Safety management and control method of power infrastructure operations based on Beidou positioning

Abstract

The present invention discloses a method for safety management and control of power infrastructure operations based on Beidou positioning, which belongs to the field of satellite positioning technology. In order to solve the problems of inaccurate positioning and the difficulty in effectively supervising the range of movement of operators, the present invention includes the following steps: positioning system construction, positioning equipment loading, real-time positioning processing, dangerous area warning, accident monitoring processing, and regular evaluation and analysis. By using Beidou satellite ground-based augmentation technology to build a high-precision Beidou positioning system and receiving Beidou satellite signals in real time, the positioning accuracy is effectively improved, which helps to achieve high-precision positioning of infrastructure vehicles and personnel. By extracting operator data from positioning information, establishing operator information, generating dynamic data, and analyzing location characteristics and movement characteristics, the behavioral characteristics and habits of operators can be deeply understood, which helps managers better understand the situation on site, discover potential safety hazards, and take corresponding measures in a timely manner.

Description

Technical Field

[0001] The present invention relates to the field of satellite positioning technology, and in particular to a method for safety management and control of power infrastructure operations based on Beidou positioning. Background Art

[0002] Power infrastructure construction is the cornerstone of the power industry's development, involving the construction and renovation of a wide range of infrastructure, including power plants, transmission lines, and substations. This operation requires not only efficiency and precision, but also complete safety. Therefore, safety management plays a crucial role in power infrastructure construction. Effective safety management measures can maximize the safety of workers. Only when safety is ensured can workers focus on their work, minimize operational errors, and improve project quality.

[0003] In actual operation, there are still the following problems:

[0004] Traditional safety management and control methods for power infrastructure operations may rely on simple positioning technology, which may lead to inaccurate positioning and difficulty in accurately monitoring workers and vehicles, making it difficult to effectively supervise the workers' movements and operating range. At the same time, power infrastructure operation sites are often located in remote or complex terrain areas, and public network signals may be weak or unstable. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for safety management and control of power infrastructure operations based on Beidou positioning to solve the problems raised in the above background technology.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for safety management and control of power infrastructure operations based on Beidou positioning, comprising the following steps:

[0007] Positioning system construction: Establishing a Beidou positioning system, which includes Beidou satellites, ground receiving stations, and a data processing center. Utilizing Beidou satellite ground-based augmentation technology to build a high-precision Beidou positioning system, the system receives Beidou satellite signals in real time and improves positioning accuracy through ground-based augmentation technology.

[0008] Positioning equipment loading: equip workers and vehicles with Beidou positioning equipment, and receive and transmit positioning information in real time. The Beidou positioning equipment includes positioning helmets, positioning work cards, and vehicle-mounted Beidou locators;

[0009] Real-time positioning processing: establish a real-time online position feedback platform to receive and process positioning information in real time, and analyze and process it through the data processing center to generate real-time position data of vehicles and the movement range of operators;

[0010] Dangerous area warning: Establish a high-precision location management and warning platform. Based on real-time location data and the movement range of operators, determine whether operators and vehicles have entered dangerous areas. If so, an alarm will be issued to remind managers to take timely measures.

[0011] Accident monitoring and processing: real-time tracking and monitoring of operators and vehicles based on real-time location data and alarm information;

[0012] Regular assessment and analysis are conducted to analyze and evaluate the safety status of power infrastructure operations based on statistical information.

[0013] Furthermore, the positioning system construction specifically includes the following steps:

[0014] Selecting a BeiDou satellite signal reception area, establishing a ground receiving station, and configuring a ground-based augmentation system, wherein the ground-based augmentation system includes adding a differential reference station and a regional augmentation station;

[0015] Establish a data processing center, configure high-performance servers and storage devices, receive, store and process Beidou satellite signal data in real time, conduct system integration testing, and ensure that the positioning accuracy of the Beidou positioning system meets the system requirements.

[0016] Furthermore, the positioning device loading specifically includes the following steps:

[0017] Select Beidou positioning equipment, distribute positioning helmets and positioning work cards to workers, install on-board Beidou positioning devices on work vehicles, and conduct equipment debugging and calibration to ensure accurate positioning;

[0018] Establish an equipment management and maintenance system and regularly check the operating status of the equipment.

[0019] Furthermore, the real-time positioning processing further includes the following steps:

[0020] Configure servers and network equipment, establish data security and privacy protection mechanisms, receive and transmit the positioning information of workers and vehicles to the data processing center in real time, parse and process the positioning information in the data processing center, and generate real-time location data of vehicles and the movement range of workers.

[0021] Furthermore, the generating of the operator movement range specifically includes the following steps:

[0022] Obtain the positioning information collected by the data processing center and extract the operator data from the positioning information;

[0023] Preprocess the operator data to obtain the number of operators included in the operator data;

[0024] Based on the number of operators and the stored data in the database, the basic data corresponding to each operator is obtained and the operator information is established;

[0025] Establishing a time axis according to the data length of the collected positioning information;

[0026] Input the collected positioning information data into the time axis to generate dynamic data;

[0027] Extract the initial position corresponding to each operator from the dynamic data, determine the actual position of each initial position in the substation, and analyze the position characteristics of the operator;

[0028] Divide the dynamic data into several unit data segments, and obtain the action position corresponding to each operator in each unit data segment;

[0029] Obtain the initial position of the same operator and the corresponding action position of each unit data segment, establish the operator's action trajectory, and generate the action characteristics corresponding to each operator based on the action trajectory;

[0030] At the same time, the data proportion of each operator's information in each unit data segment is extracted to generate the pause characteristics of each operator;

[0031] Obtain the target unit data segment where the maximum pause feature corresponding to each operator is located, and generate position attributes based on the order of the target data segments in the dynamic data;

[0032] According to the location characteristics and movement characteristics of each operator, the movement data corresponding to each operator is established;

[0033] The real geographic coordinate information of the substation site contained in the mobile data is analyzed to generate the corresponding mobile range of each operator.

[0034] Furthermore, the dangerous area warning further includes the following steps:

[0035] Collect detailed geographic coordinate information of the substation site, including the location of high-voltage equipment and prohibited areas;

[0036] Based on the real-time location data of vehicles, the movement range of operators, and the actual geographic coordinates of the substation site, combined with the safety regulations and operation plans of power infrastructure operations, the boundaries of the dangerous areas are set and the boundary information of the dangerous areas is entered;

[0037] Compare the real-time location data of the vehicle and the movement range of the operator with the pre-set boundary information of the dangerous area. Based on the comparison results, determine in real time whether the operator and vehicle have entered the dangerous area;

[0038] If it is determined that a dangerous area has been entered, an early warning alarm will be issued through the early warning platform, wherein the early warning alarm includes sound, text message and email methods. At the same time, the early warning event record is collected, wherein the early warning event record includes the warning time, location, involved personnel, and warning method.

[0039] Furthermore, the accident monitoring process further includes the following steps:

[0040] Integrate a map function on the management platform to receive and display Beidou positioning information of workers and vehicles in real time. Use points and icons on the map to indicate the locations of workers and vehicles, and display the distribution and dynamics of on-site operations.

[0041] Integrated trajectory playback function to display the historical movement trajectory of operators and vehicles;

[0042] Based on early warning alarm information, real-time monitoring of workers and vehicles entering dangerous areas is carried out. When an object enters a dangerous area, it is marked on the map and the monitoring mechanism is triggered, which is monitored by surveillance cameras.

[0043] Respond and coordinate resources to handle security incidents and emergencies.

[0044] Furthermore, the regular evaluation and analysis may further include the following steps:

[0045] Regularly collect and analyze positioning data and early warning records, evaluate the safety status of power infrastructure operations, identify existing safety risks and hidden dangers based on the analysis results, formulate and implement improvement measures, and track and evaluate the implementation effects of the improvement measures.

[0046] Furthermore, it also includes:

[0047] Determine each trajectory point on the vehicle's historical movement trajectory, compare each trajectory point with the corresponding standard trajectory point on the standard movement trajectory, determine the number of trajectory points with a difference value greater than a preset threshold, and calculate the deviation coefficient λ of the vehicle's historical movement trajectory:

[0048]

[0049] Where N is the number of trajectory points on the historical movement trajectory; n is the number of trajectory points whose difference value is greater than the preset threshold; f is the preset threshold; w i is the coordinate information of the i-th trajectory point whose difference value on the historical moving trajectory is greater than the preset threshold; w, i The coordinate information of the i-th standard trajectory point on the standard movement trajectory corresponding to the i-th trajectory point on the historical movement trajectory whose difference value is greater than the preset threshold;

[0050] Grayscale the vehicle's historical movement trajectory, obtain the grayscale value of each pixel on the historical movement trajectory, calculate the grayscale mean and standard deviation, and calculate the safety factor of the vehicle's historical movement trajectory based on the deviation coefficient of the vehicle's historical movement trajectory;

[0051]

[0052] Where E is the safety factor of the vehicle's historical trajectory; T is the preset value of the risk factor; μ is the grayscale mean of the historical trajectory; σ is the standard deviation; M is the number of pixels on the historical trajectory; k j is the gray value of the jth pixel on the historical moving trajectory; β is the signal-to-noise ratio of the pixel on the historical moving trajectory; x is the integrated parameter;

[0053] The historical movement trajectories with a safety factor lower than the preset safety threshold are marked as dangerous movement trajectories and an alarm is issued.

[0054] Furthermore, the safety status of power infrastructure operations is analyzed and evaluated, including:

[0055] Input statistical information into a pre-trained risk event identification model to identify individual risk events;

[0056] Obtaining the correlation between each risk event and constructing an operation risk map based on the correlation; the operation risk map is used to display each risk event and their correlation during the operation;

[0057] Analyze the operation risk map to identify the risk events corresponding to each risk point in the operation risk map and the association information and impact path information corresponding to the lines between the risk points;

[0058] Based on the risk events corresponding to each risk point in the operational risk map and the associated information and impact path information corresponding to the lines between the risk points, the corresponding risk patterns are identified. Risk patterns include serial risk patterns and parallel risk patterns. Serial risk patterns indicate that one risk point triggers another risk point, while parallel risk patterns indicate that multiple risk points are triggered simultaneously, leading to greater risks.

[0059] Query the preset database based on the risk pattern and determine the predicted risk event based on the matching results;

[0060] Determine the target objects for predicting risk events;

[0061] Setting risk assessment indicators according to the target object, determining correlations between the risk assessment indicators, constructing a risk assessment indicator system based on the correlations, and setting weight coefficients for each risk assessment indicator in the risk assessment indicator system;

[0062] Obtain the parameters to be evaluated of the target object, establish a mapping relationship between the parameters to be evaluated and the risk assessment index system; determine the corresponding structure and weight coefficient in the risk assessment index system based on the mapping relationship; and evaluate the risk level of the target object based on a quantitative or qualitative method to obtain a risk assessment result.

[0063] Compared with the prior art, the present invention has the following beneficial effects:

[0064] 1. The present invention uses Beidou satellite ground-based augmentation technology to build a high-precision Beidou positioning system and receives Beidou satellite signals in real time, which can effectively improve positioning accuracy, help achieve high-precision positioning of infrastructure vehicles and personnel, and provide accurate data support for subsequent monitoring and early warning. By equipping workers and vehicles with Beidou positioning equipment, positioning information can be received and transmitted in real time. Combined with the real-time online position return platform and the high-precision position management and early warning platform, it can be determined in real time whether workers and vehicles have entered dangerous areas and issue an alarm when necessary, which helps managers to promptly discover potential safety risks and take corresponding measures to avoid or reduce the occurrence of safety accidents.

[0065] 2. The present invention can accurately locate the position of each operator by extracting the operator data from the positioning information, which helps managers to accurately grasp the distribution and movement of operators, and provide strong support for optimizing resource allocation and scheduling. By establishing operator information, generating dynamic data, analyzing location characteristics and movement characteristics, etc., it can deeply understand the behavioral characteristics and habits of operators, which helps managers to better grasp the situation at the work site, discover potential safety hazards, and take corresponding measures in a timely manner.

[0066] 3. By setting the boundaries of dangerous areas and comparing the location data of vehicles and workers in real time, the present invention can promptly detect and warn of potential safety risks. This real-time warning mechanism can significantly reduce the possibility of workers and vehicles mistakenly entering dangerous areas, thereby greatly improving the safety level of power infrastructure operations. Through the warning mechanism, safety accidents caused by workers mistakenly entering dangerous areas can be avoided, which not only protects the lives of workers, but also reduces production delays and cost losses caused by accidents, thereby improving work efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 Schematic diagram of the process of the power infrastructure operation safety management and control method of the present invention. DETAILED DESCRIPTION

[0068] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0069] To address the technical issues that traditional power infrastructure operation safety management methods may rely on simple positioning technology, which may lead to inaccurate positioning and difficulty in accurately monitoring operators and vehicles, making it difficult to effectively supervise the operators' movements and operating ranges. At the same time, power infrastructure operation sites are often located in remote or complex terrain areas, where public network signals may be weak or unstable, please refer to Figure 1 , the present invention provides the following technical solutions:

[0070] The power infrastructure operation safety management and control method based on Beidou positioning includes the following steps:

[0071] Positioning system construction: Establishing a Beidou positioning system, which includes Beidou satellites, ground receiving stations, and a data processing center. Utilizing Beidou satellite ground-based augmentation technology to build a high-precision Beidou positioning system, the system receives Beidou satellite signals in real time and improves positioning accuracy through ground-based augmentation technology.

[0072] Positioning equipment loading: equip workers and vehicles with Beidou positioning equipment, and receive and transmit positioning information in real time. The Beidou positioning equipment includes positioning helmets, positioning work cards, and vehicle-mounted Beidou locators;

[0073] Real-time positioning processing: establish a real-time online position feedback platform to receive and process positioning information in real time, and analyze and process it through the data processing center to generate real-time position data of vehicles and the movement range of operators;

[0074] Dangerous area warning: Establish a high-precision location management and warning platform. Based on real-time location data and the movement range of operators, determine whether operators and vehicles have entered dangerous areas. If so, an alarm will be issued to remind managers to take timely measures.

[0075] Accident monitoring and processing: real-time tracking and monitoring of operators and vehicles based on real-time location data and alarm information;

[0076] Regular assessment and analysis are conducted to analyze and evaluate the safety status of power infrastructure operations based on statistical information.

[0077] In the above embodiment, by using Beidou satellite ground-based augmentation technology to build a high-precision Beidou positioning system and receiving Beidou satellite signals in real time, the positioning accuracy can be effectively improved, which helps to achieve high-precision positioning of infrastructure vehicles and personnel, and provide accurate data support for subsequent monitoring and early warning. By equipping workers and vehicles with Beidou positioning equipment, positioning information can be received and transmitted in real time. Combined with the real-time online location return platform and the high-precision location management and early warning platform, it can be determined in real time whether workers and vehicles have entered dangerous areas, and an alarm can be issued when necessary, which helps managers to promptly discover potential safety risks and take corresponding measures to avoid or reduce the occurrence of safety accidents.

[0078] In the above embodiment, by tracking and monitoring the location of workers and vehicles in real time, a comprehensive understanding of the daily safety status of infrastructure construction operations can be achieved. Furthermore, regular assessments and analyses, based on statistical information, can provide guidance for improvement, thereby continuously improving the safety management of power infrastructure operations. Real-time location data can be used to more effectively deploy resources and manpower, ensuring a swift response when needed and improving the efficiency of emergency response.

[0079] In the above embodiment, by applying the high-precision positioning, time and frequency synchronization, and short message communication functions of the Beidou system, the power system can ensure more accurate time synchronization and improve the stability, reliability, and security of power grid operation.

[0080] The construction of the positioning system also includes the following steps:

[0081] Selecting a BeiDou satellite signal reception area, establishing a ground receiving station, and configuring a ground-based augmentation system, wherein the ground-based augmentation system includes adding a differential reference station and a regional augmentation station;

[0082] Establish a data processing center, configure high-performance servers and storage devices, receive, store and process Beidou satellite signal data in real time, conduct system integration testing, and ensure that the positioning accuracy of the Beidou positioning system meets the system requirements.

[0083] In the above-mentioned embodiment, by deploying a ground-based augmentation system, including the addition of differential reference stations and regional augmentation stations, the positioning accuracy of the Beidou satellite positioning system can be significantly improved. The differential reference stations can eliminate or reduce the impact of satellite signal propagation errors on positioning results, while the regional augmentation stations can further enhance signal coverage and positioning performance. This allows for high-precision positioning of workers and vehicles during power infrastructure construction operations, providing more accurate data support for safety management.

[0084] In the above embodiment, the high-precision Beidou positioning system enables more accurate monitoring of the distribution of personnel and vehicles at power infrastructure construction sites, helping managers optimize resource allocation based on actual needs and improve operational efficiency. Furthermore, in the event of an emergency, relevant personnel and vehicles can be quickly located, providing strong support for emergency response.

[0085] Positioning equipment loading also includes the following steps:

[0086] Select Beidou positioning equipment, distribute positioning helmets and positioning work cards to workers, install on-board Beidou positioning devices on work vehicles, and conduct equipment debugging and calibration to ensure accurate positioning;

[0087] Establish an equipment management and maintenance system and regularly check the operating status of the equipment.

[0088] In the above example, by equipping workers and vehicles with Beidou positioning equipment, high-precision location information can be obtained in real time, helping managers accurately understand on-site conditions and make timely decisions and dispatches. The installation of positioning equipment enables real-time monitoring of workers and vehicles. Managers can view their location, movement trajectory, and other information in real time through the system platform, thereby determining whether there are safety risks or violations and taking timely appropriate measures.

[0089] In the above embodiment, based on the positioning data, managers can more reasonably arrange the work tasks of operators and vehicles, optimize resource allocation, and at the same time, in an emergency, they can quickly locate the relevant personnel and vehicles, thereby improving the speed of emergency response.

[0090] Real-time positioning processing specifically includes the following steps:

[0091] Configure servers and network equipment, establish data security and privacy protection mechanisms, receive and transmit the positioning information of workers and vehicles to the data processing center in real time, parse and process the positioning information in the data processing center, and generate real-time location data of vehicles and the movement range of workers.

[0092] The generation of the operator movement range specifically includes the following steps:

[0093] Obtain the positioning information collected by the data processing center and extract the operator data from the positioning information;

[0094] Preprocess the operator data to obtain the number of operators included in the operator data;

[0095] Based on the number of operators and the stored data in the database, the basic data corresponding to each operator is obtained and the operator information is established;

[0096] Establishing a time axis according to the data length of the collected positioning information;

[0097] Input the collected positioning information data into the time axis to generate dynamic data;

[0098] Extract the initial position corresponding to each operator from the dynamic data, determine the actual position of each initial position in the substation, and analyze the position characteristics of the operator;

[0099] Divide the dynamic data into several unit data segments, and obtain the action position corresponding to each operator in each unit data segment;

[0100] Obtain the initial position of the same operator and the corresponding action position of each unit data segment, establish the operator's action trajectory, and generate the action characteristics corresponding to each operator based on the action trajectory;

[0101] At the same time, the data proportion of each operator's information in each unit data segment is extracted to generate the pause characteristics of each operator;

[0102] Obtain the target unit data segment where the maximum pause feature corresponding to each operator is located, and generate position attributes based on the order of the target data segments in the dynamic data;

[0103] According to the location characteristics and movement characteristics of each operator, the movement data corresponding to each operator is established;

[0104] The real geographic coordinate information of the substation site contained in the mobile data is analyzed to generate the corresponding mobile range of each operator.

[0105] In the above embodiment, by receiving and transmitting real-time positioning information of workers and vehicles, managers can gain real-time insights into the dynamic situation at the work site, helping to promptly identify potential safety risks and improve the safety and controllability of power infrastructure operations. By deploying high-performance servers and network equipment, and establishing data security and privacy protection mechanisms, the real-time and accuracy of positioning information can be ensured, while also improving data processing efficiency. This allows for the rapid generation of worker movement maps, providing timely data support for safety management.

[0106] In the above embodiment, by extracting worker data from the positioning information, each worker's position can be accurately located, helping managers accurately understand the distribution and movement of workers, providing strong support for optimizing resource allocation and scheduling. By establishing worker information, generating dynamic data, and analyzing location and movement characteristics, a deep understanding of workers' behavioral characteristics and habits can be achieved, helping managers better understand the situation at the work site, identify potential safety hazards, and take timely appropriate measures.

[0107] Dangerous area warning also includes the following steps:

[0108] Collect detailed geographic coordinate information of the substation site, including the location of high-voltage equipment and prohibited areas;

[0109] Based on the real-time location data of vehicles, the movement range of operators, and the actual geographic coordinates of the substation site, combined with the safety regulations and operation plans of power infrastructure operations, the boundaries of the dangerous areas are set and the boundary information of the dangerous areas is entered;

[0110] Compare the real-time location data of the vehicle and the movement range of the operator with the pre-set boundary information of the dangerous area. Based on the comparison results, determine in real time whether the operator and vehicle have entered the dangerous area;

[0111] If it is determined that a dangerous area has been entered, an early warning alarm will be issued through the early warning platform, wherein the early warning alarm includes sound, text message and email methods. At the same time, the early warning event record is collected, wherein the early warning event record includes the warning time, location, involved personnel, and warning method.

[0112] In the above embodiment, by setting the boundaries of the danger zone and comparing the location data of vehicles and workers in real time, potential safety risks can be discovered and warned in a timely manner. This real-time warning mechanism can significantly reduce the possibility of workers and vehicles mistakenly entering the danger zone, thereby greatly improving the safety level of power infrastructure operations. Through the warning mechanism, safety accidents caused by workers mistakenly entering the danger zone can be avoided, which not only protects the lives of workers, but also reduces production delays and cost losses caused by accidents, thereby improving work efficiency.

[0113] In the above embodiment, by compiling statistics on warning event records, managers can clearly understand information such as the time, location, people involved, and warning methods of the warning, which helps managers conduct in-depth analysis of warning events, identify potential safety hazards and management loopholes, and provide strong support for subsequent decision-making and improvements.

[0114] Accident monitoring and processing also includes the following steps:

[0115] Integrate a map function on the management platform to receive and display Beidou positioning information of workers and vehicles in real time. Use points and icons on the map to indicate the locations of workers and vehicles, and display the distribution and dynamics of on-site operations.

[0116] Integrated trajectory playback function to display the historical movement trajectory of operators and vehicles;

[0117] Based on early warning alarm information, real-time monitoring of workers and vehicles entering dangerous areas is carried out. When an object enters a dangerous area, it is marked on the map and the monitoring mechanism is triggered, which is monitored by surveillance cameras.

[0118] Respond and coordinate resources to handle security incidents and emergencies.

[0119] In the above example, by receiving and displaying real-time Beidou positioning information for workers and vehicles, managers can clearly understand the distribution and dynamics of on-site operations, enabling timely identification and prevention of potential safety incidents. Furthermore, the integrated trajectory playback function, capable of retracing historical movement trajectories, facilitates analysis of accident causes and culprits, further enhancing targeted accident prevention.

[0120] In the above embodiment, when an object enters a dangerous area, the system will highlight it on the map and trigger a monitoring mechanism, enabling real-time monitoring via surveillance cameras. This immediate feedback mechanism significantly shortens incident detection and response time, enabling management to take swift action to prevent the incident from escalating. In the event of a safety incident or emergency, the system can respond and coordinate resources. This includes dispatching nearby personnel, vehicles, and rescue equipment to ensure effective rescue and disposal measures are provided in the shortest possible time, minimizing the damage caused by the incident.

[0121] In the above embodiment, by integrating mapping functions and monitoring mechanisms, managers can more easily understand on-site operations and promptly identify and address safety hazards. This not only improves safety management efficiency but also reduces the risk of accidents caused by human negligence or improper management.

[0122] Regular evaluation and analysis also includes the following steps:

[0123] Regularly collect and analyze positioning data and early warning records, evaluate the safety status of power infrastructure operations, identify existing safety risks and hidden dangers based on the analysis results, formulate and implement improvement measures, and track and evaluate the implementation effects of the improvement measures.

[0124] In the above embodiment, by regularly collecting and analyzing positioning data and warning records, we can fully understand the safety status of power infrastructure operations and promptly identify existing safety risks and hidden dangers. Based on these analysis results, targeted improvement measures can be formulated, and safety management and control methods can be continuously optimized and improved, thereby achieving continuous improvement in safety management.

[0125] In the above example, regular assessment and analysis not only helps identify potential security issues but also tracks and evaluates the effectiveness of corrective measures. By comparing data changes before and after implementation, the effectiveness of corrective measures can be assessed, ensuring that security control measures are truly implemented and improving the relevance and effectiveness of security control.

[0126] Furthermore, it also includes:

[0127] Determine each trajectory point on the vehicle's historical movement trajectory, compare each trajectory point with the corresponding standard trajectory point on the standard movement trajectory, determine the number of trajectory points with a difference value greater than a preset threshold, and calculate the deviation coefficient λ of the vehicle's historical movement trajectory:

[0128]

[0129] Where N is the number of trajectory points on the historical movement trajectory; n is the number of trajectory points whose difference value is greater than the preset threshold; f is the preset threshold; w i is the coordinate information of the i-th trajectory point whose difference value on the historical moving trajectory is greater than the preset threshold; w, i The coordinate information of the i-th standard trajectory point on the standard movement trajectory corresponding to the i-th trajectory point on the historical movement trajectory whose difference value is greater than the preset threshold;

[0130] Grayscale the vehicle's historical movement trajectory, obtain the grayscale value of each pixel on the historical movement trajectory, calculate the grayscale mean and standard deviation, and calculate the safety factor of the vehicle's historical movement trajectory based on the deviation coefficient of the vehicle's historical movement trajectory;

[0131]

[0132] Where E is the safety factor of the vehicle's historical trajectory; T is the preset value of the risk factor; μ is the grayscale mean of the historical trajectory; σ is the standard deviation; M is the number of pixels on the historical trajectory; k j is the gray value of the jth pixel on the historical moving trajectory; β is the signal-to-noise ratio of the pixel on the historical moving trajectory; x is the integrated parameter;

[0133] The historical movement trajectories with a safety factor lower than the preset safety threshold are marked as dangerous movement trajectories and an alarm is issued.

[0134] The working principle and beneficial effects of the above technical solution are as follows: determine each trajectory point on the historical movement trajectory of the vehicle, compare each trajectory point with the corresponding standard trajectory point on the standard movement trajectory, determine the trajectory point with a difference value greater than a preset threshold as an abnormal trajectory point, determine the number of abnormal trajectory points, that is, the number of trajectory points that deviate more from the predetermined trajectory, and calculate the deviation coefficient of the historical movement trajectory of the vehicle, wherein the standard movement trajectory is the predetermined trajectory and is the set safe movement trajectory. Grayscale processing is performed on the historical movement trajectory of the vehicle, and the grayscale value of each pixel point on the historical movement trajectory is obtained. The grayscale mean and standard deviation are calculated. According to the deviation coefficient of the historical movement trajectory of the vehicle, the safety factor of the historical movement trajectory of the vehicle is calculated. The historical movement trajectory with a safety factor less than the preset safety threshold is marked as a dangerous movement trajectory, and an alarm is issued. It is convenient to monitor and manage the historical movement trajectory of the vehicle, monitor the movement risk of the vehicle, improve the safety of the vehicle movement, and realize the safety control of power infrastructure operations.

[0135] Furthermore, the safety status of power infrastructure operations is analyzed and evaluated, including:

[0136] Input statistical information into a pre-trained risk event identification model to identify individual risk events;

[0137] Obtaining the correlation between each risk event and constructing an operation risk map based on the correlation; the operation risk map is used to display each risk event and their correlation during the operation;

[0138] Analyze the operation risk map to identify the risk events corresponding to each risk point in the operation risk map and the association information and impact path information corresponding to the lines between the risk points;

[0139] Based on the risk events corresponding to each risk point in the operational risk map and the associated information and impact path information corresponding to the lines between the risk points, the corresponding risk patterns are identified. Risk patterns include serial risk patterns and parallel risk patterns. Serial risk patterns indicate that one risk point triggers another risk point, while parallel risk patterns indicate that multiple risk points are triggered simultaneously, leading to greater risks.

[0140] Query the preset database based on the risk pattern and determine the predicted risk event based on the matching results;

[0141] Determine the target objects for predicting risk events;

[0142] Setting risk assessment indicators according to the target object, determining correlations between the risk assessment indicators, constructing a risk assessment indicator system based on the correlations, and setting weight coefficients for each risk assessment indicator in the risk assessment indicator system;

[0143] Obtain the parameters to be evaluated of the target object, establish a mapping relationship between the parameters to be evaluated and the risk assessment index system; determine the corresponding structure and weight coefficient in the risk assessment index system based on the mapping relationship; and evaluate the risk level of the target object based on a quantitative or qualitative method to obtain a risk assessment result.

[0144] The working principle of the above technical solution: In this embodiment, the risk event identification model is used to identify statistical information and determine individual risk events within the statistical information. After receiving the statistical information, the risk event identification model performs calculations and inferences based on its internal parameters and algorithms. The model outputs one or more prediction results, which serve as a classification or score for the risk event. The prediction results output by the model are analyzed to determine the probability, type, or level of each risk event. Based on the prediction results, different risk events can be ranked, classified, or further analyzed.

[0145] In this embodiment, risk event associations are analyzed: the potential connections between each risk event and other risk events are analyzed. These associations may include causal relationships, triggering relationships, dependency relationships, or mutual influence relationships. Tools such as fault tree analysis (FTA), event tree analysis (ETA), risk matrix, or Bayesian network can be used to help identify and analyze these associations. Determine the type and strength of the association: For the identified associations, their type and strength are determined. Types may include direct associations (such as one event directly causing another event to occur) and indirect associations (such as the impact is transmitted through a series of intermediate events). Strength can be measured using indicators such as probability, degree of impact, or importance. Construct a risk association network: Based on the analysis results, a network of associations between risk events is constructed. This network can be a graphical model, in which nodes represent risk events and edges represent the associations between them. The direction of the edge can indicate the direction of the association (such as from cause to effect), and the weight of the edge can indicate the strength of the association. Construct an operational risk map: The risk association network is converted into a visual operational risk map. The operational risk map should clearly display each risk event and the associations between them. Such a map can be created using graphics software or professional risk management tools.

[0146] In this embodiment, parsing the operational risk graph involves identifying each risk point (typically represented as a node) in the graph and the connections between them (representing associations or impact paths). Identifying risk points: Identifying each node in the graph and identifying the risk events they represent. These risk events may be specific operational errors, equipment failures, environmental factors, etc. Parsing connections: Analyzing the connections between nodes to understand the associated information and impact paths they represent. A connection may indicate that one risk event is the direct cause of another risk event, or that there is a dependency between them. 2. Identifying risk patterns: Based on the parsed risk points and the associated information between them, corresponding risk patterns are further identified. A tandem risk pattern: When there is a clear path in the graph where the occurrence of one risk point (event) triggers or increases the probability of another risk point (event), this is a tandem risk pattern. For example, equipment failure may lead to an operational error, which in turn causes a safety incident. A parallel risk pattern: When multiple risk points (events) occur simultaneously or independently but collectively lead to a greater risk, this is a parallel risk pattern. For example, the simultaneous occurrence of severe weather and human error may jointly lead to project delays. Query a pre-set database and identify predicted risk events. Based on the identified risk patterns, query a pre-set database or risk knowledge base to identify possible predicted risk events. Database query: The pre-set database should contain known risk patterns and their corresponding predicted risk events. By matching the identified risk patterns, the corresponding predicted risk events can be found in the database. Matching result analysis: Based on the matching results of the database query, the most likely predicted risk event is determined.

[0147] In this embodiment, the target object for predicting risk events is determined. The target object may be a project, a product, a process, an organization, or any other entity requiring risk assessment. Risk assessment indicators are set: A series of risk assessment indicators are set for the target object. These indicators should comprehensively reflect the various risks the target object may face. For example, for an engineering project, risk assessment indicators may include technical difficulty, construction environment, management level, material supply, etc. The correlations between risk assessment indicators are determined: The mutual influence and correlation between risk assessment indicators are analyzed to clarify the logical relationship between them. This helps understand the interaction between different risks and their impact on the overall risk level. A risk assessment indicator system is constructed: Based on the assessment indicators and their correlations, a complete risk assessment indicator system is constructed. This system clearly reflects the relationship between the various assessment indicators. Weight coefficients are set: Weight coefficients are set for each indicator in the risk assessment indicator system. The weight coefficients reflect the importance of each indicator in the overall risk assessment. The weight coefficients can be determined through various methods, such as expert scoring, historical data analysis, and statistical methods. The parameters to be evaluated for the target object are obtained: Actual data or information on the target object is collected as the parameters to be evaluated. These parameters should correspond to the indicators in the risk assessment indicator system and be able to reflect the actual situation of the target object in all aspects. Establish a mapping relationship: Establish a mapping relationship between the parameters to be evaluated and the risk assessment indicator system. This mapping relationship should clearly state which evaluation indicator each parameter to be evaluated corresponds to, as well as the corresponding relationship between them. Assess the risk level: Based on the mapping relationship and weight coefficient, use quantitative or qualitative methods to assess the risk level of the target object. Quantitative assessment can obtain specific risk values ​​through mathematical models or algorithms; qualitative assessment uses expert judgment or empirical analysis to determine the level of risk. Obtain risk assessment results: Determine the risk level of the target object based on the assessment results. The assessment result can be a specific risk value, or a risk level or classification. This result can provide decision makers with important information about the risk status of the target object and help them formulate corresponding risk management strategies.

[0148] The beneficial effects of the above technical solution are: based on the pre-trained risk event identification model, each risk event in the statistical information is accurately identified, and data analysis and data collation are carried out by constructing an operation risk map, the operation risk map is parsed, the corresponding risk pattern is determined, the preset database is queried according to the risk pattern, and the predicted risk event is determined according to the matching result. The target object of the predicted risk event is risk assessed based on the risk assessment indicator system to assess the risk level of the target object, obtain the risk assessment result, realize the analysis and evaluation of the safety status of power infrastructure operations, and realize safety management and control.

[0149] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solution and inventive concept of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. A method for safety control of power infrastructure operations based on Beidou positioning, characterized in that: The following steps are involved: Positioning system construction: Establishing a Beidou positioning system, which includes Beidou satellites, ground receiving stations, and a data processing center. Utilizing Beidou satellite ground-based augmentation technology to build a high-precision Beidou positioning system, the system receives Beidou satellite signals in real time and improves positioning accuracy through ground-based augmentation technology. Positioning equipment loading: equip workers and vehicles with Beidou positioning equipment, and receive and transmit positioning information in real time. The Beidou positioning equipment includes positioning helmets, positioning work cards, and vehicle-mounted Beidou locators; Real-time positioning processing: establish a real-time online position feedback platform to receive and process positioning information in real time, and analyze and process it through the data processing center to generate real-time position data of vehicles and the movement range of operators; Dangerous area warning: Establish a high-precision location management and warning platform. Based on real-time location data and the movement range of operators, determine whether operators and vehicles have entered dangerous areas. If so, an alarm will be issued to remind managers to take timely measures. Accident monitoring and processing: real-time tracking and monitoring of operators and vehicles based on real-time location data and alarm information; Regular assessment and analysis: regularly collect and analyze positioning data and early warning records, and analyze and evaluate the safety status of power infrastructure operations; The accident monitoring process further includes the following steps: Integrate a map function on the management platform to receive and display Beidou positioning information of workers and vehicles in real time. Use points and icons on the map to indicate the locations of workers and vehicles, and display the distribution and dynamics of on-site operations. Integrated trajectory playback function to display the historical movement trajectory of operators and vehicles; Based on early warning alarm information, real-time monitoring of workers and vehicles entering dangerous areas is carried out. When an object enters a dangerous area, it is marked on the map and the monitoring mechanism is triggered, which is monitored by surveillance cameras. Respond to and coordinate resources to handle security incidents and emergencies; Determine each trajectory point on the historical movement trajectory of the vehicle, compare each trajectory point with the corresponding standard trajectory point on the standard movement trajectory, determine the number of trajectory points whose difference value is greater than a preset threshold, and calculate the deviation coefficient of the historical movement trajectory of the vehicle. The deviation coefficient of the historical movement trajectory of the vehicle is Calculated by the following formula: ； in, is the number of trajectory points on the historical movement trajectory; n is the number of trajectory points whose difference value is greater than the preset threshold; f is the preset threshold; The difference value of the historical moving trajectory is greater than the preset threshold. Coordinate information of each trajectory point; The difference value of the historical moving trajectory is greater than the preset threshold. The coordinate information of the i-th standard trajectory point on the standard moving trajectory corresponding to the trajectory point; Grayscale the vehicle's historical movement trajectory, obtain the grayscale value of each pixel on the historical movement trajectory, calculate the grayscale mean and standard deviation, and calculate the safety factor of the vehicle's historical movement trajectory based on the deviation coefficient of the vehicle's historical movement trajectory. The safety factor of the vehicle's historical movement trajectory is calculated using the following formula: ； in, is the safety factor of the vehicle's historical moving trajectory; is the default value of the risk factor; is the grayscale mean of the historical movement trajectory; is the standard deviation; is the number of pixels on the historical movement trajectory; The first on the historical movement trajectory Gray value of each pixel; is the signal-to-noise ratio of the pixel points on the historical movement trajectory; is the integrated parameter; The historical movement trajectories with a safety factor lower than the preset safety threshold are marked as dangerous movement trajectories and an alarm is issued.

2. The method for safety management and control of power infrastructure operations based on Beidou positioning according to claim 1, characterized in that: The positioning system construction specifically further includes the following steps: Selecting a BeiDou satellite signal reception area, establishing a ground receiving station, and configuring a ground-based augmentation system, wherein the ground-based augmentation system includes adding a differential reference station and a regional augmentation station; Establish a data processing center, configure high-performance servers and storage devices, receive, store and process Beidou satellite signal data in real time, conduct system integration testing, and ensure that the positioning accuracy of the Beidou positioning system meets the system requirements.

3. The method for safety management and control of electric power infrastructure operations based on Beidou positioning according to claim 1, characterized in that: The positioning device loading specifically further includes the following steps: Select Beidou positioning equipment, distribute positioning helmets and positioning work cards to workers, install on-board Beidou positioning devices on work vehicles, and conduct equipment debugging and calibration to ensure accurate positioning; Establish an equipment management and maintenance system and regularly check the operating status of the equipment.

4. The method for safety management and control of power infrastructure operations based on Beidou positioning according to claim 1, characterized in that: The real-time positioning process further includes the following steps: Configure servers and network equipment, establish data security and privacy protection mechanisms, receive and transmit the positioning information of workers and vehicles to the data processing center in real time, parse and process the positioning information in the data processing center, and generate real-time location data of vehicles and the movement range of workers.

5. The method for safety management and control of electric power infrastructure operations based on Beidou positioning according to claim 4, characterized in that: The generating of the operator movement range specifically further includes the following steps: Obtain the positioning information collected by the data processing center and extract the operator data from the positioning information; Preprocess the operator data to obtain the number of operators included in the operator data; Based on the number of operators and the stored data in the database, the basic data corresponding to each operator is obtained and the operator information is established; Establishing a time axis according to the data length of the collected positioning information; Input the collected positioning information data into the time axis to generate dynamic data; Extract the initial position corresponding to each operator from the dynamic data, determine the actual position of each initial position in the substation, and analyze the position characteristics of the operator; Divide the dynamic data into several unit data segments, and obtain the action position corresponding to each operator in each unit data segment; Obtain the initial position of the same operator and the corresponding action position of each unit data segment, establish the operator's action trajectory, and generate the action characteristics corresponding to each operator based on the action trajectory; At the same time, the data proportion of each operator's information in each unit data segment is extracted to generate the pause characteristics of each operator; Obtain the target unit data segment where the maximum pause feature corresponding to each operator is located, and generate position attributes based on the order of the target data segments in the dynamic data; According to the location characteristics and movement characteristics of each operator, the movement data corresponding to each operator is established; The real geographic coordinate information of the substation site contained in the mobile data is analyzed to generate the corresponding mobile range of each operator.

6. The method for safety management and control of electric power infrastructure operations based on Beidou positioning according to claim 1, characterized in that: The dangerous area early warning further includes the following steps: Collect detailed geographic coordinate information of the substation site, including the location of high-voltage equipment and prohibited areas; Based on the real-time location data of vehicles, the movement range of operators, and the actual geographic coordinates of the substation site, combined with the safety regulations and operation plans of power infrastructure operations, the boundaries of the dangerous areas are set and the boundary information of the dangerous areas is entered; Compare the real-time location data of the vehicle and the movement range of the operator with the pre-set boundary information of the dangerous area. Based on the comparison results, determine in real time whether the operator and vehicle have entered the dangerous area; If it is determined that a dangerous area has been entered, an early warning alarm will be issued through the early warning platform, wherein the early warning alarm includes sound, text message and email methods. At the same time, the early warning event record is collected, wherein the early warning event record includes the warning time, location, involved personnel, and warning method.

7. The method for safety management and control of power infrastructure operations based on Beidou positioning according to claim 1, characterized in that: The regular evaluation and analysis specifically further includes the following steps: Assess the safety status of power infrastructure operations, identify existing safety risks and hidden dangers based on the analysis results, formulate and implement improvement measures, and track and evaluate the effectiveness of the implementation of improvement measures.

8. The method for safety management and control of electric power infrastructure operations based on Beidou positioning according to claim 1, characterized in that: Analyze and evaluate the safety status of power infrastructure operations, including: Input statistical information into a pre-trained risk event identification model to identify individual risk events; Obtaining the correlation between each risk event and constructing an operation risk map based on the correlation; the operation risk map is used to display each risk event and their correlation during the operation; Analyze the operation risk map to identify the risk events corresponding to each risk point in the operation risk map and the association information and impact path information corresponding to the lines between the risk points; Based on the risk events corresponding to each risk point in the operational risk map and the associated information and impact path information corresponding to the lines between the risk points, the corresponding risk patterns are identified. Risk patterns include serial risk patterns and parallel risk patterns. Serial risk patterns indicate that one risk point triggers another risk point, while parallel risk patterns indicate that multiple risk points are triggered simultaneously, leading to greater risks. Query the preset database based on the risk pattern and determine the predicted risk event based on the matching results; Determine the target objects for predicting risk events; Setting risk assessment indicators according to the target object, determining correlations between the risk assessment indicators, constructing a risk assessment indicator system based on the correlations, and setting weight coefficients for each risk assessment indicator in the risk assessment indicator system; Obtain the parameters to be evaluated of the target object, establish a mapping relationship between the parameters to be evaluated and the risk assessment index system; determine the corresponding structure and weight coefficient in the risk assessment index system based on the mapping relationship, and evaluate the risk level of the target object based on quantitative or qualitative methods to obtain a risk assessment result.

Images