A tool area anomaly detection method, device, equipment and medium are provided

Abstract

The application discloses an operation tool area anomaly detection method, device, equipment and medium. The method comprises the following steps: acquiring spatial scanning data of a relay protection room, a secondary circuit topology model of a protection screen cabinet and a target maintenance task; performing spatial registration on the spatial scanning data and the secondary circuit topology model to generate a three-dimensional virtual scene; determining a safe operation area of the target maintenance object in the three-dimensional virtual scene, and associating operation guide information of the target maintenance object to the safe operation area to generate a mixed training scene; acquiring visual data and inertial data of an operation tool of a user at at least one time, and determining a spatial motion track of the operation tool; and performing working area anomaly detection on the operation tool according to a positional relationship between the spatial motion track and the safe operation area to determine an anomaly detection result of the operation tool. The embodiment of the application can realize anomaly detection on the spatial position of the operation tool in the maintenance training process.

Description

Technical Field

[0001] This invention relates to the field of power operation training technology, and in particular to a method, device, equipment and medium for detecting abnormalities in operating tool areas. Background Technology

[0002] In power systems, 500kV line relay protection devices are crucial equipment for ensuring the safe operation of transmission lines. Regular relay protection maintenance is necessary to ensure the devices and related secondary circuits are in reliable operating condition. Due to the high voltage level and complex structure of 500kV lines, relay protection maintenance involves the testing and operation of numerous terminals, pressure plates, connecting pieces, and secondary circuit nodes, placing high demands on the professional skills and safe operating capabilities of personnel. Therefore, before actual operation, training is typically provided to familiarize personnel with the maintenance process, master equipment operating procedures, and reduce the risk of misoperation during on-site operations.

[0003] Currently, training on routine maintenance of relay protection systems is typically conducted using a physical simulation training platform. This involves configuring models of protection cabinets, terminal blocks, pressure plates, and related secondary circuit equipment based on the actual relay protection room environment, allowing trainees to perform routine maintenance procedures on the simulated equipment. During the training, professionals usually observe the trainees' operational steps on-site according to the pre-set training tasks and evaluate the trainees' performance in accordance with operating procedures to determine whether the trainees have completed the corresponding routine maintenance operations.

[0004] However, in the aforementioned training methods, the physical simulation training environment is usually built based on a fixed structure, which cannot dynamically adjust the training scenario according to the actual electrical conditions corresponding to different scheduled inspection tasks, resulting in a difference between the training environment and the on-site working environment. At the same time, the existing training process mainly relies on manual observation to judge the trainee's operating position and standard of operation, and cannot detect the spatial distance relationship between the operating tools and the live area in real time. When the operating tools approach the danger area or deviate from the target operating area, it is difficult to identify and provide timely and accurate feedback, resulting in insufficient safety risk warning capabilities during the training process. Moreover, the training evaluation results are easily affected by human experience, reducing the accuracy and effectiveness of scheduled inspection training. Summary of the Invention

[0005] This invention provides a method, apparatus, device, and medium for detecting anomalies in the operating tool area. The embodiments of this invention can realize the detection of anomalies in the spatial position of operating tools during scheduled maintenance and training.

[0006] In a first aspect, embodiments of the present invention provide a method for detecting anomalies in an operating tool area, the method comprising:

[0007] Acquire spatial scanning data of the relay protection room, the secondary circuit topology model of the protection cabinet, and the target scheduled maintenance tasks;

[0008] Spatial registration is performed on spatial scan data and secondary loop topology model to generate a three-dimensional virtual scene;

[0009] Based on the target scheduled maintenance task, the safe operation area of ​​the target maintenance object is determined in the three-dimensional virtual scene, and the operation guidance information of the target maintenance object is associated with the safe operation area to generate a hybrid training scenario;

[0010] During the routine inspection training in a hybrid training scenario, visual and inertial data of the user's operating tool at at least one moment are acquired, and the spatial motion trajectory of the operating tool is determined based on the visual and inertial data.

[0011] Based on the positional relationship between the spatial motion trajectory and the safe operating area, the operating tool is subjected to anomaly detection in the working area, and the anomaly detection result of the operating tool is determined.

[0012] Secondly, embodiments of the present invention also provide an anomaly detection device for an operating tool area, the device comprising:

[0013] The data acquisition module is used to acquire spatial scanning data of the relay protection room, the secondary circuit topology model of the protection cabinet, and the target scheduled maintenance tasks;

[0014] The 3D virtual scene generation module is used to spatially register spatial scan data and secondary loop topology model to generate a 3D virtual scene.

[0015] The hybrid training scenario generation module is used to determine the safe operating area of ​​the target maintenance object in a 3D virtual scene according to the target scheduled maintenance task, and associate the operation guidance information of the target maintenance object with the safe operating area to generate a hybrid training scenario.

[0016] The spatial motion trajectory determination module is used to acquire visual and inertial data of the user's operating tool at at least one moment during the periodic inspection training in a mixed training scenario, and determine the spatial motion trajectory of the operating tool based on the visual and inertial data.

[0017] The anomaly detection result determination module is used to perform anomaly detection on the operating tool in the working area based on the positional relationship between the spatial motion trajectory and the safe operating area, and to determine the anomaly detection result of the operating tool.

[0018] Thirdly, embodiments of the present invention also provide an anomaly detection device for the operating tool area, the operating tool area anomaly detection device comprising:

[0019] At least one processor; and

[0020] A memory that is communicatively connected to at least one processor; wherein,

[0021] The memory stores a computer program that can be executed by at least one processor, such that the at least one processor is able to perform the operational tool area anomaly detection method according to any embodiment of the present invention.

[0022] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing computer instructions, which are used to cause a processor to execute the operation tool area anomaly detection method of any embodiment of the present invention.

[0023] Fifthly, embodiments of the present invention also provide a computer program product, which includes a computer program that, when executed by a processor, implements the operation tool area anomaly detection method according to any embodiment of the present invention.

[0024] The technical solution of this invention generates a three-dimensional virtual scene corresponding to the actual working environment by spatially registering the spatial scanning data of the relay protection room with the secondary circuit topology model of the protection cabinet. Combined with the target scheduled maintenance task, it determines the safe operating area of ​​the target maintenance object and the corresponding operation guidance information, enabling the construction of targeted hybrid training scenarios based on specific tasks during training. Furthermore, by acquiring visual and inertial data of the operating tool, the spatial motion trajectory of the operating tool is determined, and anomaly detection of the operating tool is performed based on the positional relationship between the spatial motion trajectory and the safe operating area. This achieves spatial detection of the operating tool's operating range, helping to improve the accuracy and objectivity of operating area judgment during scheduled maintenance training and reducing training risks caused by the operating tool deviating from the safe operating area. It solves the technical problem in the prior art where it is difficult to accurately identify and respond in a timely manner when the operating tool approaches a dangerous area or deviates from the target operating area, resulting in insufficient safety risk warning capabilities during training and training evaluation results being easily influenced by human experience, leading to low accuracy and effectiveness of scheduled maintenance training. Therefore, it can realize the anomaly detection of the spatial position of the operating tool during scheduled maintenance training.

[0025] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 A flowchart of an anomaly detection method for an operating tool area provided in an embodiment of the present invention;

[0028] Figure 2 A flowchart of an anomaly detection method for an operating tool area provided in an embodiment of the present invention;

[0029] Figure 3 This is a schematic diagram of the structure of an anomaly detection device for an operating tool area provided in an embodiment of the present invention;

[0030] Figure 4 This is a schematic diagram of the structure of an anomaly detection device for an operating tool area provided in an embodiment of the present invention. Detailed Implementation

[0031] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0032] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0033] In the technical solutions of this invention, the acquisition, storage, and application of spatial scanning data of relay protection rooms, secondary circuit topology models of protection cabinets, and target scheduled inspection tasks all comply with relevant laws and regulations and do not violate public order and good morals.

[0034] Figure 1 This is a flowchart illustrating a method for detecting anomalies in the working area of ​​an operating tool, as provided in an embodiment of the present invention. This embodiment is applicable to situations requiring anomaly detection in the working area of ​​an operating tool. The method can be executed by an operating tool area anomaly detection device, which can be implemented in hardware and / or software.

[0035] See Figure 1 The method for detecting anomalies in the operating tool area shown includes:

[0036] S101. Obtain spatial scanning data of the relay protection room, the secondary circuit topology model of the protection cabinet, and the target scheduled inspection task.

[0037] Spatial scanning data refers to data obtained by scanning the actual relay protection room environment using spatial acquisition equipment, used to describe the spatial structure and distribution of physical objects within the relay protection room. This spatial scanning data typically includes three-dimensional coordinate information, point cloud information, dimensional information, and spatial positional relationship information for the interior walls, floor, protection cabinets, and other equipment of the relay protection room. The three-dimensional coordinate information represents the position of each physical object in the spatial coordinate system; the point cloud information describes the spatial outline of the physical objects; the dimensional information reflects the geometric size of the objects; and the spatial positional relationship information describes the relative distances and layout relationships between different devices. Spatial scanning data is generated by collecting spatial feature points in the real environment using spatial sensing devices such as laser scanning equipment and depth cameras, and then converting the real environment into digital spatial data.

[0038] The secondary circuit topology model refers to a digital model established based on the actual secondary circuit structure inside the protection cabinet. It describes the connection and electrical transmission relationships between various electrical components within the protection cabinet. By digitally abstracting the electrical structure of the actual protection cabinet, the physical electrical equipment is converted into a topology composed of nodes and connections, thus enabling the simulation of the conduction or disconnection of the secondary circuits under different electrical states. The secondary circuit topology model is used to determine the current electrical state of the protection cabinet in conjunction with the target scheduled inspection task, and to identify the effective energized nodes that maintain connection with the energized potential based on the on / off status of each electrical node.

[0039] Among them, the target scheduled inspection task can refer to the task information corresponding to the periodic testing or maintenance operation of relay protection equipment. The target scheduled inspection task is used to determine the target maintenance object, the safe operating area, and the operation guidance information. For example, the target scheduled inspection task can be "to test the specified terminals in a 500kV line protection cabinet", which includes the terminal number to be tested, the operation sequence, and the corresponding electrical isolation requirements.

[0040] S102. Spatial registration is performed on the spatial scanning data and the secondary loop topology model to generate a three-dimensional virtual scene.

[0041] Spatial registration refers to the process of converting spatial data from different sources to a unified spatial coordinate system, enabling different spatial objects to accurately correspond within the same spatial environment. By obtaining the positional relationship between the two coordinate systems, determining the coordinate transformation parameters, and performing coordinate transformation on the secondary loop topology model, the positions of devices in the model can be matched with their corresponding positions in the real environment. The principle behind spatial registration lies in establishing a mapping relationship between the virtual model space and the real physical space, allowing objects in the digital model to be accurately superimposed onto their corresponding positions in the real environment.

[0042] In this context, a 3D virtual scene refers to a three-dimensional digital scene generated by fusing spatial scanning data and secondary circuit topology models to simulate the actual environment of a relay protection room. This scene, based on a unified spatial coordinate system, integrates real-world environmental information with virtual equipment models, allowing users to observe and operate digital objects corresponding to actual equipment within a virtual environment. As the foundational environment for hybrid training scenarios, the 3D virtual scene carries safe operating areas, operational guidance information, and the movement trajectories of operating tools.

[0043] S103. Based on the target scheduled maintenance task, determine the safe operation area of ​​the target maintenance object in the three-dimensional virtual scene, and associate the operation guidance information of the target maintenance object with the safe operation area to generate a hybrid training scenario.

[0044] In a 3D virtual scene, the safe operating area refers to the spatial region defined around the target maintenance object and surrounding live nodes, used to limit the permissible operating range of the operating tools. The safe operating area serves as the basis for subsequent detection of abnormalities in the working area of ​​the operating tools. By determining whether the movement range of the operating tools is within the safe operating area, the spatial safety of the operation process is detected. For example, when testing terminal 21 in a protective cabinet, based on the spatial distribution of live terminals 11 to 20 around it, an operating area surrounding terminal 21 is generated in an area far from the live terminals; this area is the safe operating area for that terminal.

[0045] Operation guidance information refers to information generated based on the operational requirements of the target scheduled maintenance task and the standard operating procedures corresponding to the target maintenance object, used to guide users in performing scheduled maintenance operations. This operation guidance information is associated with spatial locations within the 3D virtual scene, enabling users to obtain operation prompts matching the current task within the corresponding operation area.

[0046] In this context, a hybrid training scenario refers to an interactive training environment that integrates a 3D virtual scene, a safe operating area, and operational guidance information to conduct relay protection routine maintenance training. The hybrid training scenario provides the execution environment for routine maintenance training, enabling subsequent anomaly detection in the work area based on the movement status of the user's operating tools. For example, after wearing a mixed reality device, a user can see a virtual protection cabinet, a live area, a safe operating area, and corresponding operational prompts within the hybrid training scenario, and perform terminal test training within this scenario.

[0047] S104. During the routine inspection training in a mixed training scenario, obtain the visual and inertial data of the user's operating tool at at least one moment, and determine the spatial motion trajectory of the operating tool based on the visual and inertial data.

[0048] The operating tool refers to the tool used by the user during relay protection routine maintenance training to simulate actual testing operations and interact with the target maintenance object. The operating tool includes at least one of a test pen, multimeter probes, and secondary circuit test probes. As the interactive object for the user to perform virtual routine maintenance operations, the operating tool's movement trajectory and spatial position are detected to identify anomalies in the user's operation process.

[0049] Visual data can refer to image information describing the operating tool and its surrounding environment. Visual data is used to determine the spatial position of the operating tool and, combined with inertial data, to determine the spatial trajectory of the operating tool.

[0050] Inertial data refers to data collected by inertial measurement units (IMUs) to describe the motion state of an operating tool. Based on the inertial changes generated during the tool's motion, collected by the IMU, the motion state of the tool is determined by analyzing the changes in acceleration and angular velocity during the motion.

[0051] The spatial motion trajectory refers to the path of the operating tool's position change in three-dimensional space, describing the spatial range traversed by the tool as it moves from its starting position to its target position. The spatial motion trajectory characterizes the actual operating range of the tool and is a crucial basis for subsequent determinations of whether the tool has entered a safe operating area and for detecting anomalies in the work area.

[0052] S105. Based on the positional relationship between the spatial motion trajectory and the safe operating area, perform anomaly detection on the operating tool in the working area and determine the anomaly detection result of the operating tool.

[0053] Work area anomaly detection refers to the process of determining whether a tool is within its permissible operating range based on its spatial movement range and the positional relationship between the tool and a preset safe operating area. Work area anomaly detection is used to identify whether a user's tool has exceeded the safe operating range corresponding to the target maintenance object.

[0054] As can be seen, in this embodiment, by spatially registering the spatial scanning data of the relay protection room with the secondary circuit topology model of the protection cabinet, a three-dimensional virtual scene corresponding to the actual working environment is generated. Combined with the target scheduled maintenance task, the safe operating area of ​​the target maintenance object and the corresponding operation guidance information are determined, enabling the construction of targeted hybrid training scenarios based on specific tasks during training. Furthermore, by acquiring visual and inertial data of the operating tool, the spatial motion trajectory of the operating tool is determined, and anomaly detection of the operating tool is performed based on the positional relationship between the spatial motion trajectory and the safe operating area. This achieves spatial detection of the operating tool's operating range, helping to improve the accuracy and objectivity of operating area judgment during scheduled maintenance training and reducing training risks caused by the operating tool deviating from the safe operating area. This solves the technical problem in the prior art where it is difficult to accurately identify and respond in a timely manner when the operating tool approaches a dangerous area or deviates from the target operating area, resulting in insufficient safety risk warning capabilities during training and training evaluation results being easily influenced by human experience, leading to low accuracy and effectiveness of scheduled maintenance training. Therefore, it can realize the anomaly detection of the spatial position of the operating tool during scheduled maintenance training.

[0055] In an optional embodiment, Figure 2 The flowchart of an operation tool area anomaly detection method provided by an embodiment of the present invention refines the process of "determining the safe operation area of ​​the target maintenance object in a three-dimensional virtual scene according to the target scheduled maintenance task, and associating the operation guidance information of the target maintenance object with the safe operation area to generate a hybrid training scenario" into "determining the electrical isolation status of the protection cabinet according to the pressure plate status information, connection piece status information, and switch status information of the target scheduled maintenance task; calibrating the on / off status of the electrical nodes in the secondary circuit topology model according to the electrical isolation status, and determining the effective energized nodes that are connected to the energized potential according to the on / off status and node connection relationship of the calibrated electrical nodes; mapping the effective energized nodes to the three-dimensional virtual scene according to the identification information of the effective energized nodes in the secondary circuit topology model to obtain the spatial distribution result of the energized nodes of the target maintenance object; generating the safe operation area of ​​the target maintenance object according to the spatial distribution result of the energized nodes and the spatial position of the target maintenance object; obtaining the operation guidance information of the target scheduled maintenance task; and binding the operation guidance information to the safe operation area to obtain a hybrid training scenario," thereby improving the operation of operation tool area anomaly detection.

[0056] It should be noted that for parts not described in detail in the embodiments of the present invention, please refer to the descriptions in other embodiments.

[0057] See Figure 2 The method for detecting anomalies in the operating tool area shown includes:

[0058] S201. Obtain spatial scanning data of the relay protection room, the secondary circuit topology model of the protection cabinet, and the target scheduled inspection task.

[0059] S202. Spatial registration is performed on the spatial scanning data and the secondary loop topology model to generate a three-dimensional virtual scene.

[0060] S203. Determine the electrical isolation status of the protection cabinet based on the pressure plate status information, connection piece status information, and switch status information of the target scheduled inspection task.

[0061] The status information of the pressure plates refers to the current working status of each pressure plate in the relay protection device or protection cabinet, which reflects whether the pressure plate is in operation or out of operation. Pressure plates are usually installed in the protection cabinet and have attributes such as corresponding pressure plate number, corresponding protection circuit, function type, and current operation status. The status of different pressure plates will affect the conduction relationship and electrical connection status of the protection circuit.

[0062] Among them, the connection piece status information refers to the current connection status of the connection piece in the protection cabinet, which is used to reflect whether the connection piece is in a connected, disconnected or removed state.

[0063] Among them, switch status information can refer to the current operating status information of various switch devices involved in the target scheduled inspection task, which is used to indicate whether the corresponding switch is in the closed, open or other working state.

[0064] Electrical isolation status refers to the overall electrical connection status formed by the configuration of various secondary circuits within the protection cabinet through devices such as pressure plates, connecting pieces, and switches. It reflects whether each electrical circuit maintains continuity and whether the energized potentials have been isolated. Electrical isolation status serves as a crucial basis for continuity calibration in the secondary circuit topology model. Different isolation statuses identify nodes that remain connected to the energized potential and nodes that have been isolated, thus ensuring that the subsequent generation of safe operating areas conforms to the current actual operating conditions.

[0065] S204. Based on the electrical isolation state, calibrate the on / off state of the electrical nodes in the secondary circuit topology model, and determine the effective energized nodes that maintain connection with the energized potential based on the calibrated on / off state of the electrical nodes and the node connection relationship.

[0066] In this context, an effective energized node refers to an electrical node that, under the current electrical isolation state, remains connected to a energized potential through a secondary circuit. By analyzing the continuity of the secondary circuit topology model, nodes that still maintain electrical connection can be identified and designated as effective energized nodes. This serves as a crucial basis for subsequently generating safe operating areas, enabling the system to accurately identify locations where there is a genuine risk of electric shock.

[0067] S205. Based on the identification information of the effective energized nodes in the secondary circuit topology model, the effective energized nodes are mapped to the three-dimensional virtual scene to obtain the spatial distribution result of the energized nodes of the target maintenance object.

[0068] Among them, the spatial distribution result of the energized nodes can refer to the spatial distribution of each energized node after mapping the effective energized nodes to a three-dimensional virtual scene, which is used to reflect the three-dimensional distribution status of all effective energized nodes in the actual relay protection room space.

[0069] S206. Based on the spatial distribution of energized nodes and the spatial location of the target maintenance object, generate the safe operating area of ​​the target maintenance object.

[0070] The spatial location of the target maintenance object can refer to the actual spatial coordinates of the target maintenance object in the three-dimensional virtual scene, which is used to represent the spatial positional relationship of the target maintenance object relative to the relay protection room environment and the internal structure of the protection cabinet.

[0071] S207. Obtain the operation guidance information for the target scheduled inspection task.

[0072] S208. Bind the operation guidance information to the safe operation area to obtain a mixed training scenario.

[0073] S209. During the periodic inspection training in a mixed training scenario, obtain the visual and inertial data of the user's operating tool at at least one moment, and determine the spatial motion trajectory of the operating tool based on the visual and inertial data.

[0074] S210. Based on the positional relationship between the spatial motion trajectory and the safe operating area, perform anomaly detection on the operating tool in the working area and determine the anomaly detection result of the operating tool.

[0075] As can be seen, in this embodiment, by combining the pressure plate status information, connection piece status information, and switch status information in the target scheduled maintenance task, the electrical isolation status of the protection cabinet is determined, and the effective live nodes are identified based on the on / off relationship of electrical nodes in the secondary circuit topology model. This allows for an accurate reflection of the spatial distribution of live nodes corresponding to the target maintenance object in the three-dimensional virtual scene. A safe operating area is generated based on the spatial distribution of live nodes and the spatial location of the target maintenance object, and the operation guidance information is associated with the safe operating area. This enables the hybrid training scenario to simultaneously reflect the spatial location, electrical status, and operation requirements of the maintenance object, which helps improve the accuracy of operating area judgment during virtual scheduled maintenance training and reduces training deviations caused by inaccurate operating area identification.

[0076] In some embodiments, spatial registration is performed on spatial scan data and a secondary loop topology model to generate a three-dimensional virtual scene, including:

[0077] Obtain spatial coordinate information of the spatial scan data and initial model coordinate information of the secondary loop topology model;

[0078] Based on the spatial coordinate information and the model coordinate information, the coordinate transformation of the secondary loop topology model is performed to obtain the target model coordinate information;

[0079] Coordinate fusion is performed on the target model coordinate information and spatial coordinate information to generate a three-dimensional virtual scene.

[0080] The initial model coordinate information can refer to the original spatial coordinate information used when the secondary loop topology model is established or stored, which is used to describe the positional relationship of each electrical node, connection relationship or equipment object in the model coordinate system.

[0081] The target model coordinate information refers to the spatial location information of the model after coordinate transformation, ensuring that the secondary loop topology model aligns with the actual spatial coordinate system corresponding to the spatial scan data. The target model coordinate information includes the transformed electrical node coordinates, equipment object coordinates, and the overall spatial positional relationships of the model.

[0082] As can be seen, in this embodiment, by acquiring the spatial coordinate information of the spatial scanning data and the initial model coordinate information of the secondary circuit topology model, and by spatially adjusting the secondary circuit topology model based on the coordinate transformation relationship between the two, the secondary circuit topology model can correspond to the actual relay protection room spatial environment. Then, by coordinate fusion, a three-dimensional virtual scene containing actual spatial structure information and secondary circuit topology information is generated, thereby improving the matching degree between the spatial position of the maintenance object and the electrical topology relationship in the virtual scene. This provides a more accurate spatial basis for subsequently determining the safe operating area of ​​the target maintenance object based on the three-dimensional virtual scene and conducting scheduled maintenance training.

[0083] In some embodiments, determining the spatial motion trajectory of the operating tool based on visual data and inertial data includes:

[0084] Visual data is used for position recognition to determine the spatial position data of the operating tool;

[0085] Based on inertial data, determine the motion state data of the operating tool;

[0086] Spatial position data and motion state data are fused and processed to determine the pose information of the operating tool;

[0087] Based on the pose information corresponding to at least one moment, generate the spatial motion trajectory of the operating tool.

[0088] Position recognition refers to the process of determining the location of an operating tool in an image or spatial environment based on visual data, used to obtain the spatial positioning information of the operating tool in a hybrid training scenario. Position recognition can be achieved based on the appearance features, identification features, contour features, or feature point information of the operating tool, and its output can include the position coordinates of the operating tool in the image coordinate system, the range of the target area, and the corresponding spatial positioning information.

[0089] Spatial location data refers to data representing the specific position of the operating tool in three-dimensional space, used to describe the spatial coordinate state of the operating tool in a hybrid training scenario. Spatial location data typically includes three-dimensional coordinate information, such as horizontal, vertical, and height coordinates, and may also include attributes such as the position of the operating tool's end, the position of the reference point, and the spatial distance between it and surrounding equipment.

[0090] Among them, motion state data can refer to data describing the dynamic changes of the operating tool during the movement process, which is used to reflect the state information such as the moving direction, speed and posture changes of the operating tool.

[0091] Pose information refers to information that simultaneously describes the spatial position and orientation of an operating tool, representing comprehensive data reflecting the tool's state in three-dimensional space. Pose information typically includes the tool's position coordinates and rotation angles around different spatial axes. Obtained by fusing spatial position data and motion state data, pose information accurately describes the tool's actual operating state in a hybrid training scenario and generates the tool's spatial motion trajectory based on pose information from multiple time points.

[0092] As can be seen, in this embodiment, by fusing visual and inertial data of the operating tool, spatial position change information and motion state information of the operating tool are obtained respectively. Furthermore, the two types of data are fused to determine the pose information of the operating tool, thereby generating the spatial motion trajectory of the operating tool based on the pose information at at least one moment. This method can comprehensively utilize different types of sensor data to characterize the spatial state of the operating tool, improving the completeness and accuracy of acquiring the spatial motion information of the operating tool, and providing a data foundation for subsequent anomaly detection in the work area based on the positional relationship between the spatial motion trajectory and the safe operating area.

[0093] In some embodiments, based on the positional relationship between the spatial motion trajectory and the safe operating area, anomaly detection is performed on the operating tool to determine the anomaly detection result of the operating tool, including:

[0094] Determine the spatial position range of the operating tool based on the spatial motion trajectory;

[0095] The working area status of the operating tool is determined based on the spatial overlap between the spatial location range and the safe operating area;

[0096] Based on the status of the work area, determine the abnormal detection results of the operating tools.

[0097] Spatial overlap refers to the mutual coverage of the spatial location range of the operating tool and the safe operating area in three-dimensional space, describing whether there is a spatial intersection between them. Spatial overlap is used to determine whether the operating tool is within the permissible operating range. By analyzing the spatial relationship between the spatial location range of the operating tool and the safe operating area, it is determined whether the user's current operation meets safety requirements.

[0098] The working area status refers to the current working area status of the operating tool, which is determined based on the positional relationship between the spatial location range of the operating tool and the safe operating area. It is used to indicate whether the operating tool is in the permitted operating area.

[0099] As can be seen, in this embodiment, the working area status of the operating tool is determined by analyzing the positional relationship between the spatial movement trajectory of the operating tool and the safe operating area. By determining the spatial location range of the operating tool based on its spatial movement trajectory, the actual activity area of ​​the operating tool during virtual training can be obtained. Furthermore, based on the spatial overlap between this spatial location range and the safe operating area, it can be determined whether the operating tool is within a preset permitted operating area, thereby determining the working area status of the operating tool. Anomaly detection results are generated based on this working area status, which can identify situations such as the operating tool illegally entering unsafe areas during virtual training, improving the accuracy of operating tool area detection and providing a basis for subsequent virtual operation verification and training evaluation.

[0100] In some embodiments, after determining the anomaly detection result of the operating tool, the method further includes:

[0101] When the abnormality detection result indicates that the operating tool is within the safe operating area, the contact motion parameters between the operating tool and the target maintenance object are obtained, and the validity of the operation is determined based on the contact motion parameters.

[0102] When the operation is deemed valid, the user's training evaluation result is obtained by comparing the virtual operation result of the operation tool with the standard operation result.

[0103] If the anomaly detection result indicates that the operating tool is not within the safe operating area, the current virtual operation will be terminated.

[0104] Contact motion parameters refer to data describing the motion state of the operating tool during contact or simulated contact with the target object being maintained. These parameters reflect whether the operating tool completes the operation on the target object as expected. Contact motion parameters may include contact position, contact direction, contact angle, contact duration, and motion changes during the contact process.

[0105] Operational effectiveness refers to the result of judging whether a virtual operation performed by a user meets preset operating conditions based on the contact motion parameters between the operating tool and the target maintenance object. It is used to evaluate whether the user's current operation is effectively completed. Operational effectiveness can be judged based on conditions such as whether the contact position is accurate, whether the operation direction meets the requirements, and whether the contact process is complete. Operational effectiveness reflects the degree of consistency between the user's operating behavior and standard operating requirements.

[0106] As can be seen, in this embodiment, after determining that the operating tool is within a safe operating area, the system further acquires the contact motion parameters between the operating tool and the target maintenance object, and judges the validity of the current operation based on these parameters. This allows the system to further verify the validity of the operation actions while ensuring compliance within the operating area. When the operation is valid, the system can evaluate the user's operation during scheduled maintenance training by comparing the virtual operation result corresponding to the operating tool with the standard operation result. When the operating tool is not within a safe operating area, the system promptly terminates the current virtual operation to avoid continuing to execute virtual operation procedures that do not meet safety requirements. Therefore, this solution can combine the operating area detection results and the operation process verification results during simulated training to more accurately judge and evaluate the user's scheduled maintenance operation process.

[0107] In some embodiments, the operating tools include at least one of the following: a test pen, multimeter probes, and secondary circuit test probes; the target maintenance object includes at least one of the following: terminals, pressure plates, and connecting pieces in the protection cabinet.

[0108] As can be seen, in this embodiment, by defining the specific operating tools and target maintenance objects, the abnormal detection process of the operating tool area can be applied to the actual operating scenarios in relay protection routine maintenance training. Specifically, by limiting the operating tools to actual maintenance tools such as test pens, multimeter probes, and secondary circuit test probes, the user's operating range can be detected by combining the spatial position changes of different tools in the three-dimensional virtual scene. By limiting the target maintenance objects to actual maintenance components such as terminals, pressure plates, and connecting pieces in the protection cabinet, the determination of the safe operating area and the subsequent judgment of the effectiveness of the operation can correspond to specific secondary circuit maintenance objects. This improves the correspondence between the virtual training scenario and actual relay protection routine maintenance work, making the abnormal detection of the operating tool area more closely aligned with the actual maintenance process.

[0109] In an optional embodiment, the abnormal detection method for the operating tool area can be implemented in the following way: the target maintenance object of the current scheduled maintenance work order is terminal 21 (non-energized terminal) of the protection cabinet, the scheduled maintenance training system has obtained the spatial distribution results of energized terminals 11 to 20, and preset the first distance threshold as 10 cm and the second distance threshold as 30 cm.

[0110] The scheduled inspection and training system uses each of the live terminals, numbered 11 to 20, as the center to generate a layered electronic fence: the space no more than 10 cm away from each live terminal is the absolute prohibition zone; the space more than 10 cm away from each live terminal but no more than 30 cm away is the near-electric warning zone; and the space more than 30 cm away from each live terminal and surrounding the target terminal number 21 is the permissible operation zone. This permissible operation zone is cylindrical, with a diameter of 20 cm and a height of 15 cm, precisely surrounding terminal number 21 to ensure that trainees can accurately locate the target during operation.

[0111] Subsequently, the scheduled maintenance training system binds the operation guidance information corresponding to the current operation step to the permitted operation area in the form of spatial anchor points. Among them, the test terminal is identified as "Terminal No. 21 (Line Protection Trip Output Terminal)", clearly informing the trainees of the target terminal for the current operation; the probe approach direction prompt is "From the front of the protection panel, perpendicular to the operating plane of Terminal No. 21, slowly approach from top to bottom", guiding the trainees to operate the probe in a standardized manner; the operation sequence prompt is "Currently, this is step 3 of the scheduled maintenance process. You need to complete the visual inspection of Terminal No. 21 first, then perform the probe contact test, and after completion, proceed to step 4, terminal wiring verification", guiding the trainees to operate according to the standardized process.

[0112] Finally, the scheduled maintenance training system integrates the 3D digital twin scene, the layered electronic fence, and the above-mentioned operation guidance information to form a mixed reality training scene. After wearing the MR (Mixed Reality) device, the trainees can clearly see the protective cabinet, the layered electronic fence corresponding to the live nodes, and the operation guidance information within the permitted operation area.

[0113] Trainees wear MR equipment and simultaneously hold virtual probes to operate on target terminal 21. The scheduled inspection and training system collects visual data including the virtual probes in real time through the camera of the MR equipment, and collects inertial data such as the acceleration and angular velocity of the probes in real time through the built-in inertial measurement unit.

[0114] The scheduled inspection and training system fuses the collected visual and inertial data to eliminate data errors, obtaining the probe tip's pose trajectory. This trajectory records in real time the probe's coordinates and attitude changes as it moves from its initial position (50 cm from terminal 21) towards the target terminal. The system then calculates in real time the Euclidean distance between the probe tip's spatial coordinates and each boundary of the layered electronic fence, as well as the projected distance along the boundary normal direction.

[0115] When the trainee moves the probe toward terminal 21, the Euclidean distance between the probe tip and the live terminal 11 is 25 cm, and the projection distance along the normal direction of the boundary of the near-electric warning zone corresponding to live terminal 11 is 5 cm. At this time, the probe tip is located in the near-electric warning zone. The scheduled inspection and training system immediately sends an audible warning to the trainee through the MR equipment: "Approaching a live area, please operate with caution." At the same time, the near-electric warning zone flashes yellow to remind the trainee to pay attention to safety.

[0116] If the trainee makes an operational error, the probe continues to move toward the live terminal 11. When the probe tip is 8 cm away from the live terminal 11 and enters the absolute prohibition zone, the scheduled inspection and training system immediately blocks the current virtual operation, prohibits the probe from continuing to move, and issues a piercing alarm. The MR equipment screen displays a red warning, informing the trainee that they have entered a danger zone. The trainee must move the probe out of the absolute prohibition zone before they can continue the operation.

[0117] When the trainee adjusts the operation and moves the probe out of the absolute prohibited area and continues to move towards terminal 21, when the Euclidean distance between the probe tip and all live terminals is greater than 30 cm and the probe enters the permissible operation area, the scheduled inspection and training system determines the interactive control result as allowing entry for contact validity judgment. The trainee can continue to operate the probe in this area, approach the target terminal 21, and perform subsequent contact test operations.

[0118] Once the probe tip enters the permissible operating area, the scheduled inspection training system begins to collect the contact motion parameters of the probe tip relative to target terminal 21 in real time. The operating plane of target terminal 21 is a virtual plane preset by the scheduled inspection training system that is parallel to the surface of the terminal, and its normal vector direction is perpendicular to the surface of the terminal and faces inward. The scheduled inspection training system has a preset speed threshold of 2 cm / s and a preset confirmation delay of 3 seconds.

[0119] The trainee slowly approaches the target terminal 21 with the probe. The scheduled inspection and training system collects the movement speed of the probe tip in real time and projects it onto the normal vector direction of the target terminal's operating plane, obtaining a speed projection value of 1.5 cm / s, which is not greater than the preset speed threshold of 2 cm / s. When the probe tip touches the operating plane of the target terminal 21, timing begins. The trainee keeps the probe in stable contact for 3.2 seconds before moving the probe. At this time, the contact dwell time is 3.2 seconds, which is not less than the preset confirmation delay of 3 seconds, and is judged as a valid contact.

[0120] Subsequently, the scheduled inspection training system simulates the actual on-site testing operation based on the effective contact status between the probe and terminal 21, generating a virtual operation result: "Terminal 21 has good contact, the test voltage is 110V, which meets the standard requirements." At the same time, it calls the preset standard expected result, namely, "Terminal 21 has good contact, the test voltage is 110V±5V, and there is no poor contact phenomenon."

[0121] The scheduled inspection training system compared the virtual operation results with the standard expected results and found that the test voltage of 110V was within the range of 110V±5V allowed by the standard expected results, and there was no poor contact. Therefore, the training evaluation result of this step was deemed qualified.

[0122] If the probe tip's projected speed is 3 cm / s, exceeding the preset speed threshold, it is considered an invalid contact. The MR device will then prompt the trainee with "Probe approach speed too fast, please slow down" and ask the trainee to repeat the contact operation. Similarly, if the probe contact dwell time is 2.5 seconds, less than the preset confirmation delay, it is also considered an invalid contact. The trainee will be prompted with "Probe contact is unstable, please maintain contact for at least 3 seconds" until the operation is successful. Only then will a virtual operation result be generated and compared to obtain the training evaluation result.

[0123] Figure 3 This invention provides a schematic diagram of a device for detecting anomalies in the working area of ​​an operating tool. This invention is applicable to situations requiring anomaly detection in the working area of ​​an operating tool. The device can execute an anomaly detection method for the operating tool area and can be implemented in hardware and / or software.

[0124] See Figure 3 The operation tool area anomaly detection device shown includes: a data acquisition module 301, a 3D virtual scene generation module 302, a hybrid training scene generation module 303, a spatial motion trajectory determination module 304, and an anomaly detection result determination module 305, wherein...

[0125] The data acquisition module 301 is used to acquire spatial scanning data of the relay protection room, the secondary circuit topology model of the protection cabinet, and the target scheduled inspection task;

[0126] The 3D virtual scene generation module 302 is used to perform spatial registration of spatial scanning data and secondary loop topology model to generate a 3D virtual scene.

[0127] The hybrid training scenario generation module 303 is used to determine the safe operation area of ​​the target maintenance object in a three-dimensional virtual scene according to the target scheduled maintenance task, and associate the operation guidance information of the target maintenance object with the safe operation area to generate a hybrid training scenario.

[0128] The spatial motion trajectory determination module 304 is used to acquire visual and inertial data of the user's operating tool at at least one moment during the periodic inspection training in a mixed training scenario, and determine the spatial motion trajectory of the operating tool based on the visual and inertial data.

[0129] The anomaly detection result determination module 305 is used to perform anomaly detection on the operating tool in the working area based on the positional relationship between the spatial motion trajectory and the safe operating area, and to determine the anomaly detection result of the operating tool.

[0130] The technical solution of this invention generates a three-dimensional virtual scene corresponding to the actual working environment by spatially registering the spatial scanning data of the relay protection room with the secondary circuit topology model of the protection cabinet. Combined with the target scheduled maintenance task, it determines the safe operating area of ​​the target maintenance object and the corresponding operation guidance information, enabling the construction of targeted hybrid training scenarios based on specific tasks during training. Furthermore, by acquiring visual and inertial data of the operating tool, the spatial motion trajectory of the operating tool is determined, and anomaly detection of the operating tool is performed based on the positional relationship between the spatial motion trajectory and the safe operating area. This achieves spatial detection of the operating tool's operating range, helping to improve the accuracy and objectivity of operating area judgment during scheduled maintenance training and reducing training risks caused by the operating tool deviating from the safe operating area. It solves the technical problem in the prior art where it is difficult to accurately identify and respond in a timely manner when the operating tool approaches a dangerous area or deviates from the target operating area, resulting in insufficient safety risk warning capabilities during training and training evaluation results being easily influenced by human experience, leading to low accuracy and effectiveness of scheduled maintenance training. Therefore, it can realize the anomaly detection of the spatial position of the operating tool during scheduled maintenance training.

[0131] In some embodiments, regarding the determination of the safe operating area of ​​the target maintenance object in a three-dimensional virtual scene according to the target scheduled maintenance task, and the association of the operation guidance information of the target maintenance object to the safe operating area to generate a hybrid training scenario, the hybrid training scenario generation module 303 is specifically used for:

[0132] Based on the status information of the pressure plate, connecting piece, and switch of the target scheduled inspection task, determine the electrical isolation status of the protection cabinet;

[0133] Based on the electrical isolation status, the on / off status of the electrical nodes in the secondary circuit topology model is calibrated, and based on the on / off status of the calibrated electrical nodes and the node connection relationship, the effective energized nodes that maintain connection with the energized potential are determined.

[0134] Based on the identification information of the effective energized nodes in the secondary circuit topology model, the effective energized nodes are mapped to the three-dimensional virtual scene to obtain the spatial distribution results of the energized nodes of the target maintenance object;

[0135] Based on the spatial distribution of energized nodes and the spatial location of the target maintenance object, a safe operating area for the target maintenance object is generated.

[0136] Obtain operational guidance information for the target scheduled inspection task;

[0137] By binding the operation guidance information to the safe operation area, a hybrid training scenario is obtained.

[0138] In some embodiments, in the process of spatially registering spatial scanning data and a secondary loop topology model to generate a three-dimensional virtual scene, the three-dimensional virtual scene generation module 302 is specifically used for:

[0139] Obtain spatial coordinate information of the spatial scan data and initial model coordinate information of the secondary loop topology model;

[0140] Based on the spatial coordinate information and the model coordinate information, the coordinate transformation of the secondary loop topology model is performed to obtain the target model coordinate information;

[0141] Coordinate fusion is performed on the target model coordinate information and spatial coordinate information to generate a three-dimensional virtual scene.

[0142] In some embodiments, in determining the spatial motion trajectory of the operating tool based on visual data and inertial data, the spatial motion trajectory determination module 304 is specifically used for:

[0143] Visual data is used for position recognition to determine the spatial position data of the operating tool;

[0144] Based on inertial data, determine the motion state data of the operating tool;

[0145] Spatial position data and motion state data are fused and processed to determine the pose information of the operating tool;

[0146] Based on the pose information corresponding to at least one moment, generate the spatial motion trajectory of the operating tool.

[0147] In some embodiments, in determining the anomaly detection result of the operating tool by performing work area anomaly detection based on the positional relationship between the spatial motion trajectory and the safe operating area, the anomaly detection result determination module 305 is specifically used for:

[0148] Determine the spatial position range of the operating tool based on the spatial motion trajectory;

[0149] The working area status of the operating tool is determined based on the spatial overlap between the spatial location range and the safe operating area;

[0150] Based on the status of the work area, determine the abnormal detection results of the operating tools.

[0151] In some embodiments, after determining the anomaly detection result of the operating tool, the operating tool area anomaly detection device further includes:

[0152] When the abnormality detection result indicates that the operating tool is within the safe operating area, the contact motion parameters between the operating tool and the target maintenance object are obtained, and the validity of the operation is determined based on the contact motion parameters.

[0153] When the operation is deemed valid, the user's training evaluation result is obtained by comparing the virtual operation result of the operation tool with the standard operation result.

[0154] If the anomaly detection result indicates that the operating tool is not within the safe operating area, the current virtual operation will be terminated.

[0155] In some embodiments, the operating tools include at least one of the following: a test pen, multimeter probes, and secondary circuit test probes; the target maintenance object includes at least one of the following: terminals, pressure plates, and connecting pieces in the protection cabinet.

[0156] The tool area anomaly detection device provided in this embodiment of the invention can execute the tool area anomaly detection method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the tool area anomaly detection method.

[0157] Figure 4 This is a schematic diagram of the structure of an anomaly detection device for an operating tool area provided in an embodiment of the present invention.

[0158] like Figure 4 As shown, the operating tool area anomaly detection device 400 includes at least one processor 401 and a memory, such as a read-only memory (ROM) 402 or a random access memory (RAM) 403, communicatively connected to the at least one processor 401. The memory stores computer programs executable by the at least one processor. The processor 401 can perform various appropriate actions and processes based on the computer program stored in the ROM 402 or loaded from storage unit 408 into the RAM 403. The RAM 403 can also store various programs and data required for the operation of the operating tool area anomaly detection device 400. The processor 401, ROM 402, and RAM 403 are interconnected via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0159] Multiple components in the operating tool area anomaly detection device 400 are connected to the I / O interface 405, including: an input unit 406, such as a keyboard, mouse, etc.; an output unit 407, such as various types of displays, speakers, etc.; a storage unit 408, such as a disk, optical disk, etc.; and a communication unit 409, such as a network card, modem, wireless transceiver, etc. The communication unit 409 allows the operating tool area anomaly detection device 400 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0160] Processor 401 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 401 performs the various methods and processes described above, such as the anomaly detection method for the operating tool area.

[0161] In some embodiments, the operating tool area anomaly detection method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed onto the operating tool area anomaly detection device 400 via ROM 402 and / or communication unit 409. When the computer program is loaded into RAM 403 and executed by processor 401, one or more steps of the operating tool area anomaly detection method described above may be performed. Alternatively, in other embodiments, processor 401 may be configured to perform the operating tool area anomaly detection method by any other suitable means (e.g., by means of firmware).

[0162] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include: implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0163] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0164] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0165] To provide user interaction, the systems and techniques described herein can be implemented on an operating tool area anomaly detection device, which includes: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the operating tool area anomaly detection device. Other types of devices can also be used to provide user interaction; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0166] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0167] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system. It addresses the shortcomings of traditional physical hosts and Virtual Private Server (VPS) services, such as high management difficulty and weak business scalability.

[0168] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0169] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for detecting anomalies in an operating tool area, characterized in that, The method includes: Acquire spatial scanning data of the relay protection room, the secondary circuit topology model of the protection cabinet, and the target scheduled maintenance tasks; Spatial registration is performed on the spatial scan data and the secondary loop topology model to generate a three-dimensional virtual scene; Based on the target scheduled maintenance task, the safe operating area of ​​the target maintenance object is determined in the three-dimensional virtual scene, and the operation guidance information of the target maintenance object is associated with the safe operating area to generate a hybrid training scenario; During the scheduled training in the hybrid training scenario, visual and inertial data of the user's operating tool at at least one moment are acquired, and the spatial motion trajectory of the operating tool is determined based on the visual and inertial data. Based on the positional relationship between the spatial motion trajectory and the safe operating area, the operating tool is subjected to work area anomaly detection, and the anomaly detection result of the operating tool is determined.

2. The method according to claim 1, characterized in that, The step of determining the safe operating area of ​​the target maintenance object in the three-dimensional virtual scene according to the target scheduled maintenance task, and associating the operation guidance information of the target maintenance object with the safe operating area to generate a hybrid training scenario includes: Based on the pressure plate status information, connection piece status information, and switch status information of the target scheduled inspection task, the electrical isolation status of the protection cabinet is determined; Based on the electrical isolation state, the on / off state of the electrical nodes in the secondary circuit topology model is calibrated, and based on the on / off state of the calibrated electrical nodes and the node connection relationship, the effective energized nodes that maintain connection with the energized potential are determined. Based on the identification information of the effective energized nodes in the secondary circuit topology model, the effective energized nodes are mapped to the three-dimensional virtual scene to obtain the spatial distribution result of the energized nodes of the target maintenance object; Based on the spatial distribution of the energized nodes and the spatial location of the target maintenance object, a safe operating area for the target maintenance object is generated. Obtain the operation guidance information for the target scheduled inspection task; The operation guidance information is bound to the safe operation area to obtain the hybrid training scenario.

3. The method according to claim 1, characterized in that, The step of spatially registering the spatial scan data and the secondary loop topology model to generate a three-dimensional virtual scene includes: Obtain the spatial coordinate information of the spatial scan data and the initial model coordinate information of the secondary loop topology model; Based on the spatial coordinate information and the model coordinate information, the coordinate transformation of the secondary loop topology model is performed to obtain the target model coordinate information; The target model coordinate information and the spatial coordinate information are fused to generate the three-dimensional virtual scene.

4. The method according to claim 1, characterized in that, Determining the spatial motion trajectory of the operating tool based on the visual data and the inertial data includes: The visual data is used for position recognition to determine the spatial position data of the operating tool; Based on the inertial data, determine the motion state data of the operating tool; The spatial position data and the motion state data are fused to determine the pose information of the operating tool; The spatial motion trajectory of the operating tool is generated based on the pose information corresponding to at least one moment.

5. The method according to claim 1, characterized in that, The step of performing work area anomaly detection on the operating tool based on the positional relationship between the spatial motion trajectory and the safe operating area, and determining the anomaly detection result of the operating tool, includes: Based on the spatial motion trajectory, determine the spatial position range of the operating tool; The working area status of the operating tool is determined based on the spatial overlap between the spatial location range and the safe operating area; Based on the status of the work area, determine the anomaly detection result of the operating tool.

6. The method according to claim 1, characterized in that, After determining the anomaly detection result of the operating tool, the method further includes: When the anomaly detection result indicates that the operating tool is located within the safe operating area, the contact motion parameters between the operating tool and the target maintenance object are obtained, and the validity of the operation is determined based on the contact motion parameters. When the operation is deemed valid, the user's training evaluation result is obtained by comparing the virtual operation result of the operation tool with the standard operation result. If the anomaly detection result indicates that the operating tool is not within the safe operating area, the current virtual operation is terminated.

7. The method according to claim 1, characterized in that, The operating tools include at least one of the following: a test pen, multimeter probes, and a secondary circuit test probe; the target maintenance object includes at least one of the following: terminals, pressure plates, and connecting pieces in the protection cabinet.

8. An anomaly detection device for an operating tool area, characterized in that, include: The data acquisition module is used to acquire spatial scanning data of the relay protection room, the secondary circuit topology model of the protection cabinet, and the target scheduled maintenance tasks; A 3D virtual scene generation module is used to spatially register the spatial scanning data and the secondary loop topology model to generate a 3D virtual scene. The hybrid training scenario generation module is used to determine the safe operation area of ​​the target maintenance object in the three-dimensional virtual scene according to the target scheduled maintenance task, and associate the operation guidance information of the target maintenance object with the safe operation area to generate a hybrid training scenario; The spatial motion trajectory determination module is used to acquire visual and inertial data of the user's operating tool at at least one moment during the periodic inspection training in the hybrid training scenario, and determine the spatial motion trajectory of the operating tool based on the visual and inertial data. The anomaly detection result determination module is used to perform work area anomaly detection on the operating tool based on the positional relationship between the spatial motion trajectory and the safe operating area, and to determine the anomaly detection result of the operating tool.

9. An anomaly detection device for an operating tool area, characterized in that, The anomaly detection device for the operating tool area includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the operating tool area anomaly detection method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the operation tool area anomaly detection method according to any one of claims 1-7.

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