Communication line engineering safety inspection method and system based on video images

Abstract

The invention relates to the technical field of safety inspection, in particular to a communication line engineering safety inspection method and system based on video images. According to the method, a whole-line safety reference threshold value is set based on the overall importance of a line, different safety threshold values are set for different line sections by considering the geographical environment, the service load, the equipment state and other characteristics of each line section, real-time images are collected through deployed video monitoring equipment, the images are analyzed by using a computer vision algorithm, and the safety reference threshold value is obtained. Possible potential safety hazards are identified; then, calculating overall and segmented real-time risk scores based on an analysis result, and comparing the overall and segmented real-time risk scores with corresponding threshold values; when any score exceeds a corresponding threshold value, the system can automatically trigger a targeted safety inspection task; the manual inspection cost is reduced, the accuracy and timeliness of inspection are improved, and comprehensive and effective safety monitoring is realized.

Description

Technical Field

[0001] The present application relates to the technical field of safety inspection, and in particular to a communication line engineering safety inspection method and system based on video images. Background Art

[0002] With the rapid development and expansion of communication networks, the safety inspection of communication line projects has become increasingly important. These lines are not only the key infrastructure for information transmission, but also play a vital role in social development and public safety.

[0003] At present, the safety inspection of communication line projects mainly relies on a combination of regular manual inspections and fixed monitoring equipment. This method installs cameras at key nodes, collects image data regularly, and has professionals analyze and evaluate it. At the same time, inspectors are arranged to conduct on-site inspections according to predetermined cycles and routes to identify and deal with potential safety hazards.

[0004] However, fixed inspection cycles and routes cannot dynamically adjust inspection strategies according to the importance of the line and the real-time safety status, resulting in unreasonable resource allocation and difficulty in achieving comprehensive and effective safety monitoring. This situation needs to be further improved. Summary of the invention

[0005] In order to solve the problem that the existing inspection methods are difficult to achieve comprehensive and effective security monitoring, the present application provides a communication line engineering security inspection method and system based on video images, which adopts the following technical solutions: In a first aspect, the present application provides a communication line engineering safety inspection method based on video images, comprising the following steps: According to the overall importance of the communication line project, set the safety benchmark threshold of the entire line; according to the characteristics and importance of each section of the line, set the corresponding line safety threshold for each section of the line; Acquire real-time video images from each monitoring point along the route, analyze the real-time video images, and obtain current safety status assessment results; According to the current safety status assessment result, an overall real-time risk score and a real-time risk score for each section of the route are calculated; Comparing the overall real-time risk score with the overall line safety benchmark threshold, and the real-time risk score of each line section with the corresponding line safety threshold; When the overall real-time risk score exceeds the safety benchmark threshold of the entire line, or the real-time risk score of any section of the line exceeds the corresponding line safety threshold, a safety inspection of the corresponding line is triggered.

[0006] By adopting the above technical scheme, in some optical cable lines in remote mountainous areas, due to complex terrain and changeable weather, manual inspections often fail to discover line hazards in time, such as compression of optical cables caused by tree growth, tilt of poles caused by landslides, and other problems, resulting in communication interruption accidents; this application first sets a safety benchmark threshold for the entire line based on the overall importance of the line, while considering the geographical environment, business load, equipment status and other characteristics of each section of the line, setting differentiated safety thresholds for different line sections, collecting real-time images through deployed video surveillance equipment, and analyzing the images using computer vision algorithms to identify possible safety hazards; then, based on the analysis results, the overall and segmented real-time risk scores are calculated and compared with the corresponding thresholds; when any score exceeds the corresponding threshold, the system can automatically trigger a targeted safety inspection task; reducing the cost of manual inspections, improving the accuracy and timeliness of inspections, and achieving comprehensive and effective safety monitoring.

[0007] Optionally, according to the characteristics and importance of each line segment, a corresponding line safety threshold is set for each line segment, which specifically includes the following steps: According to the geographical location of each section of the line, the initial area division is carried out to obtain the core line and non-core line; Determine the line importance coefficient based on the characteristics of the communication equipment in each section of the line and the network impact of the communication line; According to the line importance coefficient, a safety threshold of a core line and a safety threshold of a non-core line are set respectively.

[0008] By adopting the above technical scheme, the traditional communication line security threshold setting is too extensive and fails to fully consider the differences in characteristics of different regions and lines. The present application first performs an initial classification based on the geographical location of the line, and divides the line into core lines and non-core lines. For example, inter-provincial backbone transmission lines are classified as core lines, and ordinary transmission lines between cities and counties are classified as non-core lines. The line importance coefficient is calculated by evaluating the equipment type, capacity, and backup status on the line, as well as the position and influence range of the line in the entire network. Finally, differentiated security thresholds are set for core lines and non-core lines based on the line importance coefficient to ensure that important lines receive stricter security supervision; the optimal allocation of security management resources is achieved, and the importance coefficient can be flexibly adjusted according to actual operating conditions, thereby improving the adaptability of the inspection plan.

[0009] Optionally, analyzing the real-time video image to obtain a current safety status assessment result specifically includes the following steps: Preprocessing the real-time video image, performing target detection and scene segmentation on the processed video image, and identifying potential threats; Classifying and locating the potential threats, and determining the specific locations of the potential threats in the communication lines; Perform risk assessment on each potential threat identified based on pre-defined security rules and threat level criteria; Generate security status assessment results for each monitoring point based on the risk assessment results of each potential threat; Based on the safety status assessment results of each monitoring point, the current safety status assessment result is formed.

[0010] By adopting the above technical solution, although a large number of cameras are deployed in the monitoring system of traditional communication lines, it can only perform simple moving target detection and cannot effectively identify complex threat scenarios such as the approach of construction machinery and external force damage, resulting in the failure to timely warn and deal with many safety accidents; this application first performs pre-processing such as noise reduction and lighting compensation on real-time video images to improve image quality, and then uses a deep learning model to perform target detection and scene segmentation to identify potential threats such as construction vehicles, personnel activities, natural disasters, etc., and determines the relative position relationship between the threat target and the communication line through a spatial positioning algorithm, and then performs a quantitative risk assessment on each identified threat based on pre-established safety rules and threat level standards, and forms an overall safety status assessment report by integrating the assessment results of each monitoring point; it realizes the location and classification of threats, provides clear guidance for subsequent disposal, and establishes a standardized risk assessment system to make the safety assessment results more objective and quantitative.

[0011] Optionally, according to the current safety status assessment result, the overall real-time risk score and the real-time risk score of each section of the route are calculated, which specifically includes the following steps: Assign a weight coefficient to each potential threat type, and the weight coefficient reflects the impact of the potential threat type on the security of the communication line; Based on the security status assessment results of each monitoring point and the weight coefficients of various potential threat types, the risk score of each monitoring point is calculated; For each route section, the risk scores of all monitoring points in the route are summarized and combined with the importance coefficient of the route to calculate the real-time risk score of each route section; The overall real-time risk score is calculated based on the real-time risk score of each line section and the line importance coefficient of each line section.

[0012] By adopting the above technical solution, this application first assigns weight coefficients to different types of potential threats such as construction damage, natural disasters, and human interference based on expert experience and historical data, and then combines the threats identified by each monitoring point with the corresponding weights to calculate the specific risk score of each monitoring point. Taking into account the importance coefficient of the line, the risk scores of all monitoring points in the line are weighted and summarized to obtain the real-time risk score of each section of the line. Finally, based on the risk score and importance coefficient of each section of the line, the overall real-time risk score of the entire communication line is calculated; through differentiated weight setting, the impact of different threats is accurately reflected, thereby improving the comprehensiveness and accuracy of risk assessment.

[0013] Optionally, after triggering the safety inspection of the corresponding line, the following steps are also included: According to the real-time risk score of each line section, the inspection needs of the line sections are graded; Generate an inspection plan including inspection focus, inspection frequency and inspection method according to the preset hierarchical inspection strategy; According to the inspection plan, an inspection resource scheduling instruction is triggered.

[0014] By adopting the above technical solution, this application first classifies the line segments based on real-time risk scores, then matches the corresponding inspection strategies according to different risk levels, clarifies the inspection focus, inspection frequency and inspection method of each level, and finally automatically triggers the corresponding resource scheduling instructions according to the generated inspection plan to reasonably allocate inspection resources such as personnel and equipment; through demand classification, the priority configuration of inspection resources is realized, thereby improving the pertinence and efficiency of inspection.

[0015] Optionally, according to the inspection scheme, triggering an inspection resource scheduling instruction specifically includes the following steps: According to the inspection plan, determine the inspection resource requirements of each key inspection line segment; Assess currently available inspection resources, including drones, ground inspection personnel, and remote monitoring equipment; Based on the inspection resource requirements and the available inspection resources, formulate a preliminary resource scheduling plan; Calculate the expected inspection coverage rate of each key inspection line segment according to the preliminary resource scheduling plan, and compare it with the preset inspection coverage rate standard; If the expected inspection coverage rate is lower than the preset inspection coverage rate standard, the resource optimization configuration program is triggered, and the preliminary resource scheduling plan is adjusted according to the resource optimization configuration program to obtain a final inspection resource scheduling plan; According to the inspection resource scheduling scheme, an inspection resource scheduling instruction is triggered.

[0016] By adopting the above technical solutions, the traditional method lacks a systematic resource scheduling solution, resulting in idle inspection personnel and equipment in some areas, while other areas are unable to complete inspection tasks in time due to insufficient resources, which seriously affects the overall effect of the inspection work; this application first clarifies the specific needs of each key line section for resources such as drones, personnel and monitoring equipment according to the inspection plan, and conducts statistics and evaluation on various types of currently available inspection resources. Then, based on resource demand and available resources, a preliminary resource scheduling plan is formulated, and the expected inspection coverage of each line section under the scheduling plan is calculated through a mathematical model, and compared with the preset standard. If the coverage rate does not meet the standard, the optimization configuration program is started to optimize the scheduling plan by reallocating resources, adjusting the inspection time, etc., and finally a resource scheduling plan that meets the coverage requirements is generated, and specific scheduling instructions are triggered accordingly; the controllability of the inspection quality is ensured through coverage constraints, and the resource utilization efficiency is improved through a dynamic optimization mechanism.

[0017] In a second aspect, the present application provides a communication line engineering safety inspection system based on video images, comprising: The threshold setting module is used to set the safety benchmark threshold of the entire line according to the overall importance of the communication line project; at the same time, according to the characteristics and importance of each section of the line, set the corresponding line safety threshold for each section of the line; A safety status assessment result evaluation module is used to obtain real-time video images of various monitoring points along the line, analyze the real-time video images, and obtain the current safety status assessment results; A real-time risk score calculation module is used to calculate the overall real-time risk score and the real-time risk score of each section of the route according to the current safety status assessment result; A comparison module, used to compare the overall real-time risk score with the safety benchmark threshold of the entire line, and the real-time risk score of each section of the line with the corresponding line safety threshold; The safety inspection trigger module is used to trigger a safety inspection of the corresponding line when the overall real-time risk score exceeds the safety benchmark threshold of the entire line, or the real-time risk score of any section of the line exceeds the corresponding line safety threshold.

[0018] Optionally, the threshold setting module includes: An initial area division unit is used to perform initial area division according to the geographical location of each line section to obtain core lines and non-core lines; A line importance determination unit, used to determine a line importance coefficient according to the characteristics of communication equipment in each line section and the network impact of the communication line; The security threshold setting unit is used to set the security threshold of the core line and the security threshold of the non-core line respectively according to the line importance coefficient.

[0019] Optionally, the security status assessment result assessment module includes: A potential threat identification unit is used to pre-process the real-time video image, perform target detection and scene segmentation on the processed video image, and identify potential threats; A threat classification and positioning unit, used to classify and locate the potential threat and determine the specific location of the potential threat in the communication line; A risk assessment unit, which is used to perform risk assessment on each potential threat identified according to predefined security rules and threat level standards; A monitoring point security status assessment unit, used to generate security status assessment results for each monitoring point based on the risk assessment results of each potential threat; The safety status evaluation result forming unit is used to form a current safety status evaluation result according to the safety status evaluation results of each monitoring point.

[0020] Optionally, the real-time risk score calculation module includes: A threat weight allocation unit is used to allocate a weight coefficient to each potential threat type, and the weight coefficient reflects the impact of the potential threat type on the security of the communication line; A monitoring point risk score calculation unit is used to calculate the risk score of each monitoring point based on the security status assessment results of each monitoring point and the weight coefficients of various potential threat types; The line real-time risk score calculation unit is used to summarize the risk scores of all monitoring points in each line section, and calculate the real-time risk score of each line section in combination with the importance coefficient corresponding to the line; The overall real-time risk score calculation unit is used to calculate the overall real-time risk score according to the real-time risk score of each line section and the line importance coefficient of each line section.

[0021] In summary, the present application includes at least one of the following beneficial technical effects: 1. This application first sets the safety benchmark threshold for the entire line based on the overall importance of the line, and considers the geographical environment, business load, equipment status and other characteristics of each section of the line, and sets differentiated safety thresholds for different line sections. The deployed video surveillance equipment collects real-time images, and uses computer vision algorithms to analyze the images to identify possible safety hazards; then, based on the analysis results, the overall and segmented real-time risk scores are calculated and compared with the corresponding thresholds; when any score exceeds the corresponding threshold, the system can automatically trigger a targeted safety inspection task; reducing the cost of manual inspections, improving the accuracy and timeliness of inspections, and achieving comprehensive and effective safety monitoring; 2. The setting of security thresholds for traditional communication lines is too extensive and fails to fully consider the differences in characteristics of different regions and lines. This application first performs an initial classification based on the geographical location of the lines, and divides the lines into core lines and non-core lines. For example, inter-provincial backbone transmission lines are classified as core lines, and ordinary transmission lines between cities and counties are classified as non-core lines. By evaluating the equipment type, capacity, and backup status on the line, as well as the position and influence range of the line in the entire network, the line importance coefficient is calculated. Finally, based on the line importance coefficient, differentiated security thresholds are set for core lines and non-core lines respectively to ensure that important lines receive stricter security supervision; the optimal allocation of security management resources is achieved, and the importance coefficient can be flexibly adjusted according to actual operating conditions, which improves the adaptability of the inspection plan; 3. This application first assigns weight coefficients to different types of potential threats such as construction damage, natural disasters, and human interference based on expert experience and historical data, and then combines the threats identified by each monitoring point with the corresponding weights to calculate the specific risk score of each monitoring point. Taking into account the importance coefficient of the line, the risk scores of all monitoring points in the line are weighted and summarized to obtain the real-time risk score of each section of the line. Finally, based on the risk score and importance coefficient of each section of the line, the overall real-time risk score of the entire communication line is calculated; through differentiated weight setting, the impact of different threats is accurately reflected, thereby improving the comprehensiveness and accuracy of risk assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a flow chart of a communication line engineering safety inspection method based on video images according to an embodiment of the present application; Figure 2 It is a flow chart of step S110 in a communication line engineering safety inspection method based on video images in an embodiment of the present application; Figure 3 It is a flow chart of step S120 in a communication line engineering safety inspection method based on video images in an embodiment of the present application; Figure 4 It is a flowchart of step S130 in a communication line engineering safety inspection method based on video images in an embodiment of the present application; Figure 5 It is a flow chart of inspection resource scheduling in a communication line engineering safety inspection method based on video images in an embodiment of the present application; Figure 6 It is a flowchart of step S530 in a communication line engineering safety inspection method based on video images in an embodiment of the present application; Figure 7 It is a module schematic diagram of a communication line engineering safety inspection system based on video images in an embodiment of the present application. DETAILED DESCRIPTION

[0023] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification and appended claims of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more listed items.

[0024] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "multiple" means two or more.

[0025] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0026] In a first aspect, the present application provides a communication line engineering safety inspection method based on video images, referring to Figure 1 , including the following steps: S110. According to the overall importance of the communication line project, a safety benchmark threshold for the entire line is set; according to the characteristics and importance of each section of the line, a corresponding line safety threshold is set for each section of the line.

[0027] The overall importance of a communication line project refers to the position and role of the communication line in the entire communication network, including the volume of business carried by the line, the number of users served, and the number of key nodes connected. The characteristics and importance of each line section are based on the geographical location characteristics of the line section (such as urban areas, suburbs, mountainous areas, etc.), environmental risk factors (such as areas prone to natural disasters, areas prone to man-made damage, etc.), and business carrying capacity.

[0028] Specifically, this embodiment uses an expert scoring method to determine the safety benchmark threshold for the entire line. Multiple communication engineering experts score the line on a percentage basis based on its overall importance, and 80% of the average score is taken as the benchmark threshold. For the safety threshold of each section of the line, the benchmark threshold is corrected in combination with the characteristic factors of the section of the line, such as the geographical location coefficient, environmental risk coefficient, etc. For example, a section of the line that passes through a mountainous area and is close to a construction area has a characteristic factor of 1.2. If the benchmark threshold is 80 points, the safety threshold of the section of the line should be set to 96 points.

[0029] S120: Acquire real-time video images from each monitoring point along the route, analyze the real-time video images, and obtain current safety status assessment results.

[0030] Among them, monitoring points refer to the video monitoring equipment collection points arranged along the line, and the monitoring equipment includes fixed cameras, ball cameras, etc. The frequency of real-time video image collection is set according to the importance of the line. The current safety status assessment results include equipment integrity status, surrounding environment status, and personnel activity status.

[0031] Specifically, the system regularly collects video data from each monitoring point through the network, uses video preprocessing technology to reduce noise and compensate for illumination to improve image quality, and then processes the image to obtain the current security status assessment result.

[0032] S130. According to the current safety status assessment result, the overall real-time risk score and the real-time risk score of each line section are calculated.

[0033] The real-time risk score refers to a risk quantification index calculated based on the current security status assessment results. The score is based on a percentage system, with higher scores indicating greater risk. The overall real-time risk score reflects the overall security status of the entire communication line, while the real-time risk score of each line segment reflects the security status of the specific line segment.

[0034] Specifically, the risk score is calculated using a weighted average method. For example, if three types of safety hazards are identified for a certain section of line: equipment damage (weight 0.4, severity 0.8), construction interference (weight 0.3, severity 0.6), and natural disaster hazards (weight 0.3, severity 0.7), then the real-time risk score for this section of line is: 100×(0.4×0.8+0.3×0.6+0.3×0.7)=71 points.

[0035] S140. Compare the overall real-time risk score with the safety benchmark threshold of the entire line, and compare the real-time risk score of each section of the line with the corresponding line safety threshold.

[0036] The system performs a comparison every preset time. The comparison results are divided into three categories: below the threshold, close to the threshold, and above the threshold.

[0037] Specifically, the overall real-time risk score is first compared with the safety benchmark threshold of the entire line, and then the real-time risk score of each line segment is compared with its corresponding line safety threshold. For example, the safety benchmark threshold of a communication line is 80 points, and the safety threshold of a certain line segment is 85 points. When the overall risk score is detected to be 75 points, but the risk score of the line segment is 87 points, the system will trigger a safety alarm for the line segment.

[0038] S150: When the overall real-time risk score exceeds the safety benchmark threshold of the entire line, or the real-time risk score of any section of the line exceeds the corresponding line safety threshold, a safety inspection of the corresponding line is triggered.

[0039] Among them, triggering a safety inspection means that when the system detects that the risk score exceeds the corresponding threshold, the preset inspection response mechanism is automatically started. The triggering methods of safety inspection include immediate triggering and delayed triggering. The specific triggering method is determined according to the degree to which the risk score exceeds the threshold.

[0040] Specifically, when the risk score exceeds the threshold by less than 10%, the system enters the early warning state and uses a delayed trigger method to start the inspection when three consecutive tests exceed the standard; when it exceeds the threshold by more than 10%, the system directly enters the alarm state and triggers the inspection immediately.

[0041] In one embodiment, referring to Figure 2 In step S110, a corresponding line safety threshold is set for each line segment according to the characteristics and importance of each line segment, which specifically includes the following steps: S111. Perform initial regional division according to the geographical location of each line segment to obtain core lines and non-core lines.

[0042] Geographic location refers to the geographical environment characteristics of the communication line, including urban core areas, urban periphery areas, township areas and remote areas. The initial regional division is mainly based on the geographical distribution characteristics of the line and the importance of the service area. The core line is usually located in the core area of ​​the city or connects important communication nodes, and the non-core line is distributed in other areas.

[0043] Specifically, the system first obtains the geographic information system data of communication lines, and divides the lines located in the city's commercial center, government agency concentration area, important communication hub and other areas into core lines, and divides the lines in other areas into non-core lines. For example, in a city's communication network, the optical fiber transmission lines surrounding the city center's business district and the communication lines connecting the government data center are classified as core lines, while the branches connecting suburban residential areas are classified as non-core lines.

[0044] S112. Determine the line importance coefficient according to the characteristics of the communication equipment in each line section and the network impact of the communication line.

[0045] The characteristics of communication equipment include factors such as equipment type, capacity, and service life. The network impact considers the position of the line in the entire communication network, including indicators such as the amount of business carried, the number of users affected, and network redundancy.

[0046] S113. According to the line importance coefficient, set the safety threshold of the core line and the safety threshold of the non-core line respectively.

[0047] The core lines are of high importance, so their baseline safety thresholds are usually set at a lower level to allow early detection and handling of potential safety hazards. The baseline safety thresholds for non-core lines can be appropriately relaxed.

[0048] In one embodiment, referring to Figure 3 In step S120, the real-time video image is analyzed to obtain the current security status assessment result, which specifically includes the following steps: S121. Preprocess the real-time video image, perform target detection and scene segmentation on the processed video image, and identify potential threats.

[0049] Among them, video image preprocessing includes basic processing operations such as image enhancement, noise removal, and illumination compensation. Object detection and scene segmentation use deep learning algorithms to identify potential threat factors such as abnormal objects in the video (such as construction machinery, suspicious personnel) and scene changes (such as terrain changes, equipment abnormalities).

[0050] Specifically, the system first reduces noise and enhances contrast of the original video, and uses adaptive histogram equalization to improve image quality. Then, it uses the target detection model to identify abnormal objects in the picture, and uses the scene segmentation algorithm to divide the image area. For example, if an excavator appears in the video of a monitoring point, the system identifies the excavator through target detection and determines its relative position relationship with the communication facilities through scene segmentation, thus determining that this is a potential threat.

[0051] S122. Classify and locate potential threats, and determine the specific location of potential threats in the communication lines.

[0052] Among them, the classification of potential threats is based on a predefined threat type library, including threats from human activities, natural disasters, equipment failures, etc. Threat location determines the specific spatial location of the threat through the geographic coordinate information of the monitoring device and the video analysis results.

[0053] Specifically, the system uses a multi-level classification method to classify the identified threats, first determining the main category of the threat and then breaking it down into subcategories. The actual geographic coordinates of the threat target are calculated by combining the GPS coordinates and field of view information of the monitoring equipment. For example, the system detects a construction activity and classifies it as a "human activity-construction operation" type, and calculates that it is located 15 meters northeast of a communication tower.

[0054] S123. Perform a risk assessment on each potential threat identified based on pre-defined security rules and threat level standards.

[0055] Among them, safety rules are judgment criteria based on the protection requirements of communication lines, including safety distance requirements, operating specification requirements, etc. The threat level standard divides potential threats into multiple levels according to their severity, and each level corresponds to a different risk assessment score. Risk assessment considers multiple dimensions such as the type, severity, and duration of the threat.

[0056] Specifically, the risk assessment adopts a matrix assessment method, with the horizontal axis representing the threat level and the vertical axis representing the influencing factors. For example, if the detected excavator is only 5 meters away from the communication line, the system determines it as a level 4 threat, lasting for more than 30 minutes, with a large impact, and the final assessment score is 85 points, indicating a high risk.

[0057] S124. Generate a security status assessment result for each monitoring point based on the risk assessment results of each potential threat.

[0058] The security status assessment result of the monitoring point comprehensively considers the risk assessment results of all potential threats found at the monitoring point. The assessment adopts a multi-threat superposition calculation method, which considers both the risk level of a single threat and the combined effect of multiple threats.

[0059] Specifically, the security status assessment of a single monitoring point adopts the principle of maximum risk priority, with the highest risk value detected by the monitoring point as the basic score, and other threats are included in the total score at 50% of the risk level.

[0060] S125. According to the safety status evaluation results of each monitoring point, a current safety status evaluation result is formed.

[0061] The current security status assessment results need to integrate the security status assessment results of all monitoring points and consider the spatial correlation between monitoring points. The assessment results include the overall security status score, the distribution of high-risk areas, and the threat development trend.

[0062] Specifically, the system uses the regional weighted average method to calculate the final safety status assessment results. First, the adjacent monitoring points are divided into the same assessment area, then different weights are assigned according to the importance of each monitoring point, and finally the weighted average is calculated.

[0063] In one embodiment, referring to Figure 4 In step S130, according to the current safety status assessment result, the overall real-time risk score and the real-time risk score of each line segment are calculated, which specifically includes the following steps: S131. Allocate a weight coefficient for each potential threat type, where the weight coefficient reflects the impact of the potential threat type on the security of the communication line.

[0064] Among them, potential threat types include natural factors, human factors, and equipment factors, etc. The weight coefficients are allocated based on historical data statistics and expert experience, and the relative importance of various threats is determined using the hierarchical analysis method. The sum of the weight coefficients is 1.

[0065] Specifically, the system divides threat types into three categories and further divides them into subcategories.

[0066] S132. Calculate the risk score of each monitoring point based on the security status assessment results of each monitoring point and the weight coefficients of various potential threat types.

[0067] The risk score calculation of a monitoring point requires comprehensive consideration of the security status assessment results of various threats detected at the point and the corresponding weight coefficients. The calculation adopts the weighted summation method, while considering the superposition effect and mutual influence of threats. The risk score is based on a percentage system, and the higher the score, the greater the risk.

[0068] S133. For each section of the route, the risk scores of all monitoring points in the route are summarized, and combined with the importance coefficient corresponding to the route, a real-time risk score of each section of the route is calculated.

[0069] The real-time risk score of each line segment needs to consider the risk scores of all monitoring points in the line and the characteristics of the line segment. The line importance coefficient is a weighted value determined based on factors such as the line's business carrying capacity and user coverage, and is used to adjust the final result of the risk score.

[0070] Specifically, the line risk score is calculated using the segmented weighted average method. First, the average risk score of all monitoring points in the line is calculated, and then multiplied by the importance coefficient of the line segment.

[0071] S134. Calculate the overall real-time risk score based on the real-time risk score of each line section and the line importance coefficient of each line section.

[0072] The overall real-time risk score is a comprehensive assessment of the safety status of the entire line, which needs to consider the real-time risk score of each section of the line and its relative importance in the entire communication network. The calculation adopts a weighted algorithm based on the network topology to ensure that the risk status of key line sections can be fully reflected.

[0073] In one embodiment, referring to Figure 5 After the safety inspection of the corresponding line is triggered, the following steps are also included: S510. Classify the inspection requirements of the line sections according to the real-time risk scores of the line sections.

[0074] Among them, the inspection demand level is set according to the real-time risk score of the line section, and the risk score is divided into different intervals, corresponding to different inspection demand levels. The inspection demand classification takes into account the risk level, importance and urgency of potential threats of the line, and is usually divided into three levels: emergency inspection, key inspection and regular inspection.

[0075] Specifically, the system adopts a dynamic grading standard. When the real-time risk score is greater than 80 points, it is judged as an emergency inspection need; a score between 50-80 points is a key inspection need; and a score below 50 points is a routine inspection need.

[0076] S520: Generate an inspection plan including inspection focus, inspection frequency and inspection method according to a preset hierarchical inspection strategy.

[0077] Among them, the graded inspection strategy is a set of differentiated inspection rules formulated according to the level of inspection needs, including inspection focus (facilities and areas that need to be inspected), inspection frequency (time intervals for inspections) and inspection methods (manual inspection, drone inspection or intelligent robot inspection, etc.). Different levels of inspection needs correspond to different inspection strategy combinations.

[0078] Specifically, for key inspection needs, the inspection plan generated by the system includes: inspection focuses on monitoring points with higher risk scores and their surrounding areas; inspection frequency is twice a day; inspection method adopts a combination of drone inspection and manual inspection. For example, after a certain line is determined to be a key inspection, the system generates an inspection plan: focus on inspecting the three high-risk monitoring points of the line section, and inspect them once at 10 am and 4 pm every day. First, the drone will conduct a quick inspection, and if any abnormality is found, a manual inspection team will be arranged to conduct a detailed inspection. S530: triggering an inspection resource scheduling instruction according to the inspection plan.

[0079] Among them, the inspection resource scheduling instructions are resource allocation and task issuance instructions automatically generated according to the inspection plan. The scheduling system will reasonably allocate and schedule inspection resources based on the status of existing inspection resources (such as the location and working status of inspection personnel, drones, and intelligent robots) and the priority of inspection tasks.

[0080] Specifically, the system uses an intelligent scheduling algorithm to comprehensively consider factors such as the geographical location, operating capacity, and task volume of inspection resources to generate the optimal scheduling plan.

[0081] In one embodiment, referring to Figure 6 In step S530, according to the inspection plan, the inspection resource scheduling instruction is triggered, which specifically includes the following steps: S531. According to the inspection plan, determine the inspection resource requirements for each key inspection line segment.

[0082] Among them, the inspection resource demand is determined based on the inspection frequency, inspection method and inspection focus specified in the inspection plan. The demand assessment takes into account factors such as the length of the line section, terrain characteristics, weather conditions, etc., and calculates the number of various resources and working hours required to complete the inspection task.

[0083] Specifically, the system uses the task decomposition method to determine resource requirements. First, the inspection task is decomposed according to the spatial and temporal dimensions, and then the required resources are calculated based on the operating efficiency of different inspection methods.

[0084] S532. Evaluate the currently available inspection resources, which include drones, ground inspection personnel, and remote monitoring equipment.

[0085] Specifically, the system obtains the current status of available resources through the resource management platform: for drones, it counts the number of online devices, battery life and task allocation; for ground inspection personnel, it counts the number of people on duty, professional categories and working hours; for remote monitoring equipment, it counts the equipment status, coverage and detection capabilities.

[0086] S533. Based on the inspection resource requirements and available inspection resources, formulate a preliminary resource scheduling plan.

[0087] S534. Calculate the expected inspection coverage rate of each key inspection line segment according to the preliminary resource scheduling plan, and compare it with the preset inspection coverage rate standard.

[0088] Among them, inspection coverage is an important indicator to measure the effectiveness of the inspection plan, including spatial coverage and temporal coverage. The calculation of the expected inspection coverage needs to consider the superposition effect of the detection range and inspection frequency of different inspection methods.

[0089] Specifically, the system uses a gridding method to calculate the inspection coverage rate, divides the line segment into multiple grid units, and calculates the proportion of time that each grid is effectively inspected within the planning cycle.

[0090] S535. If the expected inspection coverage rate is lower than the preset inspection coverage rate standard, the resource optimization configuration program is triggered, and the preliminary resource scheduling plan is adjusted according to the resource optimization configuration program to obtain the final inspection resource scheduling plan.

[0091] Among them, the resource optimization configuration program is a dynamic adjustment mechanism. When the expected coverage rate does not meet the requirements, the coverage rate can be improved by adjusting the inspection route, increasing the inspection frequency or optimizing the resource combination.

[0092] S536. Trigger an inspection resource scheduling instruction according to the inspection resource scheduling plan.

[0093] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0094] In the second aspect, the present application provides a communication line engineering safety inspection system based on video images. The communication line engineering safety inspection system based on video images of the present application is described below in combination with the above-mentioned communication line engineering safety inspection method based on video images.

[0095] Reference Figure 7 , a communication line engineering safety inspection system based on video images, comprising: The threshold setting module is used to set the safety benchmark threshold of the entire line according to the overall importance of the communication line project; at the same time, according to the characteristics and importance of each section of the line, set the corresponding line safety threshold for each section of the line; The safety status assessment result evaluation module is used to obtain real-time video images of each monitoring point along the line, analyze the real-time video images, and obtain the current safety status assessment results; A real-time risk score calculation module is used to calculate the overall real-time risk score and the real-time risk score of each line section according to the current safety status assessment results; A comparison module is used to compare the overall real-time risk score with the safety benchmark threshold of the entire line, and the real-time risk score of each section of the line with the corresponding line safety threshold; The safety inspection trigger module is used to trigger the safety inspection of the corresponding line when the overall real-time risk score exceeds the safety benchmark threshold of the entire line, or the real-time risk score of any section of the line exceeds the corresponding line safety threshold.

[0096] In one embodiment, the threshold setting module includes: An initial area division unit is used to perform initial area division according to the geographical location of each line section to obtain core lines and non-core lines; A line importance determination unit, used to determine a line importance coefficient according to the characteristics of communication equipment in each line section and the network impact of the communication line; The security threshold setting unit is used to set the security threshold of the core line and the security threshold of the non-core line respectively according to the line importance coefficient.

[0097] In one embodiment, the safety inspection trigger module further includes: Inspection demand grading unit, used to grade the inspection demand of line sections according to the real-time risk score of each line section; An inspection plan generating unit, used to generate an inspection plan including inspection focus, inspection frequency and inspection method according to a preset hierarchical inspection strategy; The inspection resource scheduling unit is used to trigger the inspection resource scheduling instruction according to the inspection plan.

[0098] In one embodiment, the inspection resource scheduling unit includes: The resource demand determination subunit is used to determine the inspection resource demand of each key inspection line section according to the inspection plan; The resource assessment subunit is used to assess the currently available inspection resources, including drones, ground inspection personnel, and remote monitoring equipment; A preliminary scheduling plan formulation subunit is used to formulate a preliminary resource scheduling plan based on inspection resource requirements and available inspection resources; A coverage calculation subunit is used to calculate the expected inspection coverage of each key inspection line segment according to the preliminary resource scheduling plan, and compare it with the preset inspection coverage standard; The resource optimization configuration subunit is used to trigger the resource optimization configuration program when the expected inspection coverage rate is lower than the preset inspection coverage rate standard, adjust the preliminary resource scheduling plan according to the resource optimization configuration program, and obtain the final inspection resource scheduling plan; The scheduling instruction triggering subunit is used to trigger the inspection resource scheduling instruction according to the inspection resource scheduling scheme.

[0099] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A communication line engineering safety inspection method based on video images, characterized in that: The steps include: According to the overall importance of the communication line project, set the safety benchmark threshold of the entire line; according to the characteristics and importance of each section of the line, set the corresponding line safety threshold for each section of the line; Acquire real-time video images from each monitoring point along the route, analyze the real-time video images, and obtain current safety status assessment results; According to the current safety status assessment result, an overall real-time risk score and a real-time risk score for each section of the route are calculated; Comparing the overall real-time risk score with the overall line safety benchmark threshold, and the real-time risk score of each line section with the corresponding line safety threshold; When the overall real-time risk score exceeds the safety benchmark threshold of the entire line, or the real-time risk score of any section of the line exceeds the corresponding line safety threshold, a safety inspection of the corresponding line is triggered.

2. The communication line engineering safety inspection method based on video images according to claim 1 is characterized in that: According to the characteristics and importance of each line section, a corresponding line safety threshold is set for each line section, which specifically includes the following steps: According to the geographical location of each section of the line, the initial area division is carried out to obtain the core line and non-core line; Determine the line importance coefficient based on the characteristics of the communication equipment in each section of the line and the network impact of the communication line; According to the line importance coefficient, a safety threshold of a core line and a safety threshold of a non-core line are set respectively.

3. The communication line engineering safety inspection method based on video images according to claim 2 is characterized in that: Analyzing the real-time video image to obtain the current security status assessment result specifically includes the following steps: Preprocessing the real-time video image, performing target detection and scene segmentation on the processed video image, and identifying potential threats; Classifying and locating the potential threats, and determining the specific locations of the potential threats in the communication lines; Perform risk assessment on each potential threat identified based on pre-defined security rules and threat level criteria; Generate security status assessment results for each monitoring point based on the risk assessment results of each potential threat; Based on the safety status assessment results of each monitoring point, the current safety status assessment result is formed.

4. The communication line engineering safety inspection method based on video images according to claim 3 is characterized in that: According to the current safety status assessment result, the overall real-time risk score and the real-time risk score of each section of the route are calculated, which specifically includes the following steps: Assign a weight coefficient to each potential threat type, and the weight coefficient reflects the impact of the potential threat type on the security of the communication line; Based on the security status assessment results of each monitoring point and the weight coefficients of various potential threat types, the risk score of each monitoring point is calculated; For each route section, the risk scores of all monitoring points in the route are summarized and combined with the importance coefficient of the route to calculate the real-time risk score of each route section; The overall real-time risk score is calculated based on the real-time risk score of each line section and the line importance coefficient of each line section.

5. The communication line engineering safety inspection method based on video images according to claim 1 is characterized in that: After triggering the safety inspection of the corresponding line, the following steps are also included: According to the real-time risk score of each line section, the inspection needs of the line sections are graded; Generate an inspection plan including inspection focus, inspection frequency and inspection method according to the preset hierarchical inspection strategy; According to the inspection plan, an inspection resource scheduling instruction is triggered.

6. The communication line engineering safety inspection method based on video images according to claim 5 is characterized in that: According to the inspection plan, triggering the inspection resource scheduling instruction specifically includes the following steps: According to the inspection plan, determine the inspection resource requirements of each key inspection line segment; Assess currently available inspection resources, including drones, ground inspection personnel, and remote monitoring equipment; Based on the inspection resource requirements and the available inspection resources, formulate a preliminary resource scheduling plan; Calculate the expected inspection coverage rate of each key inspection line segment according to the preliminary resource scheduling plan, and compare it with the preset inspection coverage rate standard; If the expected inspection coverage rate is lower than the preset inspection coverage rate standard, the resource optimization configuration program is triggered, and the preliminary resource scheduling plan is adjusted according to the resource optimization configuration program to obtain a final inspection resource scheduling plan; According to the inspection resource scheduling scheme, an inspection resource scheduling instruction is triggered.

7. A communication line engineering safety inspection system based on video images, characterized in that: include: A threshold setting module is used to set the safety benchmark threshold of the entire line according to the overall importance of the communication line project; At the same time, according to the characteristics and importance of each line section, a corresponding line safety threshold is set for each line section; A safety status assessment result evaluation module is used to obtain real-time video images of various monitoring points along the line, analyze the real-time video images, and obtain the current safety status assessment results; A real-time risk score calculation module is used to calculate the overall real-time risk score and the real-time risk score of each section of the route according to the current safety status assessment result; A comparison module, used to compare the overall real-time risk score with the safety benchmark threshold of the entire line, and the real-time risk score of each section of the line with the corresponding line safety threshold; The safety inspection trigger module is used to trigger a safety inspection of the corresponding line when the overall real-time risk score exceeds the safety benchmark threshold of the entire line, or the real-time risk score of any section of the line exceeds the corresponding line safety threshold.

8. The video image-based communication line engineering safety inspection system according to claim 7 is characterized in that: The threshold setting module comprises: An initial area division unit is used to perform initial area division according to the geographical location of each line section to obtain core lines and non-core lines; A line importance determination unit, used to determine a line importance coefficient according to the characteristics of communication equipment in each line section and the network impact of the communication line; The security threshold setting unit is used to set the security threshold of the core line and the security threshold of the non-core line respectively according to the line importance coefficient.

9. According to the video image-based communication line engineering safety inspection system of claim 8, the safety status assessment result assessment module comprises: A potential threat identification unit is used to pre-process the real-time video image, perform target detection and scene segmentation on the processed video image, and identify potential threats; A threat classification and positioning unit, used to classify and locate the potential threat and determine the specific location of the potential threat in the communication line; A risk assessment unit, which is used to perform risk assessment on each potential threat identified according to predefined security rules and threat level standards; A monitoring point security status assessment unit, used to generate security status assessment results for each monitoring point based on the risk assessment results of each potential threat; The safety status evaluation result forming unit is used to form a current safety status evaluation result according to the safety status evaluation results of each monitoring point.

10. According to the video image-based communication line engineering safety inspection system of claim 9, the real-time risk score calculation module comprises: A threat weight allocation unit is used to allocate a weight coefficient to each potential threat type, and the weight coefficient reflects the impact of the potential threat type on the security of the communication line; A monitoring point risk score calculation unit is used to calculate the risk score of each monitoring point based on the security status assessment results of each monitoring point and the weight coefficients of various potential threat types; The line real-time risk score calculation unit is used to summarize the risk scores of all monitoring points in each line section, and calculate the real-time risk score of each line section in combination with the importance coefficient corresponding to the line; The overall real-time risk score calculation unit is used to calculate the overall real-time risk score according to the real-time risk score of each line section and the line importance coefficient of each line section.

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