Accurate positioning method and system for working field personnel

Abstract

The invention discloses a method and a system for accurately positioning a worker on an operation site, and relates to the technical field of accurate positioning, and the method comprises the steps: installing sensor groups in a petroleum collection region every 3 meters, collecting region environment data, wearing UWB label positioning equipment for an oil extraction worker, and obtaining worker positioning data in real time. After the data are transmitted to a ground station central detection system through a wireless network, the system can dynamically calculate the real-time three-dimensional position (xi, yi, zi) of an oil production worker to accurately position the oil production worker, and calculates an environment risk index ERIi according to a regional environment feature set. By comparing a preset environment risk threshold value F1 in real time, the system can quickly identify and automatically mark an environment abnormal risk area, so that early warning is given out when the environment is deteriorated, such as hydrogen sulfide concentration increase or geological vibration aggravation, timely safety prompts are provided for oil production workers, accidents in an oil collection area are effectively reduced, and the safety of the oil production workers is improved. And the safety guarantee of oil extraction workers is improved.

Description

Technical Field

[0001] The present invention relates to the field of precise positioning technology, and in particular to a method and system for precisely positioning personnel on a work site. Background Art

[0002] Safety management in oil extraction areas is one of the most challenging applications in the Industrial Internet of Things, involving complex underground environments and a large amount of equipment and personnel coordination. Especially in underground oil extraction area operations, real-time and accurate positioning of oil extraction workers is crucial to safety. Due to the complexity and potential danger of the oil extraction area environment, it is extremely important to monitor the specific location of oil extraction workers and the environmental status of the area where they are located. The precise positioning technology for oil extraction workers uses sensor groups, positioning equipment, and wireless communication technologies to ensure the safety of oil extraction workers in dynamic and dangerous oil extraction area environments, and provide all-round monitoring support for managers.

[0003] At present, in the oil collection area, inaccurate positioning of oil workers and untimely updating of environmental data are common problems. Traditional personnel positioning technologies mostly rely on satellite positioning systems such as GPS, but the underground oil collection area has complex structures and blocked signals, resulting in weak or unavailable GPS signals. Existing wireless communications or single sensor data collection methods cannot accurately track the real-time location of oil workers, especially in areas where the signal is blocked. In addition, environmental data within the oil collection area, such as hydrogen sulfide concentration, temperature and humidity, and geological vibrations, are usually collected at a low frequency and cannot be updated in real time, resulting in a lack of timely warning when danger comes, increasing safety risks. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a method and system for accurately positioning personnel on a work site, which solves the problems mentioned in the background technology.

[0005] To achieve the above objectives, the present invention is implemented by the following technical scheme: comprising the following steps: S1. By installing a sensor group in the oil collection area, the regional environmental data is collected in real time, and the oil workers are equipped with positioning equipment to collect the workers' positioning data in real time; S2, sending the regional environment data and the worker location data to the central detection system, and extracting features of the regional environment data in the central detection system to obtain a regional environment feature set; S3, based on the acquired worker positioning data, real-time calculation of the real-time position of the oil production worker (x i ,y i , z i ), and then calculate the environmental risk index ERI of the area where the i-th oil production worker is located by collecting regional environmental characteristics. i, and preset the environmental risk threshold F1 and the environmental risk index ERI of the area where the i-th oil worker is located i Conduct preliminary comparative assessment and automatically mark risk areas of environmental anomalies; S4. When the environmental abnormal risk area is initially compared and evaluated, the evacuation path planning formula and the dynamic scheduling algorithm formula of the operation task are automatically triggered to calculate and output the evacuation path OP of the i-th oil production worker. i and the workload index TLI to plan evacuation routes and job scheduling in advance; S5. Build a monitoring platform in the central detection system to generate a dynamic safety map of the oil collection area, combine sensor data to provide all-round safety monitoring, and display the real-time location of oil workers, environmental status, and abnormal environmental risk areas in real time; S6. Reconstruct the comprehensive evaluation formula based on the environmental risk index ERI of the area where the i-th oil production worker is located. i , the evacuation path OP of the i-th oil production worker i The comprehensive safety assessment index CSA of the oil collection area is calculated and output based on the workload index TLI. At the same time, a safety threshold F2 is preset, and a secondary comparative evaluation is performed between the safety threshold F2 and the comprehensive safety assessment index CSA to analyze the overall safety situation of the oil collection area, and relevant measures are generated based on the secondary comparative evaluation results.

[0006] Preferably, S1 includes S11 and S12; S11, by installing a set of sensor groups every 3 meters in the oil collection area, the sensor groups are used to collect regional environmental data in real time; The sensor group includes a hydrogen sulfide sensor, a temperature sensor, a humidity sensor, and a seismic wave sensor; Regional environmental data include hydrogen sulfide concentration C, temperature T, humidity H, and number of geological fluctuations n; S12. A UWB base station is installed every 3 meters in the oil collection area. The UWB base stations are connected to form a grid through a wireless network. At the same time, the oil workers are required to wear UWB tag positioning devices, and the UWB tag positioning devices worn by the oil workers are equipped with built-in accelerometers, gyroscopes and RFID device sensors to collect workers' positioning data in real time. Worker positioning data includes received signal strength RSS, signal flight time TOF, angle information JD, base station signal power P, and distance D between the oil production worker and the base station; Received signal strength RSS, signal flight time TOF and the distance D between the oil workers and the base station are measured through the UWB tag positioning device worn by the oil workers. When the oil workers pass through the station, the base station measures the distance D between the oil workers and the base station through the signal flight time TOF, and collects the received signal strength RSS at the same time; The angle information JD is collected and acquired through the built-in accelerometer, gyroscope and RFID device sensor in the UWB tag positioning device worn by the oil workers; RFID devices are distributed in key locations within the oil collection area, such as entrances, exits, and work surfaces. When an oil worker's RFID device passes through a reader, its current location is recorded.

[0007] Preferably, S2 includes S21 and S22; S21, connect the UWB base station to the central detection system through UWB ultra-wideband technology, inertial navigation system INS and radio frequency identification technology RFID, and transmit the real-time collected regional environmental data and worker positioning data to the central detection system; S22, extracting features from the regional environmental data in the central detection system to obtain a regional environmental feature set; The set of regional environmental characteristics includes hydrogen sulfide diffusion rate GDR, temperature and humidity gradient THG, and geological vibration frequency GFQ; The hydrogen sulfide diffusion rate GDR is obtained by calculating the concentration gradient based on the obtained hydrogen sulfide concentration C. The specific algorithm formula is: , where △C represents the difference in hydrogen sulfide concentration change at the two hydrogen sulfide sensor locations, △t represents the time interval for hydrogen sulfide concentration measurement, and △ds represents the spatial distance between the two hydrogen sulfide sensor locations; The temperature and humidity gradient THG is calculated based on the temperature T and humidity H to obtain the temperature and humidity gradient. The specific algorithm formula is: ; In the formula, △T represents the temperature difference between the two temperature sensor positions, △H represents the humidity difference between the two humidity sensor positions, △dw represents the spatial distance between the two temperature sensor positions, and △dd represents the spatial distance between the two humidity sensor positions; The geological vibration frequency GFQ is calculated based on the number of geological fluctuations n. The specific algorithm formula is: Where △t represents the time interval.

[0008] Preferably, S3 includes S31, S32 and S33; S31, calculate and output the real-time position of the oil production worker (x i ,y i , z i ); The real-time location of the oil worker (x i ,y i , z i ) is calculated by the following algorithm formula; ; Where M represents the total number of UWB base stations, RSSij It represents the received signal strength value when the i-th oil production worker transmits the signal to the j-th UWB base station, TOF ij JD represents the signal flight time required for the signal sent by the UWB tag positioning device worn by the i-th oil production worker to reach the j-th UWB base station, ij represents the angle information between the i-th oil production worker and the j-th UWB base station, P j represents the base station signal power of the jth UWB base station, D ij represents the distance between the i-th oil worker and the j-th UWB base station, represents the signal path loss factor, f represents the function corresponding to the distance and angle information. The significance of the formula is to ensure the three-dimensional positioning of oil workers in oil collection areas with weak signals and complex terrain.

[0009] Preferably, S32, based on the acquired regional environmental feature set, calculate and output the environmental risk index ERI of the area where the i-th oil production worker is located i , analyze the real-time location of oil workers (x i ,y i , z i ) Environmental conditions in the area; Environmental risk index ERI of the area where the i-th oil worker is located i Obtained through the following algorithm formula; ; Where, ERI i represents the environmental risk index of the area where the i-th oil worker is located, GDR i represents the hydrogen sulfide diffusion rate in the area where the i-th oil production worker is located, THG i represents the temperature and humidity gradient of the area where the i-th oil production worker is located, GFQ i represents the geological vibration frequency in the area where the i-th oil worker is located, represents the rate of change of hydrogen sulfide concentration, , and Represents the preset weight values ​​of hydrogen sulfide diffusion rate GDR, temperature and humidity gradient THG and hydrogen sulfide concentration change rate, and They represent the adjustment factor and attenuation control factor of the geological vibration frequency GFQ, respectively, e represents the exponential function, log represents the logarithmic function, t1 represents the current time point, and t2 represents the next time point; This exponential decay function indicates that the higher the frequency of geological vibration, the smaller the increase in the environmental risk index of oil workers. Controls the decay rate, adjustment factor Adjust the overall impact of this parameter in the risk assessment; Here, a logarithmic function is used to smooth the effect of the rate of change of hydrogen sulfide concentration. The weight value of the rate of change of hydrogen sulfide concentration The weight of this parameter is controlled to prevent the small rate of change of hydrogen sulfide concentration from having too great an impact on the index, but still retain its importance; S33, based on the user setting of the environmental risk threshold F1 and the environmental analysis index ERI of the area where the i-th oil production worker is located i Conduct a preliminary comparative assessment to identify potential risks in the current area and determine the specific assessment contents; When the environmental analysis index ERI of the area where the i-th oil worker is located i >Environmental risk threshold F1, indicating that there is an abnormal environment risk in the current oil collection area, and the current area is automatically marked as an abnormal environment risk area; When the environmental analysis index ERI of the area where the i-th oil worker is located i When ≤ environmental risk threshold F1, it means that the current oil collection area environment is normal.

[0010] Preferably, S4 includes S41 and S42; S41. When the environmental abnormality risk area is initially compared and evaluated, the evacuation path planning formula is automatically triggered to calculate and output the evacuation path OP of the i-th oil production worker. i ; The evacuation path OP of the i-th oil worker i The output is calculated by the following evacuation path planning formula; ; Where, ERI j represents the environmental risk index of the jth UWB base station area, ACT i represents the current activity status of the i-th oil production worker. The activity status of the oil production worker reflects his current movement speed and behavior pattern, such as whether he is tired and how fast he moves, which affects the evacuation speed and path selection. The UWB tag positioning device worn by the oil production worker can monitor the movement status of the oil production worker in real time. represents the partial derivative, represents the rate of change of hydrogen sulfide diffusion rate in the jth UWB base station area with time t, GFQ j represents the geological vibration frequency in the jth UWB base station area, a1, a2, a3 and a4 respectively represent the environmental risk index ERI of the i-th oil worker area, the current activity status ACT of the oil worker, the change rate of hydrogen sulfide diffusion rate and the preset weight value of the geological vibration frequency, and the specific values ​​are set by the user.

[0011] Preferably, S42, by constructing a dynamic scheduling algorithm formula for job tasks, calculating and outputting a job load index TLI, and dynamically adjusting the job load situation of the current detection area; The job load index TLI is calculated and output by the following job task dynamic scheduling algorithm formula; ; In the formula, N represents the total number of oil production workers, Wi represents the workload of the i-th oil production worker, and the task volume undertaken by the oil production worker is automatically recorded through the task management system. Ui represents the current load status of the equipment used by the i-th oil production worker, and the load status of the equipment is monitored in real time through the equipment sensor and management system. Ti represents the estimated completion time of the i-th oil production worker's task. The weight factor representing the device usage status, Represents the environmental risk weight factor of the area where the i-th oil worker is located.

[0012] Preferably, S5 includes S51 and S52; S51. In the central detection system, the regional environmental data and worker location data collected by the sensor group and the UWB base station are processed and integrated through the database and the big data analysis platform to generate a real-time three-dimensional oil collection area safety map, and a user interface GUI is built in the central detection system to provide real-time maps, data visualization and alarm prompts; S52. Using AI technology, deep learning is performed from historical regional environmental data and worker location data to optimize risk assessment and decision recommendations. The path is automatically calculated through a path planning algorithm, and the path is dynamically updated in combination with regional environmental data and worker location data. It is integrated with the equipment control system in the oil collection area. The decision support can automatically trigger the start or stop of emergency equipment to ensure timely response.

[0013] Preferably, S6 includes S61 and S62; S61, construct a comprehensive evaluation formula, and obtain the environmental risk index ERI of the area where the i-th oil production worker is located i , the evacuation path OP of the i-th oil production worker i and the workload index TLI are input into the comprehensive evaluation formula to calculate and output the comprehensive safety assessment index CSA of the oil collection area, and analyze the safety status of the oil collection area as a whole; The comprehensive safety assessment index CSA is calculated and output through the following comprehensive assessment formula; ; In the formula, A i represents the distance from the ith oil worker to the safe exit, N represents the total number of oil workers, TLI i represents the workload index of the i-th oil production worker; S62, and perform a secondary comparative evaluation based on the preset safety threshold F2 and the comprehensive safety assessment index CSA by the user, and generate relevant measures based on the secondary comparative evaluation results. The specific evaluation contents are as follows; When the comprehensive safety assessment index CSA ≥ safety threshold F2, it means that the safety status of the oil collection area is normal, and continuous monitoring and normal operation are carried out at this time; When the comprehensive safety assessment index CSA is less than the safety threshold F2, it means that the safety status of the oil collection area is abnormal. An alarm is issued, the operation is stopped, and the evacuation route OP of the i-th oil worker is notified through the UWB tag device worn. i , and then start emergency ventilation through the equipment control system.

[0014] A precise positioning system for personnel at a work site, including a data acquisition module, a data transmission and extraction module, a positioning and environmental information fusion module, a path planning and work scheduling module, a real-time monitoring module and a comprehensive safety analysis module; The data collection module collects regional environmental data in real time by installing a sensor group in the oil collection area, and collects the workers' location data in real time by having the oil workers wear positioning devices; The data transmission and extraction module sends the regional environment data and the worker location data to the central detection system, and extracts the features of the regional environment data in the central detection system to obtain the regional environment feature set; The positioning and environmental information fusion module calculates the real-time position of the oil production workers (x i ,y i , z i ), and then calculate the environmental risk index ERI of the area where the i-th oil production worker is located by collecting regional environmental characteristics. i , and preset the environmental risk threshold F1 and the environmental risk index ERI of the area where the i-th oil worker is located i Conduct preliminary comparative assessment and automatically mark risk areas of environmental anomalies; The path planning and job scheduling module automatically triggers the evacuation path planning formula and the job task dynamic scheduling algorithm formula when the environmental abnormal risk area is initially compared and evaluated, and calculates and outputs the evacuation path OP of the i-th oil production worker. i and the workload index TLI to plan evacuation routes and job scheduling in advance; The real-time monitoring module builds a monitoring platform in the central detection system to generate a dynamic safety map of the oil collection area. It combines sensor data to provide all-round safety monitoring and displays the real-time location of oil workers, environmental status, and abnormal environmental risk areas in real time. The comprehensive safety analysis module constructs a comprehensive evaluation formula based on the environmental risk index ERI of the area where the i-th oil production worker is located. i , the evacuation path OP of the i-th oil production worker i The comprehensive safety assessment index CSA of the oil collection area is calculated and output based on the workload index TLI. At the same time, a safety threshold F2 is preset, and a secondary comparative evaluation is performed between the safety threshold F2 and the comprehensive safety assessment index CSA to analyze the overall safety situation of the oil collection area, and relevant measures are generated based on the secondary comparative evaluation results.

[0015] The present invention provides a method and system for accurately positioning personnel on a work site, which has the following beneficial effects: (1) This method collects regional environmental data such as hydrogen sulfide concentration, temperature, humidity and geological fluctuations by installing sensor groups every 3 meters in the oil collection area, and provides UWB tag positioning devices for oil workers to obtain workers' positioning data in real time. After these data are transmitted to the central detection system of the ground station via a wireless network, the system can dynamically calculate the real-time three-dimensional position (x i ,y i ,z i ), and calculate the environmental risk index ERI of the area where the i-th oil production worker is located based on the regional environmental characteristics set i By comparing the preset environmental risk threshold F1 in real time, the system can quickly identify and automatically mark areas with abnormal environmental risks, thereby issuing early warnings when the environment deteriorates, such as increased hydrogen sulfide concentrations or intensified geological vibrations, providing timely safety reminders for oil workers, effectively reducing the occurrence of accidents in oil collection areas, and improving the safety of oil workers.

[0016] (2) After identifying the abnormal risk area of ​​the environment, the system can automatically trigger the evacuation path planning formula and the dynamic scheduling algorithm of the operation task. The optimal evacuation path OP of each oil production worker i By calculating the environmental risk index ERI of the location and the area where the i-th oil worker is located i , hydrogen sulfide diffusion rate changes, geological vibration frequency GFQ and other multiple parameters are calculated to ensure that oil workers can evacuate quickly according to the real-time dynamic optimal path to avoid entering the abnormal environment risk area. At the same time, the system adjusts and optimizes the task allocation based on the task load index TLI, combined with the current workload of the oil workers, equipment load status, and expected task completion time, to avoid oil workers from performing overload operations in the abnormal environment risk area. This intelligent evacuation and task scheduling not only improves the response efficiency in emergency situations, but also effectively reduces casualties and equipment losses in the operation of the oil collection area.

[0017] (3) This method generates a real-time dynamic three-dimensional oil extraction area safety map by integrating the regional environmental data and worker location data collected by the sensor group and UWB base station in the central detection system. The system uses a comprehensive evaluation formula to calculate the environmental risk index ERI of the area where the i-th oil extraction worker is located. i , the evacuation path OP of the i-th oil production worker i The system is integrated with the workload index TLI to obtain the comprehensive safety assessment index CSA of the oil collection area, and compared with the preset safety threshold F2 to evaluate the overall safety of the oil collection area. When the evaluation results show safety anomalies, the system can take emergency measures such as issuing alarms, suspending operations, and starting emergency ventilation equipment. Through deep learning of historical data and AI technology, the system can continuously optimize risk assessment models and decision support, realize intelligent and automated management of oil collection areas, and provide managers with comprehensive data support and effective decision-making suggestions, thereby greatly improving the safety management level and operational efficiency of oil collection areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A schematic diagram of the steps of a method for accurately locating personnel on a work site according to the present invention; Figure 2 The present invention is a flowchart of a system for accurately positioning personnel on a work site. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0020] Example 1 See also Figure 1 The present invention provides a method for accurately positioning personnel on a work site. To achieve the above purpose, the present invention is implemented through the following technical scheme: comprising the following steps: S1. By installing a sensor group in the oil collection area, the regional environmental data is collected in real time, and the oil workers are equipped with positioning equipment to collect the workers' positioning data in real time; S2, sending the regional environment data and the worker location data to the central detection system, and extracting features from the regional environment data in the central detection system to obtain a regional environment feature set; S3, based on the acquired worker positioning data, real-time calculation of the real-time position of the oil production worker (x i ,y i , zi ), and then calculate the environmental risk index ERI of the area where the i-th oil production worker is located by collecting regional environmental characteristics. i , and preset the environmental risk threshold F1 and the environmental risk index ERI of the area where the i-th oil worker is located i Conduct preliminary comparative assessment and automatically mark risk areas of environmental anomalies; S4. When the environmental abnormal risk area is initially compared and evaluated, the evacuation path planning formula and the dynamic scheduling algorithm formula of the operation task are automatically triggered to calculate and output the evacuation path OP of the i-th oil production worker. i and the workload index TLI to plan evacuation routes and job scheduling in advance; S5. Build a monitoring platform in the central detection system to generate a dynamic safety map of the oil collection area, combine sensor data to provide all-round safety monitoring, and display the real-time location of oil workers, environmental status, and abnormal environmental risk areas in real time; S6. Reconstruct the comprehensive evaluation formula based on the environmental risk index ERI of the area where the i-th oil production worker is located. i , the evacuation path OP of the i-th oil production worker i The comprehensive safety assessment index CSA of the oil collection area is calculated and output based on the workload index TLI. At the same time, a safety threshold F2 is preset, and a secondary comparative evaluation is performed between the safety threshold F2 and the comprehensive safety assessment index CSA to analyze the overall safety situation of the oil collection area, and relevant measures are generated based on the secondary comparative evaluation results.

[0021] In this embodiment, the method can collect environmental data and worker location data in the oil collection area in real time by using a sensor group installed in the oil collection area and combining it with the UWB tag positioning device worn by the oil workers. After these data are transmitted to the central detection system, a regional environmental feature set is generated through feature extraction, laying the foundation for subsequent environmental risk assessment. Based on the real-time positioning data of oil workers (x i ,y i ,z i ) and environmental characteristics set, the environmental risk index ERI of the area where the i-th oil production worker is located can be calculated i , and compares and evaluates it with the preset environmental risk threshold F1, automatically marking the environmental abnormality risk area, thereby realizing the rapid identification of environmental abnormality risks. When the environmental abnormality risk area is identified, the evacuation path planning formula is automatically triggered to generate the optimal evacuation path OP for each oil production worker. iThe task load index TLI is calculated through the dynamic scheduling algorithm of the task, and the evacuation route and task allocation are planned in advance to ensure that personnel evacuation and task adjustment can be carried out quickly and effectively in an emergency. At the same time, the central detection system builds a dynamic oil collection area safety map, which combines sensor data to display the real-time location, environmental status and environmental abnormality risk area of ​​the oil workers in real time, providing all-round safety monitoring support for the management of the oil collection area. Finally, by constructing a comprehensive evaluation formula, combined with the environmental risk index ERI of the area where the i-th oil worker is located i , the evacuation path OP of the i-th oil production worker i and workload index TLI, generate a comprehensive safety assessment index CSA, and compare it with the preset safety threshold F2 for a second time to analyze the overall safety status of the oil collection area and generate corresponding safety management measures. Compared with traditional oil collection area safety monitoring methods, this method has achieved significant improvements in real-time monitoring, intelligent analysis, automatic decision-making and emergency response. Through real-time data collection and intelligent risk assessment, it can identify safety hazards in the oil collection area more quickly and accurately, automatically generate evacuation routes and adjust work tasks, greatly improving accident prevention capabilities and emergency response speed. In addition, the dynamic oil collection area safety map and intelligent monitoring platform provided by the central detection system provide managers with all-round visualization support, making oil collection area management more efficient and transparent.

[0022] Example 2 This embodiment is explained in Example 1, please refer to Figure 1 , specifically: S1 includes S11 and S12; S11, by installing a set of sensor groups every 3 meters in the oil collection area, the sensor groups are used to collect regional environmental data in real time; The sensor group includes a hydrogen sulfide sensor, a temperature sensor, a humidity sensor, and a seismic wave sensor; Regional environmental data include hydrogen sulfide concentration C, temperature T, humidity H, and number of geological fluctuations n; S12. A UWB base station is installed every 3 meters in the oil collection area. The UWB base stations are connected to form a grid through a wireless network. At the same time, the oil workers are required to wear UWB tag positioning devices, and the UWB tag positioning devices worn by the oil workers are equipped with built-in accelerometers, gyroscopes and RFID device sensors to collect workers' positioning data in real time. Worker positioning data includes received signal strength RSS, signal flight time TOF, angle information JD, base station signal power P, and distance D between the oil production worker and the base station; Received signal strength RSS, signal flight time TOF and the distance D between the oil workers and the base station are measured through the UWB tag positioning device worn by the oil workers. When the oil workers pass through the station, the base station measures the distance D between the oil workers and the base station through the signal flight time TOF, and collects the received signal strength RSS at the same time; The angle information JD is collected and acquired through the built-in accelerometer, gyroscope and RFID device sensor in the UWB tag positioning device worn by the oil workers; RFID devices are distributed in key locations within the oil collection area, such as entrances, exits, and work surfaces. When an oil worker's RFID device passes through a reader, its current location is recorded.

[0023] In this embodiment, the method realizes accurate real-time monitoring of the oil collection area environment and the location of oil workers by installing sensor groups and UWB base stations every 3 meters in the oil collection area. Through the deployment of sensor groups, regional environmental data is collected in real time, and potential environmental risks can be perceived in real time and discovered in time. Then, by deploying the grid network formed by the UWB base station, combined with the UWB tag positioning device worn by the oil workers, the three-dimensional accurate positioning of the oil workers in the complex oil collection area environment is realized by receiving the worker positioning data, and the stability and reliability of positioning are further improved by the built-in accelerometer, gyroscope and RFID device sensor. This method brings significant technical improvements compared to traditional oil collection area monitoring methods. Traditional technologies rely on a single sensor or regular inspections, and have limited real-time and precision. However, this method forms a highly integrated real-time monitoring system for environment and personnel through the combination of sensor groups and UWB technology, which not only improves the perception accuracy of environmental changes, but also realizes continuous tracking and accurate positioning of oil workers through grid-based base station deployment, effectively avoiding the risk of oil workers staying in environmental abnormal risk areas for a long time.

[0024] Example 3 This embodiment is explained in Example 2. Please refer to Figure 1 , specifically: S2 includes S21 and S22; S21, connect the UWB base station to the central detection system through UWB ultra-wideband technology, inertial navigation system INS and radio frequency identification technology RFID, and transmit the real-time collected regional environmental data and worker positioning data to the central detection system; S22, extracting features from the regional environmental data in the central detection system to obtain a regional environmental feature set; The set of regional environmental characteristics includes hydrogen sulfide diffusion rate GDR, temperature and humidity gradient THG, and geological vibration frequency GFQ; The hydrogen sulfide diffusion rate GDR is obtained by calculating the concentration gradient based on the obtained hydrogen sulfide concentration C. The specific algorithm formula is: , where △C represents the difference in hydrogen sulfide concentration change at the two hydrogen sulfide sensor locations, △t represents the time interval for hydrogen sulfide concentration measurement, and △ds represents the spatial distance between the two hydrogen sulfide sensor locations; The temperature and humidity gradient THG is calculated based on the temperature T and humidity H to obtain the temperature and humidity gradient. The specific algorithm formula is: ; In the formula, △T represents the temperature difference between the two temperature sensor positions, △H represents the humidity difference between the two humidity sensor positions, △dw represents the spatial distance between the two temperature sensor positions, and △dd represents the spatial distance between the two humidity sensor positions; The geological vibration frequency GFQ is calculated based on the number of geological fluctuations n. The specific algorithm formula is: Where △t represents the time interval.

[0025] In this embodiment, the method realizes the real-time transmission and feature extraction of regional environmental data and worker positioning data. By integrating the UWB base station, the inertial navigation system INS and the radio frequency identification technology RFID, the collected regional environmental data and worker positioning data are transmitted to the central detection system, ensuring the real-time and accuracy of the data. The central detection system extracts features from these data and generates a regional environmental feature set. This integrated method improves the intelligent level of environmental monitoring in the oil collection area, significantly enhances the early warning capability and decision-making support for environmental changes, thereby effectively ensuring the safety of oil workers and improving the overall efficiency of oil collection area operations.

[0026] Example 4 This embodiment is explained in Example 3, please refer to Figure 1 , specifically: S3 includes S31, S32 and S33; S31, calculate and output the real-time position of the oil production worker (x i ,y i , z i ); The real-time location of the oil production worker (x i ,y i , z i ) is calculated and obtained through the following algorithm formula; ; Where M represents the total number of UWB base stations, RSS ij It represents the received signal strength value when the i-th oil production worker transmits the signal to the j-th UWB base station, TOF ij JD represents the signal flight time required for the signal sent by the UWB tag positioning device worn by the i-th oil production worker to reach the j-th UWB base station, ijrepresents the angle information between the i-th oil production worker and the j-th UWB base station, P j represents the base station signal power of the jth UWB base station, D ij represents the distance between the i-th oil worker and the j-th UWB base station, represents the signal path loss factor, f represents the function corresponding to the distance and angle information. The significance of the formula is to ensure the three-dimensional positioning of oil workers in oil collection areas with weak signals and complex terrain.

[0027] S32, based on the obtained regional environmental feature set, calculate and output the environmental risk index ERI of the area where the i-th oil production worker is located i , analyze the real-time location of oil workers (x i ,y i , z i ) Environmental conditions in the area; Environmental risk index ERI of the area where the i-th oil worker is located i Obtained through the following algorithm formula; ; Where, ERI i represents the environmental risk index of the area where the i-th oil worker is located, GDR i represents the hydrogen sulfide diffusion rate in the area where the i-th oil production worker is located, THG i represents the temperature and humidity gradient of the area where the i-th oil production worker is located, GFQ i represents the geological vibration frequency in the area where the i-th oil worker is located, represents the rate of change of hydrogen sulfide concentration, , and Represents the preset weight values ​​of hydrogen sulfide diffusion rate GDR, temperature and humidity gradient THG and hydrogen sulfide concentration change rate, and They represent the adjustment factor and attenuation control factor of the geological vibration frequency GFQ, respectively, e represents the exponential function, log represents the logarithmic function, t1 represents the current time point, and t2 represents the next time point; This exponential decay function indicates that the higher the frequency of geological vibration, the smaller the increase in the environmental risk index of oil workers. Controls the decay rate, adjustment factor Adjust the overall impact of this parameter in the risk assessment; Here, a logarithmic function is used to smooth the effect of the rate of change of hydrogen sulfide concentration. The weight value of the rate of change of hydrogen sulfide concentration The weight of this parameter is controlled to prevent the small rate of change of hydrogen sulfide concentration from having too great an impact on the index, but still retain its importance; S33, based on the user setting of the environmental risk threshold F1 and the environmental analysis index ERI of the area where the i-th oil production worker is located i Conduct a preliminary comparative assessment to identify potential risks in the current area and determine the specific assessment contents; When the environmental analysis index ERI of the area where the i-th oil worker is located i >Environmental risk threshold F1, indicating that there is an abnormal environment risk in the current oil collection area, and the current area is automatically marked as an abnormal environment risk area; When the environmental analysis index ERI of the area where the i-th oil worker is located i When ≤ environmental risk threshold F1, it means that the current oil collection area environment is normal.

[0028] In this embodiment, the method uses the signal strength RSS, signal flight time TOF, angle information JD and other data collected by the UWB base station, combined with the UWB tag positioning device worn by the oil workers, to accurately calculate the real-time three-dimensional position (x i ,y i ,z i ), even in oil extraction areas with weak signals and complex terrain, the positioning accuracy can be ensured. Based on the collected regional environmental feature set, the environmental risk index ERI of the area where the i-th oil extraction worker is located is calculated. i , and combined with the real-time location of the oil workers to assess the environmental risk of the current area. Then by comparing the environmental risk index ERI of the area where the i-th oil worker is located i Compared with the preset risk threshold F1, potential environmental abnormality risk areas are identified and automatically marked as environmental abnormality risk areas, ensuring that managers and oil workers can be informed of risk changes in a timely manner. Compared with traditional technologies, this method has made significant progress in real-time and accuracy. Traditional oil collection area monitoring usually relies on static data and regular assessments, and it is difficult to respond to dynamic changes in complex environments in a timely manner. This method, by combining real-time positioning with environmental risk assessment, can quickly detect potential dangers in the area where oil workers are located and realize dynamic risk warning.

[0029] Example 5 This embodiment is explained in Example 4. Please refer to Figure 1 , specifically: S4 includes S41 and S42; S41. When the environmental abnormality risk area is initially compared and evaluated, the evacuation path planning formula is automatically triggered to calculate and output the evacuation path OP of the i-th oil production worker. i ; The evacuation path OP of the i-th oil workeri The output is calculated by the following evacuation path planning formula; ; Where, ERI j represents the environmental risk index of the jth UWB base station area, ACT i represents the current activity status of the i-th oil production worker. The activity status of the oil production worker reflects his current movement speed and behavior pattern, such as whether he is tired and how fast he moves, which affects the evacuation speed and path selection. The UWB tag positioning device worn by the oil production worker can monitor the movement status of the oil production worker in real time. represents the partial derivative, represents the rate of change of hydrogen sulfide diffusion rate in the jth UWB base station area with time t, GFQ j represents the geological vibration frequency in the jth UWB base station area, a1, a2, a3 and a4 respectively represent the environmental risk index ERI of the i-th oil worker area, the current activity status ACT of the oil worker, the change rate of hydrogen sulfide diffusion rate and the preset weight value of the geological vibration frequency, and the specific values ​​are set by the user.

[0030] S42, by constructing a dynamic scheduling algorithm formula for job tasks, calculating and outputting a job load index TLI, and dynamically adjusting the job load situation of the current detection area; The job load index TLI is calculated and output by the following job task dynamic scheduling algorithm formula; ; In the formula, N represents the total number of oil production workers, Wi represents the workload of the i-th oil production worker, and the task volume undertaken by the oil production worker is automatically recorded through the task management system. Ui represents the current load status of the equipment used by the i-th oil production worker, and the load status of the equipment is monitored in real time through the equipment sensor and management system. Ti represents the estimated completion time of the i-th oil production worker's task. The weight factor representing the device usage status, Represents the environmental risk weight factor of the area where the i-th oil worker is located.

[0031] In this embodiment, the method automatically triggers the evacuation path planning formula through the preliminary assessment of the environmental abnormality risk area, and generates the optimal evacuation path OP of each oil production worker. i, ensuring that oil workers can quickly and effectively evacuate the abnormal environmental risk area in an emergency. Then, by constructing a dynamic scheduling algorithm for job tasks and calculating the job load index TLI, the job tasks of each oil worker can be dynamically adjusted, resource allocation can be optimized, and long-term operation in high-risk areas can be avoided. Compared with the existing technology, this method significantly improves the efficiency of emergency response and the level of intelligent job scheduling. Traditional evacuation path planning usually relies on static preset routes and cannot cope with the safety risks brought about by environmental changes. This method generates a personalized evacuation route for each oil worker through the combination of real-time data and dynamic algorithms to ensure the safety and efficiency of the path. At the same time, the dynamic scheduling function of job tasks can flexibly adjust the task load of oil workers in dangerous environments, avoid overwork or equipment overload, and further reduce the risk of accidents. These improvements effectively improve the risk control ability of oil collection areas in emergency situations and the safety level of oil workers, ensuring that the operation of oil collection areas is more intelligent, safe and efficient.

[0032] Example 6 This embodiment is explained in Example 5. Please refer to Figure 1 , specifically: S5 includes S51 and S52; S51. In the central detection system, the regional environmental data and worker location data collected by the sensor group and the UWB base station are processed and integrated through the database and the big data analysis platform to generate a real-time three-dimensional oil collection area safety map, and a user interface GUI is built in the central detection system to provide real-time maps, data visualization and alarm prompts; S52. Using AI technology, deep learning is performed from historical regional environmental data and worker location data to optimize risk assessment and decision recommendations. The path is automatically calculated through a path planning algorithm, and the path is dynamically updated in combination with regional environmental data and worker location data. It is integrated with the equipment control system in the oil collection area. The decision support can automatically trigger the start or stop of emergency equipment to ensure timely response.

[0033] In this embodiment, the method processes and fuses the regional environmental data and worker positioning data from the sensor group and UWB base station through a database and a big data analysis platform, generates a real-time three-dimensional oil collection area safety map, and provides data visualization and alarm prompts through the user interface GUI. This function allows managers in the oil collection area to grasp the safety status of the oil collection area in real time and respond quickly to any emergencies. At the same time, artificial intelligence AI technology is used to continuously optimize risk assessment models and decision-making recommendations through deep learning of historical data. In addition, combined with the path planning algorithm, the evacuation path can be dynamically updated according to real-time environmental data and the location of oil workers, and integrated with the equipment control system in the oil collection area to automatically trigger the start or stop of emergency equipment to ensure timely response in critical moments.

[0034] Example 7 This embodiment is explained in Example 6. Please refer to Figure 1 , specifically: S6 includes S61 and S62; S61, construct a comprehensive evaluation formula, and obtain the environmental risk index ERI of the area where the i-th oil production worker is located i , the evacuation path OP of the i-th oil production worker i and the workload index TLI are input into the comprehensive evaluation formula to calculate and output the comprehensive safety assessment index CSA of the oil collection area, and analyze the safety status of the oil collection area as a whole; The comprehensive safety assessment index CSA is calculated and output through the following comprehensive assessment formula; ; In the formula, A i represents the distance from the ith oil worker to the safe exit, N represents the total number of oil workers, TLI i represents the workload index of the i-th oil production worker; S62, and perform a secondary comparative evaluation based on the preset safety threshold F2 and the comprehensive safety assessment index CSA by the user, and generate relevant measures based on the secondary comparative evaluation results. The specific evaluation contents are as follows; When the comprehensive safety assessment index CSA ≥ safety threshold F2, it means that the safety status of the oil collection area is normal, and continuous monitoring and normal operation are carried out at this time; When the comprehensive safety assessment index CSA is less than the safety threshold F2, it means that the safety status of the oil collection area is abnormal. An alarm is issued, the operation is stopped, and the evacuation route OP of the i-th oil worker is notified through the UWB tag device worn. i , and then start emergency ventilation through the equipment control system.

[0035] In this embodiment, the method constructs a comprehensive evaluation formula to calculate the environmental risk index ERI of the area where the i-th oil production worker is located. i , the evacuation path OPi of the i-th oil production worker, and the workload index TLI are input into the comprehensive evaluation formula to calculate the comprehensive safety assessment index CSA, which provides a quantitative analysis of the safety status of the oil collection area. Then, by comparing the comprehensive safety assessment index CSA with the preset safety threshold F2, a secondary evaluation is achieved. When CSA is higher than F2, it means that the oil collection area is safe and routine monitoring is maintained; when CSA is lower than F2, an alarm will be issued and the operation will be stopped, and emergency measures will be automatically initiated, including notifying the oil production workers to evacuate and turning on ventilation equipment. Compared with traditional manual evaluation or simple monitoring, this method has made significant progress in the comprehensiveness of safety evaluation and intelligent response. Through the input and analysis of comprehensive multi-dimensional data, the current safety status of the oil collection area can be accurately calculated, and dynamic adjustments can be made based on intelligent algorithms, thereby achieving faster and more accurate risk identification and processing. Especially in dangerous conditions, the emergency plan can be automatically triggered, reducing the delay and uncertainty of manual decision-making, greatly improving the safety management efficiency and emergency response capabilities of the oil collection area, and effectively ensuring the safety of oil workers and the normal operation of the oil collection area.

[0036] Example 8 See also Figure 2 , a precise positioning system for personnel at the work site, including a data acquisition module, a data transmission and extraction module, a positioning and environmental information fusion module, a path planning and work scheduling module, a real-time monitoring module and a comprehensive safety analysis module; The data collection module collects regional environmental data in real time by installing a sensor group in the oil collection area, and collects the workers' location data in real time by having the oil workers wear positioning devices; The data transmission and extraction module sends the regional environment data and the worker location data to the central detection system, and extracts the features of the regional environment data in the central detection system to obtain the regional environment feature set; The positioning and environmental information fusion module calculates the real-time position of the oil production workers (x i ,y i , z i ), and then calculate the environmental risk index ERI of the area where the i-th oil production worker is located by collecting regional environmental characteristics. i , and preset the environmental risk threshold F1 and the environmental risk index ERI of the area where the i-th oil worker is located i Conduct preliminary comparative assessment and automatically mark risk areas of environmental anomalies; The path planning and job scheduling module automatically triggers the evacuation path planning formula and the job task dynamic scheduling algorithm formula when the environmental abnormal risk area is initially compared and evaluated, and calculates and outputs the evacuation path OP of the i-th oil production worker. i and the workload index TLI to plan evacuation routes and job scheduling in advance; The real-time monitoring module builds a monitoring platform in the central detection system to generate a dynamic safety map of the oil collection area. It combines sensor data to provide all-round safety monitoring and displays the real-time location of oil workers, environmental status, and abnormal environmental risk areas in real time. The comprehensive safety analysis module constructs a comprehensive evaluation formula based on the environmental risk index ERI of the area where the i-th oil production worker is located. i , the evacuation path OP of the i-th oil production worker i The comprehensive safety assessment index CSA of the oil collection area is calculated and output based on the workload index TLI. At the same time, a safety threshold F2 is preset, and a secondary comparative evaluation is performed between the safety threshold F2 and the comprehensive safety assessment index CSA to analyze the overall safety situation of the oil collection area, and relevant measures are generated based on the secondary comparative evaluation results.

[0037] While the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that many changes, modifications, substitutions and variations can be made to the embodiments without departing from the principles and spirit of the invention.

Claims

1. A method for accurately locating personnel at a work site, characterized in that: The following steps are involved: S1. By installing a sensor group in the oil collection area, the regional environmental data is collected in real time, and the oil workers are equipped with positioning equipment to collect the workers' positioning data in real time; S2, sending the regional environment data and the worker location data to the central detection system, and extracting features of the regional environment data in the central detection system to obtain a regional environment feature set; S3, based on the acquired worker positioning data, real-time calculation of the real-time position of the oil production worker (x i ,y i , z i ), and then calculate the environmental risk index ERI of the area where the i-th oil production worker is located by collecting regional environmental characteristics. i , and preset an environmental risk threshold F1, and compare the environmental threshold F1 with the environmental risk index ERI of the area where the i-th oil production worker is located i Conduct preliminary comparative assessment and automatically mark risk areas of environmental anomalies; S4. When the environmental abnormal risk area is initially compared and evaluated, the evacuation path planning formula and the dynamic scheduling algorithm formula of the operation task are automatically triggered to calculate and output the evacuation path OP of the i-th oil production worker. i and the workload index TLI to plan evacuation routes and job scheduling in advance; S5. Build a monitoring platform in the central detection system to generate a dynamic safety map of the oil collection area, combine sensor data to provide all-round safety monitoring, and display the real-time location of oil workers, environmental status, and abnormal environmental risk areas in real time; S6. Reconstruct the comprehensive evaluation formula based on the environmental risk index ERI of the area where the i-th oil production worker is located. i , the evacuation path OP of the i-th oil production worker i The comprehensive safety assessment index CSA of the oil collection area is calculated and output based on the workload index TLI. At the same time, a safety threshold F2 is preset, and a secondary comparative evaluation is performed between the safety threshold F2 and the comprehensive safety assessment index CSA to analyze the overall safety situation of the oil collection area, and relevant measures are generated based on the secondary comparative evaluation results.

2. The method for accurately locating personnel at a work site according to claim 1, characterized in that: Said S1 includes S11 and S12; S11, by installing a set of sensor groups every 3 meters in the oil collection area, the sensor groups are used to collect regional environmental data in real time; The sensor group includes a hydrogen sulfide sensor, a temperature sensor, a humidity sensor and a seismic wave sensor; The regional environmental data include hydrogen sulfide concentration C, temperature T, humidity H and number of geological fluctuations n; S12. A UWB base station is installed every 3 meters in the oil collection area. The UWB base stations are connected to form a grid through a wireless network. At the same time, the oil workers are required to wear UWB tag positioning devices, and the UWB tag positioning devices worn by the oil workers are equipped with built-in accelerometers, gyroscopes and RFID device sensors to collect workers' positioning data in real time. The worker positioning data includes received signal strength RSS, signal flight time TOF, angle information JD, base station signal power P, and the distance D between the oil production worker and the base station.

3. The method for accurately locating personnel at a work site according to claim 2, characterized in that: The S2 includes S21 and S22; S21, connect the UWB base station to the central detection system through UWB ultra-wideband technology, inertial navigation system INS and radio frequency identification technology RFID, and transmit the real-time collected regional environmental data and worker positioning data to the central detection system; S22, extracting features from the regional environmental data in the central detection system to obtain a regional environmental feature set; The regional environmental feature set includes hydrogen sulfide diffusion rate GDR, temperature and humidity gradient THG and geological vibration frequency GFQ.

4. The method for accurately locating personnel at a work site according to claim 3, characterized in that: The S3 includes S31, S32 and S33; S31, calculate and output the real-time position of the oil production worker (x i ,y i , z i ); The real-time location of the oil worker (x i ,y i , z i ) is calculated and obtained through the following algorithm formula; ； Where M represents the total number of UWB base stations, RSS ij It represents the received signal strength value when the i-th oil production worker transmits the signal to the j-th UWB base station, TOF ij JD represents the signal flight time required for the signal sent by the UWB tag positioning device worn by the i-th oil production worker to reach the j-th UWB base station, ij represents the angle information between the i-th oil production worker and the j-th UWB base station, P j represents the base station signal power of the jth UWB base station, D ij represents the distance between the i-th oil worker and the j-th UWB base station, represents the signal path loss factor, and f represents the function corresponding to the distance and angle information.

5. The method for accurately locating personnel at a work site according to claim 4, characterized in that: S32, based on the obtained regional environmental feature set, calculate and output the environmental risk index ERI of the area where the i-th oil production worker is located i , analyze the real-time location of oil workers (x i ,y i , z i ) Environmental conditions in the area; The environmental risk index ERI of the area where the i-th oil worker is located i Obtained through the following algorithm formula; ； Where, ERI i represents the environmental risk index of the area where the i-th oil worker is located, GDR i represents the hydrogen sulfide diffusion rate in the area where the i-th oil production worker is located, THG i represents the temperature and humidity gradient of the area where the i-th oil production worker is located, GFQ i represents the geological vibration frequency in the area where the i-th oil worker is located, represents the rate of change of hydrogen sulfide concentration, , and Represents the preset weight values ​​of hydrogen sulfide diffusion rate GDR, temperature and humidity gradient THG and hydrogen sulfide concentration change rate, and They represent the adjustment factor and attenuation control factor of the geological vibration frequency GFQ, respectively, e represents the exponential function, log represents the logarithmic function, t1 represents the current time point, and t2 represents the next time point; S33, based on the user setting of the environmental risk threshold F1 and the environmental analysis index ERI of the area where the i-th oil production worker is located i Conduct a preliminary comparative assessment to identify potential risks in the current area and determine the specific assessment contents; When the environmental analysis index ERI of the area where the i-th oil worker is located i >Environmental risk threshold F1, indicating that there is an abnormal environment risk in the current oil collection area, and the current area is automatically marked as an abnormal environment risk area; When the environmental analysis index ERI of the area where the i-th oil worker is located i When ≤ environmental risk threshold F1, it means that the current oil collection area environment is normal.

6. The method for accurately locating personnel at a work site according to claim 5, characterized in that: The S4 includes S41 and S42; S41. When the environmental abnormality risk area is initially compared and evaluated, the evacuation path planning formula is automatically triggered to calculate and output the evacuation path OP of the i-th oil production worker. i ; The evacuation path OP of the i-th oil production worker i The output is calculated by the following evacuation path planning formula; ； Where, ERI j represents the environmental risk index of the jth UWB base station area, ACT i Indicates the current activity status of the i-th oil production worker, represents the partial derivative, represents the rate of change of hydrogen sulfide diffusion rate in the jth UWB base station area with time t, GFQ j represents the geological vibration frequency in the jth UWB base station area, a1, a2, a3 and a4 respectively represent the environmental risk index ERI of the i-th oil worker area, the current activity status ACT of the oil worker, the change rate of hydrogen sulfide diffusion rate and the preset weight value of the geological vibration frequency, and the specific values ​​are set by the user.

7. The method for accurately locating personnel at a work site according to claim 6, characterized in that: S42, by constructing a dynamic scheduling algorithm formula for job tasks, calculating and outputting a job load index TLI, and dynamically adjusting the job load situation of the current detection area; The job load index TLI is calculated and output by the following job task dynamic scheduling algorithm formula; ； Where N represents the total number of oil production workers, Wi represents the workload of the i-th oil production worker, Ui represents the current load state of the equipment used by the i-th oil production worker, Ti represents the estimated completion time of the i-th oil production worker's task, The weight factor representing the device usage status, Represents the environmental risk weight factor of the area where the i-th oil worker is located.

8. The method for accurately locating personnel at a work site according to claim 1, characterized in that: The S5 includes S51 and S52; S51. In the central detection system, the regional environmental data and worker location data collected by the sensor group and the UWB base station are processed and integrated through the database and the big data analysis platform to generate a real-time three-dimensional oil collection area safety map, and a user interface GUI is built in the central detection system to provide real-time maps, data visualization and alarm prompts; S52. Use AI technology to conduct deep learning from historical regional environmental data and worker location data to optimize risk assessment and decision-making recommendations, automatically calculate through path planning algorithms, dynamically update paths based on regional environmental data and worker location data, and integrate with equipment control systems in oil collection areas.

9. The method for accurately locating personnel at a work site according to claim 1, characterized in that: The S6 includes S61 and S62; S61, construct a comprehensive evaluation formula, and obtain the environmental risk index ERI of the area where the i-th oil production worker is located i , the evacuation path OP of the i-th oil production worker i and the workload index TLI are input into the comprehensive evaluation formula to calculate and output the comprehensive safety assessment index CSA of the oil collection area, and analyze the safety status of the oil collection area as a whole; The comprehensive safety assessment index CSA is calculated and output by the following comprehensive assessment formula: ； In the formula, A i represents the distance from the ith oil worker to the safe exit, N represents the total number of oil workers, TLI i represents the workload index of the i-th oil production worker; S62, and perform a secondary comparative evaluation based on the preset safety threshold F2 and the comprehensive safety assessment index CSA by the user, and generate relevant measures based on the secondary comparative evaluation results. The specific evaluation contents are as follows; When the comprehensive safety assessment index CSA ≥ safety threshold F2, it means that the safety status of the oil collection area is normal, and continuous monitoring and normal operation are carried out at this time; When the comprehensive safety assessment index CSA is less than the safety threshold F2, it means that the safety status of the oil collection area is abnormal. At this time, an alarm is issued, the operation is stopped, and the evacuation path OP of the i-th oil worker is notified through the UWB tag device worn. i , and then start emergency ventilation through the equipment control system.

10. A precise positioning system for on-site personnel, applied to the precise positioning method for on-site personnel according to any one of claims 1 to 9, characterized in that: It includes data acquisition module, data transmission and extraction module, positioning and environmental information fusion module, path planning and operation scheduling module, real-time monitoring module and comprehensive safety analysis module; The data collection module collects regional environmental data in real time by installing a sensor group in the oil collection area, and collects worker positioning data in real time by having oil workers wear positioning equipment; The data transmission and extraction module sends the regional environment data and the worker location data to the central detection system, and extracts features from the regional environment data in the central detection system to obtain a regional environment feature set; The positioning and environmental information fusion module calculates the real-time position of the oil production worker (x i ,y i , z i ), and then calculate the environmental risk index ERI of the area where the i-th oil production worker is located by collecting regional environmental characteristics. i , and preset the environmental risk threshold F1 and the environmental risk index ERI of the area where the i-th oil worker is located i Conduct preliminary comparative assessments and automatically mark areas of environmental anomaly risk; The path planning and job scheduling module automatically triggers the evacuation path planning formula and the job task dynamic scheduling algorithm formula when the environmental abnormal risk area is preliminarily compared and evaluated, and calculates and outputs the evacuation path OP of the i-th oil production worker. i and the workload index TLI to plan evacuation routes and job scheduling in advance; The real-time monitoring module generates a dynamic safety map of the oil collection area by building a monitoring platform in the central detection system, and provides all-round safety monitoring in combination with sensor data, showing the real-time location of oil workers, environmental status and abnormal environmental risk areas in real time; The comprehensive safety analysis module constructs a comprehensive evaluation formula based on the environmental risk index ERI of the area where the i-th oil production worker is located. i , the evacuation path OP of the i-th oil production worker i The comprehensive safety assessment index CSA of the oil collection area is calculated and output based on the workload index TLI. At the same time, a safety threshold F2 is preset, and a secondary comparative evaluation is performed between the safety threshold F2 and the comprehensive safety assessment index CSA to analyze the overall safety situation of the oil collection area, and relevant measures are generated based on the secondary comparative evaluation results.

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