Temperature prediction method and system for high-voltage cable joint

Abstract

The invention relates to the technical field of cable temperature prediction, and discloses a temperature prediction method and system for a high-voltage cable joint, and the method comprises the steps: averagely dividing a cable joint into a plurality of monitoring sections, and numbering each monitoring section; collecting temperature information of a monitoring section in real time, constructing cable temperature distribution views at different moments according to the temperature information, and mapping environment temperature information on the cable temperature distribution views; calculating a temperature difference value between the temperature information of each monitoring section and the environment temperature information at the same moment according to the cable temperature distribution view, preliminarily judging whether the cable is abnormal or not according to the temperature difference value, and judging an abnormal area; and calculating an abnormal index of the abnormal area according to the historical temperature information and the current temperature information of the abnormal area, and predicting a predicted temperature of the next moment according to a temperature change condition of the abnormal area within a preset duration. According to the invention, the operation safety of the cable system is improved, and the maintenance efficiency is optimized.

Description

Technical Field

[0001] This invention relates to the field of cable temperature prediction technology, and more specifically, to a method and system for predicting the temperature of high-voltage cable joints. Background Technology

[0002] In power systems, high-voltage cables serve as crucial carriers of electrical energy transmission, and their operational status directly impacts the safety and stability of the power system. High-voltage cable joints, being weak points in cable lines, are highly susceptible to abnormal temperature increases due to their complex structure, contact resistance, and susceptibility to environmental factors.

[0003] Traditional methods for monitoring the temperature of high-voltage cable joints are often rudimentary, relying on overall monitoring or monitoring of only a few points, making it difficult to achieve refined management of cable joints. This monitoring method has significant drawbacks. When abnormal temperatures occur at cable joints, it cannot accurately and quickly locate the abnormal area, leading to low maintenance efficiency, slow response, and potential missed opportunities for optimal intervention, potentially causing more serious faults or even power outages, severely impacting the stability and reliability of the power grid. Furthermore, existing technologies also have shortcomings in the analysis and application of temperature data. While some technologies collect temperature information, they lack a systematic presentation of temperature changes at different times and fail to effectively integrate with ambient temperature information for comprehensive analysis. This results in an incomplete understanding of cable temperature changes under different environmental conditions, hindering informed decision-making. In addition, the judgment of temperature anomalies often relies on simple threshold comparisons, lacking precise location and in-depth analysis of abnormal areas, and cannot effectively predict temperature change trends, failing to meet the needs of advance maintenance planning and optimized resource allocation.

[0004] Therefore, it is necessary to provide a method and system for predicting the temperature of high-voltage cable joints to solve the problems of traditional high-voltage cable joint temperature monitoring methods, which lack refined management and system analysis, making it difficult to quickly locate abnormal areas, resulting in low maintenance efficiency, and failing to effectively predict temperature change trends, thus affecting the stability and reliability of the power grid. Summary of the Invention

[0005] In view of this, the present invention proposes a method and system for predicting the temperature of high-voltage cable joints, aiming to solve the problems of traditional high-voltage cable joint temperature monitoring methods, which lack refined management and system analysis, resulting in difficulty in quickly locating abnormal areas, low maintenance efficiency, and inability to effectively predict temperature change trends, thus affecting the stability and reliability of the power grid.

[0006] On one hand, this invention proposes a method for predicting the temperature of high-voltage cable joints, including:

[0007] The cable joint is divided into several monitoring sections, and each monitoring section is numbered.

[0008] The temperature information of the monitoring section is collected in real time, and a cable temperature distribution view at different times is constructed based on the temperature information. The ambient temperature information is collected in real time and mapped onto the cable temperature distribution view.

[0009] Calculate the temperature difference between the temperature information of each monitoring section and the ambient temperature information at the same time based on the cable temperature distribution view. Make a preliminary judgment on whether the cable is abnormal based on the temperature difference. If it is determined that an abnormality has occurred, identify the abnormal area.

[0010] Obtain historical temperature information of the abnormal area corresponding to the current ambient temperature information, calculate the abnormality index of the abnormal area based on the historical temperature information and the current temperature information, and predict the predicted temperature at the next moment based on the temperature change of the abnormal area within a preset time period.

[0011] Furthermore, the process of dividing the cable joint into several monitoring sections and numbering each monitoring section includes:

[0012] Collect the cable joint length, set the length value, calculate the sum of the cable joint length and the length value, and the difference between the cable joint length and the length value, and construct the cable length range [difference, sum] based on the sum and difference;

[0013] Obtain historical cable joints within the cable length range, calculate the average number of monitoring sections for all historical cable joints, and use the average number of monitoring sections as the number of monitoring sections for the current cable joint.

[0014] The monitoring sections are numbered sequentially in the same direction, with each monitoring section having a unique number.

[0015] Furthermore, the real-time acquisition of temperature information of the monitoring section, the construction of cable temperature distribution views at different times based on the temperature information, the construction of temperature change views for each monitoring section based on the number, and the real-time acquisition of ambient temperature information, when mapping the ambient temperature information onto the cable temperature distribution views, include:

[0016] Temperature information of each monitoring section is monitored in real time by temperature sensors, and the temperature information is stored in chronological order to form time series data.

[0017] A two-dimensional coordinate graph is constructed based on time series data, with time on the horizontal axis and temperature on the vertical axis. Temperature information in different monitoring sections is represented by different lines, thus obtaining a view of cable temperature distribution at different times.

[0018] The ambient temperature information is monitored in real time by an ambient temperature sensor, and the ambient temperature information is represented on the cable temperature distribution view as a line that is different from the temperature information.

[0019] Furthermore, the step of calculating the temperature difference between the temperature information of each monitoring section and the ambient temperature information at the same time based on the cable temperature distribution view, and preliminarily judging whether the cable has an abnormality based on the temperature difference, and if an abnormality is judged, determining the abnormal area includes:

[0020] A temperature difference threshold is set. If any of the temperature differences exceeds the temperature difference threshold, it is determined that the cable has a temperature abnormality.

[0021] If all the temperature differences are less than or equal to the difference threshold, then it is determined that the cable does not have a temperature abnormality.

[0022] Furthermore, the step of calculating the temperature difference between the temperature information of each monitoring section and the ambient temperature information at the same time based on the cable temperature distribution view, and preliminarily judging whether the cable has an abnormality based on the temperature difference, and if an abnormality is judged, the step of judging the abnormal area further includes:

[0023] If an abnormal temperature is detected in the cable, then identify the area of ​​the abnormality;

[0024] The monitoring area corresponding to the temperature difference exceeding the aforementioned difference threshold is designated as an abnormal area, and the abnormal area is marked accordingly.

[0025] The ratio of the number of abnormal areas to the number of all monitored sections of the cable joint is calculated and recorded as the abnormality ratio. The abnormality ratio is used as the cable joint abnormality index.

[0026] Furthermore, the step of using the abnormal ratio as the cable joint abnormality index includes:

[0027] Based on the cable joint anomaly index, an early warning of abnormal joint temperature level is issued for the cable joint.

[0028] The abnormality index of the cable joint is directly proportional to the level of the abnormality warning.

[0029] Furthermore, the step of obtaining historical temperature information of the abnormal area corresponding to the current ambient temperature information, and calculating the abnormality index of the abnormal area based on the historical temperature information and the current temperature information, includes:

[0030] Calculate the average temperature of the historical temperature information and obtain the maximum temperature of the historical temperature information;

[0031] If the temperature information corresponding to the abnormal region is greater than the maximum temperature, then the abnormality index is the first index;

[0032] If the temperature information corresponding to the abnormal area is greater than or equal to the average temperature and less than or equal to the maximum temperature, then the abnormality index is the second index;

[0033] If the temperature information corresponding to the abnormal area is less than the average temperature, then the abnormality index is the third index;

[0034] Among them, the abnormality indices, from high to low, are the first index, the second index, and the third index.

[0035] Furthermore, when calculating the anomaly index of the anomaly region based on its historical and current temperature information, the process includes:

[0036] The abnormality value of the joint is obtained by weighted summation of the abnormality index and the cable joint abnormality index.

[0037] If the abnormal value of the joint is greater than the preset abnormal value, the level of the abnormal warning will be increased by one level.

[0038] Furthermore, when predicting the predicted temperature at the next moment based on the temperature changes within a preset time period in the abnormal region, the process includes:

[0039] Three sampling points are set within a preset time period. The first sampling point is the starting time point of the preset time period, the second sampling point is the middle time point of the preset time period, and the third sampling point is the ending time point of the preset time period. The first temperature difference between two adjacent sampling points is calculated, and the second temperature difference between the first sampling point and the third sampling point is calculated.

[0040] Calculate the similarity between the two first temperature differences and the second temperature difference and the historical first temperature difference and the historical second temperature difference in the abnormal area in the historical data, and obtain the predicted temperature for the next moment based on the similarity.

[0041] Compared with existing technologies, the advantages of this invention are as follows: First, by dividing the cable joint into several monitoring sections and numbering them, refined management of the cable joint can be achieved. This division method helps to more accurately locate the area where the problem occurs, thereby improving maintenance efficiency and response speed. Second, real-time acquisition of temperature information of the monitoring sections and construction of cable temperature distribution views at different times can provide an intuitive visual display of the cable's operating status. Combined with the mapping of ambient temperature information, a more comprehensive understanding of the cable's temperature changes under different environmental conditions can be achieved, providing data support for subsequent analysis and decision-making. By calculating the temperature difference between the temperature information of each monitoring section and the ambient temperature information at the same time, a preliminary judgment can be made as to whether the cable is abnormal and to identify the abnormal area. This method can quickly identify potential risk points, thereby taking preventive measures to avoid faults, reduce power outages, and improve the stability and reliability of the power grid. Finally, by obtaining historical temperature information of the abnormal area corresponding to the current ambient temperature information, calculating the anomaly index, and predicting the temperature at the next moment, the trend of cable joint temperature changes can be predicted. This predictive capability is crucial for advance planning of maintenance work, optimization of resource allocation, and formulation of countermeasures, and helps to achieve long-term stable operation of the cable system. In summary, the high-voltage cable joint temperature prediction method provided in this application, through refined monitoring, real-time data acquisition, rapid location of abnormal areas, and temperature trend prediction, not only improves the operational safety of cable systems but also optimizes maintenance efficiency.

[0042] On the other hand, this application also provides a temperature prediction system for high-voltage cable joints, comprising:

[0043] The preprocessing module is configured to divide the cable joint into several monitoring sections on an average basis and number each monitoring section.

[0044] The view building module is configured to collect temperature information of the monitoring section in real time, build cable temperature distribution views at different times based on the temperature information, collect ambient temperature information in real time, and map the ambient temperature information onto the cable temperature distribution view.

[0045] The anomaly determination module is configured to calculate the temperature difference between the temperature information of each monitoring section and the ambient temperature information at the same time based on the cable temperature distribution view, and to preliminarily determine whether the cable is abnormal based on the temperature difference. If an anomaly is determined, the abnormal area is identified.

[0046] The prediction module is configured to acquire historical temperature information of the abnormal area corresponding to the current ambient temperature information, calculate the abnormality index of the abnormal area based on the historical temperature information and the current temperature information, and predict the predicted temperature at the next moment based on the temperature change of the abnormal area within a preset time period.

[0047] It is understood that the temperature prediction method and system for high-voltage cable joints provided in this application have the same beneficial effects, and will not be described in detail here. Attached Figure Description

[0048] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0049] Figure 1 A flowchart of a high-voltage cable joint temperature prediction method provided in an embodiment of the present invention;

[0050] Figure 2 A functional block diagram of a high-voltage cable joint temperature prediction system provided in an embodiment of the present invention. Detailed Implementation

[0051] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the disclosure to those skilled in the art. It should be noted that, unless otherwise specified, embodiments and features in the embodiments of the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0052] In some embodiments of this application, see Figure 1 As shown, this embodiment provides a method for predicting the temperature of a high-voltage cable joint, including the following steps:

[0053] S100. Divide the cable joint into several monitoring sections on an average basis, and number each monitoring section.

[0054] S200. Collect temperature information of the monitoring section in real time, construct cable temperature distribution view at different times based on the temperature information, collect ambient temperature information in real time, and map the ambient temperature information onto the cable temperature distribution view.

[0055] S300. Calculate the temperature difference between the temperature information of each monitoring section and the ambient temperature information at the same time based on the cable temperature distribution view. Make a preliminary judgment on whether the cable is abnormal based on the temperature difference. If it is determined that an abnormality has occurred, identify the abnormal area.

[0056] S400: Obtain historical temperature information of the abnormal area corresponding to the current ambient temperature information; calculate the abnormal index of the abnormal area based on the historical temperature information and the current temperature information; and predict the predicted temperature at the next moment based on the temperature change of the abnormal area within a preset time period.

[0057] Understandably, firstly, by dividing the cable joint into several monitoring sections and numbering them (step S100), refined management of the cable joint can be achieved. This division method helps to more accurately locate the area where the problem occurs, thereby improving maintenance efficiency and response speed. Secondly, by collecting the temperature information of the monitoring sections in real time and constructing a cable temperature distribution view at different times (step S200), an intuitive visual display of the cable's operating status can be provided. Combined with the mapping of ambient temperature information, the temperature changes of the cable under different environmental conditions can be understood more comprehensively, providing data support for subsequent analysis and decision-making. Step S300 calculates the temperature difference between the temperature information of each monitoring section and the ambient temperature information at the same time to preliminarily determine whether the cable is abnormal and to identify the abnormal area. This method can quickly identify potential risk points, thereby taking preventive measures to avoid faults, reduce power outages, and improve the stability and reliability of the power grid. Finally, by obtaining the historical temperature information of the abnormal area corresponding to the current ambient temperature information, calculating the anomaly index, and predicting the temperature at the next moment (step S400), the trend of cable joint temperature change can be predicted. This predictive capability is crucial for advance planning of maintenance work, optimization of resource allocation, and development of countermeasures, contributing to the long-term stable operation of cable systems. In summary, the high-voltage cable joint temperature prediction method provided in this application, through refined monitoring, real-time data acquisition, rapid location of abnormal areas, and temperature trend prediction, not only improves the operational safety of cable systems but also optimizes maintenance efficiency.

[0058] In some embodiments of this application, the step of dividing the cable joint into several monitoring sections and numbering each monitoring section includes:

[0059] Collect the cable joint length, set the length value, calculate the sum of the cable joint length and the length value, and the difference between the cable joint length and the length value, and construct the cable length range [difference, sum] based on the sum and difference;

[0060] Obtain historical cable joints within the cable length range, calculate the average number of monitoring sections for all historical cable joints, and use the average number of monitoring sections as the number of monitoring sections for the current cable joint.

[0061] The monitoring sections are numbered sequentially in the same direction, with each monitoring section having a unique number.

[0062] Understandably, by collecting cable joint length data and setting length values, the sum and difference between cable joint lengths and length values ​​can be calculated, thus constructing a cable length range. This range helps determine the historical cable joint length distribution, providing a reference for the number of monitoring sections for the current cable joints. By acquiring historical cable joints within this cable length range and calculating their average number of monitoring sections, the number of monitoring sections for the current cable joints can be set more accurately, ensuring that the level of monitoring detail matches historical data and improving monitoring accuracy and efficiency. Secondly, numbering the monitoring sections sequentially in the same direction, ensuring that each monitoring section number is unique, helps establish a clear monitoring system. This numbering method not only facilitates tracking and managing the status of each section but also allows for rapid identification of specific sections during fault location, maintenance, and replacement, thereby improving response speed and maintenance efficiency. Furthermore, this systematic numbering method also facilitates data recording and analysis, making cable joint monitoring and maintenance more scientific and systematic, ultimately improving the reliability and service life of the entire cable system.

[0063] In some embodiments of this application, the real-time acquisition of temperature information of the monitoring section, the construction of cable temperature distribution views at different times based on the temperature information, the construction of temperature change views for each monitoring section based on the number, the real-time acquisition of ambient temperature information, and the mapping of the ambient temperature information onto the cable temperature distribution views include:

[0064] Temperature information of each monitoring section is monitored in real time by temperature sensors, and the temperature information is stored in chronological order to form time series data.

[0065] A two-dimensional coordinate graph is constructed based on time series data, with time on the horizontal axis and temperature on the vertical axis. Temperature information in different monitoring sections is represented by different lines, thus obtaining a view of cable temperature distribution at different times.

[0066] The ambient temperature information is monitored in real time by an ambient temperature sensor, and the ambient temperature information is represented on the cable temperature distribution view as a line that is different from the temperature information.

[0067] Understandably, firstly, by monitoring the temperature information of each monitoring section in real time using temperature sensors and storing this information chronologically to form time-series data, a continuous and dynamic record of the cable's operating status is provided. This real-time monitoring mechanism can promptly detect abnormal temperature changes, thereby preventing potential faults and accidents and improving the safety of cable operation. Secondly, a two-dimensional coordinate graph constructed based on the time-series data, with time on the horizontal axis and temperature on the vertical axis, uses different lines to represent the temperature information of different monitoring sections, thus obtaining a view of the cable temperature distribution at different times. This intuitive temperature distribution view allows maintenance personnel to quickly identify hot spots in the cable and take timely measures for maintenance or adjustment, optimizing the cable's operating efficiency. Furthermore, real-time acquisition of ambient temperature information and mapping this information onto the cable temperature distribution view allows for a more comprehensive analysis of the relationship between the cable's operating status and environmental factors. Changes in ambient temperature may affect the cable's heat dissipation performance; by comparing ambient temperature and cable temperature, the cable's operating condition can be more accurately assessed, providing a scientific basis for cable maintenance and management. In summary, real-time monitoring of cable temperature and construction of a temperature distribution view can not only improve the safety of cable operation and optimize cable operating efficiency, but also provide strong data support for cable maintenance and management.

[0068] In some embodiments of this application, the step of calculating the temperature difference between the temperature information of each monitoring section and the ambient temperature information at the same time based on the cable temperature distribution view, and preliminarily determining whether the cable is abnormal based on the temperature difference, and if an abnormality is determined, determining the abnormal area includes:

[0069] A temperature difference threshold is set. If any of the temperature differences exceeds the temperature difference threshold, it is determined that the cable has a temperature abnormality.

[0070] If all the temperature differences are less than or equal to the difference threshold, then it is determined that the cable does not have a temperature abnormality.

[0071] In some embodiments of this application, the step of calculating the temperature difference between the temperature information of each monitoring section and the ambient temperature information at the same time based on the cable temperature distribution view, and preliminarily determining whether the cable is abnormal based on the temperature difference, and if an abnormality is determined, further includes:

[0072] If an abnormal temperature is detected in the cable, then identify the area of ​​the abnormality;

[0073] The monitoring area corresponding to the temperature difference exceeding the aforementioned difference threshold is designated as an abnormal area, and the abnormal area is marked accordingly.

[0074] The ratio of the number of abnormal areas to the number of all monitored sections of the cable joint is calculated and recorded as the abnormality ratio. The abnormality ratio is used as the cable joint abnormality index.

[0075] In some embodiments of this application, the step of using the anomaly ratio as a cable joint anomaly index includes:

[0076] Based on the cable joint anomaly index, an early warning of abnormal joint temperature level is issued for the cable joint.

[0077] The abnormality index of the cable joint is directly proportional to the level of the abnormality warning.

[0078] It is understood that, in the embodiments of this application, by calculating the difference between the temperature information of each monitoring section in the cable temperature distribution view and the ambient temperature information, it is possible to effectively make a preliminary judgment on whether the cable is abnormal, monitor the cable's operating status in real time, and promptly detect potential fault points, thereby avoiding power supply interruptions or other safety accidents caused by cable faults. Setting a difference threshold as a judgment standard makes the anomaly judgment more explicit and objective, improving the accuracy of the judgment. When the temperature difference exceeds the threshold, the system can quickly locate the specific abnormal area and mark it, which helps maintenance personnel to respond quickly, conduct targeted inspections and repairs, save troubleshooting time, and improve maintenance efficiency.

[0079] Furthermore, by calculating the ratio of the number of abnormal areas to the total number of monitored cable joint sections, a cable joint anomaly index is formed, which quantifies the degree of cable abnormality. This quantitative method makes the cable health status more intuitive and facilitates long-term tracking and comparison. The direct proportionality between the anomaly index and the warning level allows maintenance personnel to take different levels of countermeasures based on the index level, thereby achieving tiered early warning management. This early warning mechanism helps to achieve refined cable management, ensure the stable operation of the power system, reduce economic losses, and improve user satisfaction.

[0080] In some embodiments of this application, the step of obtaining historical temperature information of the abnormal region corresponding to the current ambient temperature information, and calculating the abnormality index of the abnormal region based on the historical temperature information and the current temperature information, includes:

[0081] Calculate the average temperature of the historical temperature information and obtain the maximum temperature of the historical temperature information;

[0082] If the temperature information corresponding to the abnormal region is greater than the maximum temperature, then the abnormality index is the first index;

[0083] If the temperature information corresponding to the abnormal area is greater than or equal to the average temperature and less than or equal to the maximum temperature, then the abnormality index is the second index;

[0084] If the temperature information corresponding to the abnormal area is less than the average temperature, then the abnormality index is the third index;

[0085] Among them, the abnormality indices, from high to low, are the first index, the second index, and the third index.

[0086] In some embodiments of this application, calculating the anomaly index of the anomaly region based on its historical and current temperature information includes:

[0087] The abnormality value of the joint is obtained by weighted summation of the abnormality index and the cable joint abnormality index.

[0088] If the abnormal value of the joint is greater than the preset abnormal value, the level of the abnormal warning will be increased by one level.

[0089] Understandably, by obtaining current ambient temperature information and comparing it with historical temperature information for the abnormal area, an anomaly index for the abnormal region can be effectively calculated. First, the average and maximum values ​​of the historical temperature information are calculated. Then, based on the comparison between the current temperature information and these historical data, the anomaly index is divided into three levels. Specifically, if the current temperature exceeds the historical maximum temperature, it is assigned the highest anomaly index; if the current temperature is between the historical average and the maximum value, it is assigned a medium anomaly index; and if the current temperature is below the historical average, it is assigned the lowest anomaly index. This grading method helps to accurately identify and quantify the severity of anomalies.

[0090] Furthermore, by weighted summing the anomaly index and the cable joint anomaly index to obtain the joint anomaly value, the health status of the cable joint can be assessed more comprehensively. If the calculated joint anomaly value exceeds the preset anomaly value, the system will automatically adjust the warning level, thereby providing timely maintenance or repair suggestions. This dynamic adjustment mechanism ensures that anomalies receive appropriate attention and handling, helping to prevent potential faults and accidents, thus improving the reliability and safety of the system. Overall, this anomaly detection and early warning mechanism based on a combination of historical and current data not only improves the accuracy of anomaly detection but also enhances prevention and response capabilities, which is of significant practical importance for ensuring the stable operation of critical equipment.

[0091] In some embodiments of this application, predicting the predicted temperature at the next moment based on the temperature change within a preset time period in the abnormal region includes:

[0092] Three sampling points are set within a preset time period. The first sampling point is the starting time point of the preset time period, the second sampling point is the middle time point of the preset time period, and the third sampling point is the ending time point of the preset time period. The first temperature difference between two adjacent sampling points is calculated, and the second temperature difference between the first sampling point and the third sampling point is calculated.

[0093] Calculate the similarity between the two first temperature differences and the second temperature difference and the historical first temperature difference and the historical second temperature difference in the abnormal area in the historical data, and obtain the predicted temperature for the next moment based on the similarity.

[0094] Understandably, the process begins by setting three sampling points within a preset timeframe: the starting point, the intermediate point, and the final point. By calculating the first temperature difference between two adjacent sampling points and the second temperature difference between the starting and final sampling points, the trend and fluctuations in temperature over time can be captured. Next, by calculating the similarity between these temperature differences and historical first and second temperature differences in abnormal areas of historical data, the degree of matching between the current temperature trend and historical patterns can be assessed. This similarity analysis helps identify temperature change patterns similar to those in historical data, thereby improving prediction accuracy. Finally, based on the similarity analysis results, the predicted temperature for the next moment can be obtained. The advantage of this method is that it considers not only the current temperature trend but also similar patterns from historical data, enabling a more comprehensive prediction of future temperature changes. This prediction method has wide applications in many fields, such as weather forecasting, industrial process control, and equipment fault detection, helping relevant personnel prepare in advance and take appropriate measures to improve efficiency and safety.

[0095] Specifically, the historical predicted temperature corresponding to the maximum similarity is used as the predicted temperature for the next moment.

[0096] On the other hand, see Figure 2 As shown, this application also provides a temperature prediction system for high-voltage cable joints, used to apply the above-mentioned temperature prediction method for high-voltage cable joints, including:

[0097] The preprocessing module is configured to divide the cable joint into several monitoring sections on an average basis and number each monitoring section.

[0098] The view building module is configured to collect temperature information of the monitoring section in real time, build cable temperature distribution views at different times based on the temperature information, collect ambient temperature information in real time, and map the ambient temperature information onto the cable temperature distribution view.

[0099] The anomaly determination module is configured to calculate the temperature difference between the temperature information of each monitoring section and the ambient temperature information at the same time based on the cable temperature distribution view, and to preliminarily determine whether the cable is abnormal based on the temperature difference. If an anomaly is determined, the abnormal area is identified.

[0100] The prediction module is configured to acquire historical temperature information of the abnormal area corresponding to the current ambient temperature information, calculate the abnormality index of the abnormal area based on the historical temperature information and the current temperature information, and predict the predicted temperature at the next moment based on the temperature change of the abnormal area within a preset time period.

[0101] Understandably, by dividing cable joints into several monitoring sections and numbering them using the preprocessing module, the system can achieve refined management of cable joints. This division helps to more accurately locate and monitor temperature changes in cable joints, thereby improving monitoring accuracy and efficiency. Secondly, the view construction module can collect temperature information from the monitoring sections in real time and construct cable temperature distribution views at different times. This not only helps operators intuitively understand the temperature status of the cable joints, but also, by collecting ambient temperature information in real time and mapping it onto the temperature distribution view, it can more comprehensively assess the working environment of the cable joints, providing an important reference for accurately judging the operating status of the cable joints. The introduction of the anomaly detection module further enhances the system's early warning capability. By calculating the temperature difference between the temperature information of each monitoring section and the ambient temperature information at the same time, the system can preliminarily determine whether the cable has an anomaly and identify the abnormal area. This rapid response mechanism is crucial for preventing cable faults and avoiding possible power system accidents. The prediction module is a major highlight of the system. It obtains historical temperature information of the abnormal area corresponding to the current ambient temperature information, calculates the anomaly index of the abnormal area, and predicts the predicted temperature at the next moment. This predictive capability not only helps to take preventative measures to avoid potential failures, but also optimizes power system operation and scheduling, improving the overall reliability and efficiency of the system. In summary, the high-voltage cable joint temperature prediction system provided in this application significantly enhances the operational monitoring capabilities of cable joints and strengthens the safety and stability of the power system through multiple functions, including refined monitoring, real-time view construction, rapid anomaly detection, and accurate prediction.

[0102] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program goods. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program goods embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0103] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program goods according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0104] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0105] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0106] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for predicting the temperature of a high-voltage cable joint, characterized in that, include: The cable joint is divided into several monitoring sections, and each monitoring section is numbered. The temperature information of the monitoring section is collected in real time, and a cable temperature distribution view at different times is constructed based on the temperature information. The ambient temperature information is collected in real time and mapped onto the cable temperature distribution view. Calculate the temperature difference between the temperature information of each monitoring section and the ambient temperature information at the same time based on the cable temperature distribution view. Make a preliminary judgment on whether the cable is abnormal based on the temperature difference. If it is determined that an abnormality has occurred, identify the abnormal area. Obtain historical temperature information of the abnormal area corresponding to the current ambient temperature information, calculate the abnormality index of the abnormal area based on the historical temperature information and the current temperature information, and predict the predicted temperature at the next moment based on the temperature change of the abnormal area within a preset time period.

2. The method for predicting the temperature of a high-voltage cable joint according to claim 1, characterized in that, The process of dividing the cable joint into several monitoring sections and numbering each monitoring section includes: Collect the cable joint length, set the length value, calculate the sum of the cable joint length and the length value, and the difference between the cable joint length and the length value, and construct the cable length range [difference, sum] based on the sum and difference; Obtain historical cable joints within the cable length range, calculate the average number of monitoring sections for all historical cable joints, and use the average number of monitoring sections as the number of monitoring sections for the current cable joint. The monitoring sections are numbered sequentially in the same direction, with each monitoring section having a unique number.

3. The method for predicting the temperature of a high-voltage cable joint according to claim 1, characterized in that, The real-time acquisition of temperature information of the monitoring section, the construction of cable temperature distribution views at different times based on the temperature information, the construction of temperature change views for each monitoring section based on the number, and the real-time acquisition of ambient temperature information, along with mapping the ambient temperature information onto the cable temperature distribution views, include: Temperature information of each monitoring section is monitored in real time by temperature sensors, and the temperature information is stored in chronological order to form time series data. A two-dimensional coordinate graph is constructed based on time series data, with time on the horizontal axis and temperature on the vertical axis. Temperature information in different monitoring sections is represented by different lines, thus obtaining a view of cable temperature distribution at different times. The ambient temperature information is monitored in real time by an ambient temperature sensor, and the ambient temperature information is represented on the cable temperature distribution view as a line that is different from the temperature information.

4. The method for predicting the temperature of a high-voltage cable joint according to claim 3, characterized in that, The process involves calculating the temperature difference between the temperature information of each monitoring section and the ambient temperature information at the same time based on the cable temperature distribution view, and using the temperature difference to preliminarily determine whether the cable is abnormal. If an abnormality is determined, the identification of the abnormal area includes: A temperature difference threshold is set. If any of the temperature differences exceeds the temperature difference threshold, it is determined that the cable has a temperature abnormality. If all the temperature differences are less than or equal to the difference threshold, then it is determined that the cable does not have a temperature abnormality.

5. The method for predicting the temperature of a high-voltage cable joint according to claim 4, characterized in that, The step of calculating the temperature difference between the temperature information of each monitoring section and the ambient temperature information at the same time based on the cable temperature distribution view, and preliminarily judging whether the cable has an abnormality based on the temperature difference, and if an abnormality is judged, further includes determining the abnormal area: If an abnormal temperature is detected in the cable, then identify the area of ​​the abnormality; The monitoring area corresponding to the temperature difference exceeding the aforementioned difference threshold is designated as an abnormal area, and the abnormal area is marked accordingly. The ratio of the number of abnormal areas to the number of all monitored sections of the cable joint is calculated and recorded as the abnormality ratio. The abnormality ratio is used as the cable joint abnormality index.

6. The method for predicting the temperature of a high-voltage cable joint according to claim 5, characterized in that, The step of using the abnormal ratio as the cable joint abnormality index includes: Based on the cable joint anomaly index, an early warning of abnormal joint temperature level is issued for the cable joint. The abnormality index of the cable joint is directly proportional to the level of the abnormality warning.

7. The method for predicting the temperature of a high-voltage cable joint according to claim 6, characterized in that, The step of obtaining historical temperature information of the abnormal area corresponding to the current ambient temperature information, and calculating the abnormality index of the abnormal area based on the historical temperature information and the current temperature information, includes: Calculate the average temperature of the historical temperature information and obtain the maximum temperature of the historical temperature information; If the temperature information corresponding to the abnormal region is greater than the maximum temperature, then the abnormality index is the first index; If the temperature information corresponding to the abnormal area is greater than or equal to the average temperature and less than or equal to the maximum temperature, then the abnormality index is the second index; If the temperature information corresponding to the abnormal area is less than the average temperature, then the abnormality index is the third index; Among them, the abnormality indices, from high to low, are the first index, the second index, and the third index.

8. The method for predicting the temperature of a high-voltage cable joint according to claim 7, characterized in that, The calculation of the anomaly index of the anomaly region based on its historical and current temperature information includes: The abnormality value of the joint is obtained by weighted summation of the abnormality index and the cable joint abnormality index. If the abnormal value of the joint is greater than the preset abnormal value, the level of the abnormal warning will be increased by one level.

9. The method for predicting the temperature of a high-voltage cable joint according to claim 8, characterized in that, The step of predicting the predicted temperature at the next moment based on the temperature change within a preset time period in the abnormal region includes: Three sampling points are set within a preset time period. The first sampling point is the starting time point of the preset time period, the second sampling point is the middle time point of the preset time period, and the third sampling point is the ending time point of the preset time period. The first temperature difference between two adjacent sampling points is calculated, and the second temperature difference between the first sampling point and the third sampling point is calculated. Calculate the similarity between the two first temperature differences and the second temperature difference and the historical first temperature difference and the historical second temperature difference in the abnormal area in the historical data, and obtain the predicted temperature for the next moment based on the similarity.

10. A temperature prediction system for high-voltage cable joints, used to apply the temperature prediction method for high-voltage cable joints as described in any one of claims 1-9, characterized in that, include: The preprocessing module is configured to divide the cable joint into several monitoring sections on an average basis and number each monitoring section. The view building module is configured to collect temperature information of the monitoring section in real time, build cable temperature distribution views at different times based on the temperature information, collect ambient temperature information in real time, and map the ambient temperature information onto the cable temperature distribution view. The anomaly determination module is configured to calculate the temperature difference between the temperature information of each monitoring section and the ambient temperature information at the same time based on the cable temperature distribution view, and to preliminarily determine whether the cable is abnormal based on the temperature difference. If an anomaly is determined, the abnormal area is identified. The prediction module is configured to acquire historical temperature information of the abnormal area corresponding to the current ambient temperature information, calculate the abnormality index of the abnormal area based on the historical temperature information and the current temperature information, and predict the predicted temperature at the next moment based on the temperature change of the abnormal area within a preset time period.

Images