High-voltage power cable state real-time intelligent monitoring system

Abstract

The invention relates to the technical field of power cable monitoring, in particular to a real-time intelligent monitoring system for the state of a high-voltage power cable. According to the method, the partial discharge signal is obtained through the original partial discharge signal of each monitoring section of the cable in combination with the field electromagnetic environment interference characteristic number, the partial discharge abnormal position is determined by adopting double-end positioning based on the actual propagation speed of the cable, and the partial discharge abnormal type is identified in combination with the characteristic parameters in the partial discharge signal. Precise positioning of a partial discharge abnormal position is realized, and the accuracy of discharge abnormal type identification is improved. Meanwhile, a partial discharge characteristic early warning reference value is adjusted based on a cable operation condition and is compared with a characteristic parameter in a partial discharge signal, and when partial discharge is not abnormal, the insulation health state of the cable is compared and evaluated in combination with a historical partial discharge signal characteristic parameter, so that the slow degradation trend of the insulation state of the cable is captured. The cable preventive operation and maintenance are realized, and the probability of cable fault occurrence is reduced.

Description

A Real-time Intelligent Monitoring System for the Status of High-Voltage Power Cables Technical Field

[0001] This invention relates to the field of power cable monitoring technology, and specifically to a real-time intelligent monitoring system for the status of high-voltage power cables. Background Technology

[0002] During long-term operation, latent faults such as insulation degradation and partial discharge are the main causes of cable failures in high-voltage power cables. Therefore, real-time monitoring and intelligent assessment of cable conditions have become important means to ensure the safe operation of power systems. Partial discharge monitoring, as an effective method to reflect the insulation condition of cables, can achieve early detection and warning of cable insulation defects, which is of great significance for preventing cable failures and extending cable service life.

[0003] In the prior art, Chinese Patent Publication No. CN120028656B discloses an online monitoring method and device for partial discharge of cable joints. This method determines the discharge type and location determination characteristics of the discharge pulse signal, determines the discharge type based on a classification and recognition model, triggers the corresponding combination of environmental sensing elements to acquire environmental data, combines the environmental data and location determination characteristics, uses a multimodal data fusion algorithm to determine the discharge location, associates the discharge location and type to generate monitoring results and pushes them, thereby improving the accuracy and reliability of discharge monitoring.

[0004] The existing technology has the following problems: 1. The existing technology only monitors partial discharge at the cable joint, without realizing signal acquisition and interference elimination of the entire cable monitoring section. Furthermore, it only identifies the discharge type through simple feature matching without verifying the type in conjunction with the discharge location. This results in a limited monitoring range and insufficient accuracy in discharge type identification, leading to missed detection of partial discharge in non-joint areas of the cable. It is also prone to misjudging the discharge type and cannot provide accurate type basis for fault handling.

[0005] 2. Existing technologies only compensate and correct the discharge location determination characteristics without considering the impact of environmental changes on the partial discharge characteristic parameters. This leads to the use of fixed thresholds for anomaly determination, which cannot adapt to the differences in the operating characteristics of cables under different working conditions. This can easily result in missed or false alarms, reducing the reliability of the warning.

[0006] 3. Existing technologies focus on the abnormal detection and location of partial discharge, lacking continuous assessment of the health status of cable insulation. This results in the inability to capture the slow deterioration trend of cable insulation, making preventive maintenance impossible. Instead, passive handling is only possible after a fault occurs, increasing the operational risks of the power system. Summary of the Invention

[0007] The present invention aims to overcome the deficiencies in the prior art and provide a real-time intelligent monitoring system for the status of high-voltage power cables, so as to realize real-time, accurate and intelligent monitoring of the operating status of high-voltage power cables and provide a scientific basis for cable operation and maintenance.

[0008] The technical solution adopted by the present invention to solve its technical problem is: a real-time intelligent monitoring system for the status of high-voltage power cables, including a discharge signal acquisition module, a discharge anomaly identification module, a warning reference value adjustment module, an anomaly warning determination module, and a cable status assessment module.

[0009] The connections between the modules are as follows: the discharge signal acquisition module is connected to the discharge anomaly identification module; the early warning reference value adjustment module is connected to both the discharge anomaly identification module and the anomaly early warning determination module; and the cable condition assessment module is connected to the anomaly early warning determination module.

[0010] The discharge signal acquisition module collects the original partial discharge signals of each monitoring section of the high-voltage power cable in real time, and performs interference elimination processing by combining the on-site electromagnetic environment interference characteristic data to obtain the partial discharge signal.

[0011] The discharge anomaly identification module obtains the actual propagation speed of the cable based on the historical pulse propagation delay record of the cable, uses dual-end positioning to determine the location of partial discharge anomalies, and identifies the type of partial discharge anomaly by combining the characteristic parameters in the partial discharge signal.

[0012] The early warning reference value adjustment module dynamically adjusts the early warning reference value of partial discharge characteristics based on real-time collected data on cable operating load, ambient temperature, and cable operating temperature.

[0013] The abnormality warning and determination module compares the characteristic parameters in the partial discharge signal with the dynamically adjusted warning reference value to determine whether the partial discharge of the power cable is abnormal.

[0014] The cable condition assessment module evaluates the insulation health status of a power cable by comparing historical partial discharge signal characteristic parameters with those of the cable when there are no abnormalities in the partial discharge.

[0015] Compared with the prior art, the present invention has the following beneficial effects: (1) The present invention obtains the partial discharge signal by collecting the original partial discharge signal of each monitoring section of the cable and combining it with the interference characteristics data of the electromagnetic environment on site for interference elimination processing, thereby realizing the accurate and synchronous acquisition of the partial discharge signal of the entire monitoring section of the cable, effectively eliminating the influence of the electromagnetic environment on the signal, and ensuring the accuracy of the data source for subsequent discharge anomaly analysis.

[0016] (2) This invention obtains the actual propagation speed of the cable based on the historical pulse propagation delay record of the cable, uses double-end positioning to determine the location of partial discharge anomalies, and combines the characteristic parameters in the partial discharge signal to identify the type of partial discharge anomaly, thereby achieving accurate positioning of the location of the partial discharge anomaly, improving the accuracy and scientific nature of the identification of discharge anomaly types, and providing accurate basis for maintenance personnel to quickly locate fault points and formulate targeted treatment plans.

[0017] (3) Based on the real-time acquisition of cable operating load, ambient temperature and cable operating temperature, the present invention dynamically adjusts the partial discharge characteristic warning reference value, so that the partial discharge characteristic warning value can adapt to different operating conditions, effectively avoid the situation of missed warning and false warning under different operating conditions, and improve the accuracy and environmental adaptability of abnormal warning.

[0018] (4) When there is no abnormality in the partial discharge of the power cable, the present invention combines the characteristic parameters of the corresponding historical partial discharge signal of the power cable to compare and evaluate the cable insulation health status, thereby realizing the extension from the monitoring of abnormal partial discharge to the longitudinal evaluation of the cable insulation health status. It can accurately capture the slow deterioration trend of the cable insulation status, realize the preventive operation and maintenance of the cable, and reduce the probability of cable failure. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 is a schematic diagram of the system module connection of the present invention.

[0021] Figure 2 is a schematic diagram of the partial discharge abnormality location calibration steps in this invention.

[0022] Figure 3 is a schematic diagram of the final partial discharge anomaly type determination steps in this invention. Detailed Implementation

[0023] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the invention. Furthermore, it should be understood that, for ease of description, the dimensions of the various parts shown in the drawings are not drawn to actual scale.

[0024] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the invention or its application or use. Techniques, methods, and apparatus known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and apparatus should be considered part of the specification.

[0025] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0026] Please refer to Figure 1. The present invention provides a real-time intelligent monitoring system for the status of high-voltage power cables, including a discharge signal acquisition module, a discharge anomaly identification module, a warning reference value adjustment module, an anomaly warning determination module, and a cable status assessment module.

[0027] The connections between the modules are as follows: the discharge signal acquisition module is connected to the discharge anomaly identification module; the early warning reference value adjustment module is connected to both the discharge anomaly identification module and the anomaly early warning determination module; and the cable condition assessment module is connected to the anomaly early warning determination module.

[0028] The discharge signal acquisition module collects the original partial discharge signals of each monitoring section of the high-voltage power cable in real time, and performs interference elimination processing by combining the on-site electromagnetic environment interference characteristic data to obtain the partial discharge signal.

[0029] Considering the complex electromagnetic environment at high-voltage power cable operating sites, the background noise of substations, transient interference from switch operations, and interference signals from communication bands are easily mixed with partial discharge signals. If the original signals are not effectively purified, it will seriously affect the accuracy of subsequent discharge anomaly identification. Therefore, it is necessary to establish a multi-dimensional interference feature library to achieve accurate identification and removal of interference components and ensure the purity of partial discharge signals.

[0030] Based on this, this module outputs a partial discharge signal by performing interference feature matching and signal restoration on the original partial discharge signal. The specific implementation method includes: S11, deploying distributed discharge signal acquisition devices at both ends of each monitoring section of the high-voltage power cable, synchronously acquiring the partial discharge electromagnetic signals of the corresponding monitoring section according to the set sampling frequency, generating an original partial discharge signal covering the entire monitoring section of the cable, and avoiding signal omission in non-joint areas.

[0031] S12. Collect electromagnetic signals within the monitoring area surrounding each monitoring section, and identify the type of interference source of the collected electromagnetic signals through electromagnetic signal feature matching.

[0032] Preferably, in a specific embodiment of the present invention, a broadband electromagnetic sensor is used to collect electromagnetic background signals in the 0-500MHz frequency band around the monitoring section, and the time-frequency characteristics of the signal are extracted by short-time Fourier transform. The interference source type (such as narrowband communication interference, periodic pulse interference, random white noise interference, etc.) is identified by combining its spectrum.

[0033] Narrowband communication interference mainly originates from mobile communication base stations and wireless intercom equipment. Its spectral energy is concentrated in the narrowband frequency band, with a bandwidth usually less than 200kHz. The spectrum shape is symmetrical bell-shaped or rectangular, and the time domain exhibits continuous or burst radiation characteristics.

[0034] Periodic pulse interference mainly originates from switching operations and power electronic devices. It exhibits periodicity in the time domain, and its spectrum shows a discrete spectral structure, containing the fundamental frequency and its integer multiples of harmonic energy.

[0035] Random white noise interference mainly originates from the background noise of substations. Its spectrum exhibits a flat broadband distribution, with energy uniformly distributed in the range of 0-500MHz. It also shows random changes in the time domain, without periodicity or clustering.

[0036] It should be noted that identifying the type of interference source is an existing technical means well known to those skilled in the art, and will not be elaborated further.

[0037] S13. Extract the signal frequency, phase, amplitude and pulse characteristics from the electromagnetic signals corresponding to each type of interference source, and establish a corresponding interference signal feature library according to the type of interference source.

[0038] S14. Perform feature matching between the original partial discharge signal and the interference signal feature library, calculate the feature matching degree between the original partial discharge signal and various interference source types in the interference signal feature library, and extract the interference components whose feature matching degree reaches the set threshold from the original partial discharge signal.

[0039] It should be noted that, considering that the closer the feature matching degree is to 1, the higher the feature matching degree is, and the closer it is to 0, the lower the matching degree is, the threshold can be set to 0.8. Implementers can adjust the threshold themselves, but it should not deviate too much from 1.

[0040] As an example, the feature matching degree can be calculated using the cosine similarity algorithm. In this embodiment, the features of the original partial discharge signal and the various types of interference sources in the interference signal feature library are first standardized and normalized to construct multi-dimensional feature vectors. Then, the cosine similarity value between the feature vector of the original partial discharge signal and the feature vector of each interference source is calculated using the cosine similarity formula. This value is the feature matching degree.

[0041] In other embodiments, implementers may also use Euclidean distance similarity or normalized correlation coefficient algorithms for calculation. Before calculating with each algorithm, the feature vectors must be standardized to ensure the comparability of the calculation results.

[0042] S15. The interference components in the original partial discharge signal are removed, and the electromagnetic signal after removing the interference components is restored using a reconstruction algorithm to obtain the partial discharge signal.

[0043] It should be noted that the preferred reconstruction algorithm in the above-mentioned method is the wavelet transform reconstruction algorithm, which reconstructs the signal after interference removal by inverse wavelet transform to restore the original characteristics of the partial discharge signal; since the wavelet transform reconstruction algorithm is an existing technology, it will not be described in detail.

[0044] This invention collects the original partial discharge signals of each monitoring section of the cable, combines them with the interference characteristics data of the on-site electromagnetic environment for interference elimination processing, and obtains the partial discharge signals. This enables accurate and synchronous acquisition of partial discharge signals of the entire monitoring section of the cable, effectively eliminates the influence of on-site electromagnetic environment interference on the signals, and ensures the accuracy of the data source for subsequent discharge anomaly analysis.

[0045] The discharge anomaly identification module obtains the actual propagation speed of the cable based on the historical pulse propagation delay record of the cable, uses dual-end positioning to determine the location of partial discharge anomalies, and identifies the type of partial discharge anomaly by combining the characteristic parameters in the partial discharge signal.

[0046] Considering that the propagation speed of partial discharge pulses in cable insulation is affected by the aging of cable materials and differences in insulation structure, there is a deviation between the theoretical propagation speed and the actual propagation speed. Directly using the theoretical speed for positioning will lead to the accumulation of position errors. At the same time, the characteristic parameters of different discharge types overlap. For example, the pulse characteristics of surface discharge and internal air gap discharge are similar. Relying on a single feature for matching is prone to misclassification. It is necessary to combine the structural characteristics at the discharge location for verification to improve the accuracy of identification.

[0047] Based on this, this module determines the location and type of partial discharge anomalies by correcting the actual propagation speed and verifying the location and structural features. The specific implementation method includes: S21, extracting pulse propagation delay records of known discharge locations from the cable monitoring historical database, combining the theoretical propagation speed of the partial discharge pulse in the cable insulation medium, determining the actual propagation speed of multiple sets of pulse propagation delay records of known discharge locations, and taking their average value as the actual propagation speed of the cable.

[0048] Preferably, in one specific embodiment, the actual propagation speed of the cable is calculated as follows: .

[0049] In the formula, The actual propagation speed of the cable. Given the known distance between the discharge location and the pulse emission location, This is the theoretical propagation speed of a partial discharge pulse in the cable insulation medium. The pulse propagation delay is given by the known discharge location.

[0050] S22. Obtain the time delay difference between the first and last sensors of the cable monitoring section that detect the same discharge pulse, and construct a set of dual-end positioning equations in combination with the actual propagation speed of the cable.

[0051] S23. Solve the double-ended positioning equations to obtain the preliminary distance between the partial discharge anomaly location and the cable end point. Combine this with the cable joint location coordinates to perform position calibration and determine the location of the partial discharge anomaly.

[0052] It should be noted that the time delay difference between the detection of the same discharge pulse by the sensor at the beginning and end of the cable monitoring section is denoted as . The length of the cable monitoring section is Then the two-ended positioning equation system is: .

[0053] In the formula, This is the initial distance between the location of the partial discharge anomaly and the cable end point; that is, this initial distance is the closest distance between the location of the partial discharge anomaly and the cable end point. This represents the farthest distance from the partial discharge anomaly location relative to the cable endpoint.

[0054] Preferably, in a specific embodiment, as shown in FIG2, the method of position calibration by combining the position coordinates of the cable joint is as follows: S231, based on the positive and negative characteristics of the time delay difference, the absolute coordinate value of the partial discharge anomaly position in the cable monitoring section is determined by combining the preliminary distance.

[0055] S232. Extract the position coordinates of all joints in each monitoring section of the cable from the cable structure database and establish a joint position coordinate sequence.

[0056] S233. Compare the absolute coordinates of the partial discharge anomaly location with the coordinate sequence of the connector location, and calculate the spatial distance between the absolute coordinates and the coordinates of the adjacent connector locations.

[0057] S234. If the spatial distance between the absolute coordinate value and the coordinates of the adjacent connector is less than the preset allowable range of positioning error near the connector (e.g., ±2 meters, which the implementer can adjust according to the connector type; ±3 meters for GIS terminal connectors and ±2 meters for intermediate connectors), then the location of the partial discharge anomaly is determined to be in the vicinity of the connector, and the coordinates of the connector are taken as the location of the partial discharge anomaly.

[0058] Conversely, the location corresponding to the absolute coordinate value is taken as the location of the partial discharge anomaly.

[0059] S24. Perform pulse extraction on the partial discharge signal, count the number of discharge pulses per unit time to obtain the discharge frequency, and measure the peak amplitude and half-peak width of each discharge pulse to obtain the discharge peak value and pulse width.

[0060] S25. Map the trigger time of each discharge pulse to the established voltage phase coordinate system (0-360°, with the zero-crossing point of the power frequency voltage as the reference), count the discharge pulse distribution density of each phase interval, generate a discharge phase distribution set, and combine the discharge frequency, discharge peak value and pulse width to form the characteristic parameters of the partial discharge signal.

[0061] S26. The similarity between the feature parameters of the partial discharge signal and the corresponding feature parameters of each partial discharge type in the partial discharge type sample library is calculated. The weighted Euclidean distance or cosine similarity algorithm is used to obtain the matching similarity between the feature parameters of the partial discharge signal and each partial discharge type.

[0062] It should be noted that the partial discharge type sample library extracts the discharge waveforms of internal air gap discharge, surface discharge, corona discharge, and floating potential discharge types from historical monitoring data of high-voltage power cables, extracts characteristic parameters of the discharge waveforms of each partial discharge type, statistically analyzes the distribution range of characteristic parameters for the same partial discharge type, and uses the central trend value of the characteristic parameter distribution range as the corresponding reference characteristic parameter.

[0063] S27. Select the partial discharge type with the highest matching similarity as the preliminary partial discharge anomaly type. Combine this with the location of the partial discharge anomaly for type verification to determine the final partial discharge anomaly type. As shown in Figure 3, the specific determination method is as follows: First, select partial discharge anomaly records from the cable monitoring historical database, count the occurrence frequency of each partial discharge anomaly type at different cable anomaly locations, and analyze the probability of each partial discharge anomaly type at different cable anomaly locations. For example, the probability of surface discharge occurring near the joint is 75%, while it is only 8% in the cable body area; the probability of internal air gap discharge occurring in the cable body area is 65%, while it is 12% near the joint.

[0064] Then, based on the location of the partial discharge anomaly, the probability of the preliminary partial discharge anomaly type at the location of the partial discharge anomaly is determined.

[0065] Finally, if the probability is the maximum probability of the initial partial discharge anomaly type at different cable anomaly locations, then the initial partial discharge anomaly type is taken as the final partial discharge anomaly type. For example, if the initial partial discharge anomaly type is surface discharge and the discharge location is near the joint, its probability of 75% is the maximum probability among all locations of this type.

[0066] Conversely, if the second largest matching similarity corresponds to the partial discharge type, it is selected for verification, and this process is iterated until the final partial discharge anomaly type is determined.

[0067] This invention obtains the actual propagation speed of the cable based on historical pulse propagation delay records, uses dual-end positioning to determine the location of partial discharge anomalies, and combines characteristic parameters in the partial discharge signal to identify the type of partial discharge anomaly, thereby achieving precise location of the partial discharge anomaly and improving the accuracy and scientific nature of discharge anomaly type identification. This provides a precise basis for maintenance personnel to quickly locate fault points and formulate targeted handling solutions.

[0068] The early warning reference value adjustment module dynamically adjusts the early warning reference value of partial discharge characteristics based on real-time collected data on cable operating load, ambient temperature, and cable operating temperature.

[0069] Considering that changes in cable operating load lead to changes in conductor heating, and that ambient temperature affects cable heat dissipation, the combined effect of these two factors causes the cable insulation aging rate to change dynamically. If a fixed threshold is used for anomaly detection, it will be unable to adapt to the differences in insulation condition under different operating conditions, and may result in missed or false warnings. Therefore, it is necessary to establish a multi-condition benchmark matrix and combine it with real-time operating parameters for dynamic correction to achieve adaptive adjustment of the warning reference value.

[0070] Based on this, this module dynamically adjusts the partial discharge characteristic warning reference value through multi-condition benchmark matching and temperature coefficient correction. The specific implementation method includes: S31, screening historical data of partial discharge characteristic parameters of different load levels and different ambient temperature ranges under normal cable operation from the cable monitoring historical database, dividing the operating conditions according to load level and ambient temperature range, statistically analyzing the distribution range of partial discharge characteristic parameters under each operating condition, taking the 95th percentile value of the historical data under each operating condition as the benchmark value of partial discharge characteristic parameters to ensure coverage of the normal operation fluctuation range, and establishing a multi-condition partial discharge characteristic parameter benchmark matrix with load level as the row dimension and ambient temperature range as the column dimension.

[0071] S32. Based on the real-time collected load and ambient temperature, match the corresponding partial discharge characteristic parameter reference values ​​from the multi-condition partial discharge characteristic parameter reference matrix.

[0072] S33. Based on the deviation between the cable operating temperature and the cable rated operating temperature, and in conjunction with the temperature sensitivity characteristic curve of the cable insulation material, determine the increase ratio of the insulation aging rate under the influence of the temperature deviation, and use it as the temperature correction coefficient.

[0073] It should be noted that the temperature sensitivity curve of the cable insulation material represents the multiple by which the insulation aging rate increases for every 10°C increase in temperature. The temperature sensitivity curve of the cable insulation material is an existing technical means well known to those skilled in the art, and will not be described in detail here.

[0074] S34. Perform a fusion calculation, such as a product operation, between the baseline value of the partial discharge characteristic parameters and the temperature correction coefficient to obtain the dynamically adjusted partial discharge characteristic warning reference value.

[0075] This invention dynamically adjusts the partial discharge characteristic warning reference value based on real-time collected cable operating load, ambient temperature, and cable operating temperature. This allows the partial discharge characteristic warning value to adapt to different operating conditions, effectively avoiding missed and false warnings under different operating conditions, and improving the accuracy and environmental adaptability of abnormal warnings.

[0076] The abnormality warning and determination module compares the characteristic parameters in the partial discharge signal with the dynamically adjusted warning reference value to determine whether the partial discharge of the power cable is abnormal.

[0077] Considering that the determination of partial discharge anomalies needs to take into account the comprehensive performance of multiple characteristic parameters, and that a single feature exceeding the standard may be caused by transient interference, directly determining the anomaly will lead to an increase in the false alarm rate, it is necessary to establish a multi-feature collaborative determination to provide complete data support for operation and maintenance decisions.

[0078] Based on this, the specific content of this module is as follows: compare all characteristic parameters of the partial discharge signal with the corresponding dynamically adjusted early warning reference values ​​one by one.

[0079] If any characteristic parameter exceeds the corresponding warning reference value, the partial discharge of the power cable is determined to be in an abnormal state, and a discharge abnormality warning information is generated simultaneously, including the location of the partial discharge abnormality, the type of abnormality, and the characteristic parameters exceeding the standard.

[0080] If all characteristic parameters do not exceed the warning reference value, it is determined that there is no abnormality in the partial discharge of the power cable, and the characteristic parameters of the partial discharge signal are stored in the cable's historical operation database.

[0081] This invention compares the characteristic parameters in the partial discharge signal with the dynamically adjusted warning reference value to determine whether the partial discharge of the power cable is abnormal. It achieves accurate anomaly determination through multi-feature collaboration, effectively distinguishes between real discharge anomalies and transient interference, reduces the false alarm rate while ensuring timely fault warning, and improves the reliability and practicality of the monitoring system.

[0082] The cable condition assessment module evaluates the insulation health status of a power cable by comparing historical partial discharge signal characteristic parameters with those of the cable when there are no abnormalities in the partial discharge.

[0083] Considering that the insulation degradation of high-voltage power cables is a gradual and cumulative process, even if the current partial discharge has not reached the abnormal threshold, the slow drift of characteristic parameters may still indicate the deterioration of the insulation condition. If we only focus on the anomaly judgment and ignore the trend analysis, we will miss the opportunity for preventive operation and maintenance. It is necessary to establish a historical time series and achieve longitudinal assessment of the insulation health status through quantitative analysis of the rate of change and the degree of deviation.

[0084] Based on this, this module assesses the health status of cable insulation through historical data retrieval, time series analysis, and trend determination. The specific implementation method includes: First, retrieving historical partial discharge signal characteristic parameters of power cables in the same monitoring section from the historical operation database of the cable, and constructing a time series sequence of historical characteristic parameters.

[0085] The second step is to superimpose the currently acquired partial discharge signal characteristic parameters onto the historical characteristic parameter time series, and calculate the rate of change and degree of deviation of the partial discharge signal characteristic parameters.

[0086] The rate of change is calculated using linear regression or exponential smoothing to determine the slope of each characteristic parameter over time, such as the unit time growth rate of discharge frequency (e.g., monthly growth rate).

[0087] The degree of deviation is the deviation of the current feature parameter from the mean of the same period in history (such as the same month of the previous year). The specific calculation method is as follows: obtain the difference between the current feature parameter and the mean of the same period in history, and use the ratio of the difference to the standard deviation of the same period in history as the degree of deviation.

[0088] The third step is to determine the cable insulation health status based on the rate of change and degree of deviation of the characteristic parameters of the partial discharge signal. The specific determination method is as follows: First, set the allowable range of the degree of deviation of the characteristic parameters (such as ±3 times the standard deviation) and the allowable threshold of the rate of change (such as ±5%). If the degree of deviation of all characteristic parameters of the partial discharge signal is within the allowable range and the rate of change is lower than the allowable threshold, then the cable insulation health status is determined to be normal.

[0089] Then, if the deviation of a certain partial discharge signal characteristic parameter exceeds the allowable range or its rate of change exceeds the allowable threshold, the cable insulation health status is determined to be abnormal, and a power outage maintenance warning is triggered and the cable monitoring section number is pushed.

[0090] When there is no abnormality in the partial discharge of the power cable, this invention combines the characteristic parameters of the corresponding historical partial discharge signal of the power cable to compare and evaluate the health status of the cable insulation, realizing the extension from the monitoring of abnormal partial discharge to the longitudinal evaluation of the cable insulation health status. It can accurately capture the slow deterioration trend of the cable insulation status, realize the preventive operation and maintenance of the cable, and reduce the probability of cable failure.

[0091] 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, in the form of a computer program product.

[0092] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0093] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0094] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0095] Finally, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A real-time intelligent monitoring system for the status of high-voltage power cables, characterized in that, include: The discharge signal acquisition module collects the original partial discharge signals of each monitoring section of the high-voltage power cable in real time, and performs interference cancellation processing in combination with the electromagnetic environment interference characteristic data at the site to obtain the partial discharge signal; The discharge anomaly identification module obtains the actual propagation speed of the cable based on the historical pulse propagation delay record of the cable, uses double-end positioning to determine the location of partial discharge anomalies, and identifies the type of partial discharge anomaly by combining the characteristic parameters in the partial discharge signal. The early warning reference value adjustment module dynamically adjusts the early warning reference value of partial discharge characteristics based on real-time collected data on cable operating load, ambient temperature, and cable operating temperature. The abnormality warning and judgment module compares the characteristic parameters in the partial discharge signal with the dynamically adjusted warning reference value to determine whether the partial discharge of the power cable is abnormal. The cable condition assessment module evaluates the insulation health status of a power cable by comparing historical partial discharge signal characteristic parameters with those of the cable when there are no abnormalities in the partial discharge.

2. The real-time intelligent monitoring system for the status of high-voltage power cables according to claim 1, characterized in that: The steps for obtaining the partial discharge signal are as follows: electromagnetic signals are collected within the monitoring area surrounding each monitoring segment; the type of interference source of the collected electromagnetic signals is identified by electromagnetic signal feature matching; the signal frequency, phase, amplitude, and pulse characteristics of the electromagnetic signals corresponding to each type of interference source are extracted, and a corresponding interference signal feature library is established according to the type of interference source; the original partial discharge signal is matched with the interference signal feature library, and interference components with a feature matching degree reaching a set threshold are extracted from the original partial discharge signal; the interference components in the original partial discharge signal are removed, and the electromagnetic signal after removing the interference components is restored to obtain the partial discharge signal.

3. The real-time intelligent monitoring system for the status of high-voltage power cables according to claim 1, characterized in that: The method for determining the location of the partial discharge anomaly is as follows: extract the pulse propagation delay records of known discharge locations from the cable monitoring historical database, and determine the actual propagation speed of the cable by combining the theoretical propagation speed of the partial discharge pulse in the cable insulation medium; obtain the time delay difference between the first-end and last-end sensors of the cable monitoring section that detect the same discharge pulse, and construct a double-end positioning equation set by combining it with the actual propagation speed of the cable; solve the double-end positioning equation set to obtain the preliminary distance of the partial discharge anomaly location relative to the cable end point, and perform position calibration by combining it with the coordinates of the cable joint location to determine the location of the partial discharge anomaly.

4. The real-time intelligent monitoring system for the status of high-voltage power cables according to claim 3, characterized in that: The method of position calibration by combining the coordinates of the cable joint is as follows: based on the positive and negative characteristics of the time delay difference, the absolute coordinates of the partial discharge anomaly location in the cable monitoring section are determined by combining the preliminary distance. Extract the position coordinates of all joints in each monitoring section of the cable from the cable structure database and establish a joint position coordinate sequence. Compare the absolute coordinate values ​​of the partial discharge anomaly location with the joint position coordinate sequence and calculate the spatial distance between the absolute coordinate values ​​and the position coordinates of adjacent joints. If the spatial distance between the absolute coordinate values ​​and the position coordinates of adjacent joints is less than the preset allowable range of positioning error near the joint, the partial discharge anomaly location is determined to be located in the vicinity of the joint, and the position coordinates of the joint are taken as the partial discharge anomaly location. Otherwise, the location corresponding to the absolute coordinate value is taken as the partial discharge anomaly location.

5. The real-time intelligent monitoring system for the status of high-voltage power cables according to claim 1, characterized in that: The partial discharge anomaly type identification steps are as follows: pulse extraction is performed on the partial discharge signal, the number of discharge pulses per unit time is counted to obtain the discharge frequency, and the peak value and half-peak width of each discharge pulse are measured to obtain the discharge peak value and pulse width. The trigger time of each discharge pulse is mapped to the established voltage phase coordinate system. The discharge pulse distribution density of each phase interval is statistically analyzed to generate a discharge phase distribution set. The discharge frequency, discharge peak value, and pulse width are combined to form the characteristic parameters of the partial discharge signal. The similarity between the characteristic parameters of the partial discharge signal and the corresponding reference characteristic parameters of each partial discharge type is calculated to obtain the matching similarity between the characteristic parameters of the partial discharge signal and each partial discharge type. The partial discharge type corresponding to the maximum matching similarity is selected as the preliminary partial discharge anomaly type. The type is verified by combining the location of the partial discharge anomaly to determine the final partial discharge anomaly type.

6. The real-time intelligent monitoring system for the status of high-voltage power cables according to claim 5, characterized in that: The method for determining the final partial discharge anomaly type is as follows: Screening partial discharge anomaly records from the cable monitoring historical database, counting the occurrence frequency of each partial discharge anomaly type at different cable anomaly locations, and analyzing the probability of each partial discharge anomaly type at different cable anomaly locations; based on the partial discharge anomaly location, determining the probability of the preliminary partial discharge anomaly type at the partial discharge anomaly location; if its probability is the maximum probability of the preliminary partial discharge anomaly type at different cable anomaly locations, then the preliminary partial discharge anomaly type is taken as the final partial discharge anomaly type; otherwise, the partial discharge type corresponding to the second largest matching similarity is screened for verification, and this process is iterated until the final partial discharge anomaly type is determined.

7. The real-time intelligent monitoring system for the status of high-voltage power cables according to claim 1, characterized in that: The method for dynamically adjusting the reference value for partial discharge characteristic warning is as follows: Select the reference values ​​of partial discharge characteristic parameters under different load levels and different ambient temperature ranges during normal cable operation from the cable monitoring historical database, and establish a multi-condition partial discharge characteristic parameter reference matrix; Based on the real-time collected load and ambient temperature, match the corresponding reference value of partial discharge characteristic parameters from the multi-condition partial discharge characteristic parameter reference matrix. Based on the deviation between the cable's operating temperature and its rated operating temperature, and combined with the temperature sensitivity curve of the cable's insulation material, the increase ratio of the insulation aging rate under the influence of the temperature deviation is determined and used as the temperature correction coefficient. The reference value of the partial discharge characteristic parameter is then fused with the temperature correction coefficient to obtain the dynamically adjusted warning reference value for partial discharge characteristics.

8. The real-time intelligent monitoring system for the status of high-voltage power cables according to claim 1, characterized in that: The specific content of the abnormal warning judgment module is as follows: all characteristic parameters of the partial discharge signal are compared one by one with the corresponding dynamically adjusted warning reference values; if any characteristic parameter exceeds the corresponding warning reference value, the partial discharge of the power cable is determined to be in an abnormal state, and a discharge abnormality warning information is generated simultaneously; if all characteristic parameters do not exceed the warning reference value, the partial discharge of the power cable is determined to be normal, and the characteristic parameters of the partial discharge signal are stored in the cable historical operation database.

9. The real-time intelligent monitoring system for the status of high-voltage power cables according to claim 8, characterized in that: The implementation steps of the cable condition assessment module are as follows: retrieve historical partial discharge signal characteristic parameters of the power cable in the same monitoring section from the cable historical operation database, and construct a time series sequence of historical characteristic parameters; superimpose the currently collected partial discharge signal characteristic parameters onto the time series sequence of historical characteristic parameters, and calculate the rate of change and degree of deviation of the partial discharge signal characteristic parameters; determine the cable insulation health status based on the rate of change and degree of deviation of the partial discharge signal characteristic parameters.

10. The real-time intelligent monitoring system for the status of high-voltage power cables according to claim 9, characterized in that: The method for determining the health status of cable insulation is as follows: set an allowable range for the degree of deviation of characteristic parameters and an allowable threshold for the rate of change. If the degree of deviation of all partial discharge signal characteristic parameters is within the allowable range and the rate of change is lower than the allowable threshold, the cable insulation health status is determined to be normal. If the degree of deviation of a certain partial discharge signal characteristic parameter exceeds the allowable range or its rate of change exceeds the allowable threshold, the cable insulation health status is determined to be abnormal, and a power outage maintenance warning is triggered and the cable monitoring section number is pushed.

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