductivity.

3. The method for evaluating the insulation status of power cables based on broadband impedance spectrum according to claim 2, characterized in that: In step S1, the aging level is calculated by using the laying medium data and the cable insulation status. The cable insulation status and the environmental driving index are used as two-dimensional status points. The aging level is calculated by the distance from the preset health benchmark point. The aging level is used as an index parameter to query the preset database. Different insulation aging types correspond to different preset aging level ranges. If the aging level falls within a certain preset aging level range, then the insulation aging type corresponding to the aging level range is determined as the insulation aging type of the cable under test.

4. The method for evaluating the insulation status of power cables based on broadband impedance spectrum according to claim 1, characterized in that: In step S2, the cable under test is divided into regions. High-frequency signals are input to the beginning of the cable under test to obtain broadband reflection data of each region. The cable under test is divided into regions according to the structural nodes of the cable under test. A high-frequency signal is input to the first end of the cable under test, and the reflected signals returned from each divided area are processed by the terminal acquisition device in the frequency domain to obtain broadband reflection data. The broadband reflection data includes a phase sequence arranged in frequency order and a reflection coefficient amplitude sequence.

5. The method for evaluating the insulation status of power cables based on broadband impedance spectrum according to claim 4, characterized in that: In step S2, broadband reflection data is used to filter and divide regions and mark them. The phase offset coefficient of the divided regions is calculated by the phase sequence of the divided regions. The preset phase offset threshold is compared with the phase offset coefficient of the divided regions to filter and mark the divided regions: If the phase offset coefficient is greater than the preset phase offset threshold, the divided region is marked. Conversely, no marking is made for the divided areas.

6. The method for evaluating the insulation status of power cables based on broadband impedance spectrum according to claim 4, characterized in that: In step S3, extract the peak value of the reflection coefficient of the marked division area, map the frequency index of the reflection coefficient amplitude sequence to the distance index corresponding to the cable length, and extract the maximum value of the reflection coefficient amplitude within the distance interval corresponding to each marked division area as the peak value of the reflection coefficient of the marked division area. Retrieve the impedance variation reference corresponding to the insulation aging type from the preset database. The impedance variation reference refers to the characteristic deviation value of broadband impedance caused by different insulation aging types. The maximum value of the reflection coefficient peak in all marked regions is taken as the peak reference. The standard reflection coefficient peak value is obtained by dividing the reflection coefficient peak value of each marked region by the peak reference value.

7. The method for evaluating the insulation status of power cables based on broadband impedance spectrum according to claim 6, characterized in that: In step S3, the corresponding impedance variation benchmark is retrieved according to the insulation aging type. The impedance variation benchmark and the peak reflection coefficient are fused to generate impedance variation characteristics and determine whether to enter the defect classification mechanism. The standard peak reflection coefficient and the impedance variation benchmark are multiplied to obtain the impedance variation characteristics. When the impedance variation characteristic is greater than or equal to the preset amplitude threshold, it indicates that the impedance change of the corresponding marked area has exceeded the normal fluctuation range under the corresponding insulation aging type, which means that there is a potential defect risk and it is necessary to further implement the defect classification mechanism. Conversely, if the impedance variation characteristics are less than the preset amplitude threshold, the corresponding marked area is considered to exhibit normal structural reflection or regular fluctuations caused by slight insulation aging, and it is determined that there is no need to enter the defect classification mechanism.

8. The method for evaluating the insulation status of power cables based on broadband impedance spectrum according to claim 1, characterized in that: When entering the defect classification mechanism in step S4, the discharge pulse count and insulation recovery time of the marked area are detected. When entering the defect classification mechanism, within the set measurement time window, the total number of discharge pulses in the marked area is identified and recorded as the discharge pulse count by the partial discharge detection device. A step voltage of predetermined amplitude is applied to the marked area to induce the insulating medium to enter the polarization response stage. The applied voltage is then removed and the time points are recorded. The leakage current monitoring device is used to monitor the decay process of the dielectric current in the marked area over time in real time, and to identify the time point when the leakage current drops from the polarization peak and finally stabilizes at the reference leakage current. The difference between the time when the applied voltage is removed and the time when the reference leakage current is reached is taken as the insulation recovery time.

9. The method for evaluating the insulation status of power cables based on broadband impedance spectrum according to claim 8, characterized in that: In step S4, a defect classification index is generated based on the detection results to divide the marked areas and the defect levels are classified. After standardizing the discharge pulse count and insulation recovery time, the discharge pulse factor and insulation recovery factor are obtained. The defect classification index is obtained by comprehensively calculating the discharge pulse factor and insulation recovery factor using a weighted summation method. The threshold for classifying defects is set using a three-part method, which divides the range of defect classification index values ​​into three intervals according to the principle of equal intervals. Each interval corresponds to a different defect level, including low-level defects, medium-level defects, and high-level defects.

10. A power cable insulation condition evaluation system based on broadband impedance spectrum, used to implement the power cable insulation condition evaluation method based on broadband impedance spectrum as described in any one of claims 1-9, characterized in that: It includes an aging identification module, a reflection acquisition module, an anomaly detection module, and a grading and positioning module. The functions of each module are as follows: The aging identification module is used to acquire historical operating data and laying medium data of the cable under test, calculate the cable insulation status and environmental driving index, generate aging levels, and match the insulation aging type corresponding to the aging level. The reflection acquisition module divides the cable under test into regions according to the cable structure, injects a high-frequency signal at the beginning and acquires the reflection response, completes the frequency domain analysis of the phase sequence and the amplitude sequence of the reflection coefficient, and marks the divided regions according to the phase offset coefficient. The anomaly determination module is used to extract the peak value of the reflection coefficient within the marked area, retrieve the impedance anomaly benchmark corresponding to the insulation aging type, generate impedance anomaly characteristics, and determine whether to enter the defect classification mechanism. The grading and positioning module, when entering the defect grading mechanism, detects the discharge pulse count and insulation recovery time of the marked area, generates a defect grading index for the marked area based on the detection results, and classifies the defect level.

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