Power grid field personnel motion trail tracking method and system based on composite positioning driving

Abstract

The invention provides a power grid field personnel motion trail tracking method and system driven by composite positioning, and relates to the technical field of multi-source fusion positioning, and the method comprises the steps: carrying out the environment modeling of a power grid field, and carrying out the static risk region distribution identification; operating the composite positioning terminal to carry out dynamic frequency track acquisition and track risk characteristics; calling multi-dimensional attribute features of the personnel according to the ID; performing power grid field abnormal risk quantification, and outputting a dynamic danger level; performing behavior trajectory prediction according to the motion trajectory sequence and outputting a predicted trajectory sequence; extracting personnel permission characteristics, screening interveners in combination with the predicted trajectory sequence, and positioning the interveners and an intervention path; and an intervener performs motion intervention along the intervention path. The technical problems that in the prior art, power grid field emergency command lacks accurate personnel positioning and trajectory tracking functions, the real-time state and position of field personnel cannot be rapidly provided, the emergency response speed is affected, and the accident risk is increased are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of multi-source fusion positioning, and in particular to a method and system for tracking the movement trajectory of on-site power grid personnel driven by composite positioning. Background Art

[0002] At present, problems such as the complex and changeable on-site operation environment of the power grid, a large number of operating personnel, intersections between various work surfaces, and heavy dependence on manual work for on-site management still exist. On-site operating personnel still face relatively high safety risks. Among them, there are the following difficulties in the safety guarantee of on-site emergency operating personnel: On the one hand, the on-site operation environment of the power grid is usually very complex, including different power facilities, equipment, and natural environmental factors. In such an environment, the number of on-site operating personnel is large, the work tasks intersect frequently, and safety monitoring often relies on manual work during the operation process. It is difficult to track the dynamic information of all operating personnel in real time, which easily causes monitoring blind spots and potential safety hazards. On the other hand, traditional positioning technologies are mainly applied to outdoor environments. However, in complex indoor or underground power grid operation areas, the occlusion of satellite signals results in low positioning accuracy and cannot meet the requirements of indoor precise positioning. To make up for this deficiency, indoor positioning technologies have been gradually introduced, but the compatibility and accuracy between different positioning systems are still challenges, resulting in the lack of accurate positioning information of operating personnel, thus affecting the safety management and behavior monitoring of on-site personnel. Summary of the Invention

[0003] This application provides a method and system for tracking the movement trajectory of on-site power grid personnel driven by composite positioning, aiming to solve the technical problem that the existing on-site emergency command of the power grid lacks accurate personnel positioning and trajectory tracking functions, cannot quickly provide the real-time status and location of on-site personnel, affects the emergency response speed, and increases the accident risk.

[0004] In the first aspect disclosed in this application, a method for tracking the movement trajectory of on-site personnel in a power grid driven by composite positioning is provided. The method includes: after performing environmental modeling on the power grid site to obtain a power grid operation area, marking the distribution of static risk areas in the power grid operation area; running a composite positioning terminal to collect the dynamic frequency trajectory of on-site personnel, and through trajectory feature analysis of the collected movement trajectory sequence, outputting trajectory risk features, where the movement trajectory sequence is visualized in the power grid operation area; calling the multi-dimensional attribute features of the on-site personnel according to the ID; using the multi-dimensional attribute features of the personnel as an evaluation benchmark, quantifying the abnormal risk in the power grid site based on the movement trajectory sequence, and outputting a dynamic danger level; sending a hierarchical early warning reminder to the on-site personnel according to the dynamic danger level, and after the non-response duration of the on-site personnel to the hierarchical early warning reminder meets a preset response window, predicting the behavior trajectory based on the movement trajectory sequence and outputting a predicted trajectory sequence; extracting the personnel authority features from the multi-dimensional attribute features of the personnel, and combining with the predicted trajectory sequence to screen intervention personnel, locate the intervention personnel and the intervention path; after receiving the intervention instruction, the intervention personnel perform movement intervention on the on-site personnel along the intervention path.

[0005] In the second aspect disclosed in this application, a system for tracking the movement trajectory of on-site personnel in a power grid driven by composite positioning is provided. The system is used for the method for tracking the movement trajectory of on-site personnel in a power grid driven by composite positioning as described above. The system includes: a risk distribution marking module, which is used for marking the distribution of static risk areas in the power grid operation area after performing environmental modeling on the power grid site to obtain a power grid operation area; a trajectory feature analysis module, which is used for running a composite positioning terminal to collect the dynamic frequency trajectory of on-site personnel, and through trajectory feature analysis of the collected movement trajectory sequence, outputting trajectory risk features, where the movement trajectory sequence is visualized in the power grid operation area; a personnel attribute feature calling module, which is used for calling the multi-dimensional attribute features of the on-site personnel according to the ID; an abnormal risk quantification module, which is used for using the multi-dimensional attribute features of the personnel as an evaluation benchmark, quantifying the abnormal risk in the power grid site based on the movement trajectory sequence, and outputting a dynamic danger level; a predicted trajectory sequence output module, which is used for sending a hierarchical early warning reminder to the on-site personnel according to the dynamic danger level, and after the non-response duration of the on-site personnel to the hierarchical early warning reminder meets a preset response window, predicting the behavior trajectory based on the movement trajectory sequence and outputting a predicted trajectory sequence; an intervention personnel screening module, which is used for extracting the personnel authority features from the multi-dimensional attribute features of the personnel, and combining with the predicted trajectory sequence to screen intervention personnel, locate the intervention personnel and the intervention path; a movement intervention module, which is used for the intervention personnel to perform movement intervention on the on-site personnel along the intervention path after receiving the intervention instruction.

[0006] One or more technical solutions provided in this application have at least the following beneficial effects: Through environmental modeling and identification of the distribution of static risk areas, potential high-risk areas can be clearly marked within the power grid operation area, which provides a spatial basis and a risk identification framework for subsequent personnel trajectory tracking and risk assessment, effectively enhancing the visualization and accuracy of on-site safety management; by operating a composite positioning terminal to collect the dynamic frequency trajectories of on-site personnel and analyzing the characteristics of the movement trajectory sequence, the real-time position, movement pattern, and behavior characteristics of personnel in the power grid operation area can be comprehensively obtained. The visualization display of this data enables managers to understand the movement of on-site personnel in real time, promptly discover potential safety hazards or abnormal behaviors, and improve the efficiency and safety of on-site personnel behavior monitoring; by invoking the multi-dimensional attribute characteristics of on-site personnel, personalized risk assessment of personnel can be carried out based on these characteristics. Combining with their actual movement trajectory data, the risk level of personnel in the power grid operation area can be more accurately quantified. This dynamic risk quantification method not only improves the accuracy of safety warnings but also can flexibly adjust response measures according to the characteristics of personnel; according to the dynamic danger level and the actual situation of on-site personnel, graded warning reminders are sent to them. When personnel do not respond in a timely manner within the preset response window, by predicting their future behavior trajectories, potential dangers are identified in advance and a basis for subsequent intervention measures is provided. This mechanism enhances the risk prediction ability, enabling safety management to intervene in advance and reducing the probability of accidents; extracting personnel permission characteristics and screening intervention personnel in combination with the predicted trajectory sequence, locating the intervention personnel and the intervention path to ensure that the intervention personnel can quickly and effectively reach the target area, which not only improves the intervention efficiency but also enhances the accuracy and timeliness of emergency response; after receiving the instructions, the intervention personnel quickly implement movement intervention on on-site personnel along the predetermined path, effectively preventing personnel from entering dangerous areas or causing accidental accidents, improving the response speed of on-site safety management, and ensuring the safety of the operation environment.

[0007] The above description is only an overview of the technical solution of this application. In order to understand the technical means of this application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features, and advantages of this application more obvious and understandable, the following specifically gives the specific embodiments of this application. Brief Description of the Drawings

[0008] Figure 1 It is a schematic flow chart of the method for tracking the movement trajectory of on-site personnel in the power grid driven by composite positioning provided by the embodiment of this application.

[0009] Figure 2 It is a schematic diagram of the arrival angle method in the method for tracking the movement trajectory of on-site personnel in the power grid driven by composite positioning provided by the embodiment of this application.

[0010] Figure 3Schematic structural diagram of a power grid on-site personnel movement trajectory tracking system driven by composite positioning provided by an embodiment of the present application.

[0011] Explanation of reference numerals: Risk distribution identification module 10, trajectory feature analysis module 20, personnel attribute feature call module 30, abnormal risk quantification module 40, predicted trajectory sequence output module 50, intervention personnel screening module 60, motion intervention module 70. Detailed implementation manners

[0012] By providing a power grid on-site personnel movement trajectory tracking method and system driven by composite positioning in an embodiment of the present application, the technical problem in the prior art that the emergency command of the power grid on-site lacks accurate personnel positioning and trajectory tracking functions, cannot quickly provide the real-time status and location of on-site personnel, affects the emergency response speed, and increases the accident risk is solved.

[0013] After introducing the basic principle of the present application, various non-limiting implementation manners of the present application will be specifically introduced below in conjunction with the drawings of the specification. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0014] Embodiment 1, as Figure 1 shown, an embodiment of the present application provides a power grid on-site personnel movement trajectory tracking method, and the method includes: After performing environmental modeling on the power grid on-site to obtain a power grid operation area, static risk area distribution identification is performed in the power grid operation area.

[0015] Through architectural design drawings, 3D scans, UAV aerial photography images, etc., collect geographical information, building layouts, positions of power facilities, and other key environmental data of the power grid on-site. According to these data, perform environmental modeling on the power grid on-site to obtain a power grid operation area. According to the actual usage requirements of the power grid operation area, divide the area into different working areas, dangerous areas, safety areas, etc. The static risk area is a known potential dangerous area within the power grid operation area, usually a fixed risk area caused by factors such as the physical properties of facilities, environmental conditions, or the nature of operations. For example, the high-voltage area of a substation, the flammable and explosive area around facilities, etc. By analyzing the environmental data and operation processes of the power grid operation area, mark out the static risk areas.

[0016] Run the composite positioning terminal to collect the dynamic frequency trajectories of on-site personnel, and output trajectory risk features by performing trajectory feature analysis on the collected motion trajectory sequence. Among them, the motion trajectory sequence is visualized in the power grid operation area.

[0017] On-site personnel wear composite positioning terminals, which integrate outdoor Beidou satellite positioning modules, indoor Bluetooth AOA modules, and multi-axis sensor modules to provide accurate positioning data. Dynamic frequency trajectory collection is carried out, that is, the terminal continuously collects the position information of on-site personnel in the power grid operation area, records the movement trajectory of personnel, and according to needs, the terminal updates the position at a higher frequency, such as updating the position information once per second, which helps to capture the real-time behavior and dynamic changes of personnel.

[0018] Through the composite positioning terminal, a movement trajectory sequence containing time and position data is collected, and this sequence describes the path of personnel in the power grid operation area. By analyzing the collected movement trajectory, multiple features of the trajectory are extracted, including trajectory direction features, trajectory speed features, risk area features, and trajectory stability features. According to the extracted trajectory features, trajectory risk features are output.

[0019] Among them, through the graphical interface, these dynamic movement trajectory sequences are displayed on the map of the power grid operation area to help monitoring personnel quickly identify the positions, movement paths, and potential risks of on-site personnel. Common visualization methods include marking the risk level with different colors or symbols, or overlapping the trajectory with static risk areas to detect and respond to possible safety hazards in a timely manner.

[0020] Call the multi-dimensional attribute features of the on-site personnel according to the ID.

[0021] The ID is the unique identifier of the on-site personnel. The multi-dimensional attribute features of the personnel are called and obtained through the ID of the on-site personnel. These multi-dimensional attribute features not only include the basic information of the personnel, but also include various types of information related to their work safety in the power grid operation area, specifically including: personal basic information, such as name, position, working years, etc.; personnel health information, such as the physical health status of the personnel, past accident records, special health requirements, etc.; position skill features, such as the operation skills of power facilities of the personnel, whether they hold relevant safety qualification certificates, whether they have received power grid safety training, etc.; historical movement trajectories, according to the past work history of the personnel in the power grid operation area, historical trajectory data is extracted, which helps to judge the behavior pattern of the personnel and whether there are potential risk behaviors; permission features, for example, some personnel may have specific operation permissions to enter certain dangerous areas, while some personnel do not have such permissions. Based on the personnel ID, relevant multi-dimensional attribute data is retrieved from the database, and these data are stored in different databases such as the employee management system, personnel health record system, training record system, etc. These information are integrated through API or query operations to obtain the multi-dimensional attribute features of the personnel.

[0022] Taking the multi-dimensional attribute features of the personnel as the evaluation benchmark, the abnormal risk in the power grid site is quantified based on the movement trajectory sequence, and a dynamic danger level is output.

[0023] Comprehensively analyze the movement trajectory sequence of personnel and their multi-dimensional attribute characteristics. Specifically, first evaluate whether the movement trajectory of personnel has entered the calibrated static risk areas, such as high-voltage areas, equipment dangerous areas, etc. At this time, combine the trajectory characteristics with the risk area characteristics to determine whether there is potential danger and output a risk assessment value. Then, based on the multi-dimensional attribute characteristics of personnel, such as whether they have operation qualifications, health status, etc., judge the possibility of the personnel entering the risk area and their response capabilities. If a person in poor health enters a high-risk area, the risk assessment value will be correspondingly increased. According to the calculated risk assessment value, output a dynamic danger level for on-site personnel, such as low risk, medium risk, high risk, to help the staff take timely response measures.

[0024] Send a hierarchical warning reminder to the on-site personnel according to the dynamic danger level. After the non-response duration of the on-site personnel to the hierarchical warning reminder meets the preset response window, perform behavior trajectory prediction based on the movement trajectory sequence and output the predicted trajectory sequence.

[0025] According to the output dynamic danger level, send a warning reminder of the corresponding level to the on-site personnel. For example, low-risk personnel receive a general reminder, and high-risk personnel receive an emergency notice. The warning reminder includes suggestions or instructions, such as "Please leave the high-risk area as soon as possible" or "Please execute an emergency evacuation".

[0026] After the warning reminder, monitor the response status of the on-site personnel from the moment of the warning reminder. If the personnel do not respond to the warning, such as not performing the evacuation operation or not providing feedback confirmation information, record the non-response duration. The preset response window is a time threshold, usually in seconds. If the on-site personnel do not respond within this time, trigger further behavior prediction and intervention measures. The setting of this response window can be adjusted according to the urgency of on-site operations.

[0027] When the non-response duration exceeds the preset response window, perform behavior trajectory prediction based on the movement trajectory sequence of the on-site personnel. The trajectory prediction is based on historical trajectory data and current dynamic trajectory characteristics to speculate on the future position and action direction of the personnel, and generate a predicted trajectory sequence for the future time period. These predicted trajectories will show the areas that the personnel may go to, helping the security personnel to take preventive measures in advance.

[0028] Extract the personnel authority characteristics from the multi-dimensional attribute characteristics of the personnel to screen the intervention personnel in combination with the predicted trajectory sequence, and locate the intervention personnel and the intervention path.

[0029] Personnel authority features are extracted from personnel's multi-dimensional attribute features. Personnel authority features include accessible areas, operable equipment, whether they are safety officers or emergency intervention officers, etc. Each on-site personnel has different authority levels, which are usually related to the personnel's functions, operating qualifications, job responsibilities, etc. For example, some personnel have the authority to enter high-risk areas, while others are limited to low-risk areas.

[0030] Combine the predicted trajectory sequence with the personnel authority characteristics. For personnel who enter high-risk areas or violate regulations, decide whether they can enter the intervention based on the authority characteristics of other personnel. For example, if the predicted trajectory shows that an unauthorized person is about to enter a high-risk area, mark the person who has the authority to enter the high-risk area as the intervention personnel. And calculate the intervention path based on the current position of the intervention personnel and the predicted trajectory sequence. The intervention path refers to the route taken by the intervention personnel to reach the predicted position of the on-site personnel, ensuring that the intervention personnel can intervene in the on-site personnel quickly and effectively.

[0031] After receiving the intervention instruction, the intervention personnel perform the movement intervention of the on-site personnel along the intervention path.

[0032] After identifying the intervention personnel, the intervention instructions are sent through the positioning device, communication device or APP. The intervention personnel who receive the intervention instructions quickly rush to the location of the on-site personnel according to the provided intervention path and the designated route, and take appropriate intervention measures according to the situation to guide the personnel out of the dangerous area, such as physical or verbal intervention, such as guiding, pushing away, and instructing evacuation. Through the above process, the safety of the on-site personnel of the power grid is more comprehensively monitored and intervened, thereby reducing the risks in power grid operations.

[0033] Furthermore, the composite positioning terminal is operated to collect the dynamic frequency trajectory of the on-site personnel, and the trajectory risk characteristics are output by analyzing the trajectory characteristics of the collected motion trajectory sequence. The method includes: The intermittent trajectory of the on-site personnel is collected through the composite positioning terminal, and the intermittent trajectory sequence is visualized in the power grid operation area, wherein the on-site personnel carry the composite positioning terminal; taking the static risk area distribution as a risk assessment benchmark, the trajectory feature analysis of the intermittent trajectory sequence is performed to obtain the trajectory risk feature, wherein the trajectory risk feature includes trajectory direction feature, trajectory speed feature and risk area feature; according to the trajectory risk feature, the continuous tracking function of the composite positioning terminal is triggered, the continuous trajectory of the on-site personnel is collected to obtain a continuous trajectory sequence, wherein the intermittent trajectory sequence and the continuous trajectory sequence constitute the motion trajectory sequence.

[0034] On-site personnel carry composite positioning terminals. During the execution of their tasks, these devices automatically record the personnel's locations at preset time intervals, for example, every 5 minutes or at each task change point. This intermittent acquisition method can effectively reduce data storage and processing requirements while still maintaining reasonable monitoring of personnel dynamics. The collected intermittent movement trajectory sequences are transmitted to the central monitoring system and visualized on the digital map of the power grid operation area, enabling the monitoring personnel to intuitively see the location changes and movement trends of each person.

[0035] Analyze the movement trajectory characteristics of on-site personnel using the intermittent trajectory sequences and conduct risk assessments based on the defined static risk areas. For example, if a person's trajectory shows that they enter a high-risk area, the risk level assessment for that person will be increased. The obtained trajectory risk characteristics include trajectory direction characteristics, trajectory speed characteristics, and risk area characteristics. Among them, analyzing the trajectory direction characteristics is to analyze the main direction of the person's movement and identify whether they are moving towards or away from a specific risk area; analyzing the trajectory speed characteristics is to calculate the person's movement speed at different time points and determine whether their movement speed is abnormal; analyzing the risk area characteristics is to determine whether the person enters or approaches a known static risk area, such as a high-voltage area or a restricted area.

[0036] If the trajectory risk characteristics indicate that a person is at risk, the composite positioning terminal will automatically switch from the intermittent tracking mode to the continuous tracking mode. This usually occurs when a person enters a high-risk area or their behavior shows an abnormal pattern. In the continuous tracking mode, the positioning terminal collects the person's location data at a higher frequency, for example, recording the location once per second, thereby generating a continuous trajectory sequence. The intermittent trajectory sequence and the continuous trajectory sequence together constitute a complete movement trajectory sequence, providing the system with a comprehensive monitoring view from rough to fine.

[0037] Furthermore, taking the distribution of the static risk areas as the risk evaluation benchmark, analyzing the trajectory characteristics of the intermittent trajectory sequence to obtain the trajectory risk characteristics, the method includes: Collect the end directions of K intermittent movement trajectories in the intermittent trajectory sequence and output K intermittent trajectory directions; perform direction stability aggregation on the K intermittent trajectory directions to obtain the trajectory direction characteristics; extend the trajectory direction characteristics in the power grid operation area to select the risk area characteristics that fall into the trajectory direction characteristics in the static risk area distribution box; based on the trajectory acquisition interval period, calculate the movement speeds of the K intermittent movement trajectories to obtain K intermittent movement speeds, and then calculate the trajectory acceleration and the average trajectory speed according to the K intermittent movement speeds, where the trajectory acceleration and the average trajectory speed constitute the trajectory speed characteristics.

[0038] The end direction refers to the movement direction at the end moment of each intermittent movement trajectory. For each intermittent movement trajectory, the last few sampling points of the trajectory are identified, and the direction of the end is calculated based on the position information of these points. For example, the vector direction between the last two points is calculated as the end direction of the trajectory. For each of the K intermittent movement trajectories, the corresponding end direction is calculated. Finally, a list containing the directions of the K intermittent trajectories is output.

[0039] Direction stability refers to the degree of change in the direction of a person during movement. If the movement direction of a person remains stable, the change in direction will be relatively small; conversely, if the direction changes frequently, it indicates that the movement direction is unstable. Analyze the directions of the K intermittent trajectories, aggregate the direction changes of each trajectory. For example, the stability of the direction is measured by calculating the standard deviation or average change of the direction change. The higher the stability, the smaller the direction change, and vice versa, the larger the direction change. The aggregated direction stability information is used as the trajectory direction feature. This feature describes the stability or consistency of the movement direction of a person throughout the intermittent trajectory sequence. By analyzing the stability of the direction, the regularity of a person's movement during the movement process can be identified.

[0040] The trajectory direction feature describes the direction of a person's movement. Simulate the extended paths of these directions in the power grid operation area according to the trajectory direction feature. Based on the extended trajectory direction feature, identify the risk areas in the power grid operation area that may fall within the range of this direction. These risk areas are identified based on the static risk area distribution. Specifically, by calculating the intersection of the trajectory direction feature and each static risk area, the parts of the risk areas that may be entered are framed. For example, if a certain trajectory direction points to a known high-risk area, then mark this area as a potential risk area feature.

[0041] Based on the trajectory acquisition interval period, calculate the movement speed of each intermittent movement trajectory. The speed calculation is obtained by measuring the distance and time difference between two consecutive sampling points. For example, if the distance between two acquisition points is d and the acquisition time interval is t, then the speed v is v = d / t. After calculation, K intermittent movement speeds are obtained.

[0042] Acceleration is a quantity that describes the change in speed, which is obtained by calculating the change in speed between two consecutive sampling intervals. For example, if the speed in the first interval is and the speed in the second interval is and the time interval is , then the acceleration is . The average trajectory speed is the average value of all calculated speed values. This average value provides an overall speed feature, reflecting the average movement rate of the entire trajectory sequence.

[0043] The calculated trajectory acceleration and the average value of the trajectory velocity are combined to form a trajectory velocity feature, which can comprehensively describe the dynamic motion characteristics of personnel on the trajectory, including the overall performance of velocity and acceleration.

[0044] Furthermore, according to the trajectory risk feature, the continuous tracking function of the composite positioning terminal is triggered to continuously collect the trajectory of the on-site personnel, and a continuous trajectory sequence is obtained. The method includes: Preset the continuous tracking trigger conditions, where the continuous tracking trigger conditions include an acceleration trigger constraint and a velocity trigger constraint; when the trajectory acceleration in the trajectory velocity feature satisfies the acceleration trigger constraint, the average value of the trajectory velocity in the trajectory velocity feature satisfies the velocity trigger constraint, and the risk area feature is a non-empty set, the continuous tracking function of the composite positioning terminal is triggered.

[0045] Define specific continuous tracking trigger conditions to determine when to switch from the intermittent trajectory collection mode to the continuous tracking mode. These trigger conditions include an acceleration trigger constraint and a velocity trigger constraint. Among them, acceleration is a physical quantity that describes the rate of change of an object's motion. In the power grid operation area, some special activities, such as rapid movement and violent exercise, may indicate abnormal behavior of on-site personnel or approaching a dangerous area. Set a threshold. When the acceleration of on-site personnel exceeds this threshold, it means that their behavior may have a higher risk, such as quickly moving into a dangerous area. For example, if the acceleration of a person reaches 2 m / s², it is determined that this behavior requires further attention and the continuous tracking is triggered; velocity is the displacement of an object per unit time. In the power grid operation area, the change in the velocity of personnel can reflect whether they are moving along the predetermined route or whether there are abnormal behaviors, such as running rapidly. Set another threshold. When the velocity of a person exceeds a certain preset value, such as 5 m / s, it is determined that the behavior or movement speed of the person is abnormal, which may indicate the approach of danger or a potential emergency, and the continuous tracking will be triggered at this time.

[0046] When the trajectory acceleration and trajectory velocity of a person simultaneously meet the preset trigger thresholds, for example, the velocity reaches 5 m / s and the acceleration exceeds 2 m / s², and the risk area feature is a non-empty set, that is, the person has entered a high-risk area, it is determined that the behavior of this person has a relatively high potential risk. In this case, the continuous tracking function of the composite positioning terminal is activated, which makes the terminal device no longer collect trajectory data intermittently, but perform real-time tracking at a higher frequency. This high-frequency data collection can accurately capture the behavior changes of personnel and ensure a quick response at critical moments.

[0047] Furthermore, the composite positioning terminal is integrated with an outdoor Beidou satellite positioning module, an indoor Bluetooth AOA module, and a multi-axis sensor module.

[0048] The outdoor Beidou satellite positioning module adopts the positioning technology of the Beidou satellite navigation system. The principle of Beidou satellite positioning is radio pseudo-range positioning. A satellite network composed of multiple satellites is established in space. Through the rational design of satellite orbit distribution, users can observe at least three satellites at any location on the earth. Since the position of a satellite is determined at a specific time, users can calculate their own coordinates as long as they measure the distance from them. If the spatial positions of points A, B, and C have been determined in space, and the distances from the fourth point D to the above three points are all known, the spatial position of D can be determined. The principle is as follows: Because the distance between the position of point A and AD is known, it can be inferred that point D must be located on the surface of a sphere with A as the center and AD as the radius. This method can also obtain two other spheres with B and C as the center, that is, point D must be at the intersection of these three spheres, that is, three-sphere intersection positioning.

[0049] The indoor Bluetooth AOA module uses the AOA (angle of arrival) method, which does not require multiple signal receiving ends, but only requires one signal receiving end to locate the transmitter to be tested. This method is based on the angle between the transmitted signal reaching the antenna direction and the antenna axis through two array antennas, and then uses TDOA (time difference of arrival method) to solve the distance between the signal transmitter and the two antennas, such as Figure 2 As shown in the figure, the coordinates of the signal transmitter are further solved by using the size of ∠1 and ∠2 using geometric relationships. The AOA method is easily affected by the environment and requires not only high-precision transmission signals but also the two positions to be in the same plane, which is highly complex.

[0050] In the multi-axis sensor module, multi-axis refers to acceleration sensor (i.e. accelerometer), angular velocity sensor (i.e. gyroscope), and magnetic induction sensor (i.e. electronic compass). The data measured by these three types of sensors can be decomposed into forces of the three axes of X, Y, and Z in the spatial coordinate system. Therefore, they are often called 3-axis accelerometers, 3-axis gyroscopes, and 3-axis magnetometers. By adding a pressure sensor to the above nine-axis sensors, altitude data can be obtained. These sensor combinations are called ten-axis sensors.

[0051] Acceleration sensor data can determine the placement state of an object. For example, a safety helmet equipped with an acceleration sensor can trigger the corresponding rotation of the screen based on the front-back state of the helmet. However, it is impossible to know the speed of flipping and rotation of the object, and the instantaneous state of the object cannot be detected. At this time, a gyroscope needs to be added. Through the integration operation of the acceleration and the gyroscope, the motion state of the object can be obtained. There is a small difference between the integration operation and the real state, which has little impact in a short time, but this error will accumulate continuously. As the usage time increases, there will be an obvious deviation. For a 6-axis device, after rotating 360 degrees, the image cannot return to the origin. This is the reason, just like a person getting lost and not being able to find the north. At this time, an accurate direction is needed, so a magnetometer is introduced to find the correct direction for correction. The fusion algorithm calculates the correct posture of the object through the data of these 9 axes.

[0052] Through the organic combination of these three modules, the composite positioning terminal provides comprehensive and accurate positioning capabilities. Whether it is in a vast outdoor area, a limited indoor space, or complex dynamic behaviors, it can perform high-precision real-time tracking and behavior analysis to ensure the safety monitoring and management of the power grid operation area.

[0053] Furthermore, intermittent trajectory collection of on-site personnel is performed through the composite positioning terminal, and the intermittent trajectory sequence is visualized in the power grid operation area. The method includes: In a preset low-frequency positioning window, the outdoor Beidou satellite positioning module collects coordinates at intervals of 1 / M of the low-frequency positioning window to obtain M Beidou coordinates; the indoor Bluetooth AOA module collects coordinates at intervals of 1 / 2M of the low-frequency positioning window to obtain 2M local Bluetooth AOA coordinates; in the low-frequency positioning window, the multi-axis sensor module continuously collects coordinates and outputs the trajectory estimated by the multi-axis sensor; the M Beidou coordinates and the 2M local Bluetooth AOA coordinates are mapped to the power grid operation area through coordinate transformation to obtain an initial intermittent motion trajectory; the trajectory estimated by the multi-axis sensor is used to perform path interpolation and correction of the initial intermittent motion trajectory to obtain a first intermittent motion trajectory; and so on. Through the composite positioning terminal, intermittent trajectory collection is performed to obtain the intermittent trajectory sequence including the K intermittent motion trajectories.

[0054] The low-frequency positioning window is a time interval defined by the system for periodically collecting coordinate data. For example, the duration of the low-frequency positioning window can be set to several seconds or dozens of seconds, and the specific time interval depends on the on-site requirements. Within this time window, the outdoor Beidou satellite positioning module collects coordinates at intervals of 1 / M of this low-frequency positioning window, where M is an integer representing the number of acquisitions within the low-frequency positioning window. Assuming the low-frequency positioning window is 20 seconds and M is 5, coordinate data will be collected every 4 seconds. In each acquisition cycle, the Beidou satellite positioning module will record the coordinates of the current position, including longitude, latitude, and altitude, thus obtaining M Beidou coordinates.

[0055] The indoor Bluetooth AOA module collects coordinates at intervals of 1 / 2M of the low-frequency positioning window. This means that within each cycle of the low-frequency positioning window, the indoor Bluetooth AOA module will collect data 2M times. For example, if the low-frequency positioning window is 20 seconds and M is 5, coordinate data will be collected every 2 seconds. The Bluetooth AOA module uses the received angle-of-arrival information of the signal to calculate the position of the person and records these local coordinates, obtaining 2M local Bluetooth AOA coordinates. The coordinates of each acquisition point will be triangulated using the angle and intensity information of the Bluetooth signal to obtain accurate position data.

[0056] Within the low-frequency positioning window, the multi-axis sensor module continuously monitors and records information such as the acceleration and angular velocity of the person. By processing the data collected by the multi-axis sensor, the movement trajectory of the person is calculated. This trajectory calculation is based on integral calculation. For example, velocity is obtained by integrating acceleration, and position is obtained by integrating velocity, and the multi-axis sensor calculated trajectory is output, providing supplementary movement trajectory data for the system.

[0057] The M Beidou coordinates and 2M local Bluetooth AOA coordinates collected respectively represent the position information of the person outdoors and indoors. Since the Beidou and Bluetooth AOA coordinates use different coordinate systems, these coordinates need to be converted to a unified power grid operation area coordinate system. This conversion process involves coordinate system mapping, scale conversion, and position calibration. After the coordinate conversion is completed, the relative positions of all acquisition points in the power grid operation area are obtained, forming an initial intermittent movement trajectory, representing the initial movement trajectory of the person.

[0058] Since the trajectory data provided by the multi-axis sensor is relatively continuous, this data is used for interpolation and correction of the initial intermittent trajectory. Through the path interpolation algorithm, according to the multi-axis sensor calculated trajectory, the points of the initial intermittent trajectory are smoothly connected, filling the gaps between the coordinate points and correcting the trajectory discontinuity problem caused by intermittent acquisition, thus generating the first intermittent movement trajectory. This trajectory has higher accuracy and continuity, providing more reliable trajectory data for subsequent analysis.

[0059] The composite positioning terminal continues to collect the positioning data of personnel according to a preset intermittent acquisition period. This data includes data from Beidou, Bluetooth AOA, and the multi-axis sensor module. Each time a new coordinate point is collected, path interpolation correction is performed to continuously update and optimize the trajectory data. Through continuous acquisition and correction, K intermittent motion trajectories are generated, where K represents the number of trajectory points obtained during the acquisition period. All the corrected intermittent motion trajectories are integrated into a complete intermittent trajectory sequence, which contains K intermittent motion trajectories, providing detailed motion trajectory data of on-site personnel within the power grid operation area.

[0060] Furthermore, taking the multi-dimensional attribute characteristics of the personnel as the evaluation benchmark, based on the motion trajectory sequence, the abnormal risk of the power grid site is quantified, and a dynamic danger level is output. The method includes: Extract the historical motion trajectory and personnel professional characteristics from the multi-dimensional attribute characteristics of the personnel; based on the historical motion trajectory, evaluate the abnormal behavior of the power grid site for the intermittent trajectory sequence and the continuous trajectory sequence to obtain the first static risk coefficient; starting from the trajectory direction feature, referring to the risk area feature, evaluate the abnormal motion of the power grid site for the continuous trajectory sequence, and output the second static risk coefficient; dynamically quantify the danger levels of the first static risk coefficient and the second static risk coefficient according to the on-site real-time environment and the personnel professional characteristics, and output the dynamic danger level.

[0061] Extract the historical motion trajectory, which reflects the action pattern of the personnel over a certain period in the past, including not only position data but also the motion law of the personnel in a specific environment, including position distribution, movement pattern, residence time, etc. For example, if a certain person frequently enters certain areas or avoids certain areas, this provides a reference for subsequent abnormal behavior assessment; extract the personnel professional characteristics, including the responsibilities, professional skills, and work positions of the personnel. For example, whether they are power grid operation personnel, emergency response personnel, or ordinary construction personnel, etc. Different professional characteristics have different impacts on their behavior patterns and behavior expectations.

[0062] Use historical trajectory features, such as position distribution, movement pattern, residence time, etc., to define the normal behavior pattern, and compare it with the current intermittent trajectory and continuous trajectory. If there is an obvious deviation, it is determined as abnormal behavior. According to the detected abnormal behavior, generate the first static risk coefficient, which reflects the deviation degree of the personnel's current behavior from the historical behavior. The greater the deviation, the higher the risk coefficient.

[0063] The trajectory direction feature reflects the movement direction and speed of personnel. At the same time, referring to the risk area features at the power grid site, such as high-voltage equipment areas, operation hazard areas, etc., if the trajectory of personnel shows that they are approaching or heading towards these risk areas, this behavior is determined to be abnormal. Based on the features of the trajectory direction and risk areas, further evaluation of the abnormal movement of the continuous trajectory sequence is carried out, and the corresponding second static risk coefficient is output. This coefficient reflects the safety risk of the current movement behavior based on the proximity of the abnormal behavior of the trajectory and the risk area. If personnel approach or head towards high-risk areas, the second static risk coefficient will increase accordingly.

[0064] Adjust the evaluation of the risk coefficient according to the on-site environment. For example, the working status of the current power grid operation area, the equipment operation status, environmental changes, etc. may all affect the safety risk of personnel. For example, the safety risk is relatively high during thunderstorm weather. At the same time, adjust the evaluation of the risk coefficient in combination with the professional characteristics of personnel. For example, the risk assessment of a highly skilled power grid engineer may be different from that of a novice worker because their familiarity with high-risk areas and emergency handling capabilities are different. Using the above on-site real-time environment and personnel professional characteristics as quantitative weights, perform weighted calculations on the first static risk coefficient and the second static risk coefficient to dynamically quantify the dynamic danger level of personnel. This level represents the safety risk of personnel in the current environment and current state, and this level will be adjusted according to the behavior of personnel, environmental changes, and real-time monitoring data to ensure that the latest risk assessment is always provided.

[0065] Furthermore, taking the multi-dimensional attribute features of the personnel as the evaluation benchmark, quantifying the abnormal risk at the power grid site based on the movement trajectory sequence, and outputting the dynamic danger level. After that, the method includes: Decompose the risk area features to obtain multiple risk types of multiple static risk areas; according to the dynamic danger level and multiple risk types, starting from the regional boundaries of the multiple static risk areas, perform dynamic expansion of the electronic fence in the multiple static risk areas to form multiple temporary electronic fences; according to the personnel permission features, update the access permission levels of the multiple static risk areas to generate multiple temporary lockdown permissions.

[0066] There are multiple static risk areas in the power grid operation area, including high-voltage power areas, construction areas, hazardous chemical storage areas, etc. Each area has different risk types and degrees of danger. According to the attributes of the risk area, such as location, function, environmental factors, etc., it is classified and the risk type of each area is identified. For example, electrical risks include high-voltage power areas, power facility areas, etc.; mechanical risks include areas involving high-risk equipment; environmental risks include thunderstorms, etc. Each static risk area contains one or more risk types. For example, an area may contain both electrical risks and mechanical risks. By dividing the risk types of each static risk area in detail, more sophisticated risk management and intervention measures can be provided.

[0067] Electronic fences are virtual boundaries that are used to monitor whether people enter or leave a specific area. Based on the dynamic danger level (such as whether people are close to high-risk areas, whether there are abnormal behaviors, etc.) and multiple risk types, the existing static risk area boundaries are dynamically expanded according to the on-site situation. This expansion is based on multiple factors, including personnel activities, changes in the on-site environment, etc. For example, in thunderstorms, the electronic fence will be expanded, such as 10 meters, to form a temporary electronic fence. Multiple temporary electronic fences are formed based on the expanded area boundaries. These fences are dynamically generated and can be adjusted at any time.

[0068] Each on-site personnel has different permission characteristics. For example, some personnel have permission to enter high-risk areas, such as power engineers and emergency response personnel, while other personnel cannot enter. Update personnel's access permissions to multiple static risk areas based on dynamic hazard levels and risk types. For example, when external environmental conditions change, some areas are temporarily blocked to restrict access to some personnel. For example, if the risk of an area that is normally accessible increases during thunderstorms, entry is prohibited. By generating temporary blockade permissions, personnel can be controlled from entering high-risk areas under special circumstances to avoid safety accidents.

[0069] Further, after receiving the intervention instruction, the intervention personnel perform the movement intervention of the on-site personnel along the intervention path, and then the method includes: Receive the risk intervention information returned by the intervention personnel; if the risk intervention information is set to 1, release the multiple temporary blocking permissions and the multiple temporary electronic fences; if the risk intervention information is set to 0, maintain the multiple temporary blocking permissions and the multiple temporary electronic fences.

[0070] When performing intervention operations, intervention personnel evaluate the current risk situation and generate risk intervention information. Risk intervention information is an identifier used to indicate whether the intervention is successful or whether further measures are required. For example, 1 means that the intervention has been successful and the safety risk has been eliminated, and 0 means that the intervention is not completed or the current control measures still need to be maintained.

[0071] When the risk intervention information feedback value is 1, it means that the intervention personnel have successfully taken measures and the risk has been lifted. In this case, according to the instructions of the intervention personnel, the previously set temporary lockdown permission is lifted. At this time, the relevant personnel regain the permission to enter the specific risk area; and the previously set multiple temporary electronic fences are lifted. At this time, the relevant personnel can re-enter the previously restricted area.

[0072] When the risk intervention information feedback value is 0, it indicates that the intervention personnel believe that the risk has not been lifted and the current risk control measures are still effective. At this time, the existing temporary lockdown permission and temporary electronic fences are continued to be maintained, and personnel are still restricted from entering the specific high-risk area to ensure site safety and avoid possible accidents.

[0073] In summary, the method for tracking the movement trajectory of on-site personnel in the power grid driven by composite positioning provided by the embodiments of the present application has the following technical effects: Through environmental modeling and static risk area distribution identification, various potential high-risk areas can be clearly marked in the power grid operation area, which provides a spatial basis and a risk identification framework for subsequent personnel trajectory tracking and risk assessment, and effectively improves the visualization and accuracy of on-site safety management; by running a composite positioning terminal to collect the dynamic frequency trajectory of on-site personnel and analyzing the characteristics of the movement trajectory sequence, the real-time position, movement pattern and behavior characteristics of personnel in the power grid operation area can be comprehensively obtained. The visualization display of these data enables managers to understand the movement of on-site personnel in real time, timely discover potential safety hazards or abnormal behaviors, and improve the efficiency and safety of on-site personnel behavior monitoring; by calling the multi-dimensional attribute characteristics of on-site personnel, personalized risk assessment can be carried out on personnel based on these characteristics. Combining with their actual movement trajectory data, the risk level of personnel in the power grid operation area can be more accurately quantified. This dynamic risk quantification method not only improves the accuracy of safety warning, but also can flexibly adjust response measures according to the characteristics of personnel; according to the dynamic danger level, graded warning reminders are sent to on-site personnel according to their actual situation. When personnel do not respond in time within the preset response window, by predicting their future behavior trajectory, potential dangers are identified in advance and a basis for subsequent intervention measures is provided. This mechanism enhances the risk prediction ability, enables safety management to intervene in advance, and reduces the probability of accidents; extracting personnel permission characteristics and screening intervention personnel in combination with the predicted trajectory sequence to locate the intervention personnel and the intervention path to ensure that the intervention personnel can quickly and effectively reach the target area, which not only improves the intervention efficiency, but also enhances the accuracy and timeliness of emergency response; after receiving the instruction, the intervention personnel quickly implement movement intervention on on-site personnel along the predetermined path, effectively preventing personnel from entering dangerous areas or causing accidental accidents, improving the response speed of on-site safety management, and ensuring the safety of the operation environment.

[0074] Embodiment 2. Based on the same inventive concept as the method for tracking the movement trajectory of on-site power grid personnel with composite positioning drive in the foregoing embodiment, as Figure 3 shown, the embodiment of the present application provides a system for tracking the movement trajectory of on-site power grid personnel with composite positioning drive. The system includes: A risk distribution identification module 10, configured to perform environmental modeling on the on-site power grid to obtain a power grid operation area, and then perform static risk area distribution identification in the power grid operation area.

[0075] A trajectory feature analysis module 20, configured to run a composite positioning terminal to collect the dynamic frequency trajectory of on-site personnel, and output trajectory risk features by analyzing the trajectory features of the collected movement trajectory sequence, where the movement trajectory sequence is visualized in the power grid operation area.

[0076] A personnel attribute feature calling module 30, configured to call the multi-dimensional personnel attribute features of the on-site personnel according to the ID.

[0077] An abnormal risk quantification module 40, configured to perform abnormal risk quantification of the on-site power grid based on the multi-dimensional personnel attribute features and according to the movement trajectory sequence, and output a dynamic danger level.

[0078] A predicted trajectory sequence output module 50, configured to send a hierarchical early warning reminder to the on-site personnel according to the dynamic danger level, and after the non-response duration of the on-site personnel to the hierarchical early warning reminder meets a preset response window, perform behavior trajectory prediction according to the movement trajectory sequence and output a predicted trajectory sequence.

[0079] An intervention personnel screening module 60, configured to extract personnel authority features from the multi-dimensional personnel attribute features, and combine with the predicted trajectory sequence to screen intervention personnel, and locate the intervention personnel and the intervention path.

[0080] A movement intervention module 70, configured to perform movement intervention on the on-site personnel along the intervention path after the intervention personnel receive an intervention instruction.

[0081] Furthermore, the trajectory feature analysis module 20 is configured to perform the following operation steps: Intermittent trajectory collection of on-site personnel is carried out through the composite positioning terminal, and the intermittent trajectory sequence is visualized in the power grid operation area, where the on-site personnel carry the composite positioning terminal; taking the static risk area distribution as the risk evaluation benchmark, trajectory feature analysis is performed on the intermittent trajectory sequence to obtain the trajectory risk features, where the trajectory risk features include trajectory direction features, trajectory speed features and risk area features; according to the trajectory risk features, the continuous tracking function of the composite positioning terminal is triggered, and continuous trajectory collection is carried out on the on-site personnel to obtain a continuous trajectory sequence, where the intermittent trajectory sequence and the continuous trajectory sequence constitute the movement trajectory sequence.

[0082] Furthermore, the trajectory feature analysis module 20 is used to perform the following operation steps: Collect the end directions of K intermittent movement trajectories in the intermittent trajectory sequence, and output K intermittent trajectory directions; perform direction stability aggregation on the K intermittent trajectory directions to obtain the trajectory direction features; extend the trajectory direction features in the power grid operation area to frame the risk area features falling into the trajectory direction features in the static risk area distribution; after calculating the movement speeds of the K intermittent movement trajectories based on the trajectory collection interval period to obtain K intermittent movement speeds, calculate the trajectory acceleration and the average trajectory speed according to the K intermittent movement speeds, where the trajectory acceleration and the average trajectory speed constitute the trajectory speed features.

[0083] Furthermore, the trajectory feature analysis module 20 is used to perform the following operation steps: Preset continuous tracking trigger conditions, where the continuous tracking trigger conditions include acceleration trigger constraints and speed trigger constraints; when the trajectory acceleration in the trajectory speed features satisfies the acceleration trigger constraints, and the average trajectory speed in the trajectory speed features satisfies the speed trigger constraints, and the risk area features are a non-empty set, trigger the continuous tracking function of the composite positioning terminal.

[0084] Furthermore, the composite positioning terminal is integrated with an outdoor Beidou satellite positioning module, an indoor Bluetooth AOA module and a multi-axis sensor module.

[0085] Furthermore, the trajectory feature analysis module 20 is used to perform the following operation steps: In the preset low-frequency positioning window, the outdoor Beidou satellite positioning module collects coordinates at intervals of 1 / M of the low-frequency positioning window to obtain M Beidou coordinates; the indoor Bluetooth AOA module collects coordinates at intervals of 1 / 2M of the low-frequency positioning window to obtain 2M Bluetooth AOA local coordinates; in the low-frequency positioning window, the multi-axis sensor module continuously collects coordinates and outputs a multi-axis sensor estimated trajectory; the M Beidou coordinates and the 2M Bluetooth AOA local coordinates are mapped to the power grid operation area through coordinate conversion to obtain an initial intermittent motion trajectory; the multi-axis sensor estimated trajectory is used to perform path interpolation correction of the initial intermittent motion trajectory to obtain a first intermittent motion trajectory; and so on, intermittent trajectory collection is performed through the composite positioning terminal to obtain the intermittent trajectory sequence including the K intermittent motion trajectories.

[0086] Furthermore, the abnormal risk quantification module 40 is used to perform the following operation steps: The historical movement trajectory and the professional characteristics of the personnel are extracted from the multi-dimensional attribute characteristics of the personnel; the intermittent trajectory sequence and the continuous trajectory sequence are evaluated for abnormal behavior of the power grid on-site according to the historical movement trajectory to obtain a first static risk coefficient; taking the trajectory direction characteristics as the starting point, the continuous trajectory sequence is evaluated for abnormal movement of the power grid on-site with reference to the risk area characteristics, and a second static risk coefficient is output; the danger levels of the first static risk coefficient and the second static risk coefficient are dynamically quantified according to the real-time on-site environment and the professional characteristics of the personnel, and the dynamic danger level is output.

[0087] Furthermore, the abnormal risk quantification module 40 is used to perform the following operation steps: Decomposing the risk area characteristics to obtain multiple risk types for multiple static risk areas; based on the dynamic hazard level and the multiple risk types, taking the area boundaries of the multiple static risk areas as the starting point, dynamically expanding the electronic fences in the multiple static risk areas to form multiple temporary electronic fences; based on the personnel authority characteristics, updating the entry authority levels of the multiple static risk areas to generate multiple temporary blocking authorities.

[0088] Furthermore, the movement intervention module 70 is further configured to perform the following operation steps: Receive the risk intervention information returned by the intervention personnel; if the risk intervention information is set to 1, release the multiple temporary blocking permissions and the multiple temporary electronic fences; if the risk intervention information is set to 0, maintain the multiple temporary blocking permissions and the multiple temporary electronic fences.

[0089] Through the foregoing detailed description of the method for tracking the movement trajectory of on-site power grid personnel with composite positioning drive, those skilled in the art can clearly understand the composite positioning drive-based on-site power grid personnel movement trajectory tracking system in this embodiment. Since it corresponds to the method disclosed in the embodiment, the description is relatively simple. For related parts, reference can be made to the description in the method section.

[0090] The foregoing description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to these embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for tracking the movement trajectory of power grid personnel on site driven by composite positioning, characterized in that: The method comprises: After the power grid site is modeled to obtain the power grid operation area, a static risk area distribution mark is made in the power grid operation area; Running the composite positioning terminal to collect the dynamic frequency trajectory of the on-site personnel, and outputting the trajectory risk characteristics by analyzing the trajectory characteristics of the collected motion trajectory sequence, wherein the motion trajectory sequence is visualized in the power grid operation area; Calling the multi-dimensional attribute characteristics of the on-site personnel according to the ID; Taking the multi-dimensional attribute characteristics of the personnel as the evaluation benchmark, quantifying the abnormal risk of the power grid site according to the motion trajectory sequence, and outputting the dynamic danger level; Sending a graded warning reminder to the on-site personnel according to the dynamic danger level, and after the on-site personnel do not respond to the graded warning reminder for a period of time that meets a preset response window, performing behavior trajectory prediction based on the motion trajectory sequence to output a predicted trajectory sequence; Extracting personnel authority features from the multi-dimensional attribute features of the personnel, so as to screen the intervention personnel in combination with the predicted trajectory sequence, locate the intervention personnel and the intervention path; After receiving the intervention instruction, the intervention personnel perform the movement intervention of the on-site personnel along the intervention path.

2. The method for tracking the movement trajectory of power grid personnel on site driven by composite positioning as claimed in claim 1, characterized in that: Run the composite positioning terminal to collect the dynamic frequency trajectory of the on-site personnel, and analyze the trajectory characteristics of the acquired motion trajectory sequence to output the trajectory risk characteristics, including: Collecting intermittent trajectories of on-site personnel through the composite positioning terminal and visualizing the intermittent trajectory sequence in the power grid operation area, wherein the on-site personnel carry the composite positioning terminal; Taking the static risk area distribution as a risk assessment benchmark, performing trajectory feature analysis on the intermittent trajectory sequence to obtain the trajectory risk feature, wherein the trajectory risk feature includes trajectory direction feature, trajectory speed feature and risk area feature; The continuous tracking function of the composite positioning terminal is triggered according to the trajectory risk feature, and the continuous trajectory collection of the on-site personnel is performed to obtain a continuous trajectory sequence, wherein the intermittent trajectory sequence and the continuous trajectory sequence constitute the motion trajectory sequence.

3. The method for tracking the movement trajectory of power grid personnel on site driven by composite positioning as claimed in claim 2, characterized in that: Taking the static risk area distribution as the risk assessment benchmark, the trajectory feature analysis is performed on the intermittent trajectory sequence to obtain the trajectory risk feature, including: Performing terminal direction acquisition on K intermittent motion trajectories in the intermittent trajectory sequence, and outputting K intermittent trajectory directions; Performing directional stability aggregation on the K intermittent trajectory directions to obtain the trajectory direction feature; Extending the trajectory direction feature in the power grid operation area to select the risk area feature falling within the trajectory direction feature in the static risk area distribution frame; Based on the trajectory acquisition interval period, the motion speed of the K intermittent motion trajectories is calculated to obtain K intermittent motion speeds, and then the trajectory acceleration and the trajectory speed average are calculated according to the K intermittent motion speeds, wherein the trajectory acceleration and the trajectory speed average constitute the trajectory speed feature.

4. The method for tracking the movement trajectory of power grid personnel on site driven by composite positioning as claimed in claim 3, characterized in that: The continuous tracking function of the composite positioning terminal is triggered according to the trajectory risk characteristics, and the continuous trajectory of the on-site personnel is collected to obtain a continuous trajectory sequence, including: Presetting a continuous tracking trigger condition, wherein the continuous tracking trigger condition includes an acceleration trigger constraint and a velocity trigger constraint; When the trajectory acceleration in the trajectory velocity feature satisfies the acceleration trigger constraint, and the trajectory velocity mean in the trajectory velocity feature satisfies the velocity trigger constraint, and the risk area feature is a non-empty set, the continuous tracking function of the composite positioning terminal is triggered.

5. The method for tracking the movement trajectory of power grid personnel on site driven by composite positioning as claimed in claim 3, characterized in that: The composite positioning terminal integrates an outdoor Beidou satellite positioning module, an indoor Bluetooth AOA module and a multi-axis sensor module.

6. The method for tracking the movement trajectory of power grid personnel on site driven by composite positioning as claimed in claim 5, characterized in that: The intermittent trajectory of the on-site personnel is collected by the composite positioning terminal, and the intermittent trajectory sequence is visualized in the power grid operation area, including: In the preset low-frequency positioning window, the outdoor Beidou satellite positioning module collects coordinates at intervals of 1 / M of the low-frequency positioning window to obtain M Beidou coordinates; The indoor Bluetooth AOA module collects coordinates at intervals of 1 / 2M of the low-frequency positioning window to obtain 2M Bluetooth AOA local coordinates; In the low-frequency positioning window, the multi-axis sensor module continuously collects coordinates and outputs a multi-axis sensor estimated trajectory; Mapping the M Beidou coordinates and the 2M Bluetooth AOA local coordinates to the power grid operation area through coordinate conversion to obtain an initial intermittent motion trajectory; Using the multi-axis sensor to estimate the trajectory, perform path interpolation correction on the initial intermittent motion trajectory to obtain a first intermittent motion trajectory; By analogy, intermittent trajectory collection is performed through the composite positioning terminal to obtain the intermittent trajectory sequence including the K intermittent motion trajectories.

7. The method for tracking the movement trajectory of power grid personnel on site driven by composite positioning as claimed in claim 2, characterized in that: Taking the multi-dimensional attribute characteristics of the personnel as the evaluation benchmark, the abnormal risk of the power grid site is quantified according to the motion trajectory sequence, and the dynamic danger level is output, including: Extracting historical movement trajectories and professional characteristics of personnel from the multi-dimensional attribute characteristics of the personnel; According to the historical motion trajectory, the intermittent trajectory sequence and the continuous trajectory sequence are evaluated for abnormal behavior of the power grid on site to obtain a first static risk coefficient; Taking the trajectory direction feature as a starting point, referring to the risk area feature, evaluating the power grid on-site motion anomaly on the continuous trajectory sequence, and outputting a second static risk coefficient; The risk levels of the first static risk coefficient and the second static risk coefficient are dynamically quantified according to the real-time on-site environment and the professional characteristics of the personnel, and the dynamic risk level is output.

8. The method for tracking the movement trajectory of power grid personnel on site driven by composite positioning as claimed in claim 7, characterized in that: Taking the multi-dimensional attribute characteristics of the personnel as the evaluation benchmark, the abnormal risk of the power grid site is quantified according to the motion trajectory sequence, and the dynamic danger level is output, and then, it includes: Decomposing the risk area characteristics to obtain multiple risk types for multiple static risk areas; According to the dynamic danger level and the multiple risk types, taking the regional boundaries of the multiple static risk areas as the starting point, dynamically expanding the electronic fences in the multiple static risk areas to form multiple temporary electronic fences; According to the personnel authority characteristics, the access authority levels of the multiple static risk areas are updated to generate multiple temporary blocking authorities.

9. The method for tracking the movement trajectory of power grid personnel on site driven by composite positioning as claimed in claim 8, characterized in that: After receiving the intervention instruction, the intervention personnel will carry out the movement intervention of the on-site personnel along the intervention path, and then include: Receiving risk intervention information sent back by the intervention personnel; If the risk intervention information is set to 1, the multiple temporary blocking permissions and multiple temporary electronic fences are released; If the risk intervention information is set to 0, the multiple temporary blocking authorities and the multiple temporary electronic fences are maintained.

10. A composite positioning driven power grid on-site personnel motion trajectory tracking system, characterized in that: A method for tracking the movement trajectory of power grid personnel on site driven by composite positioning according to any one of claims 1 to 9, the system comprising: A risk distribution identification module is used to perform static risk area distribution identification in the power grid operation area after performing environmental modeling on the power grid site to obtain the power grid operation area; A trajectory feature analysis module is used to operate the composite positioning terminal to collect the dynamic frequency trajectory of the on-site personnel, and to output the trajectory risk feature by performing trajectory feature analysis on the collected motion trajectory sequence, wherein the motion trajectory sequence is visualized in the power grid operation area; A personnel attribute feature calling module is used to call the personnel multi-dimensional attribute features of the on-site personnel according to the ID; An abnormal risk quantification module is used to quantify the abnormal risk of the power grid site based on the multi-dimensional attribute characteristics of the personnel as an evaluation benchmark and the motion trajectory sequence, and output a dynamic risk level; A predicted trajectory sequence output module is used to send a graded warning reminder to the on-site personnel according to the dynamic danger level, and after the on-site personnel do not respond to the graded warning reminder for a period of time that meets a preset response window, the behavior trajectory is predicted according to the motion trajectory sequence to output a predicted trajectory sequence; An intervention personnel screening module is used to extract personnel authority features from the multi-dimensional attribute features of the personnel, so as to screen the intervention personnel in combination with the predicted trajectory sequence, locate the intervention personnel and the intervention path; The motion intervention module is used for the intervention personnel to perform motion intervention on the on-site personnel along the intervention path after receiving the intervention instruction.

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