New energy cable fault intelligent monitoring method and system

Abstract

The invention provides a new energy cable fault intelligent monitoring method and system, and relates to the technical field of new energy cable fault intelligent monitoring, and the method comprises the steps: dividing a new energy cable into cable monitoring regions, obtaining region cable storage nodes according to cable monitoring data, and obtaining monitoring aggregation nodes; calculating an area cable abnormal coefficient of the monitoring aggregation node and a new energy cable abnormal coefficient of each new energy cable, establishing a cable abnormal sequence, sequentially obtaining node residual monitoring data after single cable monitoring data is removed, calculating the node residual abnormal coefficient, performing difference calculation of the abnormal coefficients, and after new energy cable determination, determining the new energy cable according to the difference value of the abnormal coefficients. Data extraction of the remaining new energy cables and calculation of the node remaining abnormal coefficients are sequentially carried out until the region cable abnormity judgment result is that the cable region is normal, real-time monitoring, fault early warning and abnormity positioning of the new energy cables are achieved, and the operation efficiency and safety of the new energy cables are improved.

Description

Technical Field

[0001] The present invention proposes a new energy cable fault intelligent monitoring method and system, which relate to the field of intelligent monitoring technology, and specifically to the field of new energy cable fault intelligent monitoring technology. Background Art

[0002] As a key component connecting new energy equipment with the power grid, the operating status of new energy cables directly affects the efficiency of new energy power generation and the safety and stability of the power grid. However, since new energy cables are usually laid in complex and changeable environments, such as underground, on the seabed, or exposed to severe weather conditions, they are easily affected by various factors during operation, resulting in frequent cable failures. Traditional cable fault monitoring methods mainly rely on manual inspections and regular testing, which is not only inefficient, but also difficult to detect and deal with potential faults in a timely manner. In addition, due to the particularity of new energy cables, such as high voltage, high current, and complex electrical characteristics, traditional fault monitoring methods are difficult to accurately determine the type and location of cable faults. Summary of the invention

[0003] The present invention provides a new energy cable fault intelligent monitoring method and system to solve the above problems:

[0004] The present invention proposes a new energy cable fault intelligent monitoring method and system, the monitoring method comprising:

[0005] S1. Divide the cable monitoring area for the new energy cable, obtain the cable monitoring data of the new energy cable, obtain the regional cable storage node according to the cable monitoring data, and then obtain the monitoring aggregation node;

[0006] S2. Calculate the regional cable anomaly coefficient of the monitoring aggregation node, obtain the regional cable determination result, calculate the new energy cable anomaly coefficient of each new energy cable, and obtain the new energy cable determination result;

[0007] S3. Establish cable anomaly sorting, sequentially obtain the remaining monitoring data of the nodes after removing the monitoring data of a single cable, calculate the remaining abnormality coefficient of the node, perform the difference calculation of the abnormality coefficient, and obtain the new energy cable determination information;

[0008] S4. After the new energy cable is determined, data extraction of the remaining new energy cables and calculation of the remaining abnormality coefficients of the nodes are performed in sequence until the regional cable abnormality determination result is that the cable area is normal, and then data extraction is stopped.

[0009] Furthermore, the S1 includes:

[0010] Acquire new energy cable information, divide the new energy cable into monitoring areas according to preset monitoring areas, and obtain multiple cable monitoring areas;

[0011] Mark each new energy cable in each cable monitoring area with cable information to obtain cable marking information;

[0012] Collect monitoring data of new energy cables in each cable monitoring area to obtain cable monitoring data of each new energy cable;

[0013] The cable monitoring data of all new energy cables in each cable monitoring area are stored independently to obtain a regional cable storage node;

[0014] The cable monitoring node corresponding to the regional cable storage node is the monitoring aggregation node.

[0015] Further, the S2 includes:

[0016] Calculate the regional cable anomaly coefficient of the monitoring aggregation node based on all cable monitoring data of the monitoring aggregation node;

[0017] Compare the regional cable anomaly coefficient with a preset regional anomaly threshold to obtain a regional comparison result;

[0018] Performing regional cable determination on the monitoring aggregation node according to the regional comparison result to obtain a regional cable determination result;

[0019] When the regional cable determination result is a cable regional abnormality determination, the new energy cable abnormality coefficient of each new energy cable is calculated based on the cable monitoring data of each new energy cable;

[0020] Comparing the new energy cable abnormality coefficient with a preset cable abnormality threshold to obtain a cable comparison result;

[0021] A new energy cable determination is performed on the new energy cable according to the cable comparison result to obtain a new energy cable determination result.

[0022] Further, the S3 includes:

[0023] Sort the abnormal coefficients of new energy cables in descending order to obtain the cable abnormality ranking;

[0024] The cable monitoring data of the new energy cables in the cable abnormality sorting are obtained in sequence, the cable monitoring data are extracted in the monitoring aggregation node, and the remaining monitoring data of the node is obtained;

[0025] Calculate the regional cable anomaly coefficient after removing the cable monitoring data of the new energy cable in the cable anomaly sorting according to the node remaining monitoring data, and obtain the node remaining anomaly coefficient;

[0026] The difference between the regional cable anomaly coefficient of the monitoring aggregation node and the node residual anomaly coefficient is calculated to obtain the residual anomaly difference;

[0027] Compare the remaining abnormal difference with a preset remaining threshold to obtain an abnormal difference comparison result;

[0028] According to the abnormal difference comparison result, a new energy cable determination is performed on the new energy cable corresponding to the cable monitoring data to obtain new energy cable determination information.

[0029] Further, the S4 includes:

[0030] After the new energy cable is determined, the cable monitoring data corresponding to the new energy cable determination is stored again in the monitoring aggregation node;

[0031] Extract the cable monitoring data of the next new energy cable in the cable abnormality sorting in the monitoring aggregation node to obtain the remaining monitoring data of the node;

[0032] Calculate the node's remaining anomaly coefficient until the regional cable anomaly determination result is that the cable area is normal, stop data extraction, and locate and mark the anomalies of the new energy cables corresponding to the extracted cable monitoring data.

[0033] Furthermore, the monitoring system comprises:

[0034] The aggregation monitoring module is used to divide the cable monitoring area for the new energy cable, obtain the cable monitoring data of the new energy cable, obtain the regional cable storage node according to the cable monitoring data, and then obtain the monitoring aggregation node;

[0035] The regional cable anomaly analysis module is used to calculate the regional cable anomaly coefficient of the monitoring aggregation node, obtain the regional cable determination result, calculate the new energy cable anomaly coefficient of each new energy cable, and obtain the new energy cable determination result;

[0036] The abnormality elimination analysis module is used to establish the cable abnormality ranking, sequentially obtain the remaining monitoring data of the nodes after removing the monitoring data of a single cable, calculate the remaining abnormality coefficient of the node, perform the difference calculation of the abnormality coefficient, and obtain the new energy cable determination information;

[0037] The cyclic judgment module is used to extract the data of the remaining new energy cables and calculate the remaining abnormal coefficients of the nodes in sequence after the new energy cables are judged, until the regional cable abnormality judgment result is that the cable area is normal, and then stop data extraction.

[0038] Furthermore, the aggregation monitoring module includes:

[0039] A monitoring area division module is used to obtain new energy cable information, divide the new energy cable into monitoring areas according to preset monitoring areas, and obtain multiple cable monitoring areas;

[0040] The cable marking module is used to mark the cable information of each new energy cable in each cable monitoring area and obtain the cable marking information;

[0041] The cable data monitoring module is used to collect monitoring data of the new energy cables in each cable monitoring area and obtain the cable monitoring data of each new energy cable;

[0042] An independent storage module is used to independently store the cable monitoring data of all new energy cables in each cable monitoring area to obtain a regional cable storage node;

[0043] The aggregated cable monitoring module is used for the cable monitoring node corresponding to the regional cable storage node, which is the monitoring aggregation node.

[0044] Furthermore, the regional cable anomaly analysis module includes:

[0045] A regional anomaly calculation module, used to calculate the regional cable anomaly coefficient of the monitoring aggregation node based on all cable monitoring data of the monitoring aggregation node;

[0046] Compare the regional cable anomaly coefficient with a preset regional anomaly threshold to obtain a regional comparison result;

[0047] A regional determination module, used for performing regional cable determination on the monitoring aggregation node according to the regional comparison result to obtain a regional cable determination result;

[0048] A cable anomaly calculation module, used to calculate a new energy cable anomaly coefficient of each new energy cable according to the cable monitoring data of each new energy cable when the regional cable determination result is a cable regional anomaly determination;

[0049] Comparing the new energy cable abnormality coefficient with a preset cable abnormality threshold to obtain a cable comparison result;

[0050] The cable determination module is used to determine whether the new energy cable is a new energy cable according to the cable comparison result to obtain a new energy cable determination result.

[0051] Furthermore, the abnormality elimination analysis module includes:

[0052] An abnormality sorting module is used to sort the abnormality coefficients of new energy cables in descending order to obtain the cable abnormality sorting;

[0053] The remaining monitoring module is used to sequentially obtain the cable monitoring data of the new energy cables in the cable abnormality sorting, extract the cable monitoring data in the monitoring aggregation node, and obtain the node remaining monitoring data;

[0054] A remaining abnormality calculation module is used to calculate the regional cable abnormality coefficient after removing the cable monitoring data of the new energy cable in the cable abnormality sorting according to the remaining monitoring data of the node, and obtain the node remaining abnormality coefficient;

[0055] A difference analysis module is used to calculate the difference between the regional cable anomaly coefficient of the monitoring aggregation node and the node residual anomaly coefficient to obtain the residual anomaly difference;

[0056] Compare the remaining abnormal difference with a preset remaining threshold to obtain an abnormal difference comparison result;

[0057] The difference cable determination module is used to perform new energy cable determination on the new energy cable corresponding to the cable monitoring data according to the abnormal difference comparison result, and obtain new energy cable determination information.

[0058] Furthermore, the cycle determination module includes:

[0059] A data recovery module, used for re-storing the cable monitoring data corresponding to the new energy cable determination into the monitoring aggregation node after the new energy cable determination is performed;

[0060] The sequential extraction module is used to extract the cable monitoring data of the next new energy cable in the cable anomaly sorting in the monitoring aggregation node, and obtain the remaining monitoring data of the node;

[0061] The positioning and marking module is used to calculate the remaining abnormality coefficient of the node until the regional cable abnormality judgment result is that the cable area is normal. Then, data extraction is stopped, and abnormal positioning and marking of the new energy cable corresponding to the extracted cable monitoring data are performed.

[0062] Beneficial effects of the present invention: By dividing the area and setting up monitoring aggregation nodes, abnormal areas and cables can be quickly located, thereby improving monitoring efficiency. By calculating the abnormal coefficient and difference calculation, abnormal cables can be accurately identified, reducing false alarms and missed alarms. According to the cable abnormality sorting and judgment information, targeted maintenance strategies can be formulated to give priority to cables with higher abnormalities, thereby improving maintenance efficiency and quality. At the same time, the present invention can also automatically identify abnormal cables in the area, and realize automatic, intelligent, contactless abnormal positioning of abnormal cables. Real-time monitoring and abnormality judgment can timely discover and handle potential faults of the cable system, avoiding the expansion of faults and the occurrence of safety accidents. By accurately identifying and giving priority to abnormal cables, unnecessary maintenance work and waste of resources can be reduced, thereby reducing maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 Schematic diagram of an intelligent monitoring method for new energy cable faults. DETAILED DESCRIPTION

[0064] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0065] In one embodiment of the present invention, a method and system for intelligently monitoring faults of new energy cables are provided. The monitoring method comprises:

[0066] S1. Divide the cable monitoring area for the new energy cable, obtain the cable monitoring data of the new energy cable, obtain the regional cable storage node according to the cable monitoring data, and then obtain the monitoring aggregation node;

[0067] S2. Calculate the regional cable anomaly coefficient of the monitoring aggregation node, obtain the regional cable determination result, calculate the new energy cable anomaly coefficient of each new energy cable, and obtain the new energy cable determination result;

[0068] S3. Establish cable anomaly sorting, sequentially obtain the remaining monitoring data of the nodes after removing the monitoring data of a single cable, calculate the remaining abnormality coefficient of the node, perform the difference calculation of the abnormality coefficient, and obtain the new energy cable determination information;

[0069] S4. After the new energy cable is determined, the data of the remaining new energy cables and the calculation of the remaining abnormal coefficients of the nodes are performed in sequence until the regional cable abnormality determination result is that the cable area is normal, and then the data extraction is stopped. Figure 1 shown.

[0070] The working principle of the above technical solution is: divide the new energy cable system into regions, each region represents a cable monitoring area, which can narrow the monitoring scope and improve the monitoring efficiency. Real-time monitoring data of new energy cables, such as current, voltage, temperature, etc., are obtained through sensors and other equipment. According to the obtained cable monitoring data, the cable storage nodes in each region are determined. Through further data processing, monitoring aggregation nodes are obtained, which represent the overall characteristics of the cable status in each region. The regional cable abnormality coefficient of the monitoring aggregation node is calculated to evaluate whether the cable status in each region is normal. At the same time, the abnormality coefficient of each new energy cable is also calculated to obtain more detailed cable status information. Cable abnormality sorting is established, and cables are sorted according to the size of the abnormality coefficient so that abnormal cables can be obtained in sequence in an automated and intelligent manner. By removing the monitoring data of a single cable, the node residual abnormality coefficients of the remaining cables are calculated, and the difference of the abnormality coefficients is calculated. This step helps to identify which cables have a greater impact on the overall abnormal state, and identify and process them. According to the difference calculation results, the determination information of the new energy cable is obtained, that is, which cables may have abnormalities. After the new energy cable is determined, data extraction is performed on the remaining new energy cables, and the node residual abnormality coefficients are calculated. This process is repeated until the cable area abnormality is judged to be normal, and then the data extraction is stopped. This allows all cable abnormalities to be properly handled and the entire cable system to be in normal condition.

[0071] The technical effects of the above technical scheme are as follows: through the division of regions and the setting of monitoring aggregation nodes, abnormal regions and cables can be quickly located, thereby improving monitoring efficiency. By calculating the abnormal coefficient and difference calculation, abnormal cables can be accurately identified, reducing false alarms and missed alarms. According to the cable abnormality sorting and judgment information, targeted maintenance strategies can be formulated to give priority to cables with higher abnormalities, thereby improving maintenance efficiency and quality. At the same time, the present invention can also automatically identify abnormal cables in the area, and realize automatic, intelligent, contactless abnormal positioning of abnormal cables. Real-time monitoring and abnormality judgment can timely discover and handle potential faults of the cable system, avoiding the expansion of faults and the occurrence of safety accidents. By accurately identifying and giving priority to abnormal cables, unnecessary maintenance work and waste of resources can be reduced, thereby reducing maintenance costs.

[0072] In one embodiment of the present invention, the S1 includes:

[0073] Acquire new energy cable information, divide the new energy cable into monitoring areas according to preset monitoring areas, and obtain multiple cable monitoring areas;

[0074] Mark the cable information of each new energy cable in each cable monitoring area to obtain the cable marking information;

[0075] Collect monitoring data of new energy cables in each cable monitoring area to obtain cable monitoring data of each new energy cable;

[0076] The cable monitoring data of all new energy cables in each cable monitoring area are stored independently to obtain a regional cable storage node;

[0077] The cable monitoring node corresponding to the regional cable storage node is the monitoring aggregation node.

[0078] The working principle of the above technical solution is: obtain basic information of new energy cables, such as cable model, length, location, etc. from the database or user input. According to the preset monitoring area rules, the monitoring area of ​​new energy cables is divided. The division is based on factors such as the physical layout, importance and possible failure risk of the cable. For each new energy cable in each cable monitoring area, the system will mark the information. This includes the unique identification, location information, and area of ​​the cable. Deploy sensors or other monitoring equipment in each cable monitoring area to collect monitoring data of new energy cables in real time. These data may include key parameters such as current, voltage, temperature, and humidity. The collected cable monitoring data will be stored independently in the regional cable storage node of each cable monitoring area. This ensures the integrity and independence of the data. The cable monitoring node corresponding to each regional cable storage node is determined as a monitoring aggregation node. These nodes are the focus of data processing and analysis and represent the overall status of new energy cables in their respective monitoring areas.

[0079] The technical effect of the above technical solution is: through the division of monitoring areas and independent storage, the system can more efficiently process and analyze the monitoring data of new energy cables and reduce data processing delays and errors. Independent data storage and labeling ensure the integrity and accuracy of the data and avoid the risk of data confusion or loss. Through reasonable monitoring area division and data processing strategy, the system can more effectively utilize computing resources and storage space and reduce operating costs. Real-time monitoring and data analysis can promptly detect abnormal conditions of new energy cables, improve fault response speed and accuracy, and reduce the impact of faults on power grid operation. Through reasonable monitoring area division, independent data storage and real-time monitoring and analysis, the monitoring efficiency, data reliability and fault response speed of new energy cables are improved, providing a strong guarantee for the safe and stable operation of the power grid.

[0080] In one embodiment of the present invention, S2 includes:

[0081] Calculate the regional cable anomaly coefficient of the monitoring aggregation node based on all cable monitoring data of the monitoring aggregation node;

[0082] The calculation formula of the cable anomaly coefficient in the area is:

[0083]

[0084] Among them, QDY is the regional cable anomaly coefficient, q is the total number of new energy cables in the monitoring aggregation node, z is the number of monitoring types of monitoring data for each cable, and D sli is the actual monitoring data of the lth monitoring type of the ith new energy cable, D yli is the monitoring data threshold of the lth monitoring type of the i-th new energy cable, D max is the maximum value of the sum of the average values ​​of all new energy cables;

[0085] Compare the regional cable anomaly coefficient with a preset regional anomaly threshold to obtain a regional comparison result;

[0086] According to the regional comparison result, the monitoring aggregation node is subjected to regional cable judgment to obtain a regional cable judgment result; the regional cable judgment result includes a cable regional abnormal judgment and a cable regional normal judgment; when the regional cable abnormality coefficient is greater than a preset regional abnormality threshold, a cable regional abnormality judgment is performed, otherwise the cable regional normal judgment is performed.

[0087] When the regional cable determination result is a cable regional abnormality determination, the new energy cable abnormality coefficient of each new energy cable is calculated based on the cable monitoring data of each new energy cable;

[0088] The calculation formula of the abnormal coefficient of the new energy cable is:

[0089]

[0090] Among them, XDL is the abnormal coefficient of new energy cables, z is the number of monitoring types of monitoring data for each cable, and D slx is the actual monitoring data of the first monitoring type of new energy cables, D ylx is the monitoring data threshold of the first monitoring type of new energy cable, QDY is the regional cable anomaly coefficient, QYY is the preset regional anomaly threshold, Q XDL It is the preset weight data of new energy cables;

[0091] Comparing the new energy cable abnormality coefficient with a preset cable abnormality threshold to obtain a cable comparison result;

[0092] According to the cable comparison result, the new energy cable is judged as a new energy cable to obtain a new energy cable judgment result. The new energy cable judgment result includes a new energy cable abnormality judgment and a new energy cable normal judgment; when the new energy cable abnormality coefficient is greater than a preset cable abnormality threshold, the new energy cable abnormality judgment is performed, otherwise the new energy cable is judged as normal.

[0093] The working principle of the above technical solution is: according to the monitoring data of all new energy cables collected by the monitoring aggregation node (that is, the node representing a certain cable monitoring area), a regional cable anomaly coefficient is calculated. This coefficient reflects the overall abnormality of the new energy cables in the area. Compare the calculated regional cable anomaly coefficient with the preset regional anomaly threshold. If the regional cable anomaly coefficient is greater than the preset threshold, it is determined that the cable area represented by the monitoring aggregation node is abnormal; if it is less than or equal to the preset threshold, it is determined to be normal. When a cable area is determined to be abnormal, the system will further analyze the monitoring data of each new energy cable in the area. For each new energy cable, the system will calculate its new energy cable anomaly coefficient and compare it with the preset cable anomaly threshold. If the new energy cable anomaly coefficient is greater than the preset threshold, it is determined that the new energy cable is abnormal; if it is less than or equal to the preset threshold, it is determined to be normal.

[0094] The technical effect of the above technical solution is: by first conducting an overall evaluation of the monitoring aggregation node (i.e., the cable area), and then conducting a detailed analysis of the individual new energy cables in the abnormal area, potential abnormal cables can be more effectively identified and the accuracy of detection can be improved. The abnormal difference of each cable relative to the average monitoring data of all monitoring types of all cables in the area can be calculated, and the square sum of the deviations of all new energy cable monitoring data from the average value can be calculated. This step reflects the degree of data dispersion, that is, the deviation of the data point from the average value. If the data point deviates greatly from the average value, it means that the cable status in the area may be abnormal. max It is used for normalization processing to ensure that the regional cable anomaly coefficient will not increase infinitely due to the increase in the number of cables or the increase in monitoring data. N is the number of cables, D max It is the maximum value among all types of average values ​​of monitoring data, and jointly determines the upper limit of the regional cable anomaly coefficient; the regional cable anomaly coefficient is obtained by calculating the ratio of the sum of squares of deviations to the normalization factor. The larger this coefficient is, the more unstable the cable status in the area is, and there may be a greater risk of failure; in the regional cable determination stage, if a cable area is judged to be normal, there is no need to further analyze the individual cables in the area, thus saving computing resources and time. Once a cable area or a single new energy cable is judged to be abnormal, the system can immediately trigger an alarm or notify relevant personnel to handle it, thereby responding quickly and reducing potential safety hazards. This technology can provide strong support for the intelligent operation and maintenance of new energy cables. By real-time monitoring and analysis of cable data, the system can automatically determine the health of the cable. As an important part of the power grid, the health of new energy cables directly affects the stability and security of the power grid. Through the formula The preliminary anomaly coefficient of the new energy cable can be calculated by The abnormality ratio coefficient of energy cables relative to regional abnormalities can be calculated; through real-time monitoring and abnormality judgment of new energy cables through this technology, potential problems can be discovered and dealt with in a timely manner, thereby improving the overall stability and security of the power grid.

[0095] In one embodiment of the present invention, S3 includes:

[0096] Sort the abnormal coefficients of new energy cables in descending order to obtain the cable abnormality ranking;

[0097] The cable monitoring data of the new energy cables in the cable abnormality sorting are obtained in sequence, the cable monitoring data are extracted in the monitoring aggregation node, and the remaining monitoring data of the node is obtained;

[0098] Calculate the regional cable anomaly coefficient after removing the cable monitoring data of the new energy cable in the cable anomaly sorting according to the node remaining monitoring data, and obtain the node remaining anomaly coefficient;

[0099] The difference between the regional cable anomaly coefficient of the monitoring aggregation node and the node residual anomaly coefficient is calculated to obtain the residual anomaly difference;

[0100] Compare the remaining abnormal difference with a preset remaining threshold to obtain an abnormal difference comparison result;

[0101] According to the abnormal difference comparison result, the new energy cable corresponding to the cable monitoring data is judged as a new energy cable to obtain new energy cable judgment information. When the remaining abnormal difference is greater than the preset remaining threshold, the new energy cable corresponding to the extracted cable monitoring data is judged as a new energy cable abnormality, otherwise, the new energy cable is judged as normal.

[0102] The working principle of the above technical solution is: according to the abnormal coefficient of the new energy cable, it is sorted from large to small to generate a cable abnormal sorting list. This list reflects the priority of the cable abnormality, and the cables with higher abnormal coefficients are ranked higher. The cable monitoring data of the new energy cables are obtained from the cable abnormal sorting list in sequence. In the monitoring aggregation node, the system extracts the monitoring data corresponding to these cables and retains the monitoring data of the remaining cables, that is, the remaining monitoring data of the node. Using the remaining monitoring data of the node (that is, after removing the monitoring data of a single cable in the abnormal sorting), the system recalculates the regional cable abnormality coefficient of the monitoring aggregation node to obtain the node residual abnormality coefficient. This coefficient reflects the degree of abnormality of the remaining cable area after removing some abnormal cables. The system calculates the difference between the original regional cable abnormality coefficient and the node residual abnormality coefficient to obtain the residual abnormal difference. This difference reflects the impact of the extracted abnormal cable on the overall regional abnormality. Compare the residual abnormal difference with the preset residual threshold. If the remaining abnormal difference is greater than the preset remaining threshold, it means that the new energy cable corresponding to the extracted cable monitoring data has a significant impact on the abnormality level of the overall area, so it is judged as an abnormal cable; conversely, if the remaining abnormal difference is less than or equal to the preset remaining threshold, it is judged as a normal cable.

[0103] The technical effect of the above technical solution is: through the method of sorting and gradual elimination, the system can more accurately identify the new energy cables that have a significant impact on the degree of abnormality in the overall area, and improve the accuracy of abnormality detection. According to the size of the remaining abnormal difference, the system can formulate a more reasonable abnormality handling strategy. Cables with large remaining abnormal differences can be processed first to reduce the impact on the operation of the power grid. Through the method of gradual elimination, the system can more efficiently use existing data for analysis and judgment without adding additional computing resources. This method not only takes into account the degree of abnormality of a single cable, but also takes into account the mutual influence between cables, thereby enhancing the robustness and reliability of the system. This technology provides strong data support for the intelligent operation and maintenance of new energy cables. Operation and maintenance personnel can formulate more scientific operation and maintenance plans based on the judgment information provided by the system to improve operation and maintenance efficiency and the safety of the power grid.

[0104] In one embodiment of the present invention, the S4 includes:

[0105] After the new energy cable is determined, the cable monitoring data corresponding to the new energy cable determination is stored again in the monitoring aggregation node; the cable monitoring data of the next new energy cable in the cable anomaly sorting is extracted in the monitoring aggregation node to obtain the remaining monitoring data of the node; the remaining anomaly coefficient of the node is calculated until the regional cable anomaly determination result is that the cable area is normal, then the data extraction is stopped, and the new energy cable corresponding to the extracted cable monitoring data is located and marked for anomalies.

[0106] The calculation method of the node residual anomaly coefficient is the calculation result of the calculation data used in the calculation formula of the regional cable anomaly coefficient minus the extracted data.

[0107] The working principle of the above technical solution is as follows: after completing the determination of the new energy cable, the system will re-store the new energy cable monitoring data corresponding to the determination result into the monitoring aggregation node. The integrity and traceability of the data are ensured. According to the cable abnormality sorting list, the cable monitoring data of the next new energy cable will continue to be extracted. During the extraction process, the system will obtain the monitoring data corresponding to the cable from the monitoring aggregation node again, and calculate the remaining monitoring data of the node after removing the cable monitoring data. Using the updated node remaining monitoring data, the system will recalculate the regional cable anomaly coefficient, that is, the node remaining anomaly coefficient. This coefficient reflects the degree of abnormality of the remaining cable area after the abnormal cables are gradually excluded. The system will compare the new node remaining anomaly coefficient with the preset regional anomaly threshold to make a regional cable determination. If the determination result is that the cable area is normal, that is, the node remaining anomaly coefficient is less than or equal to the preset threshold, the data extraction process is stopped. After stopping the data extraction, the system will locate and mark the abnormal monitoring data of the new energy cable that was previously extracted and determined to be abnormal. Clarify the specific location and abnormal type of the abnormal cable.

[0108] The technical effect of the above technical solution is: through the method of gradual elimination and recalculation, the system can more accurately locate the position and abnormal type of abnormal cables, and improve the accuracy and efficiency of abnormal processing. In the process of gradual extraction and analysis, the system only extracts and calculates data when necessary, thereby avoiding unnecessary waste of resources. By continuously updating the node remaining monitoring data and recalculating the node remaining abnormality coefficient, the system can more accurately reflect the degree of abnormality in the cable area and improve the accuracy of judgment. Abnormal positioning and marking provide detailed abnormal information for operation and maintenance personnel, enabling them to formulate operation and maintenance plans more scientifically, improve operation and maintenance efficiency and the safety of the power grid. This method allows the system to gradually eliminate abnormal cables according to actual needs, rather than processing all cables at once, thereby enhancing the flexibility and adaptability of the system.

[0109] In one embodiment of the present invention, the monitoring system comprises:

[0110] The aggregation monitoring module is used to divide the cable monitoring area for the new energy cable, obtain the cable monitoring data of the new energy cable, obtain the regional cable storage node according to the cable monitoring data, and then obtain the monitoring aggregation node;

[0111] The regional cable anomaly analysis module is used to calculate the regional cable anomaly coefficient of the monitoring aggregation node, obtain the regional cable determination result, calculate the new energy cable anomaly coefficient of each new energy cable, and obtain the new energy cable determination result;

[0112] The abnormality elimination analysis module is used to establish the cable abnormality ranking, sequentially obtain the remaining monitoring data of the nodes after removing the monitoring data of a single cable, calculate the remaining abnormality coefficient of the node, perform the difference calculation of the abnormality coefficient, and obtain the new energy cable determination information;

[0113] The cyclic judgment module is used to extract the data of the remaining new energy cables and calculate the remaining abnormal coefficients of the nodes in sequence after the new energy cables are judged, until the regional cable abnormality judgment result is that the cable area is normal, and then stop data extraction.

[0114] The working principle of the above technical solution is: divide the new energy cable system into regions, each region represents a cable monitoring area, which can narrow the monitoring scope and improve the monitoring efficiency. Real-time monitoring data of new energy cables, such as current, voltage, temperature, etc., are obtained through sensors and other equipment. According to the obtained cable monitoring data, the cable storage nodes in each region are determined. Through further data processing, monitoring aggregation nodes are obtained, which represent the overall characteristics of the cable status in each region. The regional cable abnormality coefficient of the monitoring aggregation node is calculated to evaluate whether the cable status in each region is normal. At the same time, the abnormality coefficient of each new energy cable is also calculated to obtain more detailed cable status information. Cable abnormality sorting is established, and cables are sorted according to the size of the abnormality coefficient so that abnormal cables can be obtained in sequence in an automated and intelligent manner. By removing the monitoring data of a single cable, the node residual abnormality coefficients of the remaining cables are calculated, and the difference of the abnormality coefficients is calculated. This step helps to identify which cables have a greater impact on the overall abnormal state, and identify and process them. According to the difference calculation results, the determination information of the new energy cable is obtained, that is, which cables may have abnormalities. After the new energy cable is determined, data extraction is performed on the remaining new energy cables, and the node residual abnormality coefficients are calculated. This process is repeated until the cable area abnormality is judged to be normal, and then the data extraction is stopped. This allows all cable abnormalities to be properly handled and the entire cable system to be in normal condition.

[0115] The technical effects of the above technical scheme are as follows: through the division of regions and the setting of monitoring aggregation nodes, abnormal regions and cables can be quickly located, thereby improving monitoring efficiency. By calculating the abnormal coefficient and difference calculation, abnormal cables can be accurately identified, reducing false alarms and missed alarms. According to the cable abnormality sorting and judgment information, targeted maintenance strategies can be formulated to give priority to cables with higher abnormalities, thereby improving maintenance efficiency and quality. At the same time, the present invention can also automatically identify abnormal cables in the area, and realize automatic, intelligent, contactless abnormal positioning of abnormal cables. Real-time monitoring and abnormality judgment can timely discover and handle potential faults of the cable system, avoiding the expansion of faults and the occurrence of safety accidents. By accurately identifying and giving priority to abnormal cables, unnecessary maintenance work and waste of resources can be reduced, thereby reducing maintenance costs.

[0116] In one embodiment of the present invention, the aggregation monitoring module includes:

[0117] A monitoring area division module is used to obtain new energy cable information, divide the new energy cable into monitoring areas according to preset monitoring areas, and obtain multiple cable monitoring areas;

[0118] The cable marking module is used to mark the cable information of each new energy cable in each cable monitoring area and obtain the cable marking information;

[0119] The cable data monitoring module is used to collect monitoring data of the new energy cables in each cable monitoring area and obtain the cable monitoring data of each new energy cable;

[0120] An independent storage module is used to independently store the cable monitoring data of all new energy cables in each cable monitoring area to obtain a regional cable storage node;

[0121] The aggregated cable monitoring module is used for the cable monitoring node corresponding to the regional cable storage node, which is the monitoring aggregation node.

[0122] The working principle of the above technical solution is: obtain basic information of new energy cables, such as cable model, length, location, etc. from the database or user input. According to the preset monitoring area rules, the monitoring area of ​​new energy cables is divided. The division is based on factors such as the physical layout, importance and possible failure risk of the cable. For each new energy cable in each cable monitoring area, the system will mark the information. This includes the unique identification, location information, and area of ​​the cable. Deploy sensors or other monitoring equipment in each cable monitoring area to collect monitoring data of new energy cables in real time. These data may include key parameters such as current, voltage, temperature, and humidity. The collected cable monitoring data will be stored independently in the regional cable storage node of each cable monitoring area. This ensures the integrity and independence of the data. The cable monitoring node corresponding to each regional cable storage node is determined as a monitoring aggregation node. These nodes are the focus of data processing and analysis and represent the overall status of new energy cables in their respective monitoring areas.

[0123] The technical effect of the above technical solution is: through the division of monitoring areas and independent storage, the system can more efficiently process and analyze the monitoring data of new energy cables and reduce data processing delays and errors. Independent data storage and labeling ensure the integrity and accuracy of the data and avoid the risk of data confusion or loss. Through reasonable monitoring area division and data processing strategy, the system can more effectively utilize computing resources and storage space and reduce operating costs. Real-time monitoring and data analysis can promptly detect abnormal conditions of new energy cables, improve fault response speed and accuracy, and reduce the impact of faults on power grid operation. Through reasonable monitoring area division, independent data storage and real-time monitoring and analysis, the monitoring efficiency, data reliability and fault response speed of new energy cables are improved, providing a strong guarantee for the safe and stable operation of the power grid.

[0124] In one embodiment of the present invention, the regional cable anomaly analysis module includes:

[0125] A regional anomaly calculation module, used to calculate the regional cable anomaly coefficient of the monitoring aggregation node based on all cable monitoring data of the monitoring aggregation node;

[0126] The calculation formula of the cable anomaly coefficient in the area is:

[0127]

[0128] Among them, QDY is the regional cable anomaly coefficient, q is the total number of new energy cables in the monitoring aggregation node, z is the number of monitoring types of monitoring data for each cable, and D sli is the actual monitoring data of the lth monitoring type of the ith new energy cable, D yli is the monitoring data threshold of the lth monitoring type of the i-th new energy cable, Dmax is the maximum value of the sum of the average values ​​of all new energy cables;

[0129] Compare the regional cable anomaly coefficient with a preset regional anomaly threshold to obtain a regional comparison result;

[0130] The regional judgment module is used to perform regional cable judgment on the monitoring aggregation node according to the regional comparison result to obtain a regional cable judgment result; the regional cable judgment result includes a cable regional abnormal judgment and a cable regional normal judgment; when the regional cable abnormality coefficient is greater than a preset regional abnormality threshold, a cable regional abnormality judgment is performed, otherwise the cable regional normal judgment is performed.

[0131] A cable anomaly calculation module, used to calculate a new energy cable anomaly coefficient of each new energy cable according to the cable monitoring data of each new energy cable when the regional cable determination result is a cable regional anomaly determination;

[0132] The calculation formula of the abnormal coefficient of the new energy cable is:

[0133]

[0134] Among them, XDL is the abnormal coefficient of new energy cables, z is the number of monitoring types of monitoring data for each cable, and D slx is the actual monitoring data of the first monitoring type of new energy cables, D ylx is the monitoring data threshold of the first monitoring type of new energy cable, QDY is the regional cable anomaly coefficient, QYY is the preset regional anomaly threshold, Q XDL It is the preset weight data of new energy cables;

[0135] Comparing the new energy cable abnormality coefficient with a preset cable abnormality threshold to obtain a cable comparison result;

[0136] The cable determination module is used to perform a new energy cable determination on the new energy cable according to the cable comparison result to obtain a new energy cable determination result. The new energy cable determination result includes a new energy cable abnormal determination and a new energy cable normal determination; when the new energy cable abnormal coefficient is greater than a preset cable abnormal threshold, a new energy cable abnormal determination is performed, otherwise, a new energy cable normal determination is performed.

[0137] The working principle of the above technical solution is: according to the monitoring data of all new energy cables collected by the monitoring aggregation node (that is, the node representing a certain cable monitoring area), a regional cable anomaly coefficient is calculated. This coefficient reflects the overall abnormality of the new energy cables in the area. Compare the calculated regional cable anomaly coefficient with the preset regional anomaly threshold. If the regional cable anomaly coefficient is greater than the preset threshold, it is determined that the cable area represented by the monitoring aggregation node is abnormal; if it is less than or equal to the preset threshold, it is determined to be normal. When a cable area is determined to be abnormal, the system will further analyze the monitoring data of each new energy cable in the area. For each new energy cable, the system will calculate its new energy cable anomaly coefficient and compare it with the preset cable anomaly threshold. If the new energy cable anomaly coefficient is greater than the preset threshold, it is determined that the new energy cable is abnormal; if it is less than or equal to the preset threshold, it is determined to be normal.

[0138] The technical effect of the above technical solution is: by first conducting an overall evaluation of the monitoring aggregation node (i.e., the cable area), and then conducting a detailed analysis of the individual new energy cables in the abnormal area, potential abnormal cables can be more effectively identified and the accuracy of detection can be improved. In the regional cable determination stage, if a cable area is determined to be normal, there is no need to further analyze the individual cables in the area, thereby saving computing resources and time. Once a cable area or a single new energy cable is determined to be abnormal, the system can immediately trigger an alarm or notify relevant personnel to handle it, thereby quickly responding and reducing potential safety hazards. This technology can provide strong support for the intelligent operation and maintenance of new energy cables. By real-time monitoring and analysis of cable data, the system can automatically determine the health of the cable. As an important part of the power grid, the health of new energy cables directly affects the stability and safety of the power grid. Through real-time monitoring and abnormal determination of new energy cables by this technology, potential problems can be discovered and handled in a timely manner, thereby improving the overall stability and safety of the power grid.

[0139] In one embodiment of the present invention, the abnormality elimination analysis module includes:

[0140] An abnormality sorting module is used to sort the abnormality coefficients of new energy cables in descending order to obtain the cable abnormality sorting;

[0141] The remaining monitoring module is used to sequentially obtain the cable monitoring data of the new energy cables in the cable abnormality sorting, extract the cable monitoring data in the monitoring aggregation node, and obtain the node remaining monitoring data;

[0142] A remaining abnormality calculation module is used to calculate the regional cable abnormality coefficient after removing the cable monitoring data of the new energy cable in the cable abnormality sorting according to the remaining monitoring data of the node, and obtain the node remaining abnormality coefficient;

[0143] A difference analysis module is used to calculate the difference between the regional cable anomaly coefficient of the monitoring aggregation node and the node residual anomaly coefficient to obtain the residual anomaly difference;

[0144] Compare the remaining abnormal difference with a preset remaining threshold to obtain an abnormal difference comparison result;

[0145] The difference cable determination module is used to determine the new energy cable corresponding to the cable monitoring data according to the abnormal difference comparison result, and obtain the new energy cable determination information. When the remaining abnormal difference is greater than the preset remaining threshold, the new energy cable corresponding to the extracted cable monitoring data is determined to be abnormal, otherwise it is determined to be normal.

[0146] The working principle of the above technical solution is: according to the abnormal coefficient of the new energy cable, it is sorted from large to small to generate a cable abnormal sorting list. This list reflects the priority of the cable abnormality, and the cables with higher abnormal coefficients are ranked higher. The cable monitoring data of the new energy cables are obtained from the cable abnormal sorting list in sequence. In the monitoring aggregation node, the system extracts the monitoring data corresponding to these cables and retains the monitoring data of the remaining cables, that is, the remaining monitoring data of the node. Using the remaining monitoring data of the node (that is, after removing the monitoring data of a single cable in the abnormal sorting), the system recalculates the regional cable abnormality coefficient of the monitoring aggregation node to obtain the node residual abnormality coefficient. This coefficient reflects the degree of abnormality of the remaining cable area after removing some abnormal cables. The system calculates the difference between the original regional cable abnormality coefficient and the node residual abnormality coefficient to obtain the residual abnormal difference. This difference reflects the impact of the extracted abnormal cable on the overall regional abnormality. Compare the residual abnormal difference with the preset residual threshold. If the remaining abnormal difference is greater than the preset remaining threshold, it means that the new energy cable corresponding to the extracted cable monitoring data has a significant impact on the abnormality level of the overall area, so it is judged as an abnormal cable; conversely, if the remaining abnormal difference is less than or equal to the preset remaining threshold, it is judged as a normal cable.

[0147] The technical effect of the above technical solution is: through the method of sorting and gradual elimination, the system can more accurately identify the new energy cables that have a significant impact on the degree of abnormality in the overall area, and improve the accuracy of abnormality detection. According to the size of the remaining abnormal difference, the system can formulate a more reasonable abnormality handling strategy. Cables with large remaining abnormal differences can be processed first to reduce the impact on the operation of the power grid. Through the method of gradual elimination, the system can more efficiently use existing data for analysis and judgment without adding additional computing resources. This method not only takes into account the degree of abnormality of a single cable, but also takes into account the mutual influence between cables, thereby enhancing the robustness and reliability of the system. This technology provides strong data support for the intelligent operation and maintenance of new energy cables. Operation and maintenance personnel can formulate more scientific operation and maintenance plans based on the judgment information provided by the system to improve operation and maintenance efficiency and the safety of the power grid.

[0148] In one embodiment of the present invention, the cycle determination module includes:

[0149] A data recovery module, used for re-storing the cable monitoring data corresponding to the new energy cable determination into the monitoring aggregation node after the new energy cable determination is performed;

[0150] The sequential extraction module is used to extract the cable monitoring data of the next new energy cable in the cable anomaly sorting in the monitoring aggregation node, and obtain the remaining monitoring data of the node;

[0151] The positioning and marking module is used to calculate the remaining abnormality coefficient of the node until the regional cable abnormality judgment result is that the cable area is normal. Then, data extraction is stopped, and abnormal positioning and marking of the new energy cable corresponding to the extracted cable monitoring data are performed.

[0152] The working principle of the above technical solution is as follows: after completing the determination of the new energy cable, the system will re-store the new energy cable monitoring data corresponding to the determination result into the monitoring aggregation node. The integrity and traceability of the data are ensured. According to the cable abnormality sorting list, the cable monitoring data of the next new energy cable will continue to be extracted. During the extraction process, the system will obtain the monitoring data corresponding to the cable from the monitoring aggregation node again, and calculate the remaining monitoring data of the node after removing the cable monitoring data. Using the updated node remaining monitoring data, the system will recalculate the regional cable anomaly coefficient, that is, the node remaining anomaly coefficient. This coefficient reflects the degree of abnormality of the remaining cable area after the abnormal cables are gradually excluded. The system will compare the new node remaining anomaly coefficient with the preset regional anomaly threshold to make a regional cable determination. If the determination result is that the cable area is normal, that is, the node remaining anomaly coefficient is less than or equal to the preset threshold, the data extraction process is stopped. After stopping the data extraction, the system will locate and mark the abnormal monitoring data of the new energy cable that was previously extracted and determined to be abnormal. Clarify the specific location and abnormal type of the abnormal cable.

[0153] The technical effect of the above technical solution is: through the method of gradual elimination and recalculation, the system can more accurately locate the position and abnormal type of abnormal cables, and improve the accuracy and efficiency of abnormal processing. In the process of gradual extraction and analysis, the system only extracts and calculates data when necessary, thereby avoiding unnecessary waste of resources. By continuously updating the node remaining monitoring data and recalculating the node remaining abnormality coefficient, the system can more accurately reflect the degree of abnormality in the cable area and improve the accuracy of judgment. Abnormal positioning and marking provide detailed abnormal information for operation and maintenance personnel, enabling them to formulate operation and maintenance plans more scientifically, improve operation and maintenance efficiency and the safety of the power grid. This method allows the system to gradually eliminate abnormal cables according to actual needs, rather than processing all cables at once, thereby enhancing the flexibility and adaptability of the system.

[0154] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A new energy cable fault intelligent monitoring method, characterized in that: The monitoring method comprises: S1. Divide the cable monitoring area for the new energy cable, obtain the cable monitoring data of the new energy cable, obtain the regional cable storage node according to the cable monitoring data, and then obtain the monitoring aggregation node; S2. Calculate the regional cable anomaly coefficient of the monitoring aggregation node, obtain the regional cable determination result, calculate the new energy cable anomaly coefficient of each new energy cable, and obtain the new energy cable determination result; S3. Establish cable anomaly sorting, sequentially obtain the remaining monitoring data of the nodes after removing the monitoring data of a single cable, calculate the remaining abnormality coefficient of the node, perform the difference calculation of the abnormality coefficient, and obtain the new energy cable determination information; S4. After the new energy cable is determined, data extraction of the remaining new energy cables and calculation of the remaining abnormality coefficients of the nodes are performed in sequence until the regional cable abnormality determination result is that the cable area is normal, and then data extraction is stopped.

2. According to claim 1, a new energy cable fault intelligent monitoring method is characterized in that: The S1 includes: Acquire new energy cable information, divide the new energy cable into monitoring areas according to preset monitoring areas, and obtain multiple cable monitoring areas; Mark each new energy cable in each cable monitoring area with cable information to obtain cable marking information; Collect monitoring data of new energy cables in each cable monitoring area to obtain cable monitoring data of each new energy cable; The cable monitoring data of all new energy cables in each cable monitoring area are stored independently to obtain a regional cable storage node; The cable monitoring node corresponding to the regional cable storage node is the monitoring aggregation node.

3. According to claim 1, a new energy cable fault intelligent monitoring method is characterized in that: The S2 includes: Calculate the regional cable anomaly coefficient of the monitoring aggregation node based on all cable monitoring data of the monitoring aggregation node; Compare the regional cable anomaly coefficient with a preset regional anomaly threshold to obtain a regional comparison result; Performing regional cable determination on the monitoring aggregation node according to the regional comparison result to obtain a regional cable determination result; When the regional cable determination result is a cable regional abnormality determination, the new energy cable abnormality coefficient of each new energy cable is calculated based on the cable monitoring data of each new energy cable; Comparing the new energy cable abnormality coefficient with a preset cable abnormality threshold to obtain a cable comparison result; A new energy cable determination is performed on the new energy cable according to the cable comparison result to obtain a new energy cable determination result.

4. According to claim 1, a new energy cable fault intelligent monitoring method is characterized in that: The S3 includes: Sort the abnormal coefficients of new energy cables in descending order to obtain the cable abnormality ranking; The cable monitoring data of the new energy cables in the cable abnormality sorting are obtained in sequence, the cable monitoring data are extracted in the monitoring aggregation node, and the remaining monitoring data of the node is obtained; Calculate the regional cable anomaly coefficient after removing the cable monitoring data of the new energy cable in the cable anomaly sorting according to the node remaining monitoring data, and obtain the node remaining anomaly coefficient; The difference between the regional cable anomaly coefficient of the monitoring aggregation node and the node residual anomaly coefficient is calculated to obtain the residual anomaly difference; Compare the remaining abnormal difference with a preset remaining threshold to obtain an abnormal difference comparison result; According to the abnormal difference comparison result, a new energy cable determination is performed on the new energy cable corresponding to the cable monitoring data to obtain new energy cable determination information.

5. According to claim 1, a new energy cable fault intelligent monitoring method is characterized in that: The S4 includes: After the new energy cable is determined, the cable monitoring data corresponding to the new energy cable determination is stored again in the monitoring aggregation node; Extract the cable monitoring data of the next new energy cable in the cable abnormality sorting in the monitoring aggregation node to obtain the remaining monitoring data of the node; Calculate the node's remaining anomaly coefficient until the regional cable anomaly determination result is that the cable area is normal, stop data extraction, and locate and mark the anomalies of the new energy cables corresponding to the extracted cable monitoring data.

6. A new energy cable fault intelligent monitoring system, characterized in that: The monitoring system comprises: The aggregation monitoring module is used to divide the cable monitoring area for the new energy cable, obtain the cable monitoring data of the new energy cable, obtain the regional cable storage node according to the cable monitoring data, and then obtain the monitoring aggregation node; The regional cable anomaly analysis module is used to calculate the regional cable anomaly coefficient of the monitoring aggregation node, obtain the regional cable determination result, calculate the new energy cable anomaly coefficient of each new energy cable, and obtain the new energy cable determination result; The abnormality elimination analysis module is used to establish the cable abnormality ranking, sequentially obtain the remaining monitoring data of the nodes after removing the monitoring data of a single cable, calculate the remaining abnormality coefficient of the node, perform the difference calculation of the abnormality coefficient, and obtain the new energy cable determination information; The cyclic judgment module is used to extract the data of the remaining new energy cables and calculate the remaining abnormal coefficients of the nodes in sequence after the new energy cables are judged, until the regional cable abnormality judgment result is that the cable area is normal, and then stop data extraction.

7. According to claim 6, a new energy cable fault intelligent monitoring system is characterized in that: The aggregation monitoring module includes: A monitoring area division module is used to obtain new energy cable information, divide the new energy cable into monitoring areas according to preset monitoring areas, and obtain multiple cable monitoring areas; The cable marking module is used to mark the cable information of each new energy cable in each cable monitoring area and obtain the cable marking information; The cable data monitoring module is used to collect monitoring data of the new energy cables in each cable monitoring area and obtain the cable monitoring data of each new energy cable; An independent storage module is used to independently store the cable monitoring data of all new energy cables in each cable monitoring area to obtain a regional cable storage node; The aggregated cable monitoring module is used for the cable monitoring node corresponding to the regional cable storage node, which is the monitoring aggregation node.

8. According to claim 6, a new energy cable fault intelligent monitoring system is characterized in that: The regional cable anomaly analysis module includes: A regional anomaly calculation module, used to calculate the regional cable anomaly coefficient of the monitoring aggregation node based on all cable monitoring data of the monitoring aggregation node; Compare the regional cable anomaly coefficient with a preset regional anomaly threshold to obtain a regional comparison result; A regional determination module, used for performing regional cable determination on the monitoring aggregation node according to the regional comparison result to obtain a regional cable determination result; A cable anomaly calculation module, used to calculate a new energy cable anomaly coefficient of each new energy cable according to the cable monitoring data of each new energy cable when the regional cable determination result is a cable regional anomaly determination; Comparing the new energy cable abnormality coefficient with a preset cable abnormality threshold to obtain a cable comparison result; The cable determination module is used to determine whether the new energy cable is a new energy cable according to the cable comparison result to obtain a new energy cable determination result.

9. According to claim 6, a new energy cable fault intelligent monitoring system is characterized in that: The abnormality elimination analysis module includes: An abnormality sorting module is used to sort the abnormality coefficients of new energy cables in descending order to obtain the cable abnormality sorting; The remaining monitoring module is used to sequentially obtain the cable monitoring data of the new energy cables in the cable abnormality sorting, extract the cable monitoring data in the monitoring aggregation node, and obtain the node remaining monitoring data; A remaining abnormality calculation module is used to calculate the regional cable abnormality coefficient after removing the cable monitoring data of the new energy cable in the cable abnormality sorting according to the remaining monitoring data of the node, and obtain the node remaining abnormality coefficient; A difference analysis module is used to calculate the difference between the regional cable anomaly coefficient of the monitoring aggregation node and the node residual anomaly coefficient to obtain the residual anomaly difference; Compare the remaining abnormal difference with a preset remaining threshold to obtain an abnormal difference comparison result; The difference cable determination module is used to perform new energy cable determination on the new energy cable corresponding to the cable monitoring data according to the abnormal difference comparison result, and obtain new energy cable determination information.

10. The intelligent monitoring system for new energy cable faults according to claim 6 is characterized in that: The cycle judgment module comprises: A data recovery module, used for re-storing the cable monitoring data corresponding to the new energy cable determination into the monitoring aggregation node after the new energy cable determination is performed; The sequential extraction module is used to extract the cable monitoring data of the next new energy cable in the cable anomaly sorting in the monitoring aggregation node, and obtain the remaining monitoring data of the node; The positioning and marking module is used to calculate the remaining abnormality coefficient of the node until the regional cable abnormality judgment result is that the cable area is normal. Then, data extraction is stopped, and abnormal positioning and marking of the new energy cable corresponding to the extracted cable monitoring data are performed.

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