A cable on-line monitoring and early warning system based on intelligent inspection technology

Abstract

The application belongs to the field of cable monitoring, and relates to a data analysis technique, which is used to solve the problem that the prior art cannot screen the cable area needing key inspection in combination with multi-source data, so that the generated inspection path cannot take into account the timeliness and accuracy of the monitoring of the key area, and specifically relates to a cable online monitoring and early warning system based on intelligent inspection technology, which comprises environment supervision modules, a path planning module and a transport capacity evaluation module connected in sequence, the path planning module is further communicatively connected with an inspection and monitoring module, and the environment supervision modules and the transport capacity evaluation module are both communicatively connected with a database; the application realizes real-time monitoring and intelligent early warning of the cable state, the comprehensive analysis of the environmental factors and the equipment state improves the accuracy of abnormal detection, the dynamically adjusted inspection path ensures that the key area is checked in time, the inspection efficiency is improved, and the transport capacity evaluation mechanism ensures the reliability of the system operation, avoiding potential risks caused by insufficient inspection.

Description

Technical Field

[0001] This invention belongs to the field of cable monitoring and involves data analysis technology. Specifically, it is a cable online monitoring and early warning system based on intelligent inspection technology. Background Technology

[0002] The cable online monitoring and early warning system is a comprehensive solution that integrates the Internet of Things, big data, artificial intelligence and modern sensing technologies. It aims to achieve real-time perception, intelligent analysis and forward-looking early warning of the operating status of power cables, thereby completely changing the traditional operation and maintenance mode that relies on regular manual inspections.

[0003] The invention patent with publication number CN118334561A discloses a smart panoramic inspection and monitoring method and system for high-voltage cables. This monitoring method generates morphological and structural data of cable components based on multi-frame optical flow diagrams of cable components and acquires environmental perception parameters, realizing real-time and efficient panoramic inspection and monitoring of cables. However, this monitoring method cannot combine multi-source data to filter cable areas that need to be inspected, resulting in the generated inspection path failing to take into account the timeliness and accuracy of monitoring key areas. Furthermore, when dynamically generating inspection routes based on cable status and environmental changes, the existing technology cannot assess the inspection capacity. While ensuring the timeliness and accuracy of monitoring key areas, if the inspection capacity is overloaded or the single-trip inspection cycle is too long, it is still impossible to guarantee the timeliness of abnormal alarms for cables as a whole.

[0004] To address the aforementioned technical problems, this application proposes a solution. Summary of the Invention

[0005] The purpose of this invention is to provide an online cable monitoring and early warning system based on intelligent inspection technology, which solves the problem that existing technologies cannot combine multi-source data to screen cable areas that need to be inspected, resulting in the generated inspection path failing to take into account the timeliness and accuracy of monitoring key areas.

[0006] The technical problem to be solved by this invention is: how to provide an online cable monitoring and early warning system based on intelligent inspection technology that can combine multi-source data to screen cable areas that require key inspection.

[0007] The objective of this invention can be achieved through the following technical solutions:

[0008] A cable online monitoring and early warning system based on intelligent inspection technology includes an environmental monitoring module, a route planning module, and a capacity assessment module connected in sequence. The route planning module is also communicatively connected to the inspection and monitoring module, and both the environmental monitoring module and the capacity assessment module are communicatively connected to a database.

[0009] The inspection and monitoring module is used to inspect and monitor the cable status: the cable coverage area is divided into several monitoring areas, a monitoring cycle is generated, and within the monitoring cycle, the inspection robot sequentially monitors the status of the monitoring areas according to the predetermined inspection route and marks the abnormal points in the monitoring areas; after the inspection robot completes the inspection and monitoring of all the monitoring areas to be inspected according to the predetermined inspection route, the monitoring cycle ends and a new monitoring cycle is generated.

[0010] The environmental monitoring module is used to monitor and analyze the working environment of the cable and obtain the environmental monitoring coefficient of the monitoring area, and send the environmental monitoring coefficient of all monitoring areas to the path planning module;

[0011] The path planning module is used to plan and analyze the inspection path of the cable: at the end of the monitoring cycle, the number of abnormal points in the monitoring area is marked as the abnormal value of the monitoring area, and the predetermined inspection path for the next monitoring cycle is generated by the abnormal value and the environmental supervision coefficient.

[0012] The capacity assessment module is used to perform capacity assessment and analysis on cable inspections.

[0013] Furthermore, the specific process of marking abnormal points in the monitoring area includes: setting up several monitoring points on the cables in the monitoring area. The monitoring points are generally set at cable joints and bends and intersections in the laying path. Insulation resistance test, dielectric loss test and partial discharge detection are performed on the cables at the monitoring points. The monitoring points that fail the insulation resistance test, dielectric loss test or partial discharge detection are marked as abnormal points. An early warning signal is generated and the early warning signal and the location information of the abnormal points are sent to the mobile terminal of the management personnel.

[0014] Furthermore, the specific process of the environmental monitoring module to monitor and analyze the working environment of the cable includes: setting up several monitoring points in the monitoring area, obtaining the rainfall and maximum temperature values ​​of the monitoring points during the monitoring period through rain sensors and temperature sensors, marking the maximum values ​​of rainfall and maximum temperature values ​​of all monitoring points in the monitoring area as the rainfall performance value and high temperature performance value of the monitoring area, respectively, and performing numerical processing on the rainfall performance value and high temperature performance value to obtain the environmental monitoring coefficient of the monitoring area.

[0015] Furthermore, the process of obtaining the environmental regulatory coefficient of the monitoring area includes: retrieving the rainfall performance threshold and the high temperature performance threshold from the database, marking the ratio of the rainfall performance value to the rainfall performance threshold as the rainfall coefficient, marking the ratio of the high temperature performance value to the high temperature performance threshold as the high temperature coefficient, and marking the sum of the rainfall coefficient and the high temperature coefficient as the environmental regulatory coefficient of the monitoring area.

[0016] Furthermore, the process of generating the predetermined inspection path for the next monitoring cycle includes: sorting all monitoring areas in descending order of outlier values ​​to obtain an anomaly sequence; arranging all monitoring areas in descending order of environmental regulatory coefficients to obtain an environmental sequence; marking the sum of the serial numbers of the monitoring areas in the anomaly sequence and the serial numbers in the environmental sequence as the priority values ​​of the monitoring areas; marking the K1 monitoring areas with the smallest priority values ​​as key areas; marking the remaining monitoring areas as general inspection areas; and generating the predetermined inspection path for the next monitoring cycle based on the marking results of the key areas and general inspection areas.

[0017] Furthermore, the established inspection path meets the following requirements: the K1 monitoring areas ranked first and last in the established inspection path are both key areas, and the number of times the general inspection area is inspected in the established inspection path is one, while the number of times the key area is inspected in the established inspection path is two.

[0018] Furthermore, the specific process of the capacity assessment module for evaluating and analyzing the capacity of cable inspection includes: obtaining the duration of the monitoring cycle at the end of the monitoring cycle and marking it as the execution value; obtaining the execution threshold from the database; comparing the execution value with the execution threshold; if the execution value is less than the execution threshold, it is determined that the inspection capacity of the monitoring cycle meets the requirements and no action is taken; if the execution value is greater than or equal to the execution threshold, it is determined that the inspection capacity of the monitoring cycle does not meet the requirements, generating a counter with an initial value of K2, and evaluating the necessity of optimizing the inspection capacity based on the value of the counter.

[0019] Furthermore, the specific process for assessing the necessity of optimizing inspection capacity includes: if the execution value of the next monitoring cycle is less than the execution threshold, the counting ends and the counter value is reset; if the execution value of the next monitoring cycle is greater than or equal to the execution threshold, the counter value is decremented by one; when the counter value is zero, a capacity optimization signal is generated and sent to the mobile terminal of the management personnel.

[0020] The present invention has the following beneficial effects:

[0021] 1. This application realizes real-time monitoring and intelligent early warning of cable status. The comprehensive analysis of environmental factors and equipment status improves the accuracy of anomaly detection. The dynamically adjusted inspection path ensures that key areas are inspected in a timely manner, improving inspection efficiency. The capacity assessment mechanism ensures the reliability of system operation and avoids potential risks caused by insufficient inspection. This intelligent monitoring and early warning system greatly reduces the probability of cable faults and improves the overall stability and reliability of the power system.

[0022] 2. This application enables accurate location and timely early warning of cable anomalies. By setting monitoring points at key locations and conducting multiple electrical parameter tests, the operating status of the cable can be comprehensively evaluated. By comparing the test results with preset thresholds, it is possible to objectively determine whether there are any abnormalities in the cable. For detected anomalies, an early warning signal is generated and sent to the mobile terminal of the management personnel, enabling real-time notification of abnormal situations. This facilitates timely implementation of corresponding measures by management personnel to prevent the occurrence and spread of cable faults. Compared with traditional periodic manual inspections, this method has higher efficiency and accuracy, and can significantly improve the reliability and safety of cable operation.

[0023] 3. This application implements inspection path optimization based on outliers and environmental monitoring coefficients. This method comprehensively considers anomalies and environmental factors in the monitoring area, prioritizing these areas to generate more reasonable and efficient inspection paths. This ensures that key areas receive more attention and more frequent inspections, improving the targeting and effectiveness of cable monitoring. Furthermore, by placing key areas at the beginning and end of the inspection path, the timeliness of monitoring critical areas is further enhanced. This optimized inspection path helps to identify and address potential problems in the cable system early, improving the safety and reliability of cable operation.

[0024] 4. This application realizes dynamic evaluation and optimization of cable inspection capacity, thereby enabling timely detection of insufficient inspection capacity and avoiding the impact of excessively long inspection cycles on the timely detection and handling of cable anomalies. At the same time, by setting a counter mechanism, short-term inspection delays can be effectively filtered out. The optimization signal will only be triggered when insufficient capacity occurs for several consecutive cycles, thereby reducing unnecessary manual intervention and improving the stability and reliability of the system. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is a system block diagram of the present invention;

[0027] Figure 2 This is a flowchart of the capacity assessment and analysis for cable inspection according to the present invention. Detailed Implementation

[0028] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0029] In traditional high-voltage cable panoramic inspection systems, the multi-source heterogeneous data fusion mechanism suffers from structural defects. A dynamic correlation model is not established between environmental perception parameters and cable condition monitoring data, preventing path planning algorithms from constructing a priority evaluation matrix based on multi-dimensional risk factors. Environmental monitoring data and anomaly distribution data are analyzed in isolation, and path optimization relies solely on historical fault statistics or fixed inspection rules, failing to establish adaptive regional risk weight allocation strategies based on real-time operating conditions. The lack of a capacity assessment component prevents the system from quantifying the execution efficiency of a single inspection cycle, and a dynamic feedback mechanism is lacking between the inspection robot's trajectory and task load.

[0030] For example, in a multi-terrain cable network encompassing mountainous areas and urban underground utility tunnels, environmental sensors detected that rainfall in a certain area exceeded historical averages for three consecutive days, with temperature fluctuations reaching ±15℃. Simultaneously, intermittent abnormal partial discharge was observed at cable joints in the same area. Because the existing system lacks a coupled analysis model linking environmental parameters and equipment status, the path planning module continues to perform routine inspections of the area according to a preset cycle, failing to identify the synergistic effect of environmental stress and equipment degradation, leading to an increased rate of missed anomaly detections. Furthermore, due to the lack of a capacity assessment mechanism, the system continues to use a fixed inspection frequency, failing to dynamically detect early warning delays caused by excessively long inspection cycles.

[0031] If the above problems are not addressed, a risk-overlapping early warning system cannot be established between areas of sudden environmental changes and areas with potential equipment failures. The detection intervals at key monitoring points will exceed the critical time window for material aging, significantly reducing the probability of detecting transient anomalies such as partial discharge. The static planning characteristics of inspection paths lead to insufficient detection coverage in high-risk areas, while the lack of a capacity assessment mechanism prevents the system from recognizing timeliness degradation caused by path redundancy. Ultimately, this results in early warning response times for serious accidents such as cable insulation breakdown exceeding safety thresholds.

[0032] like Figure 1 As shown, an online cable monitoring and early warning system based on intelligent inspection technology includes an environmental monitoring module, a route planning module, and a capacity assessment module connected in sequence. The route planning module is also communicatively connected to the inspection and monitoring module, and both the environmental monitoring module and the capacity assessment module are communicatively connected to a database.

[0033] The inspection and monitoring module is used to inspect and analyze the cable status: the cable coverage area is divided into several monitoring zones, a monitoring cycle is generated, and within the monitoring cycle, the inspection robot sequentially monitors the status of the monitoring zones according to a predetermined inspection route: several monitoring points are set on the cables within the monitoring zone, generally at cable joints, bends, and intersections along the laying path. Insulation resistance testing, dielectric loss testing, and partial discharge detection are performed on the cables at the monitoring points. Monitoring points that fail the insulation resistance test, dielectric loss test, or partial discharge detection are marked as abnormal points, and an early warning signal is generated and sent to the mobile terminal of the management personnel along with the location information of the abnormal points. After the inspection robot completes the inspection and monitoring of all the monitoring zones to be inspected according to the predetermined inspection route, the monitoring cycle ends and a new monitoring cycle is generated.

[0034] The monitoring points are strategically placed to cover areas with weak points in the cable structure. Poor contact is common at cable joints due to material differences, and insulation damage is prone to occur at bends and intersections due to concentrated mechanical stress. Insulation resistance testing detects the insulation performance between the conductor and the insulation layer; dielectric loss testing assesses the aging of the insulation material; and partial discharge detection identifies discharge phenomena caused by localized electric field distortion. The three test data are logically ORed to trigger anomaly markers; failure of any test results in an anomaly. Warning signals and location information are transmitted to a mobile terminal via a wireless communication module, enabling real-time synchronization of anomaly information.

[0035] Specifically, sensors are mounted at cable joints using fixed clamps, while those at bends and intersections are suspended to accommodate complex paths. Insulation resistance testing uses a megohmmeter to apply DC voltage and measure the resistance between the conductor and shield; a reading below a preset threshold triggers an anomaly. Dielectric loss testing measures the dielectric loss tangent by applying AC voltage; values ​​exceeding the standard range indicate material aging. Partial discharge detection uses a high-frequency current sensor to capture discharge pulse signals; anomaly markers are generated when the signal strength exceeds a critical value. The location information of anomaly points is obtained via GPS using latitude and longitude coordinates, packaged with warning signals, and transmitted to mobile terminals via a 4G network. By limiting the location of monitoring points and detection methods, anomaly markers are ensured to cover high-incidence areas of cable faults. Multi-dimensional detection standards enhance the comprehensiveness of anomaly identification, and the synchronous transmission of location information and warning signals shortens fault response time.

[0036] As a preferred embodiment, the solution of this application is specifically implemented as follows:

[0037] Several monitoring points are set up on the cables within the monitoring area. These points are typically located at cable joints, bends, and intersections along the cable laying path. Insulation resistance, dielectric loss, and partial discharge are tested at these monitoring points. Specifically, insulation resistance is measured using a megohmmeter at a voltage of 500V for one minute; dielectric loss is measured using a dielectric loss meter at a voltage of 10kV and a frequency of 50Hz; and partial discharge is detected using an ultrasonic partial discharge detector with a frequency range of 20kHz-200kHz.

[0038] Furthermore, monitoring points that fail the insulation resistance test, dielectric loss test, or partial discharge detection are marked as abnormal points. Specifically, monitoring points with insulation resistance test results below 100 MΩ, dielectric loss test results above 0.5%, and partial discharge detection results above 50 pC are marked as abnormal points.

[0039] This generates an early warning signal and sends the signal, along with the location information of the anomaly, to the mobile terminals of management personnel. The early warning signal includes information such as the type, severity, and location of the anomaly. For example, the early warning signal could be: "An abnormal insulation resistance of 80 MΩ has been detected in the cable line from XX substation to XX distribution room at a distance of 500 meters from the substation. Please handle this promptly."

[0040] The environmental monitoring module is used to monitor and analyze the working environment of cables. Several monitoring points are set up within the monitoring area. Rainfall and maximum temperature values ​​at the monitoring points are obtained through rain and temperature sensors during the monitoring period. The maximum values ​​of rainfall and maximum temperature at all monitoring points within the monitoring area are marked as the rainfall performance value and high temperature performance value of the monitoring area, respectively. Rainfall performance thresholds and high temperature performance thresholds are retrieved from the database. The ratio of the rainfall performance value to the rainfall performance threshold is marked as the rainfall coefficient, and the ratio of the high temperature performance value to the high temperature performance threshold is marked as the high temperature coefficient. The sum of the rainfall coefficient and the high temperature coefficient is marked as the environmental monitoring coefficient of the monitoring area. The environmental monitoring coefficients of all monitoring areas are sent to the path planning module.

[0041] Monitoring points are distributed across different locations within the monitoring area, such as areas where cables are susceptible to water accumulation and high temperatures. Rainfall and temperature sensors are deployed at these monitoring points to continuously collect cumulative rainfall and peak temperature data over the monitoring period. Rainfall and temperature performance values ​​are calculated using the maximum values ​​from each monitoring point to reflect the most severe environmental conditions the monitoring area may face. The numerical processing further transforms the rainfall and temperature performance values ​​into coefficients with unified dimensions, facilitating priority calculations in the subsequent path planning module.

[0042] Specifically, during the monitoring period, rain sensors at the monitoring points record cumulative rainfall, and temperature sensors record the highest temperature value. By selecting the maximum rainfall value from all monitoring points as the rainfall performance value and the maximum temperature value as the high temperature performance value, extreme environmental conditions within the monitoring area can be captured. For example, if a monitoring point experiences a rainstorm during the monitoring period due to terrain, its rainfall data is selected as the rainfall performance value, significantly increasing the environmental monitoring coefficient for that area. When the route planning module combines this coefficient with outliers to generate inspection routes, it can prioritize inspections of high-environmental-risk areas, thereby improving the timeliness of anomaly detection. Furthermore, since the environmental monitoring coefficient is generated based on objective sensor data, subjective errors from human judgment are avoided, ensuring the scientific nature of route planning decisions.

[0043] As a preferred embodiment, the solution of this application is specifically implemented as follows:

[0044] The specific process of the environmental monitoring module to monitor and analyze the working environment of cables includes: setting up several monitoring points in the monitoring area, obtaining the rainfall and maximum temperature values ​​of the monitoring points during the monitoring period through rain sensors and temperature sensors, marking the maximum values ​​of rainfall and maximum temperature values ​​of all monitoring points in the monitoring area as the rainfall performance value and high temperature performance value of the monitoring area, respectively, and performing numerical processing on the rainfall performance value and high temperature performance value to obtain the environmental monitoring coefficient of the monitoring area.

[0045] Specifically, 10 monitoring points are evenly distributed within each monitoring area. Each monitoring point is equipped with one rainfall sensor and one temperature sensor. The rainfall sensor is a tipping bucket rain gauge with an accuracy of 0.1 mm. The temperature sensor is a PT100 platinum resistance temperature sensor with a measurement range of -50℃ to 150℃ and an accuracy of ±0.1℃. Within a monitoring cycle (e.g., 24 hours), the rainfall sensor records rainfall data hourly, and the temperature sensor records temperature data every 10 minutes.

[0046] At the end of the monitoring period, the environmental monitoring module collects data from each monitoring point. For rainfall, the maximum cumulative rainfall across all monitoring points during the entire monitoring period is taken as the rainfall performance value for that monitoring area. For temperature, the highest temperature recorded by all monitoring points during the entire monitoring period is taken as the high temperature performance value for that monitoring area.

[0047] The path planning module is used to plan and analyze the inspection path for cables. At the end of the monitoring cycle, the number of abnormal points in the monitoring area is marked as the abnormal value of the monitoring area. All monitoring areas are sorted in descending order of abnormal value to obtain an abnormal sequence. All monitoring areas are arranged in descending order of environmental supervision coefficient to obtain an environmental sequence. The sum of the serial number of the monitoring area in the abnormal sequence and the serial number in the environmental sequence is marked as the priority value of the monitoring area. The K1 monitoring areas with the smallest priority value are marked as key areas, and the remaining monitoring areas are marked as general inspection areas. Based on the marking results of key areas and general inspection areas, the predetermined inspection path for the next monitoring cycle is generated. The predetermined inspection path meets the following requirements: the K1 monitoring areas at the beginning and end of the predetermined inspection path are both key areas, and the number of inspections for general inspection areas in the predetermined inspection path is one, while the number of inspections for key areas in the predetermined inspection path is two.

[0048] Among them, the abnormal sequence reflects the density of abnormal points in the monitoring area by sorting out the outliers, and the environmental sequence reflects the degree of environmental risk in the monitoring area by sorting out the environmental regulatory coefficient. The priority value is calculated by summing the abnormal sequence number and the environmental sequence number to comprehensively evaluate the inspection priority of the monitoring area. The division between key areas and general inspection areas is dynamically adjusted based on the priority value sorting results. The value of K1 is set proportionally according to the total number of monitoring areas. For example, when the total number of monitoring areas is 20, K1 is set to 5. The generation of the predetermined inspection path further takes into account the difference in the number of inspections between key areas and general inspection areas. Key areas are inspected twice in the path, and general inspection areas are inspected once.

[0049] Specifically, at the end of the monitoring cycle, the route planning module obtains the outliers and environmental monitoring coefficients for each monitoring area, generating anomaly sequences and environmental sequences respectively. The sequence number of each monitoring area in the anomaly sequence reflects its ranking in the number of anomalies, while its sequence number in the environmental sequence reflects its ranking in environmental risk. A priority value is obtained by adding the two sequences; a smaller priority value indicates a higher overall priority. For example, if a monitoring area ranks 2nd in the anomaly sequence and 3rd in the environmental sequence, its priority value is 5. Based on the priority values ​​of all monitoring areas, the top K1 areas are selected as key areas. When generating the inspection route, key areas are placed at the beginning and end of the route and inspected twice, while general inspection areas are inspected only once in the middle of the route. For example, when K1 is set to 3, the first 3 and last 3 monitoring areas of the inspection route are key areas, and the middle area is a general inspection area. In this way, areas with high anomaly risk and severe environmental conditions are prioritized and inspected multiple times during the inspection cycle, improving the timeliness of monitoring key areas and avoiding resource allocation imbalances caused by a single ranking.

[0050] As a preferred embodiment, the solution of this application is specifically implemented as follows:

[0051] The process of generating the predetermined inspection path for the next monitoring cycle includes the following steps:

[0052] First, all monitoring areas are sorted in descending order of outlier values ​​to obtain an anomaly sequence. For example, suppose there are 5 monitoring areas A, B, C, D, and E, with outliers of 10, 8, 6, 4, and 2 respectively, then the anomaly sequence is A, B, C, D, and E.

[0053] Secondly, all monitoring areas are arranged in descending order of their environmental regulatory coefficients to obtain an environmental sequence. For example, assuming the environmental regulatory coefficients of the five monitoring areas A, B, C, D, and E are 1.5, 1.2, 1.8, 1.0, and 1.3 respectively, the environmental sequence would be C, A, E, B, and D.

[0054] Furthermore, the sum of the monitoring area's index in the anomaly sequence and its index in the environmental sequence is used as the priority value for the monitoring area. Specifically, if area A has an index of 1 in the anomaly sequence and an index of 2 in the environmental sequence, its priority value is 3; if area B has an index of 2 in the anomaly sequence and an index of 4 in the environmental sequence, its priority value is 6; and so on, the priority values ​​for areas C, D, and E are 4, 9, and 7, respectively.

[0055] Therefore, the K1 monitoring areas with the lowest priority values ​​are marked as key areas, and the remaining monitoring areas are marked as general inspection areas. For example, assuming K1=2, areas A and C with the lowest priority values ​​are marked as key areas, and areas B, D, and E are marked as general inspection areas.

[0056] Finally, based on the marking results of key areas and general inspection areas, a predetermined inspection path for the next monitoring cycle is generated. For example, the inspection path can be generated in the order of ACBDEAC to ensure that key areas A and C are inspected at the beginning and end of the path.

[0057] The value of K1 is dynamically adjusted according to the total number of key areas to ensure that a certain number of key monitoring areas are included at both the beginning and end of the path. Key areas are checked twice in the path: the first check is used to initially identify anomalies, and the second check is used for verification. General inspection areas are checked only once to reduce redundant inspection time.

[0058] Specifically, when the path planning module generates the inspection path, it first assigns key areas to the first K1 and last K1 positions of the path to ensure that high-priority areas are covered first at the beginning and end of the inspection. General inspection areas are filled in the middle of the path. Key areas are allocated two inspection opportunities within the path. After the first inspection, the inspection robot continues to inspect subsequent areas. After completing the first inspection of all areas, it returns to the key areas for a second inspection. In this way, the anomaly marking results of key areas are verified within a single cycle, avoiding false alarms or missed alarms due to errors in a single inspection. General inspection areas only undergo a single inspection, reducing the robot's travel distance and time consumption, allowing inspection resources to be concentrated on critical areas.

[0059] like Figure 2 As shown, the capacity assessment module is used to perform capacity assessment and analysis for cable inspection: at the end of the monitoring cycle, the duration of the monitoring cycle is obtained and marked as the execution value. The execution threshold is obtained from the database, and the execution value is compared with the execution threshold: if the execution value is less than the execution threshold, it is determined that the inspection capacity of the monitoring cycle meets the requirements, and no action is taken; if the execution value is greater than or equal to the execution threshold, it is determined that the inspection capacity of the monitoring cycle does not meet the requirements, and a counter with an initial value of K2 is generated. If the execution value of the next monitoring cycle is less than the execution threshold, the counting ends and the counter is reset; if the execution value of the next monitoring cycle is greater than or equal to the execution threshold, the counter value is decremented by one. When the counter value is zero, a capacity optimization signal is generated and sent to the mobile terminal of the management personnel.

[0060] Specifically, when the execution value in a monitoring period exceeds the threshold, a counter with an initial value of K2 is generated. This counter only decrements if the execution value continues to exceed the limit in subsequent monitoring periods. If the execution value returns to normal in the next period, the counter is immediately reset and its value returns to zero; if the execution value still exceeds the limit in the next period, the counter value is decremented by one. When the counter value decrements to zero, it indicates that the insufficient capacity state has occurred K2 times consecutively. At this point, a capacity optimization signal is generated and sent to the management personnel. This mechanism judges the persistence of the capacity problem through the accumulation of data over multiple periods, avoiding misjudgments caused by a single abnormal fluctuation, while providing management personnel with clear optimization trigger conditions.

[0061] The initial value of the counter is set to K2, which is set to 3 based on historical operation and maintenance data, to construct a continuous monitoring cycle evaluation mechanism. When the execution value is first detected to exceed the limit, the counter remains in its initial state; if the limit is exceeded for two consecutive subsequent cycles, the counter decreases sequentially until it reaches zero. The triggering of the capacity optimization signal strictly follows the judgment logic of three consecutive limit exceedances, and is correlated with the inspection robot's moving speed and path complexity parameters to ensure that the evaluation results match the actual operating load of the equipment.

[0062] Specifically, when the execution value of a monitoring cycle exceeds the execution threshold, the system activates a counter with an initial value of 3. In subsequent monitoring cycles, if the execution value is detected to exceed the limit again, the counter value is decremented by one; if the execution value is detected to return to normal, the counter is immediately reset. When the counter reaches zero, it indicates that there has been an inspection timeout for three consecutive monitoring cycles, at which point a capacity optimization signal is generated. After this signal is triggered, the system automatically retrieves the path planning data and anomaly distribution heatmap of the most recent ten cycles, combined with the inspection robot's battery life parameters, to provide management personnel with a basis for decision-making regarding increasing the number of robots or optimizing the path algorithm. For example, when K2 is set to 3 and the execution values ​​for three consecutive cycles are 72 minutes, 68 minutes, and 70 minutes (the execution threshold is 65 minutes), the system generates a capacity optimization signal after the third cycle ends, and simultaneously pushes an analysis report containing historical execution value curves to the management terminal.

[0063] An online cable monitoring and early warning system based on intelligent inspection technology divides the cable coverage area into several monitoring zones during operation, generating a monitoring cycle. Within the monitoring cycle, an inspection robot sequentially monitors the status of the monitoring zones according to a predetermined inspection route. The system also performs regulatory analysis on the cable's working environment and obtains the environmental regulatory coefficient for each monitoring zone. At the end of the monitoring cycle, the number of anomalies within the monitoring zone is marked as the anomaly value. Key areas and general inspection areas are marked based on the anomaly values ​​and environmental regulatory coefficients. A predetermined inspection path for the next monitoring cycle is generated based on the marking results of the key and general inspection areas. At the end of the monitoring cycle, the duration of the monitoring cycle is obtained and marked as the execution value. The execution value is used to determine whether the cable inspection capacity meets the requirements.

[0064] The above description is merely an example and illustration of the structure of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the structure of the invention or exceed the scope defined in the claims, all of which should fall within the protection scope of the present invention.

[0065] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0066] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A cable online monitoring and early warning system based on intelligent inspection technology, characterized in that, Comprise environmental supervision module, path planning module and transport capacity evaluation module connected in turn, the path planning module is also connected with the inspection monitoring module in communication, and environmental supervision module, transport capacity evaluation module are connected with database in communication; The inspection monitoring module is used for inspection monitoring analysis of cable state: the cable coverage area is divided into several monitoring areas, a monitoring period is generated, and the monitoring area is monitored in sequence according to the established inspection route by the inspection robot in the monitoring period and the abnormal points in the monitoring area are marked; After the inspection robot completes the inspection monitoring of all the monitoring areas to be inspected according to the established inspection route, the monitoring period ends and a new monitoring period is generated; The environmental supervision module is used for monitoring analysis of cable working environment and obtains the environmental supervision coefficient of the monitoring area, and the environmental supervision coefficient of all monitoring areas is sent to the path planning module; The path planning module is used for planning analysis of the inspection path of the cable: at the end of the monitoring period, the number of abnormal point markers in the monitoring area is marked as the abnormal value of the monitoring area, and the established inspection path of the next monitoring period is generated by the abnormal value and the environmental supervision coefficient; The transport capacity evaluation module is used for transport capacity evaluation analysis of cable inspection; The specific process of the environmental supervision module for monitoring analysis of the cable working environment comprises: a plurality of supervision points are arranged in the monitoring area, the rainfall and the maximum temperature value of the supervision points in the monitoring period are obtained by the rainfall sensor and the temperature sensor, the maximum value of the rainfall and the maximum temperature value of all supervision points in the monitoring area is marked as the rainfall performance value and the high temperature performance value of the monitoring area respectively, and the rainfall performance value and the high temperature performance value are numerically processed to obtain the environmental supervision coefficient of the monitoring area; The process of obtaining the environmental supervision coefficient of the monitoring area comprises: the rainfall performance threshold and the high temperature performance threshold are called from the database, the ratio of the rainfall performance value to the rainfall performance threshold is marked as the rainfall coefficient, the ratio of the high temperature performance value to the high temperature performance threshold is marked as the high temperature coefficient, and the sum of the rainfall coefficient and the high temperature coefficient is marked as the environmental supervision coefficient of the monitoring area; The generation process of the established inspection path of the next monitoring period comprises: all monitoring areas are sorted in descending order of abnormal value to obtain an abnormal sequence, all monitoring areas are arranged in descending order of environmental supervision coefficient to obtain an environmental sequence, the sum of the sequence number of the monitoring area in the abnormal sequence and the sequence number in the environmental sequence is marked as the priority value of the monitoring area, the K1 monitoring areas with the minimum priority value are marked as key areas, and the remaining monitoring areas are marked as general inspection areas, and the established inspection path of the next monitoring period is generated according to the marking results of the key areas and the general inspection areas; The established inspection path meets the following requirements: the K1 monitoring areas at the front and the back of the established inspection path are all key areas, and the detection frequency of the general inspection areas in the established inspection path is one, and the detection frequency of the key areas in the established inspection path is two.

2. The cable online monitoring and early warning system based on intelligent patrol technology according to claim 1, characterized in that, The specific process of marking the abnormal points in the monitoring area includes: setting a plurality of monitoring points on the cable in the monitoring area, performing insulation resistance test, dielectric loss test and partial discharge detection on the cable at the monitoring points, marking the monitoring points that do not pass the insulation resistance test, dielectric loss test or partial discharge detection as abnormal points, generating a warning signal and sending the warning signal and the position information of the abnormal points to the mobile terminal of the management personnel.

3. The cable online monitoring and early warning system based on intelligent patrol technology according to claim 2, characterized in that, The specific process of the transport capacity evaluation module performing transport capacity evaluation analysis on the cable inspection includes: acquiring the length of the monitoring period at the end of the monitoring period and marking it as an execution value, obtaining an execution threshold value from the database, comparing the execution value with the execution threshold value: if the execution value is less than the execution threshold value, it is determined that the inspection transport capacity of the monitoring period meets the requirements and no processing is performed; if the execution value is greater than or equal to the execution threshold value, it is determined that the inspection transport capacity of the monitoring period does not meet the requirements, an initial value K2 of a counter is generated, and the necessity of optimizing the inspection transport capacity is evaluated through the value of the counter.

4. The cable online monitoring and early warning system based on intelligent patrol technology according to claim 3, characterized in that, The specific process of evaluating the necessity of optimizing the inspection transport capacity includes: if the execution value of the next monitoring period is less than the execution threshold value, the counting is ended and the counter value is reset; if the execution value of the next monitoring period is greater than or equal to the execution threshold value, the counter value is reduced by one; when the counter value is zero, a transport capacity optimization signal is generated and sent to the mobile terminal of the management personnel.

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