Inspection model debugging configuration method and system

Abstract

The invention relates to the technical field of electric power system inspection, and provides an inspection model debugging configuration method and system, and the method comprises the steps: splitting a complex inspection task into a plurality of independent and correlated data models, and carrying out the configuration, comprising a navigation map model, a scene model, a point position model, a robot model, an electronic map model, a stop position model, a preset position model and the like, the data models with different functions are decoupled, the low coupling degree between data is achieved, when a certain function is modified or added, the whole architecture does not need to be comprehensively adjusted, and the cost is reduced. According to the method, the development cost and risk are reduced, each model can be independently updated and optimized without influencing other models, and the maintainability and expandability of the whole model are greatly improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of power system inspection, and in particular relates to an inspection model debugging configuration method and system. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] In the current application field of inspection robots, there is a common and severe challenge: the fragmentation and complexity of the configuration and debugging process. The configuration and debugging process of inspection robots generally presents a "chain" structure, and each key link needs to rely on specific professional tools. Specifically, from the basic configuration of the robot model to the debugging of advanced functions, such as electronic map editing, standard point model management, patrol model configuration, task management and monitoring, and even all aspects of system operation and maintenance, they all rely on multiple independent and highly professional tool software. This decentralized state of tooling will lead to the following problems:

[0004] (1) It increases the learning cost of operation and maintenance personnel, and leads to low efficiency due to frequent tool switching. The lack of effective integration and coordination between various links makes it difficult to improve the overall configuration efficiency, which seriously restricts the rapid deployment and efficient operation and maintenance of the inspection robot system.

[0005] (2) The configuration and debugging progress cannot be intuitively controlled. Since the configuration and debugging process of the inspection robot involves multiple independent tools, and there is a lack of effective progress synchronization and status feedback mechanism between these tools, it is difficult for operation and maintenance personnel to grasp the progress of the entire configuration and debugging process in real time. This leads to great uncertainty in project management and time control, and is prone to task delays or improper resource allocation.

[0006] (3) The lack of a unified data interface and standard among various tools makes it difficult to centrally manage and output the data in a unified format when the inspection robot performs tasks. This decentralization not only increases the difficulty of data integration, but also reduces the systematicness and processing efficiency of the data. In addition, there are generally problems of highly coupled data models and insufficient system flexibility. Specifically, the data of each functional module are closely intertwined. Once a specific function (such as the inspection path or alarm threshold) needs to be adjusted, it often requires touching the core architecture of the entire system, resulting in a long development cycle and high risks. In addition, due to the lack of sufficient decoupling of the data model, the system is difficult to quickly respond to changes in the inspection scenario and cannot meet the growing customization requirements. At the same time, the existing inspection systems often adopt an integrated data display method and lack a customized display interface for different user roles, making it difficult for non-technical background users to understand and operate the system. In addition, the data processing efficiency is low, and the inspection results often need to be presented to users after complex conversion and collation, affecting the timeliness and accuracy of the inspection work.

[0007] (4) The insufficient systematicness of the data further leads to an imperfect data-driven mechanism for the navigation map, low reuse efficiency and interactivity, seriously restricting the flexibility and personalized needs in the inspection operation. Specifically, the existing system lacks an efficient and integrated map editing module, which should be deeply integrated on the map base to support the drawing of diverse map elements, including but not limited to docking points, precise layout of inspection devices, flexible planning of complex paths, and accurate division of functional areas and equipment areas. In addition, the ability to configure the attributes of the above map elements is also insufficient, and it is impossible to make detailed adjustments and optimizations according to the specific inspection task requirements. This situation directly hinders the overall automation and intelligent process from the intelligent division of multi-functional areas to the robot behavior control, restricting the further improvement of the inspection operation in terms of flexibility, customization, and response speed. Summary of the Invention

[0008] To solve the technical problems existing in the above background technology, the present invention provides an inspection model debugging and configuration method and system, which splits complex inspection tasks into multiple independent but interrelated data models for configuration. By decoupling the data models with different functions, a low coupling degree between the data is achieved, so that when modifying or adding a certain function, there is no need to comprehensively adjust the entire architecture, reducing the development cost and risks. Moreover, each model can be independently updated and optimized without affecting other models, greatly improving the maintainability and scalability of the entire model.

[0009] To achieve the above object, the present invention adopts the following technical solutions:

[0010] The first aspect of the present invention provides an inspection model debugging and configuration method, which includes:

[0011] Control the robot to perform laser scanning mapping to obtain a navigation map model;

[0012] Generate area information based on the navigation map model and associate it with the substation to obtain a scene model;

[0013] Obtain the target device points associated with the substation to obtain a point model;

[0014] Create a robot, configure basic information and bind the scene model to obtain a robot model;

[0015] Draw an autonomous patrol path, stop points, functional areas, operation areas, and inspection equipment areas on the navigation map to obtain an electronic map model;

[0016] Send down the autonomous patrol path. During the process of the robot moving along the autonomous patrol path, control the robot to navigate to the stop point. After obtaining the stop point model, adjust the pan-tilt to the optimal viewing angle and adjust the camera parameters to obtain a preset position model. Associate the stop point model, preset position model, and target device points, and optimize the autonomous patrol path based on the stop point, update the topological relationship of the electronic map, and add it to the electronic map model;

[0017] Combine the navigation map model, scene model, point model, robot model, electronic map model, stop point model, and preset position model as an inspection model, so that the robot can perform substation inspection based on the inspection model.

[0018] Furthermore, the inspection model further includes an alarm model, a result display model, and a three-phase association model; the alarm model, result display model, and three-phase association model respectively store alarm information, result display templates, and three-phase association relationships associated with the target device points.

[0019] Furthermore, the stop point and preset position are automatically generated or manually remotely adjusted during the process of the robot moving along the autonomous patrol path.

[0020] Furthermore, for the stop points and preset positions in the repeated space, they are generated using a replication algorithm. The steps of the replication algorithm include:

[0021] Select the space to be replicated and the repeated space in the electronic map. The target devices in the replicated space and the repeated space are the same, and the distribution of the target device points is the same. The stop point model and preset position model of the target device points in the replicated space are known, while those in the repeated space are unknown;

[0022] Select a stop point in the replicated space as a reference point, and control the robot to move to the reference point. The position of the reference point in the repeated space is the same as the position of the reference point in the replicated space;

[0023] Calculate the coordinate offset and angular offset between the calculation reference point and the reference point, and based on the coordinate offset and angular offset, copy the docking point model and the preset position model in the copy space to the duplicate space.

[0024] Further, it further includes: performing intersection path splitting during the drawing process of the autonomous patrol path, and the steps of the intersection path splitting include: obtaining a new line segment; determining whether the new line segment intersects with the existing line segment; if so, obtaining the intersection point, and taking the line intersecting with the new line segment as an intersecting line, and determining whether the intersection point is an endpoint of the intersecting line; if it is not an endpoint, splitting the intersecting line into two line segments with the intersection point; if it is an endpoint, determining whether the intersection point is an endpoint of the new line segment, and if not, splitting the new line segment into two line segments with the intersection point.

[0025] The second aspect of the present invention provides an inspection model debugging and configuration system, which includes:

[0026] A map management module, which is configured to: control the robot to perform laser scanning mapping to obtain a navigation map model;

[0027] A scene management module, which is configured to: generate area information based on the navigation map model and associate it with the substation to obtain a scene model;

[0028] A point position management module, which is configured to: obtain the target device point positions associated with the substation to obtain a point position model;

[0029] A robot management module, which is configured to: create a robot, configure basic information and bind the scene model to obtain a robot model;

[0030] A map editing module, which is configured to: draw an autonomous patrol path, docking points, functional areas, operation areas, and inspection equipment areas in the navigation map to obtain an electronic map model;

[0031] A point position recording module, which is configured to: issue an autonomous patrol path, during the process of the robot traveling along the autonomous patrol path, control the robot to navigate to the docking point, after obtaining the docking point model, adjust the pan-tilt to the optimal viewing angle, and adjust the camera parameters to obtain a preset position model, associate the docking point model, the preset position model, and the target device point positions, optimize the autonomous patrol path based on the docking point, update the electronic map topology relationship, and add it to the electronic map model;

[0032] A task management module, which is configured to: combine the navigation map model, the scene model, the point position model, the robot model, the electronic map model, the docking point model, and the preset position model as an inspection model, so that the robot performs substation inspection based on the inspection model.

[0033] Further, the docking points and preset positions of the repeated space are generated by using a copying algorithm, and the steps of the copying algorithm include:

[0034] Select the space to be copied and the repeated space in the electronic map. The target devices in the copied space and the repeated space are the same, and the distribution of the target device points is consistent. The docking point model and the preset position model of the target device points in the copied space are known, while those in the repeated space are unknown;

[0035] Select a docking point in the copied space as the reference point, and control the robot to move to the reference point. The position of the reference point in the repeated space is the same as that of the reference point in the copied space;

[0036] Calculate the coordinate offset and angle offset between the reference point and the reference point, and based on the coordinate offset and angle offset, copy the docking point model and the preset position model in the copied space to the repeated space.

[0037] Further, the map editing module is further configured to: perform intersection path splitting during the drawing of the autonomous patrol path. The steps of the intersection path splitting include: obtaining a new line segment; determining whether the new line segment intersects with the existing line segments; if so, obtaining the intersection point, and taking the line intersecting with the new line segment as an intersecting line, and determining whether the intersection point is an endpoint of the intersecting line; if it is not an endpoint, split the intersecting line into two line segments with the intersection point; if it is an endpoint, determine whether the intersection point is an endpoint of the new line segment. If not, split the new line segment into two line segments with the intersection point.

[0038] The third aspect of the present invention provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps in a patrol model debugging and configuration method as described above are implemented.

[0039] The fourth aspect of the present invention provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the steps in a patrol model debugging and configuration method as described above are implemented.

[0040] Compared with the prior art, the beneficial effects of the present invention are:

[0041] The present invention provides a patrol model debugging and configuration method, which splits complex patrol tasks into multiple independent and interrelated data models for configuration. By decoupling data models with different functions, low coupling between data is achieved, so that when modifying or adding a certain function, there is no need to comprehensively adjust the entire architecture, reducing development costs and risks. Moreover, each model can be independently updated and optimized without affecting other models, greatly improving the maintainability and scalability of the entire model.

[0042] The present invention provides a method for debugging and configuring an inspection model. Based on the designed automatic association rules, it realizes the automatic association of alarm templates, result display templates, and three phases in point management, not only reducing the workload of manual configuration but also significantly reducing the configuration error rate, and achieving the intelligent upgrade of substation point management.

[0043] The present invention provides a method for debugging and configuring an inspection model, which introduces the automatic generation and replication functions of preset positions, docking points, and point association models, effectively reducing the configuration complexity of repeated areas, intervals, strings, devices, etc., and improving the efficiency and accuracy of point recording. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings forming a part of this invention are used to provide a further understanding of the invention. The schematic embodiments and descriptions thereof of the invention are used to explain the invention and do not constitute an improper limitation to the invention.

[0045] Figure 1 is a flowchart of a method for debugging and configuring an inspection model according to Embodiment 1 of the present invention;

[0046] Figure 2 is a flowchart of splitting intersecting paths during the process of drawing an autonomous inspection route according to Embodiment 1 of the present invention;

[0047] Figure 3 is a flowchart of optimizing an inspection route according to Embodiment 1 of the present invention;

[0048] Figure 4 is a schematic diagram of a replication algorithm according to Embodiment 1 of the present invention;

[0049] Figure 5 is a schematic diagram of the second case of splitting a route according to Embodiment 1 of the present invention;

[0050] Figure 6 is a schematic diagram of the third case of splitting a route according to Embodiment 1 of the present invention;

[0051] Figure 7 is an architecture diagram of an inspection model debugging and configuration system according to Embodiment 2 of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0052] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0053] It should be noted that the following detailed descriptions are all illustrative and are intended to provide a further description of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs.

[0054] Embodiment 1

[0055] This embodiment provides a method for debugging and configuring an inspection model.

[0056] The method for debugging and configuring an inspection model provided by this embodiment constructs an integrated configuration and debugging platform to achieve seamless connection and progress synchronization among various tools, so as to break the existing limitations and comprehensively improve the efficiency and intelligent level of inspection operations, which is crucial for improving the configuration and debugging efficiency and accuracy of the inspection robot system.

[0057] The method for debugging and configuring an inspection model provided by this embodiment, as Figure 1 shown, includes the following steps:

[0058] Step 1: The operation and maintenance personnel conduct a preliminary on-site inspection to be familiar with the equipment and routes.

[0059] Step 2: The robot performs laser scanning to build a map for subsequent map interaction and real-time information display, and outputs a navigation map model.

[0060] Step 3: Establish a substation, import the navigation map and automatically generate area information, and associate it with the substation, that is, complete the creation of the substation-map-area scenario for subsequent binding of the robot and the scenario, and output a scenario model. At the same time, the standard points (target equipment points) in the superior system can be imported (or points can be established step by step according to the six-level point tree) and bound to the affiliated substation to obtain a point model. The points are automatically matched and associated according to the preset alarm and result display templates, and are automatically three-phase associated according to the three-phase rules to obtain an alarm model, a result display model, and a three-phase association model. By importing standard points and automatic association, the workload of on-site personnel and the manual configuration error rate are further reduced.

[0061] Among them, the steps for creating a scenario include: (1) First, the first-level node is the substation level. When a new substation is created, the substation type, substation name, and other substation-related information will be selected. After saving, a substation data will be generated, which is the root node of the scenario tree; (2) Under this substation, a second-level node, that is, a map node, is created. It is a child node of the substation. When a new map is created, the map type, map name, and the navigation map file after the robot's laser scanning will be selected and uploaded. After saving, a second-level map node will be generated; (3) After uploading the navigation map, a default area (also called the default scenario), that is, the third-level node, which is a child node of this map, will be automatically generated. The default scenario data mainly includes the scenario name and a set of vertex coordinates generated according to the four vertices of the parent map. If necessary later, a new scenario can be created under this map. When editing the map, a region can be manually selected, and a new set of vertex coordinates, that is, a new scenario, will be generated according to the selected region.

[0062] Step 4: Create a robot, configure basic information and bind it to a scenario, and output a robot model; after selecting the current scenario, remote operation and maintenance configuration of the robot in the current scenario can be performed.

[0063] Step 5: Complete the drawing of docking points, autonomous patrol routes, functional areas, operating areas, inspection equipment areas, etc. in the map editing and configure the corresponding control logics and attributes to obtain an electronic map model, which is used for subsequent autonomous patrol route distribution and replication of repeated areas, intervals, strings, and equipment, reducing the workload and complexity of preset position configuration during the recording of target device points.

[0064] Among them, the docking points include: speed adjustment points, parking points, detection points, charging points, turning points, etc.; operating area: the area where the robot can operate, and the robot is prohibited from entering the area outside the operating area; functional area: an area with certain functional attributes, such as a door control area, a speed adjustment area, a no-entry area, etc., and different areas can be configured with different robot operating speed and other attributes; inspection equipment area: the area where the target equipment is located.

[0065] In this embodiment, the map base component uses canvas technology to implement map element drawing.

[0066] (1) According to the map element type, function, and operation implementation, the map is divided into several layers to achieve classified display of map elements, split and encapsulation of drawing logics, and can reduce the redrawing frequency and improve the map drawing efficiency.

[0067] ① Background layer: Draw auxiliary grids and the map base map, and support base map switching;

[0068] ② Single-point drawing layer: Draw point elements, and support functions such as point stamping drawing, dragging, and dragging and rotating;

[0069] ③ Path drawing layer: Draw line segment elements, and support functions such as point-line adsorption, auxiliary correction, and dragging and modification;

[0070] ④ Area drawing layer: Draw surface elements, and support functions such as arbitrary polygon drawing and dragging and modification;

[0071] ⑤ Operation layer: Support functions such as element click selection, area selection, and right-click menu;

[0072] ⑥ Real-time drawing layer: Implement the real-time information drawing and display functions of the robot's planned path, real-time position, etc.

[0073] (2) Map coordinate conversion:

[0074] ① The canvas size is calculated and set according to the map base map size and the map size parameters in the configuration file to balance the rendering clarity and rendering rate;

[0075] ② The coordinates of map elements are converted based on parameters such as the origin offset, scaling ratio, canvas size, and coordinate system quadrant in the configuration file, and the coordinate data is converted to the standard coordinates for robot navigation when stored.

[0076] (3) Map main operation functions:

[0077] ① Support operations such as mouse wheel zooming and mouse dragging to support fine drawing operations of the map;

[0078] ② Implement a ruler function on the map border, combined with auxiliary grids, to improve the user's perception of coordinate positions;

[0079] ③ Store drawing operations during the drawing process to implement functions such as operation undo and redo;

[0080] ④ Operations such as map element deletion and saving support keyboard shortcuts.

[0081] (4) Introduce calculations related to the relationships between points, lines, and surfaces to implement functions such as drawing auxiliary correction, element single selection, area selection, and point-line adsorption. The implemented calculation logics are as follows:

[0082] ① Calculate the distance between element points;

[0083] ② Calculate the distance from a point to a line segment and return the projection coordinates of the point on the line segment;

[0084] ③ Determine whether a point is inside a surface;

[0085] ④ Determine whether a line is inside a surface;

[0086] ⑤ Determine whether two lines intersect and return the intersection point coordinates;

[0087] ⑥ Determine whether a point is on a line, including whether it is an endpoint.

[0088] (5) Design the path drawing and splitting logic to implement the function of splitting intersecting paths during the drawing process of the autonomous patrol path, which is used to support the generation of electronic maps and topological matrix calculations.

[0089] Specifically, as Figure 2 shown, the steps for splitting intersecting paths during the drawing process of the autonomous patrol path include: obtaining the newly added line segment; determining whether the newly added line segment intersects with the existing line segments (not end-to-end connected); if so, obtaining the intersection point and taking the line intersecting with the newly added line segment as an intersecting line, and determining whether the intersection point is an endpoint of the intersecting line; if it is not an endpoint, splitting the intersecting line into two line segments at the intersection point; if it is an endpoint, determining whether the intersection point is an endpoint of the newly added line segment, and if not, splitting the newly added line segment into two line segments at the intersection point.

[0090] Step 6: Start point recording. The specific steps are as follows:

[0091] Step 601: Click on the map point or send the autonomous patrol route, manually control or automatically control the robot with one key to navigate to the best observation point (i.e., the docking point) to obtain the docking point model.

[0092] Step 602: Based on video control or through the control panel, remotely control the pan-tilt to the best observation angle, and manually control or automatically control the zoom, focus, and exposure of the visible light camera or infrared camera with one key to obtain the preset position model.

[0093] As an implementation method, the docking point and the preset position can be automatically generated or manually remotely adjusted during the process of the inspection robot moving along the set inspection route (autonomous patrol route). Among them, the set inspection route contains several inspection points (i.e., the positions close to the target device points).

[0094] Step 603: In the device point directory, select the target device point observed at the current preset position and associate the target device point.

[0095] Step 604: Click to preview or save the preset position, generate the docking point, preset position, point association model, and generate the capture template; the map automatically draws the docking point, optimizes the inspection route, and updates the docking point topology matrix file.

[0096] In this embodiment, as Figure 3 shown, the steps of optimizing the inspection route and updating the topological relationship of the electronic map include:

[0097] (1) First, draw several inspection routes (i.e., the above-mentioned autonomous patrol routes) in the configuration tool, and there are already several docking points in the map; the starting point and the ending point in the inspection route must have clear coordinates.

[0098] (2) Split the route according to the nearest position of the docking point to the nearest route, and there are three cases: The first case is that the docking point is on the line, and in this case, the route is directly split into two routes; the second case is that the docking point is at both ends of the line, and the vertical distance from the docking point to the route (the distance from the intersection point of the perpendicular line drawn from the docking point to the route and the docking point is called the vertical distance) is less than the straight-line distance to the line segment (that is, the shortest distance from the docking point to the end point of the line). In this case, directly add a line segment, the starting point of the added line segment is the end point of the original line segment, and the docking point is the end point of the new line segment, as Figure 5 shown; the third case is that the docking point is in the middle position of the line but not on the line, and the vertical distance from the docking point to the route is equal to the straight-line distance from the docking point to the line segment. In this case, the disassembly method is the same as the first case, and the disassembly position is the vertical point of the docking point to the line segment; delete the original line, as Figure 6 shown.

[0099] (3) Additionally, if there are intersections with three or more branches, stop points (turning points) are automatically generated at the intersections. The generation logic of the turning points is relatively simple. When saving the map route, it only needs to be determined which line segments the starting point and the ending point of the line segment belong to respectively. If they belong to three or more line segments, stop points (turning points) are generated based on the intersection points.

[0100] (4) Split the route according to the above situation, only retain the line segments with stop points at both ends, and recalculate the distances between the stop points, then the automatically planned topological matrix (i.e., the updated topological relationship of the electronic map) will be obtained.

[0101] (5) Generate an svg file according to the selected map; generate points, lines, and background graphics and export them as an svg format file according to the svg standard file generation specifications.

[0102] Step 605: The device directory distinguishes between recorded and unrecorded device points according to the preset position configuration status;

[0103] Step 606: According to the current area situation, perform copy operations on overlapping areas, intervals, strings, and devices, and configure reference stop points and preset positions.

[0104] Among them, the steps of the copy algorithm for spatial overlapping areas, intervals, and main device configuration information include:

[0105] (1) Select the set of stop points to be copied in the electronic map.

[0106] (2) Move the robot to the reference point corresponding to the reference point, such as the 4th stop point in the figure, as Figure 4 shown.

[0107] (3) Calculate the offset (delta_x, delta_y) of the 4th reference point relative to the positioning coordinates of the 1st reference point, and the angular offset (delta_yaw).

[0108] (4) For each point in the set of stop points to be copied, add the previously calculated coordinate offsets (delta_x, delta_y) to its coordinates respectively, and add the angular offset (delta_yaw) to its heading angle for rotation adjustment. At the same time, for the preset positions to be copied, the horizontal offset angle needs to be subtracted by the heading angle offset (delta_yaw) to ensure that they maintain the correct direction relative to the new position.

[0109] (5) The numbers of the newly distributed stop points and preset positions are incremented successively.

[0110] Step 7: After the recording is completed, an inspection model is obtained.

[0111] The inspection model includes a basic model, an inspection model, and an electronic map model, as shown in Table 1, Table 2, and Table 3 respectively.

[0112] Table 1. Basic Model

[0113] Name Description Scene model It includes a three - level structure of substation, map, and area Robot model It includes type, model, IP, etc

[0114] Table 2. Inspection Model.

[0115]

[0116]

[0117] Table 3. Electronic Map Model

[0118] Name Description Functional area Door control area, speed regulation area, no - entry area, etc SVG map SVG map description file Topology matrix file Docking point topology matrix file, that is, the topological relationship of the electronic map

[0119] Step 8: After obtaining the inspection model, an inspection task can be created for automatic inspection. Through the two-way linkage interaction operation between the map and the point tree, different types of inspection tasks can be created for the selected points. During the inspection process, the execution progress and inspection results of the tasks can be viewed in real time. Rectification is carried out according to the inspection results.

[0120] In this embodiment, a method for evaluating debugging quality and debugging status is proposed as the basis for subsequent rectification.

[0121] The debugging status is displayed in the configuration overview module. The user selects the scenario by dropping down in the page header bar, and the configuration overview loads the progress overview of the current scenario. The progress synchronization or status feedback mechanism is as follows:

[0122] Status rule: Green indicates completion, gray indicates not yet started, and yellow flashing dynamically indicates in progress, enhancing visual attraction and immediate feedback effect.

[0123] Progress display: Multilevel progress bars are introduced in key modules (such as scenario management, robot management), not only showing the overall progress but also refining to each sub-item or stage.

[0124] Historical record: Build a modular and structured operation log system to automatically record the time, user, and specific changed content of each module access, edit, and save. Combining the historical records, the effective working time of each operator is automatically calculated, supporting multi-dimensional analysis by project, time period, etc., providing a basis for performance evaluation and resource allocation.

[0125] Form configuration progress linkage: Each form configuration page adopts a verification mechanism. Once the submission is successful, the system automatically calculates and updates the total configuration progress to ensure that the progress bar accurately reflects the actual completion situation.

[0126] The specific content is as follows:

[0127] Scene Management: After creating a new substation and importing a map, the area is automatically generated and the return is successful. The scene management configuration progress is 100%. At this time, the scene management module turns green.

[0128] Robot Management: It includes N form configuration pages such as FTP configuration, visible light configuration, and infrared configuration. Each form setting has an independent progress bar to display the current completion percentage. After the form setting is submitted for verification and saved successfully, the total configuration progress increases by 1 / N. When the progress reaches 100%, the robot management module turns green.

[0129] Point Management: The point progress is displayed by the ratio of the existing number of points to the total number of points that should exist in this scene.

[0130] Map Editing: Mainly edit the operation area, functional area, inspection equipment area, and draw the inspection path. The coverage rate is obtained by summing the total area of the docking points and the independently patrolled path drawing area and dividing it by the area of the navigation map. The "editing efficiency index" is proposed. This index comprehensively considers the editing time and area complexity (coverage rate), providing a comprehensive evaluation basis for operation and maintenance personnel.

[0131] The calculation formula for the editing efficiency index is as follows:

[0132]

[0133] Among them, E0 is the basic efficiency value, used to adjust the overall efficiency level. C is the coverage rate, which directly reflects the complexity and fineness of the editing. T is the editing time. By taking the square root and adding a very small positive number ε, the influence of time on the efficiency index is smoothed, making the influence of time change on the index more gradual.

[0134] Point Recording: During point recording, all points are displayed in a tree form. Above the tree, there are switching labels for recorded and unrecorded points and the number of recorded and unrecorded points is shown. The corresponding recorded and unrecorded point tree data can be switched and loaded. When the points in the point tree have preset position and docking point association information, they are classified into the recorded point tree and the number of recorded points is counted. The point recording progress is the ratio of the number of recorded points to the total number. Based on the operation complexity during recording (such as the number of zoom and focus operations), recording duration, and the association between points, a point recording complexity score is automatically generated to help optimize subsequent recording strategies.

[0135] Task Management and Monitoring: Through the task board, the execution status (to be executed, in execution, completed, abnormal), actual time consumption, and result viewing (mainly screenshot) of all inspection tasks are displayed in real time. For tasks in execution, a real-time video stream preview is provided so that operation and maintenance personnel can remotely monitor the robot operation. After the task is completed, an inspection result analysis report is automatically generated, including abnormal points, reasons for abnormalities, and quantity statistics, facilitating subsequent rectification and optimization.

[0136] A method for debugging and configuring an inspection model provided in this embodiment develops an integrated configuration platform, integrating functions such as the basic configuration of the robot model, electronic map editing, inspection model configuration, task management and monitoring, and system operation and maintenance into a unified interface. This can greatly reduce the learning cost of operation and maintenance personnel, improve the configuration efficiency, and significantly reduce the error rate.

[0137] A method for debugging and configuring an inspection model provided in this embodiment embeds a progress visualization page to display the progress of each link in the configuration and debugging of the inspection robot in real time, including key information such as task status, time consumption, and personnel allocation. By introducing innovative mechanisms such as dynamic state feedback, multi-level progress display, historical record analysis, editing efficiency index, point recording complexity scoring, and real-time task monitoring, the transparency, accuracy, and efficiency of the debugging process are greatly improved. These innovations not only provide operation and maintenance personnel with an instant and comprehensive overview of the debugging status and a basis for performance evaluation, but also optimize resource allocation and operation strategies through intelligent means, which is of great significance for improving the overall operation and maintenance quality and efficiency.

[0138] A method for debugging and configuring an inspection model provided in this embodiment splits the complex inspection system into multiple independent but interrelated data models, including basic models, inspection models, and electronic map models in general categories. By decoupling data models with different functions, such as separating device information from inspection paths (docking points, preset positions) and separating alarm configuration from result display, a low coupling degree between data is achieved. This design enables modification or addition of a certain function without a full adjustment of the entire system architecture, reducing development costs and risks. This modular design allows each module to be updated and optimized independently without affecting other modules, greatly improving the maintainability and scalability of the system. Additionally, based on the designed automatic association rules, automatic association of alarm templates, result display templates, and three phases is realized in point management, not only reducing the workload of manual configuration, but also significantly reducing the configuration error rate, achieving an intelligent upgrade of substation point management.

[0139] A method for debugging and configuring an inspection model provided in this embodiment develops a map base that supports the drawing of diverse map elements, including but not limited to docking points, precise layout of inspection devices, flexible planning of complex paths, and accurate division of functional areas and operating areas. Combining map stamping movement (including stamping to control the robot to move to this position, stamping servo) and path distribution technology enables the robot to quickly navigate to the best observation point. The introduction of functions such as automatic generation and replication of preset positions, docking points, and point association models effectively reduces the configuration complexity of repetitive areas, intervals, strings, devices, etc., and improves the efficiency and accuracy of point recording. At the same time, based on the above customized operations, electronic map files such as topological matrices, SVG maps, and docking point connection relationships can be automatically calculated and exported, solving the problems of large workload and high error rate in hand-drawn electronic maps.

[0140] Embodiment 2

[0141] This embodiment provides an inspection model debugging and configuration system, as Figure 7 shown, which specifically includes: an interaction layer, an application layer, a platform layer, a perception layer, and a persistence layer. It can be deployed to the substation layer, centralized control station layer, and provincial platform layer for application, and is mainly deployed in the station-side layer application according to business characteristics. At the same time, it supports the application of robots in multiple scenarios such as inspection, operation, fire protection, emergency rescue, and security, and can run on the robot industrial control computer, debugging computer, or background host to perform debugging, configuration, and operation and maintenance of the robot and inspection model.

[0142] Perception layer: The inspection model debugging and configuration system controls the task execution unit, lower computer, and navigation system by interacting with the robot body control system.

[0143] Persistence layer: Structured data is stored in the MySQL database, and unstructured data is stored in the specified directory of the robot industrial control computer through the FTP service.

[0144] Platform layer: Encapsulates map editing components, robot control components, video control components, and point recording components, and provides reusable core capabilities to the application layer. The map editing component supports the calibration, drawing, and attribute configuration of docking points, paths, functional areas, operating areas, and inspection device areas. The robot control component supports the control of the vehicle body, pan-tilt, and robot peripherals. The video control component pulls visible light and infrared video streams in real time and supports users to perform one-key operations on the video to control the automatic or manual focus, zoom, exposure, servo, and other quick operations of the camera. The point recording component provides functions such as docking point calibration, preset position calibration, preset position associated points, detection point calibration, and grabbing picture templates.

[0145] Application layer: Provides core business functions such as configuration, management, monitoring, and data distribution. Specifically as follows:

[0146] Configuration Overview Module: This module fully enables real-time debugging node status monitoring, and displays core data such as task execution status, time details, personnel allocation optimization, editing efficiency index evaluation, and recording complexity analysis in detail, providing solid data support for system tuning.

[0147] System configuration module: preset alarm rules and result display templates, flexible configuration to meet the needs of various scenarios, laying a solid foundation for the seamless association of subsequent points; in addition, this module also gives users the ability to configure key information such as the relevant IP of the parent system, and paves a convenient channel for real-time synchronization and sharing of data, ensuring the accurate flow and efficient use of information.

[0148] Scenario management module: Build a three-level refined management system of "substation-map-area" to ensure that the scenario management is clearly structured and the operation is intuitive, providing a clear navigation framework for operation and maintenance work in complex environments.

[0149] Robot management module: can configure the robot and deeply bind it with the scene to achieve accurate matching of robot operations and scene requirements;

[0150] Point management module: supports the step-by-step construction or batch import of six-level standard point models, automatically associates three-phase information, alarm mechanism and result display, builds a comprehensive and integrated point management system, simplifies the operation process and enhances data linkage.

[0151] Map editing module: A map editing component developed based on an innovative map base, which supports the drawing of stops, patrol equipment, paths, functional areas, and operating areas, as well as related attribute configurations, and is used to achieve everything from multi-functional area division to robot behavior control, thereby improving the flexibility and customization of patrol operations.

[0152] Point recording module: It integrates the video-based PTZ and camera parameter control, map-based navigation control and repeated area, interval, string, and device copy functions, preset position configuration based on a six-level point tree, and real-time information display. It mainly completes core business functions such as navigation control, robot control, point association and configuration, and establishes stop point models, preset position models, point association model configuration, and template capture. Through the strong visual interaction effect of video and map, it accelerates the model building and template capture process.

[0153] Task management module: supports the creation of tasks of different task types and execution methods through the linkage selection of map stops and associated point trees, providing an intuitive and convenient task management interface for operation and maintenance personnel.

[0154] Task Monitoring Module: It monitors the task execution status in real time, instantaneously feedbacks the inspection results, ensures that the operation and maintenance personnel can respond quickly and handle abnormal situations effectively, significantly shortens the response time, and improves the overall work efficiency and emergency handling ability.

[0155] Data Export Module: It fully supports the export of electronic map files such as topological matrices, SVG maps, and connection relationships of docking points. At the same time, it supports customized synchronization with the superior system, facilitating data sharing and analysis.

[0156] Remote Operation and Maintenance Module: It integrates the debugging and configuration of software and hardware functional modules, covers key areas such as the new ontology control system and power management, supports remote parameter configuration, real-time log acquisition, and online program upgrade, provides a one-stop solution for remote operation and maintenance, and ensures the stable operation and continuous optimization of the system.

[0157] An inspection model debugging and configuration system provided in this embodiment uses an advanced B / S (browser / server) architecture and microservice design concept. Through innovative debugging mode to reconstruct the on-site configuration link and modular data design, it realizes the configuration and debugging process of the full life cycle of the inspection robot. At the same time, it integrates debugging quality and debugging status evaluation methods, map base and electronic map calculation methods.

[0158] It should be noted here that each module in this embodiment corresponds to each step in Embodiment 1 one by one, and its specific implementation process is the same, so it will not be repeated here.

[0159] Embodiment 3

[0160] This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, it realizes the steps in an inspection model debugging and configuration method as described in Embodiment 1 above.

[0161] Embodiment 4

[0162] This embodiment provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it realizes the steps in an inspection model debugging and configuration method as described in Embodiment 1 above.

[0163] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing relevant hardware through a computer program. The program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above-mentioned method embodiments. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM), etc.

[0164] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A patrol inspection model debugging configuration method, characterized in that: include: Control the robot to scan and map with laser to obtain the navigation map model; Generate regional information based on the navigation map model and associate it with the substation to obtain a scenario model; Obtaining the target equipment points associated with the substation and obtaining a point model; Create a robot, configure basic information and bind the scene model to obtain the robot model; Draw autonomous patrol routes, stop points, functional areas, operating areas and patrol equipment areas in the navigation map to obtain an electronic map model; Send an autonomous patrol path. When the robot moves along the autonomous patrol path, control the robot to navigate to the stop point. After obtaining the stop point model, adjust the gimbal to the optimal observation angle and adjust the camera parameters to obtain the preset position model. Associate the stop point model, the preset position model and the target device point, optimize the autonomous patrol path based on the stop point, update the electronic map topology, and add the electronic map model. The navigation map model, scene model, point model, robot model, electronic map model, stop point model and preset position model are combined as an inspection model, so that the robot can perform substation inspection based on the inspection model.

2. A patrol inspection model debugging configuration method as claimed in claim 1, characterized in that: The inspection model also includes an alarm model, a result display model and a three-association model; the alarm model, the result display model and the three-association model respectively store the alarm information associated with the target equipment point, the result display template and the three-association relationship.

3. A patrol inspection model debugging configuration method as claimed in claim 1, characterized in that: The stopping points and preset positions are automatically generated or manually adjusted by remote control when the robot moves along the autonomous line patrol path.

4. A patrol inspection model debugging configuration method as claimed in claim 1, characterized in that: The stop points and preset positions of the repeated space are generated by using a replication algorithm, and the steps of the replication algorithm include: Select the space to be copied and the space to be repeated in the electronic map. The target devices in the copied space and the repeated space are the same, and the target device point distribution is consistent. The stop point model and the preset position model of the target device point in the copied space are known, and the stop point model and the preset position model of the target device point in the repeated space are unknown. A stop point is selected in the duplication space as a reference point, and the robot is controlled to move to the reference point, and the position of the reference point in the duplication space is consistent with the position of the reference point in the duplication space; The coordinate offset and angle offset between the base point and the reference point are calculated, and based on the coordinate offset and angle offset, the docking point model and the preset position model in the copy space are copied to the duplicate space.

5. A patrol inspection model debugging configuration method as claimed in claim 4, characterized in that: Also includes: In the process of drawing the autonomous line patrol path, the intersecting path splitting is performed, and the step of the intersecting path splitting includes: obtaining a newly added line segment; judging whether the newly added line segment intersects with the existing line segment; if so, obtaining the intersection point, and taking the line intersecting with the newly added line segment as an intersecting line, judging whether the intersection point is the endpoint of the intersecting line; if not, splitting the intersecting line into two line segments at the intersection point; if it is an endpoint, judging whether the intersection point is the endpoint of the newly added line segment, and if not, splitting the newly added line segment into two line segments at the intersection point.

6. A patrol model debugging configuration system, characterized in that: include: A map management module is configured to: control the robot to perform laser scanning and map building to obtain a navigation map model; A scenario management module is configured to: generate regional information based on a navigation map model and associate it with a substation to obtain a scenario model; A point management module is configured to: obtain the target equipment point associated with the substation and obtain a point model; The robot management module is configured to: create a robot, configure basic information and bind the scene model to obtain a robot model; A map editing module is configured to: draw autonomous patrol routes, stop points, functional areas, equipment areas, and patrol equipment areas in a navigation map to obtain an electronic map model; The point recording module is configured to: send an autonomous patrol path, control the robot to navigate to a stop point while the robot is moving along the autonomous patrol path, obtain a stop point model, adjust the pan / tilt to an optimal observation angle, and adjust the camera parameters to obtain a preset position model, associate the stop point model, the preset position model, and the target device point, optimize the autonomous patrol path based on the stop point, update the electronic map topology, and add the electronic map model; The task management module is configured to combine the navigation map model, the scene model, the point model, the robot model, the electronic map model, the stop point model and the preset position model as an inspection model so that the robot can inspect the substation based on the inspection model.

7. The inspection model debugging configuration system according to claim 6, characterized in that: The stop points and preset positions of the repeated space are generated by using a replication algorithm, and the steps of the replication algorithm include: Select the space to be copied and the space to be repeated in the electronic map. The target devices in the copied space and the repeated space are the same, and the target device point distribution is consistent. The stop point model and the preset position model of the target device point in the copied space are known, and the stop point model and the preset position model of the target device point in the repeated space are unknown. A stop point is selected in the duplication space as a reference point, and the robot is controlled to move to the reference point, and the position of the reference point in the duplication space is consistent with the position of the reference point in the duplication space; The coordinate offset and angle offset between the base point and the reference point are calculated, and based on the coordinate offset and angle offset, the docking point model and the preset position model in the copy space are copied to the duplicate space.

8. The inspection model debugging configuration system according to claim 6, characterized in that: The map editing module is further configured to: split the intersecting paths during the drawing process of the autonomous patrol path, and the step of splitting the intersecting paths includes: obtaining a newly added line segment; determining whether the newly added line segment intersects with the existing line segment; if so, obtaining the intersection point, and taking the line intersecting with the newly added line segment as an intersecting line, and determining whether the intersection point is the endpoint of the intersecting line; if not, splitting the intersecting line into two line segments at the intersection point; if it is an endpoint, determining whether the intersection point is the endpoint of the newly added line segment, and if not, splitting the newly added line segment into two line segments at the intersection point.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps in the inspection model debugging configuration method as described in any one of claims 1 to 5 are implemented.

10. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps in the inspection model debugging configuration method as described in any one of claims 1-5 are implemented.

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