Power plant inspection personnel positioning management method and system based on BIM

Abstract

The invention discloses a BIM-based power plant inspection personnel positioning management method and system, and particularly relates to the field of inspection personnel management, and the method comprises the steps: mapping the positioning and equipment state data of inspection personnel into a BIM model for deviation analysis, so as to verify an actual track. According to the BIM-based power plant inspection personnel positioning management method and system, by binding the BIM model for the track points, systematic positioning deviation caused by a high-pressure valve group is corrected in a targeted manner, continuous deviation between the personnel track and the real position in the BIM model is reduced, and the basic accuracy of inspection track data is improved; through fusion error compensation of BIM space alignment, a signal distortion error caused by a high-temperature thermal field around the boiler is dynamically corrected, dual calibration is formed in combination with multipath effect compensation, the deviation between a track display value and a real position is remarkably reduced, the credibility and stability of track data are improved, and the method is suitable for popularization and application. The negative influence of positioning deviation on personnel scheduling efficiency and emergency response decision reliability in the prior art is effectively relieved.

Description

Technical Field

[0001] This invention relates to the field of inspection personnel management technology, and more specifically, to a BIM-based method and system for the location management of power plant inspection personnel. Background Technology

[0002] As boiler-centric thermal power plants transform towards intelligent operation and maintenance, precise location and dynamic management of inspection personnel operating deep in high-temperature and high-pressure core areas are crucial to improving the efficiency of operation and maintenance tasks and the level of safety supervision. Traditional methods of managing inspection personnel often rely on wireless communication technologies such as ultra-wideband to obtain location data. However, actual tests show that in environments with high-density metal equipment, such as boiler rooms, radio signals are easily interfered with by multipath effects and signal blockage, resulting in a significant reduction in the accuracy of location data. This makes it impossible to achieve refined personnel scheduling and risk warning, and causes delays in emergency response in case of emergencies, posing a challenge to overall production safety management and resource planning.

[0003] To address the shortcomings of traditional location data applications, existing technologies have developed solutions that integrate positioning systems with 3D BIM models to extract feature information. This enables a visual correlation between personnel location and the work environment, alleviating to some extent the management challenges caused by inaccurate positioning, such as difficulty in tracking inspection tasks and monitoring personnel dynamics. It also enhances the business value of location information for operation and maintenance scheduling and safety monitoring.

[0004] However, in actual use, it still has some shortcomings, such as the inability to dynamically correct positioning errors based on the known signal distortion model of the high-temperature thermal field around the boiler or the multipath effect predicted by the high-pressure valve group. This results in a continuous and uncorrected deviation between the displayed value of personnel trajectory in the BIM model and the actual location, which significantly reduces the efficiency of personnel scheduling optimization and the reliability of emergency response decisions. Summary of the Invention

[0005] To overcome the aforementioned deficiencies of the prior art, this invention provides a BIM-based method and system for the location management of power plant inspection personnel, which addresses the problems mentioned in the background section through the following solutions.

[0006] To achieve the above objectives, the present invention provides the following technical solution: BIM-based methods for managing the location of power plant inspection personnel include: S1: Issue a task list containing the preset first personnel trajectory and equipment inspection items to the inspection personnel, and receive the location data of the inspection personnel and the equipment status data associated with the location data in real time; S2: Preprocess the positioning data and the device status data to generate a second personnel trajectory; S3: Obtain the BIM model of the target power plant and integrate a management rule library containing multiple inspection management rules into the BIM model; S4: Map the second personnel trajectory to the BIM model to calculate the positioning error compensation value corresponding to each trajectory point in the second personnel trajectory, and generate a task deviation report that includes at least the third personnel trajectory; S5: Based on the task deviation report, the trajectory of the third person is verified in real time against the inspection management rules. If there is a violation, an early warning is automatically triggered and pushed to the management personnel terminal.

[0007] Preferably, in step S1, the sequence of trajectory points of the first personnel trajectory matches the execution order and spatial location of the equipment inspection items in the task list.

[0008] Preferably, S2, the generation of the second personnel trajectory, specifically includes: A prior error vector is bound to each trajectory point in the positioning data, and the positioning data is compensated in the first stage based on the prior error vector to generate the second personnel trajectory.

[0009] Preferably, S3, the integration of the management rule base, specifically includes: The judgment threshold of the inspection management rule is associated with the expected positioning accuracy of the corresponding area in the BIM model. For areas where the expected positioning accuracy is lower than the preset standard, the judgment threshold is automatically adjusted.

[0010] Preferably, step S3, the self-adaptive adjustment of the determination threshold, specifically includes: The inspection management rules include at least the personnel crossing the boundary alarm rules, and the judgment threshold is the boundary tolerance distance of the electronic fence; In areas where the expected positioning accuracy is low, the boundary tolerance distance is increased.

[0011] Preferably, step S4, calculating the positioning error compensation value, specifically includes: Based on the signal distortion model aligned with the BIM model space, the trajectory points in the second personnel trajectory are mapped to the corresponding three-dimensional voxels. Based on the real-time collected temperature data, the real-time thermal field intensity of the trajectory points is calculated by interpolation; The temperature-related error is obtained by inputting the thermal field intensity into the signal distortion model. The temperature-related error is weighted and fused with the corresponding multipath effect probability within the three-dimensional voxel to obtain the error vector. Based on the error vector, the trajectory points in the second person's trajectory are reverse-compensated to obtain the coordinates of the trajectory points in the third person's trajectory.

[0012] Preferably, in step S4, the real-time thermal field intensity of the trajectory point is calculated, specifically as follows: , in, Represented as trajectory points The location is at the 8 vertices of the voxel. The above temperature value comes from the sensor. , , Represented as trajectory points The relative distance to the coordinates of each vertex point.

[0013] Preferably, in step S4, the weighting coefficients of the weighted fusion are adaptively adjusted based on the real-time deviation distance between the trajectory point and the preset first personnel trajectory, specifically expressed as follows: , in, This is represented as the unadjusted weighting coefficient. Represented as the attenuation factor; The greater the deviation distance, the lower the weighting coefficient of the multipath effect probability.

[0014] Preferably, S5, which automatically triggers an early warning, specifically includes: The system classifies violations based on their severity, duration, and location reliability, and generates a structured warning message containing the location of the violation, warning level, and suggested actions, which is then pushed to the terminal.

[0015] To achieve the above objectives, the present invention provides the following technical solution: a BIM-based power plant inspection personnel location management system, which implements the above-mentioned BIM-based power plant inspection personnel location management method, including: Multi-source data acquisition module: used to issue a task list containing a preset first personnel trajectory and equipment inspection items to the inspection personnel, and to receive the location data of the inspection personnel and the equipment status data associated with the location data in real time; Standard trajectory generation module: used to preprocess the positioning data and the device status data to generate a second personnel trajectory; Model building module: used to acquire the BIM model of the target power plant, and integrate a management rule library containing multiple inspection management rules into the BIM model; Dynamic error correction module: used to map the second personnel trajectory to the BIM model, calculate the positioning error compensation value corresponding to each trajectory point in the second personnel trajectory, and generate a task deviation report that includes at least the third personnel trajectory; Early warning verification module: Based on the task deviation report, it performs real-time verification between the trajectory of the third person and the inspection management rules. If a violation is found, an early warning is automatically triggered and pushed to the management personnel terminal.

[0016] The technical effects and advantages of this invention are as follows: 1. This invention, by binding trajectory points to a BIM model, specifically corrects the systematic positioning deviation caused by high-pressure valve groups, reduces the continuous deviation between personnel trajectories in the BIM model and their actual locations, improves the basic accuracy of inspection trajectory data, and provides reliable data support for subsequent personnel scheduling optimization and emergency response decision-making. 2. This invention dynamically corrects signal distortion errors caused by the high-temperature thermal field around the boiler through BIM spatial alignment fusion error compensation. Combined with multipath effect compensation, it forms a dual calibration, which significantly reduces the deviation between the trajectory display value and the actual position, improves the reliability and stability of trajectory data, and effectively alleviates the negative impact of positioning deviation on personnel dispatch efficiency and emergency response decision reliability in the prior art. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating the steps of a BIM-based power plant inspection personnel location management method provided in an embodiment of this application.

[0018] Figure 2 This is a block diagram of a BIM-based power plant inspection personnel location management system provided according to an embodiment of this application.

[0019] Figure 3 This is a flowchart illustrating the calculation of positioning error compensation values ​​in a BIM-based power plant inspection personnel positioning management method provided in an embodiment of this application. Detailed Implementation

[0020] 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.

[0021] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification of this application, the singular expressions “a,” “an,” “the,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to and includes any or all possible combinations of one or more of the listed items.

[0022] Hereinafter, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first," "second," and "third" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0023] As attached Figure 1 The BIM-based power plant inspection personnel location management method shown here maps the location of inspection personnel to equipment status data in a BIM model for deviation analysis to verify the actual trajectory; specifically, it includes the following steps: S1: Issue a task list containing the preset first personnel trajectory and equipment inspection items to the inspection personnel, and receive the location data of the inspection personnel and the equipment status data associated with the location data in real time; S2: Preprocess the positioning data and the device status data to generate a second personnel trajectory; S3: Obtain the BIM model of the target power plant and integrate a management rule library containing multiple inspection management rules into the BIM model; S4: Map the second personnel trajectory to the BIM model to calculate the positioning error compensation value corresponding to each trajectory point in the second personnel trajectory, and generate a task deviation report that includes at least the third personnel trajectory; S5: Based on the task deviation report, the trajectory of the third person is verified in real time against the inspection management rules. If there is a violation, an early warning is automatically triggered and pushed to the management personnel terminal.

[0024] Specifically, in S1, the preset first personnel trajectory is automatically generated based on the network path in the BIM model and the safety rules in the management rule base, and the trajectory point sequence of the first personnel trajectory matches the execution order and spatial location of the equipment inspection items in the task list.

[0025] Furthermore, the system administrator can automatically trigger the generation of the task list through the management platform or by the system according to the preset inspection plan cycle. The generation process includes: calculating the optimal path connecting all specified inspection equipment based on the network path analysis algorithm in the BIM model, that is, the preset first personnel trajectory; the network path is a topology network diagram formed by connecting the center lines of components representing corridors, platforms and stairs in the model.

[0026] In this embodiment, the constraint for generating the optimal path is to minimize the total cost. Specifically, it is expressed as: , in, Represented as the trajectory points passing through the centerline of the BIM model. Construct candidate paths, Represented as path length cost, This represents the accumulated cost of a path traversing areas of different risk levels. This represents the cost of violating the task order. , , The path is represented by the weighting coefficients corresponding to each cost coefficient. The total geometric length is specifically expressed as: , in, and These are the trajectory points representing candidate paths. Represented as trajectory points and trajectory points The distance between them; the accumulated cost of the path traversing areas of different risk levels. The calculation is specifically expressed as follows: , in, Represented as a line segment The set of risk areas traversed This is indicated as a risk area based on the aforementioned management rule base. The assigned weights, The risk area is represented by the number of trajectory points on the candidate path. The weighting of the risk areas includes: safe passage weight = 1, high-temperature zone weight = 100, and prohibited zone weight = +∞; the task order violation cost. In the path Accessing devices in an order that does not conform to the specified priority will incur high costs.

[0027] Furthermore, the task list is encapsulated in JSON data format and distributed to the inspection terminals of each inspection personnel by calling a predefined RESTful API interface through the central server. After receiving the task list, the inspection terminal stores it locally. When the network connection is interrupted, the inspection can still be performed according to the locally stored task list, and the generated device status data and location data are cached locally. After the network is restored, the cached data is automatically synchronized to the edge computing nodes in chronological order.

[0028] It should be noted that the equipment inspection items in the task list are uniquely associated with specific equipment components in the BIM model; the real-time received equipment status data includes inspection results uploaded by the inspection terminal that correspond to the specific equipment component, and the inspection results are automatically associated with and updated with the latest status attributes of the component.

[0029] In this embodiment, the task list is a structured data object, whose fields include at least: task ID, task name, preset first personnel trajectory, a list of equipment inspection items including associated equipment component ID, inspection content and standard values; the equipment status data includes at least task ID, personnel ID, equipment component ID, inspection result value, inspection timestamp, and transaction ID used to associate location data.

[0030] Specifically, in S2, a prior error vector based on its two-dimensional plane coordinates is bound to each trajectory point in the positioning data, and the positioning data is compensated in the first level based on the prior error vector to generate the second personnel trajectory.

[0031] Furthermore, the process of binding the prior error vector based on two-dimensional planar coordinates is specifically as follows: for each trajectory point in the first person's trajectory... The system queries the two-dimensional grid cell in the BIM model where the error is located using a spatial index and reads its pre-stored prior error vector. ,in, Represented as trajectory points in the first person's trajectory of coordinate, Represented as trajectory points in the first person's trajectory The y-coordinate; the prior error vector Used to characterize the predictable multipath effect signal distortion deviation caused by the geometry of the high-pressure valve group in this area under standard operating conditions; trajectory points after the first stage of compensation. .

[0032] Furthermore, the preprocessing includes: performing prior error compensation on all trajectory points; performing parallel trajectory point optimization based on event clustering and weight calculation based on path consistency on the compensated data; performing adaptive filtering by combining weight information and expected signal quality parameters to generate a second personnel trajectory; and continuously detecting abnormal data during the preprocessing process, marking abnormal data, and not participating in subsequent calculations.

[0033] It should be noted that the quantitative standards for detecting abnormal data include, but are not limited to: calculating the instantaneous velocity between continuous trajectory points; if the velocity value exceeds the maximum reasonable movement speed of personnel, it is judged as abnormal; if the signal strength of the positioning data source is lower than the trusted communication threshold, the data is judged to have low credibility and is marked; if the deviation of a single trajectory point from the predicted position formed by the historical trajectory exceeds 10m and there are no supporting positioning points around it, it is judged as abnormal.

[0034] In this embodiment, the adaptive filtering employs an extended Kalman filter, and the path consistency weight... The adjustment factor, which is transformed into the observation noise covariance matrix, has a higher weight and a smaller observation noise setpoint, indicating that the data is reliable.

[0035] Furthermore, the preprocessing also includes: trajectory point optimization based on event clustering. Based on the events representing inspection actions in the equipment status data, cluster analysis is performed on the positioning data within the corresponding time window, and the geometric center of the positioning data of the cluster is used as the trajectory point corresponding to the event, so as to help generate a smoother second personnel trajectory with stronger semantic association.

[0036] In this embodiment, the clustering analysis uses the density-based DBSCAN algorithm, with its neighborhood radius set according to the accuracy of the specific positioning technology used, and the minimum number of points set to 3; when a cluster consisting of multiple trajectory points is identified... After forming a cluster, the geometric center of all points in the cluster is taken as the precise trajectory point representing the inspection event.

[0037] Furthermore, the preprocessing also includes: weight calculation based on path consistency, assigning a path consistency weight to the real-time received positioning data according to the preset first personnel trajectory in the task list; in the filtering algorithm for generating the second personnel trajectory, assigning higher confidence to the positioning data with high path consistency weight to suppress sudden trajectory drift.

[0038] In this embodiment, the path consistency weight The calculation is specifically expressed as follows: ,in, This represents the shortest vertical distance from the current location point to the preset trajectory of the first person. This is represented as a preset distance threshold, defined as 2 meters in this embodiment; when When D is much larger than 1, the weight is close to 1; when D is much larger than 1, the weight is close to 1. When the weight approaches 0.

[0039] Furthermore, the preprocessing also includes: obtaining the expected signal quality parameters of the area that the inspection personnel will enter at the next moment, and dynamically adjusting the smoothing coefficient of the data filtering algorithm; in areas with poor expected signal quality, increasing the smoothing intensity to suppress noise, and in areas with good expected signal quality, decreasing the smoothing intensity to preserve motion details.

[0040] It should be noted that the smoothing coefficient... Used to adjust the noise covariance matrix; the dynamic adjustment strategy for the smoothing coefficient is as follows: set a base smoothing coefficient. The expected signal quality parameters Normalize to the [0,1] interval, and then calculate the smoothing coefficient used in practice. Specifically, it is expressed as: in, The expected signal quality parameter is expressed as the maximum permissible smoothing coefficient. A mapping relationship is established between the multipath effect probability and the multipath effect probability pre-stored in the BIM model.

[0041] In this embodiment, It can be initially set to 0.8. The initial value is set to 2.0; the basic smoothing coefficient and maximum smoothness coefficient The specific value is determined by backtesting and debugging historical positioning data.

[0042] Specifically, in S3, the inspection management rules integrated in the management rule base include at least personnel boundary crossing alarm rules, behavior sequence rules, time constraint rules, and state dependency rules; the integration is achieved by coupling the formalized rule objects with the spatial areas in the BIM model.

[0043] It should be noted that obtaining the BIM model of the target power plant includes: extracting the stored original BIM model file from the central document library of the target power plant; and preprocessing the BIM model before integrating the rule base, including: lightweighting the BIM model, removing internal invisible components and high-precision textures, and retaining the geometric information and attribute data of the main equipment, structures, and spatial areas; converting the local coordinate system of the BIM model to a global coordinate system consistent with the actual measurement and positioning base station network of the plant area through registration with common control points; recoding the component IDs and structuring the attributes of key equipment in the BIM model, including but not limited to boilers, pressure valves, etc., and their respective spatial areas; coupling formal rule objects with spatial areas in the BIM model in the database architecture of the BIM model, including: extending a rule ID list attribute field for specific spatial area components; and when the positioning coordinates of personnel fall into a predefined spatial area, obtaining all rule IDs bound to that area and performing real-time verification.

[0044] In this embodiment, the natural language description of the personnel boundary crossing alarm rule includes, but is not limited to, prohibiting entry into the 3-meter area around the boiler, etc., which is converted into an executable data logic structure through a predefined domain-specific language; the formalization of the behavior sequence rule is achieved by defining a directed acyclic graph, where nodes represent equipment inspection items and edges represent legal movement sequences.

[0045] In one possible implementation, the judgment threshold of the inspection management rule is associated with the expected positioning accuracy of the corresponding area in the BIM model, and the judgment threshold is the boundary tolerance distance of the electronic fence; for areas where the expected positioning accuracy is lower than the preset standard, the judgment threshold is automatically adjusted.

[0046] It should be noted that in areas with low expected positioning accuracy, the boundary tolerance distance is increased; the inspection management rules integrated in the management rule base have a trigger linkage relationship, and the trigger condition is that when one rule is violated, the monitoring level or warning level of another related rule is automatically activated or upgraded; the calculation of the expected positioning accuracy is an automated process, which is based on the signal distortion model aligned with the BIM model space, the historical or simulated positioning error vector set on the grid vertices of a specific spatial area, the standard deviation of the magnitude of all vectors in the set is calculated, and this standard deviation is used as the quantitative value of the expected positioning accuracy of the area; the accuracy of the preset standard is an empirical threshold, which is determined based on: determining the maximum allowable value of personnel positioning error according to the power plant safety regulations; and using the standard deviation of positioning accuracy in areas with good signal in the plant area as a benchmark; in this embodiment, when the standard deviation of the expected positioning accuracy value is greater than 0.8, it is determined to be lower than the preset standard.

[0047] Specifically, in S4, at least two different signal distortion compensation models aligned with the BIM model space are provided. For each trajectory point, the compensation value output by each model is calculated in parallel, and the outputs of multiple models are weighted and fused based on the trajectory point. The weighting coefficients of the weighted fusion are based on the real-time deviation distance between the trajectory point and the preset first personnel trajectory. Adaptive adjustments are made; the greater the deviation distance, the lower the weighting coefficient of the multipath effect probability.

[0048] In this embodiment, the at least two different signal distortion compensation models include, but are not limited to: a temperature variation model based on linear regression and an empirical model based on a lookup table. By simulating the positioning error under different combinations of temperature and humidity in the laboratory, a high-dimensional lookup table is constructed, and the error value is directly obtained through parameter indexing.

[0049] In one possible implementation, calculating the positioning error compensation value includes: mapping the trajectory points in the second personnel trajectory to corresponding three-dimensional voxels based on a signal distortion model aligned with the BIM model space; calculating the real-time thermal field intensity of the trajectory points by interpolation based on real-time collected temperature data; inputting the thermal field intensity into the signal distortion model to obtain a temperature-related error; weighting and fusing the temperature-related error with the corresponding multipath effect probability within the three-dimensional voxels to obtain an error vector, the direction of which is predefined by the relative positional relationship between the trajectory points and the boiler center; and performing reverse compensation on the trajectory points in the second personnel trajectory based on the error vector to obtain the coordinates of the trajectory points in the third personnel trajectory.

[0050] It should be noted that, based on discrete temperature sensor readings, the spatial continuous temperature distribution value at the location of the trajectory point is calculated through interpolation. Specifically, it is expressed as: , in, Represented as trajectory points The location is at the 8 vertices of the voxel. The above temperature value comes from the sensor. , , Represented as trajectory points The relative distance to the coordinates of each vertex point is used; the closer the distance, the greater the weight. In this embodiment, , , ,in , , Represented as voxel dimensions; the temperature-related error is the quantitative relationship between temperature and positioning error, specifically expressed as: , in, This is expressed as the prediction error value caused by the thermal field intensity; This represents the spatially continuous temperature distribution value calculated through interpolation at the location of the trajectory point. , , This represents the specific distortion effect of the boiler on the positioning signal at different temperatures; the temperature-related error and the multipath effect error are combined, specifically represented as follows: , in, This is represented as the final predicted error value after fusion. This is expressed as temperature-dependent error. This represents the multipath interference probability value at that location, obtained from the multipath effect probability map. It is represented as a weighting coefficient, used to adjust the weight of the multipath effect.

[0051] Specifically, the formula for adaptively adjusting the weighting coefficients is expressed as follows: in This is represented as the unadjusted weighting coefficient. This is represented as a decay factor, so that when personnel temporarily deviate from the path due to obstacle avoidance, the fusion model is used normally; when there is a large and unreasonable deviation, the dependence on the potentially unreliable multipath model is reduced.

[0052] Furthermore, when generating the task deviation report, the trajectory of the third person is compared with the preset trajectory of the first person, and one or more quantitative indicators among the real-time position deviation, cumulative path deviation, and task progress difference are calculated; the quantitative indicators are mapped to an impact assessment on the progress of the inspection work plan, specifically manifested as the delay in the expected task completion time.

[0053] Specifically, in S5, the real-time verification suppresses false alarms by applying threshold filtering to the quantitative indicators in the task deviation report and weighting the trajectory points of the third person's trajectory with confidence.

[0054] In this embodiment, the threshold filtering is used to set thresholds for various quantitative indicators in the task deviation report; the subsequent rule verification process is only triggered when the indicator value exceeds its corresponding threshold.

[0055] In one possible implementation, the automatically triggered warning is graded based on the severity of the violation rule, the duration of the violation, and the location reliability of the current trajectory point. A structured warning message containing the violation location, warning level, and suggested handling measures is then pushed to the terminal. The structured warning message includes at least the following fields: a unique warning identifier, warning trigger time, relevant inspection personnel ID, the violated rule ID and description, the warning level determined based on the risk score, the coordinates of the violation point in the BIM model, and the receipt status. After the warning message is pushed to the management personnel's terminal, the management personnel's selections and processing results are recorded and associated with the warning message, forming a closed-loop management data for subsequent analysis and rule optimization.

[0056] In this embodiment, a multi-factor weighted formula is constructed, which takes at least the severity level of the violation rule, the duration of the violation status, and the location confidence of the current trajectory point as input factors for weighted calculation, and outputs a comprehensive risk score. The severity level of the violation rule is represented by the pre-defined enumeration value for each rule in the management rule base. The duration of the violation status starts counting when the violation status is first detected. The location confidence is derived from the confidence index calculated when the trajectory of a third party is observed. The warning level is dynamically determined based on the comprehensive risk score.

[0057] As attached Figure 2 The BIM-based power plant inspection personnel positioning management system shown includes a multi-source data acquisition module, a standard trajectory generation module, a model building module, a dynamic error correction module, and an early warning verification module.

[0058] Specifically, the multi-source data acquisition module is used to issue a task list containing a preset first personnel trajectory and equipment inspection items to the inspection personnel, and to receive the location data of the inspection personnel and the equipment status data associated with the location data in real time.

[0059] Specifically, the standard trajectory generation module is used to preprocess the positioning data and the device status data to generate a second personnel trajectory.

[0060] Specifically, the model building module is used to obtain the BIM model of the target power plant, and integrates a management rule library containing multiple inspection management rules into the BIM model.

[0061] Specifically, the dynamic error correction module is used to map the second personnel trajectory to the BIM model to calculate the positioning error compensation value corresponding to each trajectory point in the second personnel trajectory, and generate a task deviation report that includes at least the third personnel trajectory.

[0062] Specifically, the early warning verification module is used to verify the trajectory of the third person against the inspection management rules in real time based on the task deviation report. If there is a violation, an early warning is automatically triggered and pushed to the management personnel terminal.

[0063] Secondly: The accompanying drawings of the embodiments disclosed in this invention only involve the structures involved in the embodiments disclosed in this invention. Other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of this invention can be combined with each other. In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A BIM-based method for managing the location of power plant inspection personnel, characterized in that, include: S1: Issue a task list containing the preset first personnel trajectory and equipment inspection items to the inspection personnel, and receive the location data of the inspection personnel and the equipment status data associated with the location data in real time; S2: Preprocess the positioning data and the device status data to generate a second personnel trajectory; S3: Obtain the BIM model of the target power plant and integrate a management rule library containing multiple inspection management rules into the BIM model; S4: Map the second personnel trajectory to the BIM model to calculate the positioning error compensation value corresponding to each trajectory point in the second personnel trajectory, and generate a task deviation report that includes at least the third personnel trajectory; S5: Based on the task deviation report, the trajectory of the third person is verified in real time against the inspection management rules. If there is a violation, an early warning is automatically triggered and pushed to the management personnel terminal.

2. The BIM-based power plant inspection personnel location management method according to claim 1, characterized in that: In step S1, the sequence of trajectory points of the first personnel trajectory is matched with the execution order and spatial location of the equipment inspection items in the task list.

3. The BIM-based power plant inspection personnel location management method according to claim 1, characterized in that: S2, the generation of the second personnel trajectory, specifically includes: A prior error vector is bound to each trajectory point in the positioning data, and the positioning data is compensated in the first stage based on the prior error vector to generate the second personnel trajectory.

4. The BIM-based power plant inspection personnel location management method according to claim 1, characterized in that: The integration of the management rule base, specifically S3, includes: The judgment threshold of the inspection management rule is associated with the expected positioning accuracy of the corresponding area in the BIM model. For areas where the expected positioning accuracy is lower than the preset standard, the judgment threshold is automatically adjusted.

5. The BIM-based power plant inspection personnel location management method according to claim 4, characterized in that: The S3, which adaptively adjusts the judgment threshold, specifically includes: The inspection management rules include at least the personnel crossing the boundary alarm rules, and the judgment threshold is the boundary tolerance distance of the electronic fence; In areas where the expected positioning accuracy is low, the boundary tolerance distance is increased.

6. The BIM-based power plant inspection personnel location management method according to claim 1, characterized in that: S4, calculating the positioning error compensation value, specifically includes: Based on the signal distortion model aligned with the BIM model space, the trajectory points in the second personnel trajectory are mapped to the corresponding three-dimensional voxels. Based on the real-time collected temperature data, the real-time thermal field intensity of the trajectory points is calculated by interpolation; The temperature-related error is obtained by inputting the thermal field intensity into the signal distortion model. The temperature-related error is weighted and fused with the corresponding multipath effect probability within the three-dimensional voxel to obtain the error vector. Based on the error vector, the trajectory points in the second person's trajectory are reverse-compensated to obtain the coordinates of the trajectory points in the third person's trajectory.

7. The BIM-based power plant inspection personnel location management method according to claim 6, characterized in that: S4 calculates the real-time thermal field intensity of the trajectory point, specifically as follows: ， in, Represented as trajectory points The location is at the 8 vertices of the voxel. The above temperature value comes from the sensor. , , Represented as trajectory points The relative distance to the coordinates of each vertex point.

8. The BIM-based power plant inspection personnel location management method according to claim 6, characterized in that: In step S4, the weighting coefficients of the weighted fusion are adaptively adjusted based on the real-time deviation distance between the trajectory point and the preset first personnel trajectory, specifically as follows: ， in, This is represented as the unadjusted weighting coefficient. Represented as the attenuation factor; The greater the deviation distance, the lower the weighting coefficient of the multipath effect probability.

9. The BIM-based power plant inspection personnel positioning management system according to claim 1, characterized in that: The S5 automatically triggers an early warning, specifically including: The system classifies violations based on their severity, duration, and location reliability, and generates a structured warning message containing the location of the violation, warning level, and suggested actions, which is then pushed to the terminal.

10. A BIM-based power plant inspection personnel location management system, comprising the BIM-based power plant inspection personnel location management method according to any one of claims 1-9, characterized in that, include: Multi-source data acquisition module: used to issue a task list containing a preset first personnel trajectory and equipment inspection items to the inspection personnel, and to receive the location data of the inspection personnel and the equipment status data associated with the location data in real time; Standard trajectory generation module: used to preprocess the positioning data and the device status data to generate a second personnel trajectory; Model building module: used to acquire the BIM model of the target power plant, and integrate a management rule library containing multiple inspection management rules into the BIM model; Dynamic error correction module: used to map the second personnel trajectory to the BIM model, calculate the positioning error compensation value corresponding to each trajectory point in the second personnel trajectory, and generate a task deviation report that includes at least the third personnel trajectory; Early warning verification module: Based on the task deviation report, it performs real-time verification between the trajectory of the third person and the inspection management rules. If a violation is found, an early warning is automatically triggered and pushed to the management personnel terminal.

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