Power plant personnel positioning management platform

Abstract

The invention discloses a power plant personnel positioning management platform, relates to the technical field of personnel positioning, and solves the technical problems that differential correction strategies are not designed for static and dynamic scenes of a power plant, and a partial region management scheme only pays attention to a high-risk region and neglects fine management of a normal region. Static drift and dynamic track errors are reduced through static confidence region anchoring and dynamic step length self-adaptive adjustment in combination with gyroscope direction angle correction, the problem of positioning distortion in a complex environment is solved, static and dynamic states are judged in a multi-dimensional mode based on the three-axis acceleration, the stride frequency and the position change rate, a switching buffer mechanism is added, the misjudgment rate is reduced, and the positioning accuracy is improved. High-frequency monitoring and qualification verification are adopted in a high-risk area, normal monitoring is performed in a working period in a normal area, and only the electronic fence is activated in a non-working period, so that safety is guaranteed, privacy is protected, and abnormal intrusion response time in the non-working period is shortened.

Description

Technical Field

[0001] This invention relates to the field of personnel positioning technology, specifically a power plant personnel positioning management platform. Background Technology

[0002] As core facilities for energy production, power plants are characterized by dense equipment, complex environments, and numerous high-risk areas. Therefore, personnel safety management and operational efficiency improvement are the core management requirements.

[0003] According to patent publication number CN102456170A, this patent discloses an indoor personnel positioning management system, including a terminal computer, a communication module, several positioning communication modules, and several handheld terminals. The terminal computer communicates wirelessly with the communication module and the several positioning communication modules. The handheld terminals send signals to the several positioning communication modules. After receiving the signal, the positioning communication modules return a communication quality value to the handheld terminals. The handheld terminals determine the nearest positioning communication module based on the returned communication quality value and transmit their coordinates level by level to the terminal computer through the communication module.

[0004] Traditional power plant personnel management relies on manual attendance, paper records, or simple location systems, which have the following limitations:

[0005] Single positioning technology is prone to drift in complex electromagnetic environments or areas with metal obstruction. When static, signal fluctuations lead to false location reports, and when dynamic, the trajectory lags or jumps, making it difficult to meet the needs of precise control. It cannot distinguish between the static and dynamic states of personnel, and adopting a unified monitoring strategy leads to resource waste or delayed early warning.

[0006] There is a lack of differentiated monitoring between high-risk and normal areas; excessive monitoring during non-working hours infringes on privacy; insufficient monitoring may lead to unauthorized intrusion risks; areas with signal interference are prone to false alarms; risks such as deviation from inspection routes and mismatch of personnel qualifications are difficult to identify accurately, leading to management personnel desensitizing to early warnings. Summary of the Invention

[0007] To address the shortcomings of existing technologies, this invention provides a power plant personnel location management platform, which solves the problems of not designing differentiated correction strategies for static and dynamic scenarios in power plants, and some regional management schemes only focusing on high-risk areas while neglecting the refined management of normal areas.

[0008] To achieve the above objectives, the present invention provides the following technical solution: a power plant personnel location management platform, comprising:

[0009] The personnel information acquisition module is used to obtain personnel location information through UWB communication with the base station via the positioning tag and transmit it to the positioning status recognition module;

[0010] The positioning status recognition module is used to determine whether a person is in a static or dynamic state. When the person is in a static state, it sets the signal area correction signal and generates static correction information. When the person is in a dynamic state, it calculates and adaptively adjusts the step size, and combines the movement distance calculated by the gyroscope to generate dynamic correction information. Based on the static and dynamic correction information, the module identifies the person's position and determines whether it is a high-risk or normal area. It then generates a high-risk area analysis signal or a normal area analysis signal, respectively, and transmits both signals.

[0011] The high-risk location area analysis module is used to process signals from high-risk areas. If there is a valid inspection task and the personnel match the task, a normal monitoring signal is generated and transmitted to the comprehensive analysis module; otherwise, a high-risk early warning information is generated.

[0012] The comprehensive analysis and identification module is used to process normal monitoring signals, generate inspection paths and calculate the overlap rate with the positioning trajectory. If the overlap rate meets the standard, continuous monitoring information is generated; otherwise, difference analysis signals and trajectory correction information are generated.

[0013] The normal positioning area analysis module processes signals from normal areas, dividing them into working and non-working periods. During working periods, signals are generated in real time, while during non-working periods, high-risk areas are monitored only through electronic fences. The module analyzes real-time monitoring signals, marks areas affected by positioning drift, verifies early warnings for these areas by frequency or monitoring, and generates continuous inspection information or high-risk early warning information.

[0014] As a further aspect of the present invention, a management information output module is also included, which is used to display continuous monitoring information, trajectory correction information, high-risk early warning information, or continuous inspection information.

[0015] As a further aspect of the present invention, the specific method by which the positioning status recognition module determines the static or dynamic state of a person is as follows:

[0016] The tag uses its built-in accelerometer and positioning data change rate to determine the state. If the acceleration is less than 0.1g and the position change is less than 30cm for 5 consecutive seconds, the state is determined to be static and a static analysis signal is generated. Conversely, if the acceleration is greater than 0.1g or the position change is greater than 30cm / second, the state is determined to be dynamic and a dynamic analysis signal is generated.

[0017] As a further aspect of the present invention, the specific method by which the positioning state recognition module sets the signal area correction signal and generates static correction information when the positioning state is static is as follows:

[0018] A static confidence zone is set with radius d as the standard, and the specific value of d is set by the operator. The positioning signal is corrected with the center of the zone as the reference point. If a drift point that exceeds the zone occurs, it is directly removed and the reference point is used until obvious movement is detected and then the system is unlocked to generate static correction information.

[0019] As a further aspect of the present invention, the specific method by which the positioning status recognition module combines the gyroscope to calculate the movement distance and generate dynamic correction information is as follows:

[0020] Using formula The step length SL of the power plant personnel is calculated, where a, b, and c are calibration coefficients, H is height, and SF is step frequency. The step length is adaptively adjusted based on different environments. Then, the movement time of the power plant personnel is obtained, and the movement distance is calculated using the formula: [Formula omitted for brevity]. in The direction deviation between the i-th step and the previous step is calculated, and corresponding positioning corrections are performed based on the obtained movement distance to generate dynamic correction information.

[0021] As a further aspect of the present invention, the high-risk location area analysis module processes high-risk area signals in the following specific manner:

[0022] The system identifies the corresponding high-risk areas and determines whether an inspection task exists. If it exists, an inspection analysis signal is generated; otherwise, a high-risk warning message is generated. The generated inspection analysis signal is processed to obtain the corresponding power plant personnel and their information, including personnel permissions, employee numbers, and job positions. The system determines whether the personnel information matches the inspection task. If they match, a normal monitoring signal is generated and transmitted to the integrated analysis and identification module. Otherwise, a high-risk warning message is generated.

[0023] As a further aspect of the present invention, the specific method by which the comprehensive analysis and identification module processes normal monitoring signals is as follows:

[0024] The corresponding inspection path is generated based on the inspection task. At the same time, the location trajectory path of the power plant personnel is obtained and the overlap rate between the inspection path and the location trajectory path is analyzed. Then, the obtained overlap rate is compared with the preset percentage. If the overlap rate is greater than the preset percentage, continuous monitoring information is generated. Otherwise, if the overlap rate is less than the preset percentage, a difference analysis signal is generated and analyzed.

[0025] The trajectory direction corresponding to the positioning trajectory path is obtained, and the trajectory direction corresponding to the inspection path is also obtained. The deviation between the two trajectory directions is analyzed. At the same time, the obtained trajectory direction deviation is used as the standard to generate trajectory correction information and transmit it to the management information output module.

[0026] As a further aspect of the present invention, the normal positioning area analysis module processes the normal area signal in the following specific manner:

[0027] The time is segmented to obtain working and non-working periods. During working periods, real-time monitoring of power plant personnel is performed and real-time monitoring signals are generated. During non-working periods, real-time monitoring of power plant personnel is turned off, and the identification information of the electronic fence is obtained to determine whether there are any abnormalities. If there are, a high-risk warning message is generated; otherwise, it remains unchanged.

[0028] As a further aspect of the present invention, the specific method by which the normal positioning area analysis module processes high-risk early warning information is as follows:

[0029] Analyze historical data and divide the area into regions, mark the areas affected by signal interference that often cause location drift, monitor the location signals of people in the affected areas, judge the early warning situation according to the established method, generate early warning verification analysis signal if there is an early warning, and generate continuous monitoring information if there is no early warning.

[0030] The system processes and verifies early warning signals, calculates the frequency of early warning occurrence using a set period t, and compares it with a preset frequency. If the frequency exceeds the preset frequency, it is determined to be a genuine early warning, and a high-risk early warning message is generated. If the frequency does not exceed the preset frequency, monitoring and verification are retrieved, and continuous inspection information or high-risk early warning information is generated.

[0031] This invention provides a power plant personnel location management platform. Compared with existing technologies, it has the following advantages:

[0032] This invention reduces static drift and dynamic trajectory error by using static confidence zone anchoring and dynamic step size adaptive adjustment, combined with gyroscope orientation angle correction, thus solving the positioning distortion problem in complex environments. It determines the static and dynamic states based on three-axis acceleration, step frequency, and position change rate in multiple dimensions, adds a switching buffer mechanism to reduce the false judgment rate, and ensures that the monitoring strategy is adapted to the actual scenario. High-risk areas use high-frequency monitoring and qualification verification, while normal areas are monitored routinely during working hours and only the electronic fence is activated during non-working hours, which ensures both safety and privacy, and shortens the response time for abnormal intrusions during non-working hours.

[0033] By marking affected areas, verifying early warning frequencies, and conducting video-linked reviews, the false alarm rate in areas with signal interference is reduced. Combined with the overlap rate analysis of the two-ticket system and inspection paths, risks such as qualification mismatch and path deviation are accurately identified. The positioning data is deeply integrated with inspection tasks, video surveillance, and the two-ticket system to achieve a closed-loop process from positioning, status identification, area management, early warning, and decision-making. This provides data support for power plant safety management and efficiency optimization. Parameters such as static confidence zone radius, step size calibration coefficient, and early warning threshold can be customized according to the actual scenario of the power plant to adapt to the needs of power plants of different sizes and equipment distributions, thereby improving versatility and scalability. Attached Figure Description

[0034] Figure 1 This is a system block diagram of the present invention. Detailed Implementation

[0035] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] Example 1

[0037] Please see Figure 1 This application provides a power plant personnel positioning management platform, including: a personnel information acquisition module, a positioning status identification module, a high-risk positioning area analysis module, a normal positioning area analysis module, a comprehensive analysis and identification module, and a positioning management information output module, and in conjunction with... Figure 1 It can be seen that the information between the above functional modules is transmitted in one direction only.

[0038] The personnel information acquisition module is used to acquire the location information of power plant personnel. The location information specifically includes the corresponding location signal, which is mainly acquired through the location tags worn by the personnel. The tags and the base station communicate with each other through UWB pulse signals. The base station forwards the collected tag information data to the positioning server through a network switch, and at the same time transmits the acquired location information to the positioning status recognition module.

[0039] The positioning status recognition module is used to determine the positioning status of power plant personnel based on the acquired positioning information. Specifically, it is determined by the accelerometer built into the tag and the rate of change of positioning data. If the acceleration is <0.1g and the position change is <30cm for 5 consecutive seconds, the status is determined to be static and a static analysis signal is generated. Conversely, if the acceleration is >0.1g or the position change is >30cm / second, the status is determined to be dynamic and a dynamic analysis signal is generated.

[0040] The tag's built-in accelerometer (three-axis acceleration), the rate of change of positioning data (the amount of change in position coordinates over time), and the motion frequency (step frequency sensor) are used as core indicators to comprehensively determine the status.

[0041] Static judgment: If the three-axis acceleration is all <0.1g (excluding slight vibration of the equipment) and the position change is <30cm for 5 consecutive seconds, and the step frequency is 0 (no gait characteristics), it can be judged as static and a static analysis signal is generated.

[0042] Dynamic determination: If the following conditions are met, such as "acceleration on any axis > 0.1g (e.g., vertical acceleration fluctuation during walking)", "rate of position change > 30cm / second", or "step frequency > 0.5 steps / second (gait detected)", it is determined to be dynamic, and a dynamic analysis signal is generated.

[0043] For example, when an inspector is recording data at the control panel in the central control room, his body remains stable (acceleration < 0.1g), and his position changes by only 10cm within 5 seconds (without leaving the control panel), with a step frequency of 0, so the system judges him as static; when he gets up and walks to the equipment area, his first step triggers the peak acceleration (0.3g), and the position change rate reaches 40cm / second, which continuously meets the dynamic conditions for 2 seconds, so the system switches to dynamic state.

[0044] The generated static analysis signal is processed, and a static confidence zone is set with radius d as the standard. The specific value of d is set by the operator. The positioning signal is corrected with the center of the zone as the reference point. If a drift point that exceeds the zone occurs, such as a sudden jump to more than 1 meter due to electromagnetic interference, it is directly removed and the reference point is used until obvious movement is detected and then the system is unlocked to generate static correction information.

[0045] The generated dynamic analysis signal is processed using formulas. The step length SL of the power plant personnel is calculated, where a, b, and c are calibration coefficients, H is height, and SF is step frequency. The step length is adaptively adjusted based on different environments. Specifically, when the positioning signal detects that a person is approaching metal equipment, the step length is automatically reduced (e.g., to 80% of the original step length). Then, the corresponding movement time of the power plant personnel is obtained, combined with the gyroscope's orientation angle. Calculate the actual distance traveled using the formula: Distance traveled = in The direction deviation between the i-th step and the previous step is calculated, and corresponding positioning corrections are made based on the obtained moving distance to generate dynamic correction information.

[0046] Based on static and dynamic correction information, the real-time location of power plant personnel is identified, and the regional attributes of the real-time location are determined to identify high-risk areas and normal areas. The regional attributes are classified by the operators according to the importance of the area. For example, high-risk areas include high-voltage equipment areas, explosion-proof areas, high-altitude work areas, and confined spaces, while normal areas include office areas, rest areas, and inspection passages. At the same time, high-risk area analysis signals or normal area analysis signals are generated, and then they are transmitted to the high-risk positioning area analysis module and the normal positioning area analysis module, respectively.

[0047] The high-risk location area analysis module processes the acquired high-risk area analysis signals, identifies the corresponding high-risk areas, and determines whether an inspection task exists. If it exists, an inspection analysis signal is generated; otherwise, a high-risk warning message is generated. Further processing of the generated inspection analysis signal retrieves the corresponding power plant personnel and their information, including personnel permissions, employee ID, and job position. The module then determines whether the personnel information matches the inspection task, specifically based on personnel permissions and job position. If a match is found, a normal monitoring signal is generated and transmitted to the comprehensive analysis and identification module; otherwise, a high-risk warning message is generated and transmitted to the location management information output module.

[0048] The comprehensive analysis and identification module performs secondary analysis and processing on the acquired normal monitoring signals. It generates corresponding inspection paths based on the inspection tasks, acquires the location trajectory paths of power plant personnel, and analyzes the overlap rate between the inspection paths and the location trajectory paths. The overlap rate here represents the overlap rate between the paths already traversed by power plant personnel and the inspection paths. The specific overlap rate is calculated by dividing the length of the overlapping path by the total length of the analyzed path. Then, the obtained overlap rate is compared with a preset percentage, the specific value of which is set by the operator. If the overlap rate is greater than the preset percentage, it indicates that the location trajectory path of the power plant personnel is similar to the inspection path, and continuous monitoring information is generated. Conversely, if the overlap rate is less than the preset percentage, it indicates that there is a difference between the location trajectory path of the power plant personnel and the inspection path, and a difference analysis signal is generated.

[0049] The generated difference analysis signal is processed, and the corresponding trajectory direction is obtained based on the positioning trajectory path. At the same time, the trajectory direction corresponding to the inspection path is also obtained. The trajectory direction obtained here is the trajectory direction corresponding to the same trajectory segment. The deviation between the two trajectory directions is analyzed. Simultaneously, the obtained trajectory direction deviation is used as the standard to generate trajectory correction information and transmit it to the management information output module.

[0050] The management information output module is used to display the acquired continuous monitoring information and trajectory correction information to the corresponding management personnel.

[0051] Example 2

[0052] As a second embodiment of the present invention, it is implemented based on the first embodiment, and the difference from the first embodiment is as follows:

[0053] The normal positioning area analysis module processes the acquired normal area analysis signals, segments the time to obtain working and non-working periods. During working periods, real-time monitoring of power plant personnel is performed and real-time monitoring signals are generated. During non-working periods, real-time monitoring of power plant personnel is turned off, and the identification information of the electronic fence is acquired to determine whether there are any abnormal situations. Here, abnormal situations are indicated by entering high-risk areas during non-working periods. If such situations exist, high-risk warning information is generated; otherwise, the status remains unchanged.

[0054] Next, the generated real-time monitoring signals are analyzed to obtain historical data. Simultaneously, the power plant is divided into regions. Based on historical data, areas of the power plant that frequently experience location drift due to signal interference are identified and marked as affected areas. Then, the corresponding power plant personnel and their location signals within the affected areas are obtained, and it is determined whether a warning situation exists. Specifically, the determination of a warning situation here is the same as in Implementation Example 1. If a warning situation exists, a warning verification analysis signal is generated; otherwise, continuous monitoring information is generated. The warning verification analysis signal is further processed using a time period t, the specific value of which is set by the operator. The location where the warning signal is generated is obtained, and its corresponding occurrence frequency is calculated. The obtained occurrence frequency is compared with a preset frequency, the specific value of which is set by the operator. If the occurrence frequency is greater than the preset frequency, it indicates that the warning situation for the corresponding power plant personnel is real, and a high-risk warning information is generated. Conversely, if the occurrence frequency is less than the preset frequency, the monitoring video of the corresponding affected area is retrieved, and verification analysis is performed in conjunction with the monitoring video to generate continuous inspection information or high-risk warning information. Both are then transmitted to the management information output module.

[0055] The management information output module is used to display the acquired continuous monitoring information or high-risk early warning information to the corresponding management personnel.

[0056] Example 3

[0057] As a third embodiment of the present invention, the focus is on combining the implementation processes of the first and second embodiments.

[0058] The data in the above formulas are all calculated using numerical values, without substituting the units of the parameters. In addition, the contents not described in detail in this specification are all prior art known to those skilled in the art.

[0059] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A power plant personnel positioning management platform, characterized in that, include: The personnel information acquisition module is used to obtain personnel location information through UWB communication with the base station via the positioning tag and transmit it to the positioning status recognition module; The positioning status recognition module is used to determine whether a person is in a static or dynamic state. When the person is in a static state, it sets the signal area correction signal and generates static correction information. When the person is in a dynamic state, it calculates and adaptively adjusts the step size, and combines the movement distance calculated by the gyroscope to generate dynamic correction information. Based on the static and dynamic correction information, the module identifies the person's position and determines whether it is a high-risk or normal area. It then generates a high-risk area analysis signal or a normal area analysis signal, respectively, and transmits both signals. The high-risk location area analysis module is used to process signals from high-risk areas. If there is a valid inspection task and the personnel match the task, a normal monitoring signal is generated and transmitted to the comprehensive analysis module; otherwise, a high-risk early warning information is generated. The comprehensive analysis and identification module is used to process normal monitoring signals, generate inspection paths and calculate the overlap rate with the positioning trajectory. If the overlap rate meets the standard, continuous monitoring information is generated; otherwise, difference analysis signals and trajectory correction information are generated. The normal positioning area analysis module processes signals from normal areas, dividing them into working and non-working periods. During working periods, signals are generated in real time, while during non-working periods, high-risk areas are monitored only through electronic fences. The module analyzes real-time monitoring signals, marks areas affected by positioning drift, verifies early warnings for these areas by frequency or monitoring, and generates continuous inspection information or high-risk early warning information.

2. The power plant personnel positioning management platform according to claim 1, characterized in that, It also includes a management information output module, which displays continuous monitoring information, trajectory correction information, high-risk early warning information, or continuous inspection information.

3. The power plant personnel positioning management platform according to claim 1, characterized in that, The specific method by which the positioning status recognition module determines a person's static or dynamic status is as follows: The tag uses its built-in accelerometer and positioning data change rate to determine the state. If the acceleration is less than 0.1g and the position change is less than 30cm for 5 consecutive seconds, the state is determined to be static and a static analysis signal is generated. Conversely, if the acceleration is greater than 0.1g or the position change is greater than 30cm / second, the state is determined to be dynamic and a dynamic analysis signal is generated.

4. The power plant personnel positioning management platform according to claim 1, characterized in that, The specific method by which the positioning status recognition module sets the signal area correction signal and generates static correction information when in a static state is as follows: A static confidence zone is set with radius d as the standard, and the specific value of d is set by the operator. The positioning signal is corrected with the center of the zone as the reference point. If a drift point that exceeds the zone occurs, it is directly removed and the reference point is used until obvious movement is detected and then the system is unlocked to generate static correction information.

5. The power plant personnel positioning management platform according to claim 1, characterized in that, The specific method by which the positioning status recognition module combines the gyroscope to calculate the movement distance and generate dynamic correction information is as follows: Using formula The step length SL of the power plant personnel is calculated, where a, b, and c are calibration coefficients, H is height, and SF is step frequency. The step length is adaptively adjusted based on different environments. Then, the movement time of the power plant personnel is obtained, and the movement distance is calculated using the formula: [Formula omitted for brevity]. in The direction deviation between the i-th step and the previous step is calculated, and corresponding positioning corrections are performed based on the obtained movement distance to generate dynamic correction information.

6. The power plant personnel positioning management platform according to claim 1, characterized in that, The specific method by which the high-risk location area analysis module processes high-risk area signals is as follows: The system identifies the corresponding high-risk areas and determines whether an inspection task exists. If it exists, an inspection analysis signal is generated; otherwise, a high-risk warning message is generated. The generated inspection analysis signal is processed to obtain the corresponding power plant personnel and their information, including personnel permissions, employee numbers, and job positions. The system determines whether the personnel information matches the inspection task. If they match, a normal monitoring signal is generated and transmitted to the integrated analysis and identification module. Otherwise, a high-risk warning message is generated.

7. A power plant personnel positioning management platform according to claim 1, characterized in that, The specific method by which the comprehensive analysis and identification module processes normal monitoring signals is as follows: The corresponding inspection path is generated based on the inspection task. At the same time, the location trajectory path of the power plant personnel is obtained and the overlap rate between the inspection path and the location trajectory path is analyzed. Then, the obtained overlap rate is compared with the preset percentage. If the overlap rate is greater than the preset percentage, continuous monitoring information is generated. Otherwise, if the overlap rate is less than the preset percentage, a difference analysis signal is generated and analyzed. The trajectory direction corresponding to the positioning trajectory path is obtained, and the trajectory direction corresponding to the inspection path is also obtained. The deviation between the two trajectory directions is analyzed. At the same time, the obtained trajectory direction deviation is used as the standard to generate trajectory correction information and transmit it to the management information output module.

8. The power plant personnel positioning management platform according to claim 1, characterized in that, The normal positioning area analysis module processes normal area signals in the following specific way: The time is segmented to obtain working and non-working periods. During working periods, real-time monitoring of power plant personnel is performed and real-time monitoring signals are generated. During non-working periods, real-time monitoring of power plant personnel is turned off, and the identification information of the electronic fence is obtained to determine whether there are any abnormalities. If there are, a high-risk warning message is generated; otherwise, it remains unchanged.

9. A power plant personnel positioning management platform according to claim 8, characterized in that, The normal positioning area analysis module processes high-risk early warning information in the following specific way: Analyze historical data and divide the area into regions, mark the areas affected by signal interference that often cause location drift, monitor the location signals of people in the affected areas, judge the early warning situation according to the established method, generate early warning verification analysis signal if there is an early warning, and generate continuous monitoring information if there is no early warning. Process the early warning verification and analysis signal, calculate the early warning occurrence frequency with a set period t, and compare it with the preset frequency; If the risk exceeds the preset threshold, it is considered a genuine warning, and a high-risk warning message is generated. If the risk does not exceed the threshold, monitoring data is retrieved for verification, and continuous inspection information or a high-risk warning message is generated.

Images