A space equipment management optimization method based on digital twin visual positioning

Abstract

The application provides a space equipment management optimization method based on digital twin visual positioning, and relates to the field of data processing. In the method, multi-source positioning data is formed by acquiring visual positioning, laser scanning, inertial positioning and wireless positioning, and a position deviation change relationship is generated. After identifying a false stable state, re-verification is performed using a fixed reference object to generate position offset data. Based on the position offset data, hierarchical positioning correction and consistency joint verification are performed, and the digital twin model is updated. Further, positioning abnormal risk areas are identified, and the inspection path, equipment search order and remote operation permission are dynamically adjusted. The technical solution provided by the application improves the accuracy of digital twin visual positioning and facilitates space equipment management optimization.

Description

Technical Field

[0001] This application relates to the field of data processing technology, specifically to a spatial equipment management optimization method based on digital twin visual positioning. Background Technology

[0002] With the development of technology, existing digital twin visual positioning systems typically integrate multiple sensing results, such as visual perception, laser perception, inertial perception, and wireless positioning, to improve the positioning accuracy of spatial devices and the stability of spatial scene construction. In existing technologies, most fusion algorithms usually perform weighted fusion of different sensing results based on the historical stability, data continuity, or real-time confidence scores of each sensing source, and directly use the fused result as the basis for device location in the digital twin model. Under normal conditions, this approach can, to some extent, reduce the positioning error caused by occlusion, noise, or local interference from a single sensing source.

[0003] However, in complex spatial environments such as large industrial plants, underground utility tunnels, smart warehousing spaces, and rail transit equipment areas, different sensing sources may be simultaneously affected by different types of interference. For example, visual perception may be affected by changes in lighting, movement of obstructions, or reflection interference; laser perception may be affected by missing point clouds, transparent objects, or metal reflections; inertial perception may be affected by cumulative drift; and wireless positioning may be affected by signal blockage or multipath propagation. In this situation, although each sensing source produces deviations, the different deviations may exhibit a locally consistent relationship in spatial direction or numerical change. Therefore, the fused positioning result still maintains a superficial stability, causing the fusion system to mistakenly believe that the current positioning result has high reliability, which is detrimental to the optimization of spatial equipment management.

[0004] Therefore, there is an urgent need for a spatial equipment management optimization method based on digital twin visual positioning. Summary of the Invention

[0005] This application provides a spatial equipment management optimization method based on digital twin visual positioning, which improves the accuracy of digital twin visual positioning and facilitates spatial equipment management optimization.

[0006] The first aspect of this application provides a spatial device management optimization method based on digital twin visual positioning. The method includes: acquiring the device number, installation area, connection relationship, operating status, digital twin model, historical positioning trajectory, and spatial reference coordinates of each spatial device within a target space; combining visual positioning results, laser scanning results, inertial positioning results, and wireless positioning results to form multi-source positioning data; extracting visual features, structural features, motion features, and distance features based on the multi-source positioning data, and performing device appearance matching, structural contour matching, trajectory continuity matching, and spatial position matching respectively to generate position deviation change relationships corresponding to each positioning result; identifying false stable states based on the position deviation change relationships between each positioning result; and, upon identifying a false stable state, using fixed walls, fixed columns, fixed device bases, and preset positioning points to adjust the positioning structure... If a re-verification is performed, position offset data corresponding to each positioning result is generated. Based on the position offset data, the baseline positioning result, abnormal positioning result, and associated abnormal positioning result are determined. Based on the relationship between the baseline positioning result, abnormal positioning result, and associated abnormal positioning result, hierarchical positioning correction is performed to generate corrected device visual positioning results. Joint verification is performed based on the consistency relationship between the corrected device visual positioning results and device number, device installation area, device connection relationship, and device operating status. When the consistency condition is met, the digital twin model is updated. Based on the updated digital twin model, the visual position, device connection relationship, and device operating status of each spatial device are jointly analyzed to identify positioning anomaly risk areas. Based on the positioning anomaly risk areas, the inspection path, device retrieval order, and remote operation permissions are adjusted to complete the optimization of spatial device management based on digital twin visual positioning.

[0007] A second aspect of this application provides a spatial device management optimization apparatus based on digital twin visual positioning. The apparatus includes an acquisition module and a processing module. The acquisition module acquires the device number, installation area, connection relationship, operating status, digital twin model, historical positioning trajectory, and spatial reference coordinates of each spatial device within a target space, and combines this with visual positioning results, laser scanning results, inertial positioning results, and wireless positioning results to form multi-source positioning data. The processing module extracts visual features, structural features, motion features, and distance features based on the multi-source positioning data, and performs device appearance matching, structural contour matching, trajectory continuity matching, and spatial position matching respectively to generate position deviation change relationships corresponding to each positioning result. The processing module further identifies false stable states based on the position deviation change relationships between the positioning results, and when a false stable state is identified, utilizes fixed walls, fixed columns, fixed device bases, and preset positioning points. The processing module re-verifies each positioning result to generate corresponding position offset data. It further determines the baseline positioning result, abnormal positioning result, and associated abnormal positioning result based on the position offset data, and performs hierarchical positioning correction based on the relationship between these results to generate corrected device visual positioning results. The module also performs joint verification based on the consistency relationship between the corrected device visual positioning results and the device number, device installation area, device connection relationship, and device operating status, and updates the digital twin model when the consistency condition is met. Finally, the module performs joint analysis of the visible position, device connection relationship, and device operating status of each spatial device based on the updated digital twin model to identify positioning anomaly risk areas, and adjusts the inspection path, device retrieval order, and remote operation permissions based on these risk areas to optimize spatial device management based on digital twin visual positioning.

[0008] A third aspect of this application provides an electronic device including a processor and a memory; the memory stores a computer program, wherein the computer program, when executed by the processor, implements a spatial device management optimization method based on digital twin visual positioning as described above.

[0009] In a fourth aspect, this application provides a non-transitory computer-readable storage medium storing instructions that, when executed, perform a spatial device management optimization method based on digital twin visual positioning as described above.

[0010] In summary, one or more technical solutions provided in this application have at least the following technical effects or advantages: By fusing visual positioning results, laser scanning results, inertial positioning results, and wireless positioning results to form multi-source positioning data, and further generating position deviation change relationships, the stability and reliability of space equipment positioning in complex spatial environments can be improved. By identifying false stable states and performing re-verification using fixed walls, fixed columns, fixed equipment bases, and preset positioning points, hidden position offset problems that are difficult to identify in traditional multi-source fusion processes can be discovered, preventing the digital twin model from maintaining an incorrect position for a long time. By distinguishing between baseline positioning results, abnormal positioning results, and associated abnormal positioning results, and performing hierarchical positioning correction, the interference of abnormal positioning results on the final visual positioning results of the equipment can be reduced, improving the positioning accuracy of the equipment. Furthermore, by performing joint verification of the corrected visual positioning results of the equipment with the equipment number, equipment installation area, equipment connection relationship, and equipment operating status, erroneous positioning results can be prevented from being written into the digital twin model, improving the consistency between the digital twin model and the real space equipment. Finally, by identifying positioning anomaly risk areas and dynamically adjusting inspection paths, equipment retrieval order, and remote operation permissions, the efficiency of space equipment management, anomaly investigation efficiency, and remote operation security can be improved. Therefore, it improves the accuracy of digital twin visual positioning and facilitates the optimization of space equipment management. Attached Figure Description

[0011] Figure 1 A flowchart illustrating a spatial equipment management optimization method based on digital twin visual positioning, provided for an embodiment of this application; Figure 2 A schematic diagram of a spatial equipment management optimization device based on digital twin visual positioning provided in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0012] Explanation of reference numerals in the attached figures: 21. Acquisition module; 22. Processing module; 31. Processor; 32. Communication bus; 33. User interface; 34. Network interface; 35. Memory. Detailed Implementation

[0013] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0014] In the description of the embodiments of this application, the words "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design that is described as "for example" or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design options. Rather, the use of the words "for example" or "for instance" is intended to present the relevant concepts in a specific manner.

[0015] In the description of the embodiments of this application, the term "multiple" means two or more. For example, multiple systems means two or more systems, and multiple screen terminals means two or more screen terminals. In addition, the terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0016] To address the aforementioned technical problems, this application provides a spatial equipment management optimization method based on digital twin visual positioning, referring to... Figure 1 , Figure 1 This is a flowchart illustrating a spatial device management optimization method based on digital twin visual positioning, provided in an embodiment of this application. The method is applied to a server and includes steps S110 to S160, as follows: S110. Obtain the device number, device installation area, device connection relationship, device operating status, digital twin model, historical positioning trajectory and spatial reference coordinates of each spatial device in the target space, and combine them with visual positioning results, laser scanning results, inertial positioning results and wireless positioning results to form multi-source positioning data.

[0017] Specifically, the server first retrieves the device number, installation area, connection relationship, and operating status of each spatial device within the target space from the spatial device ledger, operation and maintenance management system, and digital twin model. The device number is a data identifier used to uniquely identify spatial devices, such as a QR code number, asset number, RFID number, or internal system number. The installation area is the permitted spatial range for the device within the target space, which can be determined by area boundary points, floor zones, cabinet numbers, or the range of the device's base. The connection relationship is the connection between the spatial device and adjacent spatial devices, cables, pipelines, control cabinets, and communication nodes, used to determine whether the spatial device's location conforms to the actual connection logic. The operating status is information about whether the spatial device is currently operating normally, shut down, under maintenance, moved, locked, or experiencing an abnormality. Using the device number as an index, the server retrieves the model position, model posture, and model outline of the corresponding spatial device from the digital twin model. Simultaneously, it reads the historical positioning trajectory formed by the spatial device at historical moments, ensuring that subsequently collected visual positioning results, laser scanning results, inertial positioning results, and wireless positioning results can all be mapped to the same spatial device, avoiding the mixing of positioning data from different spatial devices.

[0018] The server establishes spatial reference coordinates based on pre-calibrated spatial reference points, spatial coordinate axis directions, and spatial region boundaries within the target space. Spatial reference points are long-term stable reference points within the target space that have already been measured, such as corner calibration points, ground calibration points, fixed column calibration points, or fixed equipment base calibration points. Spatial coordinate axis directions describe the length, width, and height directions within the target space. Spatial region boundaries are the boundary ranges corresponding to walls, passageways, floors, cabinet areas, or equipment areas within the target space. The server uniformly transforms the model positions in the digital twin model, historical positions in historical positioning trajectories, and regional ranges in the equipment installation area to the spatial reference coordinates, enabling comparison of data from different sources within the same coordinate system. If visual positioning results, laser scanning results, inertial positioning results, or wireless positioning results originally used different coordinate systems, the server performs a unified transformation using a coordinate transformation matrix. The coordinate transformation expression is:

[0019] in, This represents the position vector transformed to a spatial reference coordinate system, which is calculated through coordinate transformation. This represents the position vector in the original positioning device coordinates, which is obtained by visual positioning devices, laser scanning devices, inertial positioning devices, or wireless positioning devices. This represents the rotation matrix that transforms the original positioning device coordinates to the spatial reference coordinates. It is calibrated based on the position of the spatial reference point in the original positioning device coordinates and the position in the spatial reference coordinates. This represents the translation vector from the original positioning device coordinates to the spatial reference coordinates, which is determined based on the position difference between the origin of the original positioning device coordinates and the origin of the spatial reference coordinates.

[0020] The server collects visual positioning results through visual positioning devices. These devices can be fixed cameras, inspection robot cameras, or mobile terminal cameras. The visual positioning results include the appearance area of ​​the spatial device in the image, the device number identifier, edge contour, installation direction, and the image relative position of the device to a fixed wall, fixed column, or adjacent spatial device. When collecting visual positioning results, the server first identifies the device area in the image data, then determines whether the device number identifier can be identified in the image data. If the device number identifier can be identified, the visual positioning result is directly associated with the corresponding device number. If the device number identifier cannot be identified, candidate spatial devices are determined based on the appearance area, edge contour, installation direction, and device installation area. The image relative position here is not the final spatial position, but is used to determine whether the visual positioning result matches the model contour, model posture, and device installation area of ​​the corresponding spatial device in the digital twin model. It will subsequently be combined with laser scanning results, inertial positioning results, and wireless positioning results to form multi-source positioning data.

[0021] The server acquires laser scanning results using a laser scanning device. This device can be a 3D LiDAR, a 2D LiDAR, or a point cloud scanning device mounted on an inspection robot. The laser scanning results include point cloud data formed by the space equipment and its surrounding structures. From this point cloud data, the 3D contour, surface boundaries, installation height, location of the fixed equipment base, and spatial occupancy range of the space equipment can be extracted. After converting the laser scanning results to spatial reference coordinates, the server matches them with the corresponding space equipment's model contour and location in the digital twin model to determine the candidate space equipment corresponding to the laser scanning results. If there are occlusions, missing data, or reflection interference in the point cloud data, the server does not directly delete the laser scanning results. Instead, it retains markers for missing point cloud areas, discontinuous point cloud boundaries, and abnormal reflection areas, enabling the generation of subsequent multi-source positioning data to identify potential deviations in the laser scanning results.

[0022] The server collects inertial positioning results using inertial positioning devices. These devices typically include accelerometers, gyroscopes, or inertial measurement units (IMUs), which record the device's movement path, attitude changes, turning changes, and velocity changes within the target space. The acquisition device can be an inspection robot, a mobile terminal, or other mobile device equipped with visual positioning and laser scanning devices. Since inertial positioning results often accumulate errors over time, the server does not use them as the final position of the spatial device alone. Instead, it uses them to describe the continuous motion relationship between consecutive acquisition moments. This motion continuity is used to constrain positional jumps in visual positioning and laser scanning results. For example, if a visual positioning result suddenly jumps to a distant area within an adjacent time window, while the inertial positioning result shows no corresponding displacement of the acquisition device, the server can mark this visual positioning result as a suspected jump. The server can estimate the positional change of the acquisition device within adjacent time windows based on the inertial positioning results; the positional recursion expression is as follows:

[0023] in, This indicates the estimated position of the data acquisition device within the current time window, which is recursively derived from the position, velocity, and current acceleration of the previous time window. This indicates the estimated position of the data acquisition device within the previous time window, which is obtained from the previous round of inertial positioning results or the calibrated position under spatial reference coordinates; This indicates the velocity of the data acquisition device within the previous time window, which is calculated based on the velocity changes recorded by the inertial positioning device or the displacement changes between adjacent calibrated positions. This represents the acceleration of the data acquisition device within the current time window. It is acquired by the accelerometer in the inertial positioning device and processed by attitude compensation and gravity component removal. This indicates the time interval between the current time window and the previous time window, which is determined based on the difference between the two collection timestamps.

[0024] The server collects wireless positioning results through wireless positioning devices. These devices can employ Bluetooth, ultra-wideband, RFID, Wi-Fi, or other wireless positioning methods. The wireless positioning results include the distance relationships, signal strength relationships, and time-of-arrival relationships between the space device or data acquisition device and multiple wireless base stations, as well as the determined wireless positioning area. The wireless positioning area is the spatial range where the space device may be located; it is not necessarily a precise coordinate point. Its function is to provide range constraints for the space device's position. When visual positioning results are obstructed, laser scanning results show missing point clouds, or inertial positioning results show increased cumulative errors, the server can use the wireless positioning area to determine whether the space device is still near its installation area, thus avoiding erroneous positioning based solely on local visual or point cloud results. When the wireless positioning area is determined using the distance relationships between multiple wireless base stations, the spatial relationship between the space device and the wireless base stations can be described by a distance constraint expression:

[0025] in, This represents the estimated wireless position of a space device or data acquisition device in spatial reference coordinates, which is obtained by jointly solving the distance relationships between multiple wireless base stations. Indicates the first The position of each wireless base station in the spatial reference coordinate system is obtained from the measurement and calibration results during the installation of the wireless base station. Indicates the space device or acquisition device and the first The distance between wireless base stations can be obtained from ultra-wideband ranging results, time difference of arrival results, or signal strength conversion results; This represents the number of the wireless base station, and its value corresponds to the set of wireless base stations participating in the current wireless positioning calculation.

[0026] The server performs time alignment on visual positioning results, laser scanning results, inertial positioning results, and wireless positioning results. Time alignment refers to merging different positioning results whose acquisition times fall within the same time window into the same positioning data group, so that the positioning data group can represent multiple positioning results of the same spatial device under the same time conditions. The server first reads the acquisition timestamp of each positioning result, and then determines the size of the time window based on the device's operating status. When the spatial device is in a fixed, locked, or stopped state, the time window can be appropriately widened because the spatial device should not undergo significant positional changes in a short period of time. When the spatial device is in a moving, maintenance, or abnormal state, the time window should be narrowed to avoid incorrect merging of position results from different times. If the acquisition time of a positioning result is significantly delayed or advanced, the server can combine historical positioning trajectories to determine whether it can still be classified into the same positioning data group. If it cannot be classified, it is marked as data to be confirmed. The server can determine whether positioning results belong to the same time window based on the time difference, and the judgment expression is:

[0027] in, This indicates the time when the location results to be merged were collected, which is obtained from the timestamp record of the corresponding location device; This indicates the reference time for the current location data set, which can be the earliest collection time, the average collection time, or the collection cycle time set by the server within the location data set. This represents the allowed time window threshold for space equipment under its current operating state, which is determined based on the equipment's operating state, acquisition frequency, and allowed movement speed of the space equipment.

[0028] The server performs spatial unification processing on the time-aligned visual positioning results, laser scanning results, inertial positioning results, and wireless positioning results. Spatial unification processing involves unifying the image positions in the visual positioning results, the point cloud positions in the laser scanning results, the path positions in the inertial positioning results, and the wireless positioning areas in the wireless positioning results to a spatial reference coordinate system, and establishing associations with the device number, device installation area, device connection relationship, device operating status, digital twin model, and historical positioning trajectory. During spatial unification processing, the server determines whether each positioning result falls within the device installation area, whether it disrupts the spatial adjacency relationships corresponding to device connections, and whether it conforms to the position change patterns corresponding to the device operating status. If a positioning result exceeds the device installation area or significantly disrupts device connections, the server does not discard the positioning result directly but adds an anomaly marker, enabling subsequent identification of position deviation changes to determine whether the positioning result belongs to an abnormal positioning source.

[0029] Finally, the server binds the time-aligned and spatially unified positioning data group with the device number, device installation area, device connection relationship, device operating status, digital twin model, historical positioning trajectory, and spatial reference coordinates to form multi-source positioning data. Multi-source positioning data is not simply a collection of positioning coordinates, but a comprehensive data structure that includes visual positioning results, laser scanning results, inertial positioning results, wireless positioning results, as well as basic information about spatial devices, spatial constraint information, model information, and historical information.

[0030] S120. Based on multi-source positioning data, extract visual features, structural features, motion features and distance features, and perform device appearance matching, structural contour matching, trajectory continuity matching and spatial position matching respectively to generate the position deviation change relationship corresponding to each positioning result.

[0031] Specifically, the server first reads the visual positioning results, laser scanning results, inertial positioning results, and wireless positioning results corresponding to the same spatial device within the same time window. Based on the device's serial number, it binds these four types of positioning results to the device's installation area, operating status, digital twin model, historical positioning trajectory, and spatial reference coordinates. The same spatial device refers to a device object uniquely identified by the same serial number; the same time window refers to a short time range where the acquisition time meets a preset time difference requirement; and the spatial reference coordinates are a coordinate system used to uniformly describe all positions in the target space. The server converts the image positions in the visual positioning results, the point cloud positions in the laser scanning results, the path positions in the inertial positioning results, and the wireless positioning areas in the wireless positioning results to the spatial reference coordinates, enabling comparison of different positioning results within the same coordinate system. If a positioning result fails to complete the coordinate conversion, it is marked as a positioning result to be confirmed but is still retained in the multi-source positioning data for subsequent assessment of whether the positioning result caused a positional deviation.

[0032] The server extracts visual features from the visual positioning results, including the appearance area, device identification number, edge contour, and installation direction. The appearance area refers to the pixel region in the image identified as a space device. The device identification number is a QR code, nameplate number, label number, or other identifiable identifier on the surface of the space device. The edge contour is the outer boundary of the space device in the image, and the installation direction is the orientation of the space device relative to a fixed wall, fixed column, or spatial reference coordinate. The server performs device appearance matching with the appearance and contour of the model in the digital twin model to obtain the visual matching position corresponding to the visual positioning result. It then compares the visual matching position with the corresponding model position of the space device in the digital twin model to generate visual position differences.

[0033] The server extracts structural features from the laser scan results, including the 3D contour, surface boundary, installation height, and the position of the fixed equipment base. The 3D contour is the 3D boundary of the spatial equipment's external structure in the point cloud data; the surface boundary is the edge range of the point cloud on the spatial equipment's surface; the installation height is the height of the spatial equipment relative to the ground or the fixed equipment base; and the fixed equipment base position is the position of the spatial equipment's installation support structure in spatial reference coordinates. The server performs structural contour matching with the model contour and equipment installation area in the digital twin model to obtain the structural matching position corresponding to the laser scan results. This structural matching position is then compared with the corresponding model position of the spatial equipment in the digital twin model to generate structural position differences.

[0034] The server extracts motion features from the inertial positioning results, including movement path, attitude changes, turning changes, and velocity changes. The movement path is the path traversed by the acquisition device within a continuous time window; attitude changes are the pitch, roll, and yaw changes of the acquisition device; turning changes are the change in the direction of movement of the acquisition device; and velocity changes are the changes in the speed of the acquisition device within adjacent time windows. The server performs trajectory continuity matching with historical positioning trajectories, determining whether the position changes corresponding to the visual positioning results and laser scan results within the current time window conform to the continuous movement patterns in the historical positioning trajectories. If the visual positioning results or laser scan results show a significant position jump within adjacent time windows, and neither the inertial positioning results nor the historical positioning trajectories support this jump, a motion position difference is generated.

[0035] The server extracts distance relationships, signal strength relationships, time-of-arrival relationships, and the wireless positioning area based on the wireless positioning results to form distance features. The distance relationship refers to the ranging relationship between the space device or acquisition device and the wireless base station; the signal strength relationship refers to the relative strength of signals received by the space device or acquisition device from different wireless base stations; the time-of-arrival relationship refers to the time it takes for the wireless signal to travel from the wireless base station to the space device or acquisition device; and the wireless positioning area is a possible location range defined by the distance relationship, signal strength relationship, or time-of-arrival relationship. The server performs spatial location matching between the distance features and the wireless base station locations and device installation areas in the spatial reference coordinates to determine whether the wireless positioning area covers the model location or device installation area in the digital twin model, and generates wireless location differences.

[0036] The server generates a position difference sequence by arranging visual position differences, structural position differences, motion position differences, and wireless position differences in chronological order of acquisition. This position difference sequence refers to the set of position differences generated by different positioning results for the same spatial device within a continuous time window. It records not only the deviation of each positioning result within a single time window but also the direction, magnitude, and stability of this deviation over time. When generating the position difference sequence, the server uses the device's operating status as a constraint. If the spatial device is fixed, locked, or shut down, even small changes in position difference may be marked as abnormal. If the spatial device is in a moving, maintenance, or abnormal state, it is necessary to combine historical positioning trajectories to determine whether the position difference changes fall within the permissible range. The position difference sequence can be represented as:

[0037] in, The sequence of positional differences corresponding to space devices consists of visual positional differences, structural positional differences, motion positional differences, and wireless positional differences within a continuous time window. Indicates the first Each time window is divided according to the time alignment rules of the timestamps of the location results. This indicates the number of time windows participating in the current analysis, which is determined by the analysis cycle and data collection frequency set by the system. Indicates the first Visual positional differences within a time window; Indicates the first Differences in structural position within a time window; Indicates the first Differences in movement position within a time window; Indicates the first Wireless location differences within a time window.

[0038] The server generates the positional deviation relationship for each positioning result based on the direction, magnitude, and stability of positional changes within a continuous time window. The direction of positional change indicates the offset direction of the positional difference in the spatial reference coordinates; the magnitude of positional change indicates the magnitude of the positional difference; and the stability of positional change indicates whether the positional difference continuously changes in the same direction or remains stable within a continuous time window. The server compares the relationships between visual positional differences, structural positional differences, motion positional differences, and wireless positional differences to determine whether there is unidirectional offset, reverse cancellation, delayed following, or local stability among different positioning results. The magnitude of positional change can be determined by the following formula:

[0039] in, Indicates the first Within the first time window The magnitude of positional change in the class positioning result is determined by the first... The length of the location difference vector of the class localization result is calculated. Indicates the type of location result, and its possible values ​​include: , , and These correspond to visual positioning results, laser scanning results, inertial positioning results, and wireless positioning results, respectively. Indicates the first Within the first time window The location difference of the positioning results is obtained by matching the corresponding positioning results with the model location, historical positioning trajectory, or wireless positioning area; This indicates the calculation of vector length, used to convert positional differences in spatial directions into comparable deviation magnitudes.

[0040] The direction of positional change can be determined by the change in positional differences between adjacent time windows, and its expression is:

[0041] in, Indicates the first Within the first time window The direction of positional change in the class localization result is obtained by normalizing the positional difference change vector between adjacent time windows; Indicates the first Within the first time window The positional differences in the class localization results; Indicates the first Within the first time window The positional differences in the class localization results are obtained from the matching results of the previous time window; This indicates the magnitude of the positional difference between adjacent time windows.

[0042] The stability of positional changes can be determined by the degree of fluctuation in the amplitude of positional changes within a continuous time window, and its expression is:

[0043] in, Indicates the first The stability of the location change of the positioning result is indicated by the value of the smaller value, which means that the position change of the positioning result is more stable, and the larger value means that the position change of the positioning result fluctuates more significantly. This indicates the number of time windows participating in the current analysis, which is determined by the analysis cycle and data collection frequency set by the system. Indicates the first Within the first time window The magnitude of positional change in the class localization result; Indicates the first The average positional change of the class localization results within a continuous time window is composed of all [variables / items] within the continuous time window. The average is obtained.

[0044] The server integrates the direction, magnitude, and stability of positional changes to generate a positional deviation relationship. This relationship describes the degree, direction, duration, and correlation of deviations between visual positioning results, laser scanning results, inertial positioning results, and wireless positioning results. For example, if visual positional differences and structural positional differences increase in the same direction within a continuous time window, while wireless positional differences remain stable, the positional deviation relationship indicates that visual positioning results and laser scanning results may be affected by the same occlusion or spatial structural changes. If visual positional differences appear stable, but motion positional differences continue to increase, the positional deviation relationship indicates that visual positioning results may be incorrectly stabilized on historical appearance features. If multiple positioning results maintain low fluctuations but have directional cancellation relationships, the positional deviation relationship can serve as a basis for subsequent identification of false stable states.

[0045] S130. Identify false stable states based on the position deviation changes between each positioning result. When a false stable state is identified, re-verify each positioning result using a fixed wall, fixed column, fixed equipment base, and preset positioning point to generate position offset data corresponding to each positioning result.

[0046] Specifically, based on the positional deviation changes corresponding to each positioning result, the server reads the direction, magnitude, and duration of changes in visual positional differences, structural positional differences, motion positional differences, and wireless positional differences within a continuous time window. Visual positional differences are the spatial deviations of the visual positioning result relative to the model position in the digital twin model; structural positional differences are the spatial deviations of the laser scan result relative to the model position in the digital twin model; motion positional differences are the continuous deviations of the inertial positioning result relative to the historical positioning trajectory; and wireless positional differences are the range deviations of the wireless positioning result relative to the device installation area or model position. The server compares these four types of positional differences with the device installation area, device operating status, historical positioning trajectory, and model position, respectively. The device installation area is used to determine whether the positional difference exceeds the permissible installation range of the spatial device; the device operating status is used to determine whether the positional difference conforms to the current permissible motion state of the spatial device; the historical positioning trajectory is used to determine whether the positional difference disrupts the continuous motion pattern; and the model position is used to determine whether the positional difference has deviated from the device reference position recorded in the digital twin model. The magnitude of the positional difference change can be determined using the following expression:

[0047] in, Indicates the first Within the first time window The magnitude of the change in the positional difference corresponding to the class localization result is determined by the first... The length of the location difference vector corresponding to the class localization result is calculated. Indicates the type of location result, and its possible values ​​include: , , and These correspond to visual positioning results, laser scanning results, inertial positioning results, and wireless positioning results, respectively. Indicates the first Within the first time window The positional differences corresponding to the class positioning results are read from the positional deviation change relationship generated in the previous stage; Indicates the first A time window is determined by aligning the visual positioning results, laser scanning results, inertial positioning results, and wireless positioning results in time. This indicates calculating the length of the position difference vector.

[0048] The server further determines the direction of change of each location difference within a continuous time window. The direction of change refers to the offset trend of the location difference corresponding to a certain positioning result relative to the previous time window. It is used to determine whether visual location differences, structural location differences, motion location differences, and wireless location differences change in the same direction or in opposite directions, thus canceling each other out in the fusion result. The server determines the direction of change based on the changes in location differences between adjacent time windows, and its expression is:

[0049] in, Indicates the first Within the first time window The direction of change of the positional difference corresponding to the class localization result is obtained by normalizing the positional difference change vector of adjacent time windows; Indicates the first Within the first time window The location differences corresponding to the class localization results; Indicates the first Within the first time window The location difference corresponding to the class positioning result is read from the location deviation change relationship of the previous time window; This indicates the prevention of extremely small positive values ​​where the denominator is zero, and can be preset by the server; Indicates the type of location result.

[0050] The server identifies spurious stable states based on the directional and amplitude relationships between at least two location differences. Similar offset directions refer to two location differences changing in close directions within a continuous time window, indicating that the two localization results may be affected by the same spatial structure change, occlusion, or sensor drift. Mutually canceling offset trends refer to two location differences changing in opposite directions, but after fusion, the device's visible position remains stable, causing the digital twin model to mistakenly believe the device's position is reliable. The server can determine whether two location differences exhibit similar offset directions using directional similarity, expressed as:

[0051] in, Indicates the first Within the first time window Class location results and the first The directional similarity between class localization results is calculated by the dot product of two changing direction vectors; Indicates the first The direction of change of the positional differences corresponding to the class localization results; Indicates the first The direction of change of the positional differences corresponding to the class localization results; and This indicates different localization result types, and the two are not the same.

[0052] The server identifies spurious stable states among the positioning results when at least two location differences exhibit similar offset directions or mutually cancel each other out, and the visible device position in the digital twin model remains stable within a continuous time window. The visible device position is the spatial location of the device displayed in the digital twin model, which may be obtained by fusing multiple positioning results. A spurious stable state refers to a situation where each positioning result itself has undergone implicit offset, but the fused visible device position still appears continuous, stable, and reliable. The server can determine whether the visible device position remains stable based on the magnitude of its changes, expressed as:

[0053] in, Indicates the first The change in the visible position of a device within a time window relative to the previous time window is obtained by subtracting the visible positions of the devices in adjacent time windows and then calculating the length. Indicates the first The visible location of the device in the digital twin model within a time window is read by the digital twin model; Indicates the first The visible location of a device in a digital twin model within a time window is read from the digital twin model of the previous time window.

[0054] Upon detecting a false stable state, the server pauses the writing of the current device's visual positioning results into the digital twin model and uses pre-registered fixed walls, fixed columns, fixed equipment bases, and preset positioning points within the target space as re-verification objects. The re-verification objects are spatial reference objects in the target space that have long-term stable positions and do not move with changes in the operating status of the spatial equipment; fixed walls are wall planes in the target space that have already been calibrated; fixed columns are load-bearing columns or structural columns in the target space that have already been calibrated; fixed equipment bases are base structures used to fix and install spatial equipment; and preset positioning points are stable reference points calibrated manually or by the system. The server pauses the writing of data into the digital twin model to prevent potentially hidden offsets in the current device's visual positioning results from contaminating the digital twin model and to ensure that subsequent positioning corrections can be re-evaluated based on stable spatial reference objects.

[0055] The server uses a fixed wall to re-verify the appearance area and edge contours in the visual positioning results. Specifically, the server reads the appearance area and edge contours of the spatial device from the visual positioning results and identifies the relative positional relationship of the appearance area and edge contours relative to the fixed wall. Simultaneously, the server reads the model-relative positional relationship between the spatial device and the fixed wall from the digital twin model. If the relative positional relationship of the image is inconsistent with the relative positional relationship of the model, it indicates that the visual positioning results may be affected by occlusion, reflection, the appearance of similar devices, or changes in viewing angle. The server generates positional offset data corresponding to the visual positioning results based on the direction and degree of inconsistency between the two. The positional offset data corresponding to the visual positioning results can be determined using the following expression:

[0056] in, Indicates the first The position offset data corresponding to the visual positioning results within a time window is obtained by subtracting the relative position vector of the device relative to the fixed wall in the visual positioning results from the relative position vector of the device relative to the fixed wall in the digital twin model. This represents the relative position vector of the spatial device with respect to the fixed wall in the visual positioning result. It is obtained by transforming the appearance area, edge contour, and the position of the fixed wall in the image through spatial reference coordinates. This represents the relative position vector of a spatial device in a digital twin model with respect to a fixed wall surface. It is calculated from the model's position and the calibrated position of the fixed wall surface; subscript... Indicates the visual localization result, subscript Indicates a fixed wall surface.

[0057] The server uses a fixed column and a fixed equipment base to re-verify the 3D contour, surface boundaries, and spatial occupancy range in the laser scan results. The 3D contour is the 3D shape boundary of the spatial device in the point cloud data; the surface boundary is the boundary line or boundary surface of the point cloud on the surface of the spatial device; and the spatial occupancy range is the actual area occupied by the spatial device in the target space. The server extracts the relative positional relationship of the spatial device with respect to the fixed column and the fixed equipment base from the laser scan results and reads the corresponding model relative positional relationship from the digital twin model. If the relative positional relationship of the point cloud is inconsistent with the relative positional relationship of the model, it indicates that the laser scan results may be affected by missing point clouds, metal reflection, temporary obstacle occlusion, or structural mismatch. The server generates positional offset data corresponding to the laser scan results based on the direction and degree of inconsistency. The positional offset data corresponding to the laser scan results can be determined using the following expression:

[0058] in, Indicates the first The positional offset data corresponding to the laser scanning results within a time window is obtained by weighting the positional offset of the space device relative to the fixed column and the positional offset relative to the base of the fixed device. This represents the relative position vector of the space device with respect to the fixed column in the laser scanning results. It is calculated from the three-dimensional contour, surface boundary, and point cloud position of the fixed column. This represents the relative position vector of the spatial device in the digital twin model with respect to the fixed column, which is calculated from the model position and the calibration position of the fixed column; This represents the relative position vector of the space device with respect to the fixed device base in the laser scanning results. It is calculated from the three-dimensional contour, the space occupancy range, and the point cloud position of the fixed device base. This represents the relative position vector of the spatial device in the digital twin model with respect to the fixed device base, which is calculated from the model position and the calibration position of the fixed device base; This represents the reference weight of the fixed column, and its value range is... to It can be determined based on the integrity of the point cloud of the fixed column, the distance between the fixed column and the spatial equipment, and the stability of the point cloud matching.

[0059] The server re-verifies the movement path, attitude changes, turning changes, and velocity changes in the inertial positioning results using preset positioning points. The movement path is the path formed by the continuous movement of the acquisition device within the target space; attitude changes are the pitch, roll, and yaw changes generated by the acquisition device during movement; turning changes are the change in the direction of movement of the acquisition device; and velocity changes are the changes in the movement speed of the acquisition device within a continuous time window. The server determines whether the inertial positioning results before and after the acquisition device passes the preset positioning point are consistent with the calibration position of the preset positioning point. If there is a continuous deviation between the path position displayed in the inertial positioning results and the calibration position of the preset positioning point, it indicates that the inertial positioning results may have accumulated drift. The position offset data corresponding to the inertial positioning results can be determined using the following expression:

[0060] in, Indicates the first The position offset data corresponding to the inertial positioning results within a time window is obtained by subtracting the preset positioning point calibration position from the position calculated from the inertial positioning results. This indicates the position of the data acquisition device calculated from the inertial positioning results, which is recursively derived from the movement path, attitude changes, turning changes, and velocity changes. This indicates the preset location point corresponding to the current time window, which is read from the preset location point database pre-registered in the target space; subscript This indicates the result of inertial positioning.

[0061] The server re-verifies the wireless positioning area in the wireless positioning results using preset positioning points, fixed walls, and fixed pillars. The wireless positioning area is a spatial range determined based on distance, signal strength, or time of arrival relationships in the wireless positioning results. The wireless positioning area is typically a candidate region rather than a single precise point. The server compares the wireless positioning area with the stable spatial range defined by the preset positioning points, fixed walls, and fixed pillars to determine if the wireless positioning area continuously deviates from the stable spatial range. If the center position or boundary range of the wireless positioning area is consistently deviated in a certain direction, it indicates that the wireless positioning results may be affected by signal obstruction, multipath propagation, or abnormal wireless base station operation. The position offset data corresponding to the wireless positioning results can be determined using the following expression:

[0062] in, Indicates the first The location offset data corresponding to the wireless positioning results within a time window is obtained by subtracting the reference position of the stable spatial range from the center position of the wireless positioning area. It indicates the center location of the wireless positioning area, which is determined by the geometric center of the wireless positioning area, the distance relationship solution center, or the signal strength weighting center; Indicates the reference position of a stable spatial range, which is jointly determined by the positions of the preset positioning point, the fixed wall surface, and the fixed column under the spatial reference coordinates; subscript This indicates the wireless positioning result.

[0063] After generating position offset data corresponding to visual positioning results, laser scanning results, inertial positioning results, and wireless positioning results, the server unifies all position offset data under a spatial reference coordinate system and stores them in association according to device number, positioning result type, time window, offset direction, offset magnitude, and duration. Position offset data is not a single positioning coordinate, but rather represents the deviation of a positioning result relative to a stable spatial reference. The offset direction indicates the direction of the deviation from the stable spatial reference, the offset magnitude indicates the magnitude of the deviation, and the duration indicates the duration of the offset within a continuous time window. The server continues to associate the position offset data with the device installation area, device operating status, historical positioning trajectory, and digital twin model, enabling subsequent determination of reference positioning results, abnormal positioning results, and associated abnormal positioning results based on the position offset data, and further performing hierarchical positioning correction.

[0064] S140. Determine the baseline positioning result, abnormal positioning result, and associated abnormal positioning result based on the position offset data, and perform hierarchical positioning correction based on the relationship between the baseline positioning result, abnormal positioning result, and associated abnormal positioning result to generate the corrected device visual positioning result.

[0065] Specifically, based on the position offset data corresponding to the visual positioning results, laser scanning results, inertial positioning results, and wireless positioning results, the server reads the offset direction, offset amplitude, offset duration, and offset change stability of each position offset data within a continuous time window. The offset direction indicates the direction in which the positioning result deviates from the stable spatial reference; the offset amplitude indicates the magnitude of the deviation; the offset duration indicates the length of time the offset direction and amplitude persist within the continuous time window; and the offset change stability indicates whether the offset amplitude remains stable within the continuous time window. The server compares these parameters with the device installation area, historical positioning trajectory, and model position in the digital twin model, and performs positioning reliability analysis on the visual positioning results, laser scanning results, inertial positioning results, and wireless positioning results respectively. If the position offset data corresponding to a certain positioning result maintains small fluctuations within the continuous time window, and the corresponding positioning result does not exceed the device installation area, does not disrupt the continuous change pattern of the historical positioning trajectory, and remains consistent with the model position in the digital twin model, then this positioning result is determined as the baseline positioning result. The baseline positioning result refers to the positioning result that can be used as the main positioning basis within the current time window, and it is used as the main positioning reference in subsequent hierarchical positioning correction.

[0066] The expression for calculating the offset magnitude is:

[0067] in, Indicates the first Within the first time window The offset magnitude of the location offset data corresponding to the class positioning result is determined by the first... The vector length of the position offset data corresponding to the class localization result is calculated. Indicates the type of location result, and its possible values ​​include: , , and These correspond to visual positioning results, laser scanning results, inertial positioning results, and wireless positioning results, respectively. Indicates the first Within the first time window The position offset data corresponding to the positioning result is obtained by re-verifying the fixed wall, fixed column, fixed equipment base or preset positioning point; Indicates the first A time window is determined by aligning the visual positioning results, laser scanning results, inertial positioning results, and wireless positioning results in time. This indicates the calculation of vector length.

[0068] The expression for calculating the stability of offset changes is:

[0069] in, Indicates the first The stability of the offset change of the location offset data corresponding to the positioning result. The smaller the value, the more stable the offset of the positioning result. The larger the value, the more obvious the fluctuation of the offset of the positioning result. This indicates the number of time windows participating in the current location reliability analysis, which is determined based on the analysis cycle set by the server and the frequency of location result collection. Indicates the first Within the first time window The offset magnitude of the location offset data corresponding to the class positioning result; Indicates the first The average offset of the class localization results within a continuous time window is determined by analyzing all data within that continuous time window. The average is obtained.

[0070] The server identifies positioning results where the location offset data continuously increases or deviates from the device installation area, historical positioning trajectory, or model position in the digital twin model as abnormal positioning results. Abnormal positioning results refer to those that have been affected by occlusion, missing point clouds, cumulative inertial errors, wireless signal interference, or changes in spatial structure within the current time window, and cannot be used as the primary basis for the final spatial location. Specifically, if the location offset data of the visual positioning result continuously increases, it indicates that the visual positioning result may be affected by occlusions, reflected light, or similarly appearing devices; if the location offset data of the laser scanning result continuously increases, it indicates that the laser scanning result may be affected by missing point clouds, metal reflections, or temporary obstacles; if the location offset data of the inertial positioning result continuously increases, it indicates that the inertial positioning result may have cumulative drift; if the location offset data of the wireless positioning result continuously increases, it indicates that the wireless positioning result may be affected by multipath propagation, signal obstruction, or abnormal wireless base station. The increasing trend of offset can be determined by the difference in offset amplitude between adjacent time windows, expressed as:

[0071] in, Indicates the first Within the first time window The offset increment of the location offset data corresponding to the class positioning result is obtained by subtracting the offset magnitude of the previous time window from the offset magnitude of the current time window. Indicates the number of times within the current time window The offset magnitude of the location offset data corresponding to the class positioning result; Indicates the number of times within the previous time window The offset magnitude of the location offset data corresponding to the class positioning result is calculated from the location offset data of the previous time window; Indicates the type of location result.

[0072] The server compares the offset correlations between the location offset data corresponding to different positioning results and identifies positioning results whose offset direction is consistent with the location offset direction corresponding to abnormal positioning results and whose offset change trends show a synchronous relationship as associated abnormal positioning results. Offset correlation refers to the degree of correlation between the location offset data of different positioning results in terms of offset direction, offset amplitude changes, and offset duration. Associated abnormal positioning results refer to positioning results whose own offset amplitude does not meet the judgment criteria for abnormal positioning results, but whose offset direction and offset change trends have been affected by abnormal positioning results. For example, when a laser scan result undergoes structural offset due to a temporary obstacle, and a visual positioning result undergoes offset in the same direction due to occlusion by the same obstacle, if the laser scan result is identified as an abnormal positioning result, the visual positioning result can be identified as an associated abnormal positioning result. The degree of consistency in offset direction can be determined by direction similarity, the expression of which is:

[0073] in, Indicates the first Within the first time window The degree of consistency between the offset directions of the class localization results and the anomaly localization results is calculated by the dot product of the two offset direction vectors; Indicates the first The offset direction of the position offset data corresponding to the class positioning result is determined by the first The location offset data corresponding to the class positioning result is obtained by normalization; This indicates the offset direction of the location offset data corresponding to the abnormal location result, which is obtained by normalizing the location offset data corresponding to the abnormal location result. This indicates the type of location result that has been identified as an abnormal location result.

[0074] The degree of synchronization in the offset change trend can be determined by the consistency of changes between the offset increment sequences, and its expression is:

[0075] in, Indicates the first The degree of synchronization between the offset change trends of the class localization results and the anomaly localization results is calculated by the similarity of their offset increment sequences within a continuous time window; Indicates the first Within the first time window The offset increment of the location offset data corresponding to the class positioning result; Indicates the first The offset increment of the location offset data corresponding to the abnormal location results within a time window; Indicates the number of time windows involved in the analysis; This indicates the prevention of extremely small positive values ​​where the denominator is zero, and can be preset by the server.

[0076] The server performs hierarchical positioning correction based on the relationships between baseline positioning results, abnormal positioning results, and associated abnormal positioning results. It retains the location coordinates, spatial direction, and spatial adjacency relationships corresponding to the baseline positioning results as the primary positioning reference, while restricting the participation of abnormal and associated abnormal positioning results in the final spatial location calculation. Location coordinates are the coordinate values ​​of the positioning result under the spatial reference coordinates; spatial direction is the orientation of the spatial device under the spatial reference coordinates; and spatial adjacency relationships are the spatial relationships between the spatial device and adjacent spatial devices, fixed walls, fixed columns, pipelines, cables, control cabinets, or communication nodes. Hierarchical positioning correction means that different types of positioning results play different roles in the positioning correction process. The baseline positioning result is used to determine the corrected spatial location; abnormal positioning results are only used to determine the offset range that needs to be avoided; and associated abnormal positioning results are only used to determine whether the offset has a propagation trend, and do not participate in the final spatial location calculation on an equal footing with the baseline positioning result.

[0077] The server uses the location coordinates corresponding to the baseline positioning results to recalibrate the spatial positions of visual positioning, laser scanning, inertial positioning, and wireless positioning results under the spatial baseline coordinates. It also limits the spatial position correction boundary based on the position offset range corresponding to abnormal positioning results, and performs smooth spatial position correction based on the offset propagation trend of associated abnormal positioning results. The spatial position correction boundary refers to the range that the corrected spatial position must not exceed; it can be jointly defined by the equipment installation area, the range of the fixed equipment base, the area occupied by adjacent spatial equipment, and the offset range of abnormal positioning results. The offset propagation trend refers to the trend of associated abnormal positioning results changing synchronously with the abnormal positioning results; it is used to determine whether the corrected spatial position needs smooth adjustment within a continuous time window. Spatial position correction can be expressed as follows:

[0078] in, Indicates the first The corrected spatial position within a time window is determined by the position coordinates corresponding to the baseline positioning result, the position offset data corresponding to the abnormal positioning result, and the position offset data corresponding to the associated abnormal positioning result. It represents the position coordinates corresponding to the reference positioning result, which are obtained from the visual positioning result, laser scanning result, inertial positioning result, or wireless positioning result that is determined as the reference positioning result; This represents the location offset data corresponding to the abnormal location result, which is generated by the aforementioned re-verification step. This represents the location offset data corresponding to the associated anomaly location result, which is obtained from the location result that was determined to be an associated anomaly location result; The correction suppression coefficient represents the anomaly localization result, and its value range is: to The offset can be determined based on the offset magnitude, offset duration, and offset change stability of the abnormal location results. The larger the offset magnitude and the longer the duration, the better. The larger; This represents the propagation correction coefficient for the correlation anomaly localization results, and its value range is... to The correlation can be determined based on the degree of consistency in the offset direction and the degree of synchronization in the offset change trend between the associated anomaly location results and the anomaly location results. The higher the degree of consistency and synchronization, the better. The larger; The spatial location correction boundary is determined by the equipment installation area, the range of the fixed equipment base, the area occupied by adjacent spatial equipment, and the equipment connection relationship. This indicates that the corrected spatial location is restricted to the boundary limit within the spatial location correction boundary.

[0079] The server generates a revised device visual positioning result based on the revised spatial location, revised spatial orientation, and revised spatial adjacency. The revised spatial orientation can be adjusted by combining the spatial orientation corresponding to the baseline positioning result with the device connection relationship; the revised spatial adjacency relationship can be re-determined by the spatial relationship between the revised spatial location and adjacent spatial devices, pipelines, cables, control cabinets, communication nodes, fixed walls, and fixed columns. If the revised spatial location meets the device installation area constraints, the revised spatial orientation meets the orientation requirements corresponding to the device connection relationship, and the revised spatial adjacency relationship does not disrupt the connection logic between adjacent spatial devices, then the server encapsulates the revised spatial location, revised spatial orientation, and revised spatial adjacency relationship into a revised device visual positioning result. The revised device visual positioning result is used for subsequent consistency checks with device number, device installation area, device connection relationship, and device operating status, and updates the digital twin model when the consistency conditions are met.

[0080] S150. Perform joint verification based on the consistency relationship between the corrected device visual positioning results and the device number, device installation area, device connection relationship and device operating status, and update the digital twin model when the consistency conditions are met.

[0081] Specifically, the server first binds the corrected device visual positioning result to the device number of the corresponding spatial device. The corrected device visual positioning result includes the corrected spatial location, corrected spatial direction, and corrected spatial adjacency; the device number is the unified identification basis for spatial devices in the device ledger, digital twin model, and historical positioning trajectory. The server reads the registration records in the device ledger, the virtual device object in the digital twin model, and the historical records in the historical positioning trajectory based on the device number, and determines whether the three types of records all point to the same spatial device. If the device number registered in the device ledger, the device number associated with the virtual device object, and the device number associated with the historical positioning trajectory are consistent, and the appearance of the spatial device, model outline, or wireless positioning object in the corrected device visual positioning result does not cross-match with other device numbers, then the corrected device visual positioning result is determined to meet the device number consistency requirement. The device number consistency requirement is used to prevent the corrected device visual positioning result from being incorrectly written into the virtual device object of other spatial devices.

[0082] Device serial number consistency can be represented by a consistency judgment value, the expression of which is:

[0083] in, This represents the consistency judgment value for the device number, and its value is... This indicates that the device number consistency requirement is met, and the value is [value]. This indicates that the device number consistency requirement is not met; This function evaluates to a condition when the condition within the parentheses is true. The value is taken as follows when the condition inside the parentheses is not true. ; This indicates the device number associated with the corrected device visual positioning result, which is obtained by binding the corrected device visual positioning result; This indicates the equipment number in the equipment ledger, which is read from the equipment ledger. This indicates the device number associated with the virtual device object in the digital twin model, which is read from the digital twin model; This indicates the device ID associated with the historical location trajectory, which is read from the historical location trajectory. This represents the set of device IDs that cross-match with other spatial devices within the current time window. It is obtained by statistically analyzing the candidate matching relationships of visual positioning results, laser scanning results, and wireless positioning results.

[0084] The server compares the corrected device visual positioning result with the device installation area. The device installation area is the spatial range within which the device is allowed to be installed, remain, or move; it can be defined by a polygonal area, the area of ​​a fixed device base, a server rack area, a device room area, or a passageway boundary. The spatial location is the coordinate position of the corrected device visual positioning result under a spatial reference coordinate system. The server determines whether the spatial location is within the permissible range corresponding to the device installation area, and further determines whether the spatial location enters a wall, a prohibited passageway area, an area occupied by other devices, or an abnormal space outside the device installation area. If the spatial location is within the permissible range corresponding to the device installation area and does not enter a prohibited space, then the corrected device visual positioning result meets the device installation area consistency requirement. The device installation area consistency requirement ensures that the corrected device visual positioning result does not deviate from the actual deployment range of the spatial devices.

[0085] The consistency of equipment installation areas can be represented by an area inclusion judgment value, the judgment expression of which is:

[0086] in, This represents the consistency judgment value for the equipment installation area, and its value is... This indicates that the equipment installation area consistency requirement is met, and the value is [value missing]. This indicates that the equipment installation area consistency requirement is not met; This indicates the spatial position in the corrected visual positioning result of the device, which is obtained after hierarchical positioning correction; This indicates the permissible range corresponding to the equipment installation area, which can be obtained from equipment ledgers, digital twin models, or on-site calibration data; This indicates the area of ​​space that is not allowed to be occupied, including wall areas, passageway restricted areas, areas occupied by other space equipment, and system-preset prohibited areas; This indicates that the spatial location is within the allowable range corresponding to the equipment installation area; This indicates that the spatial location has not entered the area where it is not allowed to be occupied.

[0087] The server reads the spatial adjacency relationships between the corresponding spatial device and adjacent spatial devices, pipelines, cables, control cabinets, and communication nodes based on the device connection relationships. Device connection relationships refer to the electrical, communication, mechanical, or pipeline connections between spatial devices; spatial adjacency relationships are the spatial representation of these connections, including connection distance, connection direction, and connection area. The server compares the corrected spatial position and direction in the device's visual positioning result with the spatial adjacency relationships to determine whether the corrected spatial position causes the spatial device to detach from adjacent spatial devices, pipelines, cables, control cabinets, or communication nodes, or whether the corrected spatial direction conflicts with the connection direction. If neither the corrected spatial position nor the corrected spatial direction disrupts the spatial adjacency relationships, the corrected device visual positioning result is deemed to meet the device connection relationship consistency requirements. These consistency requirements prevent situations where the spatial position falls within the device installation area, but the connection logic no longer conforms to the actual device layout.

[0088] The consistency of device connectivity can be represented by a connectivity deviation judgment value, the expression of which is:

[0089] in, This represents the consistency judgment value for device connection relationships, and its value is... This indicates that the consistency requirements of device connection relationships are met, and the value is [value to be filled in]. This indicates that the device connection consistency requirement is not met; This represents the set of adjacent objects that have a device connection relationship with the space device corresponding to the current device number. It is read from the device connection relationship. Adjacent objects include adjacent space devices, pipelines, cables, control cabinets, and communication nodes. Represents any adjacent object in the set of adjacent objects; This indicates the spatial location in the corrected visual positioning result of the device. Indicates the first The position of each adjacent object in spatial reference coordinates is obtained from the digital twin model or on-site calibration data; Indicates the current space equipment and the first The minimum allowable connection distance between adjacent objects is determined by the device connection relationship or installation specifications. Indicates the current space equipment and the first The maximum allowable connection distance between adjacent objects is determined by the device connection relationship or installation specifications. Indicates the corrected spatial direction and the first The directional deviation between the connection directions of adjacent objects is calculated based on the corrected spatial direction and connection direction. This indicates the maximum permissible directional deviation, which is determined by the equipment connection relationship, installation direction requirements, or system preset rules.

[0090] The server determines whether a change in the location of a corresponding spatial device is permissible within the current time window based on its operational status, and compares the corrected visual positioning result with the operational status. The operational status includes normal operation, shutdown, maintenance, relocation, locking, or abnormality. If the spatial device is in a normal, shutdown, or locked state, the server determines whether the corrected spatial position remains stable relative to the previous trusted position. If a significant positional change occurs, it indicates that the corrected visual positioning result is inconsistent with the operational status. If the spatial device is in a maintenance, relocation, or abnormal state, the server determines whether the corrected spatial position is within the allowed relocation range or maintenance area of ​​the historical positioning trajectory. If the change in the corrected spatial position conforms to the permissible change pattern of the operational status, the corrected visual positioning result is determined to meet the consistency requirement of the operational status. The consistency requirement of the operational status is used to prevent stationary devices from being incorrectly updated to a moved position, or mobile devices from being incorrectly fixed in an unreasonable position.

[0091] The consistency of equipment operating status can be represented by state constraint judgment values, and the judgment expression is as follows:

[0092] in, This represents the consistency judgment value of the equipment's operating status, and its value is... This indicates that the equipment's operating status consistency requirement is met, and the value is [value missing]. This indicates that the equipment's operating status consistency requirements are not met; This indicates the spatial location in the corrected visual positioning result of the device. It indicates the previous trusted location of the current space device, which is read from the digital twin model or the location that most recently passed the consistency check in the historical positioning trajectory; This indicates the allowable position change threshold corresponding to the current device operating status. It is determined based on the device operating status corresponding to the current device number. When the device operating status is normal operation, shutdown, or locked... Take the smaller value when the equipment is under maintenance, being moved, or malfunctioning. Take the larger value based on the historical positioning trajectory's allowable range or the maintenance area range; This indicates the operating status of the device corresponding to the current device number, which is read from the device operating status record.

[0093] The server determines that the corrected device visual location result meets the consistency requirements when it simultaneously satisfies the consistency requirements for device number, device installation area, device connection relationship, and device operating status. The consistency condition is a comprehensive condition used to verify the corrected device visual location result before writing it. It ensures that the corrected device visual location result belongs to the correct device number, is located in the correct device installation area, does not disrupt device connection relationships, and conforms to the device operating status. The comprehensive consistency judgment expression is:

[0094] in, This represents the overall consistency judgment value, which takes the value of... The value indicates that the corrected device visual positioning result meets the consistency condition. This indicates that the corrected device visual positioning result does not meet the consistency condition; This indicates the consistency judgment value for the device serial number; This indicates the consistency judgment value for the equipment installation area; This indicates the consistency judgment value of device connection relationship; This indicates the consistency judgment value of the equipment's operating status.

[0095] When the overall consistency judgment value indicates that the corrected device visual positioning result meets the consistency condition, the server writes the corrected device visual positioning result into the virtual device object with the corresponding device number in the digital twin model. The virtual device object is a virtual object in the digital twin model used to represent a real-world spatial device, containing attributes such as visible location, spatial orientation, spatial adjacency, and positioning status. The server writes the corrected spatial location into the visible location field of the virtual device object, the corrected spatial orientation into the spatial orientation field, and the corrected spatial adjacency into the spatial adjacency field, and updates the positioning status to the verified status. Simultaneously, the server writes the current time window, location offset data, baseline positioning result, abnormal positioning result, and associated abnormal positioning result as update records into the digital twin model to facilitate subsequent tracking of the update source of the digital twin model.

[0096] Virtual device objects in a digital twin model can be updated using the following expression:

[0097] in, This represents the updated virtual device object, which is obtained by writing the corrected device visual positioning result into the update function; This represents the virtual device object before the update, which is read from the digital twin model based on the device number; Indicates the device number of the corresponding space device; Indicates the corrected spatial location; This indicates the corrected spatial orientation, which is obtained from the spatial orientation corrected by hierarchical positioning. It represents the corrected spatial adjacency relationship, which is determined by the corrected spatial location and the spatial relationship between adjacent spatial equipment, pipelines, cables, control cabinets, and communication nodes; This indicates the location status, which is updated to the verified status when the consistency condition is met. Indicates the current time window.

[0098] S160. Based on the updated digital twin model, the visible location, device connection relationship and device operating status of each space device are jointly analyzed to identify the location anomaly risk area, and the inspection path, device retrieval order and remote operation permission are adjusted according to the location anomaly risk area to complete the optimization of space device management based on digital twin visual positioning.

[0099] Specifically, the server reads the visible location, installation area, connection relationships, operating status, historical positioning trajectory, location offset data, and positioning status of each spatial device based on the updated digital twin model. The visible location is the currently displayed location of the spatial device in the digital twin model; the installation area is the spatial range within which the spatial device is allowed to be deployed or moved; the connection relationships are the connections between the spatial device and adjacent spatial devices, pipelines, cables, control cabinets, and communication nodes; the operating status is the current state of the spatial device—whether it is operating normally, shut down, under maintenance, moved, locked, or abnormal; and the positioning status is a marker indicating whether the positioning result of the spatial device has passed consistency verification or is in a pending confirmation state. The server associates the above data according to the device number, enabling joint analysis of the spatial location, connection logic, operating status, and positioning anomaly records of each spatial device under the same data structure.

[0100] Based on the relationship between the visible position of each spatial device and its installation area, the server determines whether any spatial device has deviated from its installation area, entered the area occupied by other spatial devices, or detached from its fixed base. Deviating from the installation area means the visible position is outside the allowable range corresponding to the spatial device; entering the area occupied by other spatial devices means the visible position of the spatial device overlaps with the occupied area of ​​other spatial devices in the digital twin model; detaching from the fixed base means the relative position between the visible position and the fixed base exceeds the allowable deviation. The server identifies spatial areas exhibiting any of these anomalies as candidate anomaly areas. Candidate anomaly areas serve as a preliminary area for locating anomaly risk areas, temporarily storing suspicious spatial areas identified from a single anomaly source. The expression for calculating the visible position anomaly judgment value is:

[0101] in, Indicates the first The device number within each time window is The visual location anomaly judgment value corresponding to the spatial equipment; the larger the value, the more types of visual location anomalies there are. This function evaluates to a condition when the condition within the parentheses is true. The value is taken as follows when the condition inside the parentheses is not true. ; The device number is Space equipment in the The visible location within a time window is read by the updated digital twin model; The device number is The equipment installation area corresponding to the space equipment can be read from the equipment ledger or digital twin model; Indicates that, except for the device number, Other space equipment besides space equipment in the first The set of occupied areas within a time window is determined based on the visible location of other spatial devices and the model outline; The device number is The location of the fixed equipment base corresponding to the space equipment is read from the target space calibration data or digital twin model; The device number is The maximum allowable deviation of the space equipment relative to the fixed equipment base is determined by the installation specifications or system preset rules.

[0102] The server reads the spatial adjacency relationships between adjacent spatial devices, pipelines, cables, control cabinets, and communication nodes based on the device connection relationships of each spatial device, and determines whether the updated visible position violates the spatial adjacency relationships. Spatial adjacency relationships are the geometric representation of device connection relationships in the target space, including connection distance, connection direction, and connection area. An abnormal connection distance means the distance between a spatial device and its adjacent object exceeds the allowable distance range of the device connection relationship; an abnormal connection direction means the spatial direction of the spatial device is inconsistent with the corresponding connection direction of the adjacent object; and an abnormal connection area means the visible position of the spatial device deviates from the allowable connection area of ​​the cable, pipeline, control cabinet, or communication node. When abnormal connection distance, abnormal connection direction, or abnormal connection area exists, the server identifies the corresponding spatial range as a candidate abnormal area. The calculation expression for the device connection relationship abnormality judgment value is:

[0103] in, Indicates the first The device number within each time window is The value for judging abnormal device connection relationships corresponding to the space equipment; the larger the value, the more obvious the abnormality of the device connection relationship. Indicates that the device number is The space equipment has a set of adjacent objects with equipment connection relationships, which are read from the equipment connection relationships. The adjacent objects include adjacent space equipment, pipelines, cables, control cabinets and communication nodes. Represents any adjacent object in the set of adjacent objects; The device number is Space equipment in the The visible location within a time window; Indicates the first The neighboring objects in the first The location within a time window is read from a digital twin model or target space calibration data; The device number is Space equipment and the first The minimum allowable connection distance between adjacent objects is determined by the device connection relationship or installation specifications. The device number is Space equipment and the first The maximum allowable connection distance between adjacent objects is determined by the device connection relationship or installation specifications. The device number is Space equipment and the first The deviation of the connection direction between adjacent objects is calculated from the angle between the spatial direction of the space device and the corresponding connection direction of the adjacent objects. This indicates the maximum permissible deviation in the connection direction, which is determined by the device connection relationship or system preset rules.

[0104] The server determines whether the visible position of each spatial device conforms to the spatial change pattern corresponding to its operating status, based on the device's operational status and historical positioning trajectory. The spatial change pattern refers to the permissible positional changes of the spatial device under different operating states. For example, spatial devices in normal operation, shutdown, or locked states should remain near their previous trusted position. Spatial devices in moving or maintenance states can change within the permitted movement range or maintenance area of ​​their historical positioning trajectory. Spatial devices in abnormal states should have their permissible change range limited by anomaly records. If a spatial device in a fixed state exhibits continuous positional drift, or a spatial device in a moving state deviates from its permissible movement range, the server identifies the corresponding spatial area as a candidate abnormal region. The calculation expression for the device operating status anomaly judgment value is:

[0105] in, Indicates the first The device number within each time window is The abnormal judgment value of the equipment operation status corresponding to the space equipment; the larger the value, the less the visible position is consistent with the equipment operation status. The device number is Space equipment in the The visible location within a time window; The device number is The previous trusted location corresponding to the space device is read from a digital twin model or historical positioning trajectory; The device number is The permissible position change threshold for space equipment under the current operating state is determined based on the equipment's operating state, equipment type, and historical positioning trajectory. The device number is The operating status of the space equipment is read by the operation and maintenance management system or digital twin model; The device number is The historical trajectory range or maintenance area that space equipment is allowed to enter under the current equipment operating state is determined based on the historical positioning trajectory, maintenance work order or system preset rules.

[0106] The server merges candidate anomaly regions identified by visible location, device connectivity, and device operating status. Merging involves grouping overlapping, adjacent, or identically numbered candidate anomaly regions into a single candidate anomaly region and counting the number of anomaly sources, the number of device numbers involved, the duration of the anomaly, and the number of recurrences within that region. If at least two types of anomalies exist simultaneously within the same spatial region, or if the same candidate anomaly region repeatedly appears within a consecutive time window, the server identifies the candidate anomaly region as a location anomaly risk region. A location anomaly risk region refers to a spatial region where there may be hidden location errors, device connectivity mismatches, or remote operation risks. The risk trigger judgment expression after merging candidate anomaly regions is:

[0107] in, Indicates the first Candidate anomaly regions within a time window Whether the trigger value for determining the abnormal risk area is triggered; This represents the merged candidate anomaly region, which is obtained by merging candidate anomaly regions that have overlapping spatial ranges, are adjacent, or correspond to the same device number. Indicates candidate anomaly regions In the The number of anomaly sources within each time window is calculated based on the occurrence of anomalies in visible locations, anomalies in device connection relationships, and anomalies in device operating status. Indicates candidate anomaly regions The number of times an event repeats within a continuous time window is obtained by counting the number of times the same candidate anomaly region appears backward from the current time window. This indicates the minimum number of repetitions required to identify the same candidate anomaly region as a location anomaly risk region, which is preset by the system based on the scenario's security level.

[0108] The server determines the risk level of each spatial device within the location anomaly risk area based on its position offset data, positioning status, anomaly types in device connectivity, and anomaly types in device operation. The risk level indicates the impact of the location anomaly risk area on inspection, retrieval, and remote operation, and can be categorized as high-risk, medium-risk, and low-risk areas. Position offset data indicates the deviation of the positioning result from a stable spatial reference point; positioning status indicates whether the spatial device is in a verified or pending-confirmation state; anomaly types in device connectivity include connection distance anomalies, connection direction anomalies, and connection area anomalies; and anomaly types in device operation include fixed-state drift, movement range deviation, and maintenance area deviation. The server calculates a risk score based on these factors and determines the risk level accordingly. The expression for calculating the risk score is:

[0109] in, Indicates the first Locating abnormal risk areas within a time window Corresponding risk score; Indicates the location of abnormal risk areas The average offset of the position offset data of each space device in the area is obtained by reading the position offset data of all space devices in the area and averaging them. Indicates the location of abnormal risk areas The number of space devices in the pending confirmation state is obtained from the positioning status statistics in the digital twin model; Indicates the location of abnormal risk areas The number of abnormal types of internal device connection relationships is obtained by statistically analyzing the occurrence of abnormal connection distance, abnormal connection direction, and abnormal connection area. Indicates the location of abnormal risk areas The number of abnormal operating status types of internal equipment is obtained by statistically analyzing the occurrence of fixed state drift, movement range deviation, and maintenance area deviation. Indicates the location of abnormal risk areas The number of times it repeats within a continuous time window; , , , and The weighting coefficients represent different risk factors. Their values ​​can be set according to the security level of the target space, the importance of the equipment, and the operation and maintenance strategy. Each weighting coefficient can be corrected through historical anomaly handling records.

[0110] The server adjusts inspection paths, device retrieval order, and remote operation permissions based on risk levels. For inspection paths, the server prioritizes high-risk areas and regenerates inspection paths by combining data from the digital twin model, including access boundaries, obstacle locations, occupied areas of spatial devices, and the current location of the inspection terminal. This ensures that the inspection terminal approaches or passes through high-risk areas first, followed by medium-risk and low-risk areas. If a high-risk area presents a passage hazard, a verification path is generated that approaches the high-risk area but does not enter the danger zone. For device retrieval order, the server prioritizes spatial devices located within high-risk areas that are in a pending confirmation state, have abnormal device connection relationships, or exhibit abnormal device operation status. This allows management personnel to prioritize viewing spatial devices that may have location errors or associated control errors. For remote operation permissions, the server restricts automatic control and remote operation of spatial devices in high-risk areas, retaining only status viewing, manual verification requests, and low-risk monitoring permissions. Secondary confirmation conditions are added for spatial devices in medium-risk areas. Regular remote operation permissions are maintained for spatial devices in low-risk areas, and location offset data is continuously recorded within subsequent time windows. The server writes the adjusted inspection path, equipment retrieval order, and remote operation permissions into the digital twin model, and associates and stores them with the corresponding location anomaly risk area, risk level, equipment number, and current time window, so that the space equipment management process can be dynamically optimized according to location risks.

[0111] This application also provides a spatial equipment management optimization device based on digital twin visual positioning, referring to... Figure 2 , Figure 2This application provides a schematic diagram of a spatial device management optimization device based on digital twin visual positioning. The device is a server, comprising an acquisition module 21 and a processing module 22. The acquisition module 21 acquires the device number, installation area, connection relationship, operating status, digital twin model, historical positioning trajectory, and spatial reference coordinates of each spatial device within the target space, and combines this with visual positioning results, laser scanning results, inertial positioning results, and wireless positioning results to form multi-source positioning data. The processing module 22 extracts visual features, structural features, motion features, and distance features from the multi-source positioning data, and performs device appearance matching, structural contour matching, trajectory continuity matching, and spatial position matching respectively to generate position deviation change relationships corresponding to each positioning result. The processing module 22 also identifies false stable states based on the position deviation change relationships between the positioning results, and when a false stable state is identified, it uses fixed walls, fixed columns, and fixed device bases to... The processing module 22 re-verifies each positioning result based on the seat and preset positioning points to generate position offset data corresponding to each positioning result. The processing module 22 is also used to determine the baseline positioning result, abnormal positioning result, and associated abnormal positioning result based on the position offset data, and to perform hierarchical positioning correction based on the relationship between the baseline positioning result, abnormal positioning result, and associated abnormal positioning result to generate corrected equipment visual positioning results. The processing module 22 is also used to perform joint verification based on the consistency relationship between the corrected equipment visual positioning results and the equipment number, equipment installation area, equipment connection relationship, and equipment operating status, and to update the digital twin model when the consistency conditions are met. The processing module 22 is also used to perform joint analysis on the visual position, equipment connection relationship, and equipment operating status of each spatial device based on the updated digital twin model to identify positioning anomaly risk areas, and to adjust the inspection path, equipment retrieval order, and remote operation permissions based on the positioning anomaly risk areas to complete the optimization of spatial device management based on digital twin visual positioning.

[0112] This application also provides an electronic device, with reference to... Figure 3 , Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include: at least one processor 31, at least one network interface 34, a user interface 33, a memory 35, and at least one communication bus 32.

[0113] The communication bus 32 is used to enable communication between these components.

[0114] The user interface 33 may include a display screen and a camera. Optionally, the user interface 33 may also include a standard wired interface and a wireless interface.

[0115] The network interface 34 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0116] The processor 31 may include one or more processing cores. The processor 31 connects to various parts of the server via various interfaces and lines, executing instructions, programs, code sets, or instruction sets stored in the memory 35, and calling data stored in the memory 35 to perform various server functions and process data. Optionally, the processor 31 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 31 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content to be displayed on the screen; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 31 and may be implemented as a separate chip.

[0117] The memory 35 may include random access memory (RAM) or read-only memory. Optionally, the memory 35 may include a non-transitory computer-readable storage medium. The memory 35 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 35 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 35 may also be at least one storage device located remotely from the aforementioned processor 31. Figure 3 As shown, the memory 35, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for space equipment management optimization based on digital twin visual positioning.

[0118] exist Figure 3 In the electronic device shown, the user interface 33 is mainly used to provide an input interface for the user and to obtain the user input data; while the processor 31 can be used to call an application stored in the memory 35 for a spatial device management optimization method based on digital twin visual positioning. When executed by one or more processors, the electronic device executes one or more methods as described in the above embodiments.

[0119] This application also provides a non-transitory computer-readable storage medium storing instructions. When executed by one or more processors, these instructions cause an electronic device to perform one or more of the methods described in the above embodiments.

[0120] The foregoing description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Those skilled in the art will readily conceive of other embodiments of this disclosure upon considering the specification and the disclosure of practical truth. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure. The specification and embodiments are considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A spatial equipment management optimization method based on digital twin visual positioning, characterized in that, The method includes: The system acquires the device number, installation area, connection relationship, operating status, digital twin model, historical positioning trajectory, and spatial reference coordinates of each spatial device within the target space. It then combines these data with visual positioning results, laser scanning results, inertial positioning results, and wireless positioning results to form multi-source positioning data. Based on the multi-source positioning data, visual features, structural features, motion features, and distance features are extracted, and device appearance matching, structural contour matching, trajectory continuity matching, and spatial position matching are performed respectively to generate the position deviation change relationship corresponding to each positioning result. Based on the relationship between the positional deviation changes of each positioning result, false stable states are identified. When a false stable state is identified, each positioning result is re-verified using a fixed wall, a fixed column, a fixed equipment base, and a preset positioning point to generate positional offset data corresponding to each positioning result. Based on the position offset data, the baseline positioning result, abnormal positioning result, and associated abnormal positioning result are determined. Then, based on the relationship between the baseline positioning result, abnormal positioning result, and associated abnormal positioning result, hierarchical positioning correction is performed to generate the corrected device visual positioning result. Perform joint verification based on the consistency relationship between the corrected device visual positioning results and the device number, device installation area, device connection relationship and device operating status, and update the digital twin model when the consistency conditions are met; Based on the updated digital twin model, the visible location, device connection relationship and device operation status of each space device are jointly analyzed to identify the location anomaly risk area, and the inspection path, device retrieval order and remote operation permission are adjusted according to the location anomaly risk area to complete the space device management optimization based on digital twin visual positioning. The step of identifying false stable states based on the relationship between positional deviation changes among the positioning results specifically includes: Based on the position deviation change relationship corresponding to each positioning result, analyze the direction, magnitude and duration of change of visual position difference, structural position difference, motion position difference and wireless position difference within a continuous time window, and compare them with the equipment installation area, equipment operating status, historical positioning trajectory and model position in digital twin model. A false stable state is identified when at least two positional differences show a tendency to shift in the same direction or cancel each other out, and the visible position of the device remains stable.

2. The spatial equipment management optimization method based on digital twin visual positioning according to claim 1, characterized in that, The process involves acquiring the device number, installation area, connection relationship, operating status, digital twin model, historical positioning trajectory, and spatial reference coordinates of each spatial device within the target space. This data is then combined with visual positioning results, laser scanning results, inertial positioning results, and wireless positioning results to form multi-source positioning data. Specifically, this includes: Obtain the device number, installation area, connection relationship and operating status of each spatial device in the target space, and call the model position, model attitude, model outline and historical positioning trajectory in the digital twin model according to the device number; Establish spatial reference coordinates based on spatial reference points, coordinate axis directions, and area boundaries, and unify the equipment model, historical positioning trajectory, and equipment installation area under the aforementioned spatial reference coordinates; Visual positioning results, laser scanning results, inertial positioning results, and wireless positioning results are collected by visual positioning equipment, laser scanning equipment, inertial positioning equipment, and wireless positioning equipment, respectively. The position jumps of visual positioning results and laser scanning results are constrained by the movement path, attitude change, and velocity change in the inertial positioning results. The positioning results are aligned in time and processed in a unified spatial manner, and then associated with the device number, device installation area, device connection relationship, device operating status, digital twin model, historical positioning trajectory and spatial reference coordinates to form multi-source positioning data.

3. The spatial equipment management optimization method based on digital twin visual positioning according to claim 1, characterized in that, The step involves extracting visual features, structural features, motion features, and distance features based on the multi-source positioning data, and performing device appearance matching, structural contour matching, trajectory continuity matching, and spatial position matching respectively to generate the position deviation change relationship corresponding to each positioning result. Specifically, this includes: Read the visual positioning results, laser scanning results, inertial positioning results and wireless positioning results of the spatial devices within the same time window, and unify them under the spatial reference coordinates; Based on the visual positioning results, extract appearance features and match them with the appearance of the execution device using the digital twin model to generate visual position differences; Structural features are extracted based on laser scanning results and matched with the model outline and equipment installation area to generate structural position differences. Motion features are extracted from the inertial positioning results and matched with historical positioning trajectories to generate motion position differences; Distance features are extracted from wireless positioning results and spatially matched with the location of wireless base stations and the equipment installation area to generate wireless location differences. Based on the temporal direction, magnitude, and stability of the location differences, a relationship between the location deviation changes corresponding to the positioning results is formed.

4. The spatial equipment management optimization method based on digital twin visual positioning according to claim 1, characterized in that, The process of re-verifying each positioning result using fixed walls, fixed columns, fixed equipment bases, and preset positioning points to generate position offset data corresponding to each positioning result specifically includes: Use fixed walls, fixed columns, fixed equipment bases, and preset positioning points as verification benchmarks, and pause updating the digital twin model; Based on each verification benchmark, the visual positioning results, laser scanning results, inertial positioning results, and wireless positioning results are re-verified to generate corresponding position offset data.

5. The spatial equipment management optimization method based on digital twin visual positioning according to claim 1, characterized in that, The process of determining the baseline positioning result, abnormal positioning result, and associated abnormal positioning result based on the position offset data, and performing hierarchical positioning correction based on the relationship between the baseline positioning result, abnormal positioning result, and associated abnormal positioning result to generate a corrected device visual positioning result, specifically includes: Based on the offset direction, offset amplitude, duration and stability of each offset data, a reliability analysis is performed on the visual positioning results, laser scanning results, inertial positioning results and wireless positioning results to determine the baseline positioning results, abnormal positioning results and associated abnormal positioning results. Hierarchical positioning correction is performed based on the correlation between the baseline positioning results, abnormal positioning results, and related abnormal positioning results. The position coordinates, spatial orientation, and spatial adjacency of the baseline positioning results are preserved, and the influence range of the abnormal positioning results is limited. Based on the offset range and propagation trend, spatial position correction and smoothing are performed on each positioning result to generate a corrected visual positioning result for the device.

6. The spatial equipment management optimization method based on digital twin visual positioning according to claim 1, characterized in that, The step of performing joint verification based on the consistency relationship between the corrected device visual positioning results and the device number, device installation area, device connection relationship, and device operating status, and updating the digital twin model when the consistency condition is met, specifically includes: The corrected visual positioning results of the equipment are verified to be consistent with the equipment number, equipment installation area, equipment connection relationship and equipment operating status. Based on the equipment number, determine the equipment identity matching relationship; based on the equipment installation area, determine whether the spatial location is within the allowable range; based on the equipment connection relationship, determine whether the spatial location and direction conform to the adjacency relationship; based on the equipment operating status, determine whether the location change conforms to the operating pattern. When all consistency conditions are met, the corrected device visual positioning results are written into the digital twin model, updating the visual position, spatial orientation, spatial adjacency relationship, and positioning status of the virtual device object.

7. The spatial equipment management optimization method based on digital twin visual positioning according to claim 1, characterized in that, The updated digital twin model is used to jointly analyze the visible location, device connection relationships, and device operating status of each space device to identify areas of location anomaly risk. Based on these risk areas, inspection paths, device retrieval order, and remote operation permissions are adjusted to optimize space device management based on digital twin-based visual positioning. Specifically, this includes: Based on the updated digital twin model, the visible location, installation area, connection relationship, and operating status of each spatial device are analyzed to identify candidate abnormal areas that deviate from the installation area, disrupt spatial adjacency relationships, or do not conform to the operating rules. By merging candidate anomaly regions from different sources, and determining the location of anomaly risk regions based on the recurrence of anomalies; By combining location offset data, positioning status, connection relationship anomaly types, and operational status anomaly types, the risk level is determined, and the inspection path, equipment retrieval order, and remote operation permissions are adjusted according to the risk level to optimize space equipment management.

8. A spatial equipment management optimization device based on digital twin visual positioning, characterized in that, The apparatus is used to execute the space equipment management optimization method based on digital twin visual positioning as described in any one of claims 1 to 7, the apparatus comprising an acquisition module and a processing module, wherein... The acquisition module is used to acquire the device number, device installation area, device connection relationship, device operating status, digital twin model, historical positioning trajectory and spatial reference coordinates of each spatial device in the target space, and combine them with visual positioning results, laser scanning results, inertial positioning results and wireless positioning results to form multi-source positioning data; The processing module is used to extract visual features, structural features, motion features and distance features based on the multi-source positioning data, and perform device appearance matching, structural contour matching, trajectory continuity matching and spatial position matching respectively to generate the position deviation change relationship corresponding to each positioning result; The processing module is also used to identify false stable states based on the position deviation change relationship between each positioning result, and when the false stable state is identified, to re-verify each positioning result using a fixed wall, a fixed column, a fixed equipment base and a preset positioning point, so as to generate position offset data corresponding to each positioning result. The processing module is further configured to determine the baseline positioning result, abnormal positioning result, and associated abnormal positioning result based on the position offset data, and perform hierarchical positioning correction based on the relationship between the baseline positioning result, abnormal positioning result, and associated abnormal positioning result to generate a corrected device visual positioning result. The processing module is also used to perform joint verification based on the consistency relationship between the corrected device visual positioning result and the device number, device installation area, device connection relationship and device operating status, and update the digital twin model when the consistency condition is met. The processing module is also used to jointly analyze the visible location, device connection relationship and device operating status of each space device based on the updated digital twin model, so as to identify the location anomaly risk area, and adjust the inspection path, device retrieval order and remote operation permission according to the location anomaly risk area, so as to complete the space device management optimization based on digital twin visual positioning.

9. An electronic device, characterized in that, The electronic device includes a processor and a memory; the memory stores a computer program, wherein the computer program, when executed by the processor, implements a spatial device management optimization method based on digital twin visual positioning as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium stores instructions that, when executed, perform a spatial equipment management optimization method based on digital twin visual positioning as described in any one of claims 1 to 7.

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