Method for managing and controlling autonomous flight path of low-altitude unmanned aerial vehicle in transformer substation

Abstract

The invention discloses a method for managing and controlling the autonomous flight path of a low-altitude unmanned aerial vehicle in a transformer substation, and relates to the technical field of power system automatic inspection, and the method comprises the steps: obtaining a real-time space coordinate system constructed by at least three transformer substation positioning devices, and carrying out the fusion operation of the real-time space coordinate system and a pre-established transformer substation three-dimensional coordinate system, obtaining flight coordinate data of the unmanned aerial vehicle; unmanned aerial vehicle flight nodes are generated based on the flight coordinate data, and a connection relation between the flight nodes is determined according to a preset path planning rule; and in the process that the unmanned aerial vehicle flies according to the flight node, acquiring the position data of the unmanned aerial vehicle according to a preset frequency, performing spatial position measurement and correction when the unmanned aerial vehicle arrives at the preset flight node, and filtering abnormal data according to a preset rule. Through multi-point positioning, real-time data updating, position correction, path planning optimization and a multi-stage data filtering mechanism, the inspection efficiency and safety of the unmanned aerial vehicle in the transformer substation are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of automated inspection of electric power systems, and in particular to a method for autonomous flight path control of low-altitude unmanned aerial vehicles in a substation. Background Art

[0002] The inspection of hidden dangers of equipment in substations mainly relies on ground inspections by staff or robots. However, due to the high voltage level and high equipment installation height of high-voltage substations, the top of operating equipment, medium and high-rise structures, lightning rods, etc. cannot be inspected on the ground at all. There have been many power outages in the system due to the rust and breakage of structural supports or the failure to discover defects on the top of the equipment in time, which led to the expansion of power outages. Therefore, it is necessary to transform and upgrade the drone inspection technology so that it can realize one-click drone inspections according to the preset planned path, solve the common problem of the inability to inspect low-altitude equipment in substations, and make it have good technical foresight and promotion and application value.

[0003] In the power system, the inspection of substation equipment is an important part of ensuring the safe and stable operation of the power grid. Traditional substation inspections mainly rely on manual or ground robots, but these methods have many limitations. Manual inspections are not only labor-intensive and inefficient, but also difficult to conduct comprehensive inspections of high-altitude equipment in high-voltage substations. In recent years, with the rapid development of drone technology, the application of drones in substation inspections has gradually increased. Drone inspections can effectively cover various areas within the substation and improve inspection efficiency and safety. However, the existing drone inspection technology still has some shortcomings. Most drone inspections rely on pilot control or can only fly in the outer area of ​​the substation, and cannot go deep into the equipment-intensive area for detailed inspections. In addition, due to the complex internal environment of the substation and strong electromagnetic interference, the existing drone positioning and path planning technology is difficult to achieve high-precision autonomous flight, resulting in unsatisfactory inspection results.

[0004] Existing drone inspection technology mainly faces the following problems: 1. Traditional GPS positioning is difficult to provide high-precision location information indoors or in obstructed environments, and single sensor positioning is easily affected by environmental factors, resulting in accumulated positioning errors. 2. Existing path planning methods usually lack a real-time position correction mechanism, which makes it easy for drones to deviate from the preset path when performing tasks, affecting inspection efficiency and safety. 3. Existing technologies are difficult to cope with complex substation environments, such as electromagnetic interference and equipment-intensive areas in high-voltage substations, making it difficult for drones to achieve efficient and accurate autonomous flight during actual inspections. Summary of the invention

[0005] In view of the above-mentioned problems, the present invention is proposed.

[0006] Therefore, the present invention provides a method for autonomous flight path control of low-altitude UAVs in substations, which can solve the problems mentioned in the background technology.

[0007] To solve the above technical problems, the present invention provides the following technical solutions: a method for autonomous flight path control of low-altitude UAVs in a substation, comprising: obtaining a real-time spatial coordinate system constructed by at least three substation positioning devices, fusing the real-time spatial coordinate system with a pre-established substation three-dimensional coordinate system to obtain flight coordinate data of the UAV; generating UAV flight nodes based on the flight coordinate data, and determining the connection relationship between the flight nodes according to preset path planning rules; collecting UAV position data at a preset frequency during the flight of the UAV according to the flight nodes, performing spatial position measurement and correction when the UAV reaches the preset flight node, and filtering abnormal data according to preset rules.

[0008] As a preferred solution of the method for autonomous flight path control of low-altitude UAVs in substations described in the present invention, the calculation process of the flight coordinate data includes the following steps: at least three positioning devices are set in the substation as signal sources; the spatial position data of the UAV is obtained through real-time communication between the positioning device and the sensor carried by the UAV; the spatial position data is integrated with the pre-established substation three-dimensional coordinate system to obtain the flight coordinate data of the UAV.

[0009] As a preferred solution of the method for autonomous flight path control of low-altitude UAVs in substations described in the present invention, the spatial position data is fused with a pre-established substation three-dimensional coordinate system, including the following steps: the three-dimensional coordinates of the UAV in the micro-radar coordinate system are calculated according to the real-time communication data between the sensors carried by the UAV and multiple micro-radars in the substation; the three-dimensional coordinates under the micro-radar coordinate system are converted into coordinates under the substation site cloud three-dimensional coordinate system, and the flight coordinates of the UAV in the substation site cloud three-dimensional coordinate system are obtained after the coordinate transformation is performed by corresponding to the position of the known micro-radar coordinate system points in the substation site cloud three-dimensional coordinate system and the micro-radar coordinate system coordinate value of the target device; if the flight coordinates of the UAV in the substation site cloud three-dimensional coordinate system deviate from the coordinates on the preset planned path, the position correction program is started, and positioning measurement and correction are performed through the hovering point set in the path planning; if the deviation exceeds the preset threshold, the UAV is adjusted to the nearest hovering point and the flight coordinates are recalculated until the deviation is within the allowable range, and the next path flight is continued.

[0010] As a preferred solution of the method for autonomous flight path control of low-altitude UAVs in substations described in the present invention, the flight node includes position coordinate information and motion control information.

[0011] As a preferred solution of the method for autonomous flight path control of low-altitude UAVs in substations described in the present invention, wherein: UAV flight nodes are generated based on the flight coordinate data, and the connection relationship between the flight nodes is determined according to the preset path planning rules, including the following steps: based on the flight coordinate data, node information is selected in the three-dimensional model of the substation, and the node information is stored in the database; the nodes include take-off points, inspection points, travel points and landing points; according to the preset path planning rules, the connection relationship between the flight nodes is determined to form a preliminary flight path of the UAV; if multiple devices are on the same y-axis, the devices on the same y-axis are inspected first, and then other devices are inspected in turn according to the distance on the x-axis, and an intermediate point is generated between each two nodes for adjustment and correction; if there are obstacles or non-flyable areas in the preliminary flight path, the detour path is recalculated based on the three-dimensional model of the substation, by adding new detour nodes or adjusting the positions of existing nodes.

[0012] As a preferred solution of the method for autonomous flight path control of low-altitude UAVs in substations described in the present invention, wherein: when the UAV flies according to the flight nodes, the UAV position data is collected according to a preset frequency, and when the UAV reaches the preset flight node, the spatial position is measured and corrected, and abnormal data is filtered according to preset rules, including the following steps: when the UAV flies according to the flight nodes, the UAV position data is collected according to a preset frequency, and the position data is transmitted to a ground control station in real time; when the UAV reaches the preset flight node, the spatial position is measured by a micro radar and other sensors, and the position of the UAV is corrected according to the measurement results; if there is a deviation between the measurement result and the preset flight node coordinates, the position correction program is started to ensure that the UAV accurately reaches the preset position by adjusting the posture and speed of the UAV; and the abnormal data is filtered according to the preset rules.

[0013] As a preferred solution of the method for autonomous flight path control of low-altitude UAVs in substations described in the present invention, the preset rules are as follows: if the data change value exceeds 50%, it is regarded as invalid data and is eliminated; at the same time, if the data change value exceeds the threshold for multiple consecutive times, the emergency shutdown procedure is triggered to ensure the safety of the UAV.

[0014] In order to further solve the above technical problems, the present invention provides the following technical solutions: a system for autonomous flight path control of low-altitude UAVs in substations, comprising:

[0015] A computer device includes a memory and a processor, wherein the memory stores a computer program, and is characterized in that when the processor executes the computer program, the steps of the method for autonomous flight path control of low-altitude drones in a substation are implemented as described above.

[0016] A computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of the method for autonomous flight path control of a low-altitude UAV in a substation as described above are implemented.

[0017] Beneficial effects of the present invention: The present invention constructs a real-time spatial coordinate system by setting at least three micro-radar positioning devices, and fuses the coordinate system with the pre-established substation cloud stereo coordinate system to obtain the flight coordinate data of the drone. This method not only improves the positioning accuracy, but also performs position correction by presetting the hovering point, effectively reduces the cumulative error of the flight path, and improves the reliability and safety of the inspection task. The present invention generates drone flight nodes based on flight coordinate data, and determines the connection relationship between flight nodes according to preset path planning rules. Through the Dijkstra algorithm or the A* algorithm, a preliminary flight path is formed, and dynamic path adjustment is performed when encountering obstacles, ensuring the feasibility and safety of the path. In the process of the drone flying according to the flight node, the present invention collects the position data of the drone according to the preset frequency, and performs spatial position measurement and correction when arriving at the preset flight node. Abnormal data is filtered by preset rules. If the data change value exceeds 50%, it is regarded as invalid data and is eliminated; if the data change value exceeds the threshold for multiple consecutive times, the emergency shutdown program is triggered to ensure the safety of the drone. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use 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 ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0019] Figure 1 This is a schematic diagram of the overall process of a method for autonomous flight path control of low-altitude UAVs in a substation proposed by the present invention;

[0020] Figure 2 A diagram of computer equipment in a method for autonomous flight path control of a low-altitude UAV in a substation proposed by the present invention. DETAILED DESCRIPTION

[0021] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0022] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0023] Example 1, reference Figure 1 , as an embodiment of the present invention, provides a method for autonomous flight path control of low-altitude UAVs in a substation.

[0024] S1: Obtain a real-time spatial coordinate system constructed by at least three substation positioning devices, fuse the real-time spatial coordinate system with a pre-established substation three-dimensional coordinate system, and obtain the flight coordinate data of the UAV.

[0025] S1.1: At least three positioning devices are installed in the substation as signal sources.

[0026] It should be noted that in a substation environment, by setting up at least three positioning devices (such as micro radars) as signal sources, the spatial position of the drone can be accurately determined. These positioning devices provide multi-point references and use the principle of triangulation to improve positioning accuracy and stability. The use of multiple positioning devices significantly improves the accuracy of drone positioning and reduces the errors that may be caused by a single signal source. Even if a positioning device fails, other devices can still ensure the normal operation of the system, enhancing the robustness and reliability of the overall system.

[0027] S1.2: Obtain the spatial position data of the drone through real-time communication between the positioning device and the sensors carried by the drone.

[0028] It should be noted that through real-time communication technology, the positioning device and the sensors on the drone can continuously exchange data, ensuring the real-time update of the drone's location information. This real-time communication mechanism is crucial for accurate positioning in dynamic environments, especially in complex and potentially interfering environments such as substations.

[0029] S1.3: The spatial position data is integrated with the pre-established substation three-dimensional coordinate system to obtain the flight coordinate data of the UAV.

[0030] It should be noted that by converting the position data of the drone in the micro-radar coordinate system into the flight coordinates in the substation cloud stereo coordinate system and making necessary position corrections, step S1.3 ensures that the drone can accurately fly autonomously in the substation. This process not only improves the accuracy of drone positioning, but also effectively reduces the cumulative error of the flight path through the preset hovering point and position correction mechanism, thereby improving the reliability and safety of the inspection task.

[0031] S1.3.1: Based on the real-time communication data between the sensors carried by the drone and multiple micro radars (at least 3) in the substation, calculate the three-dimensional coordinates of the drone in the micro radar coordinate system.

[0032] S1.3.2: Convert the 3D coordinates in the micro-radar coordinate system into the coordinates in the substation cloud 3D coordinate system. By using the known micro-radar coordinate system point (0,0,1) corresponding to the position (15.21,13.41,0) in the substation cloud 3D coordinate system, and the micro-radar coordinate system coordinate value of the target device, execute the coordinate transformation formula X'=X+15.21, Y'=Y+13.41, Z'=Z-1 to obtain the flight coordinates of the drone in the substation cloud 3D coordinate system.

[0033] S1.3.3: If there is a deviation between the flight coordinates of the UAV in the cloud stereo coordinate system of the substation and the coordinates on the preset planned path, the position correction program is started, and positioning measurement and correction are performed through the hovering points set in the path planning; if the deviation exceeds the preset threshold, the UAV is adjusted to the nearest hovering point and the flight coordinates are recalculated until the deviation is within the allowable range, and the next path flight is continued.

[0034] It should be noted that in the prior art, the positioning accuracy and path control of drones in complex environments are often limited, especially in environments such as substations where electromagnetic interference is strong and the spatial layout is complex. Traditional positioning methods such as GPS are difficult to provide high-precision location information indoors or in obstructed environments, and single sensor positioning is easily affected by environmental factors, resulting in accumulated positioning errors. In addition, existing path planning methods usually lack a real-time position correction mechanism, which makes it easy for drones to deviate from the preset path when performing tasks, affecting inspection efficiency and safety.

[0035] The spatial position accuracy of the UAV can be significantly improved by constructing a real-time spatial coordinate system through multiple micro-radar positioning devices in step S1, and fusing the coordinate system with the pre-established substation stereo coordinate system. In step S1.1, at least three positioning devices are set as signal sources, and the positioning accuracy is improved by using the principle of triangulation; in step S1.2, the spatial position data of the UAV is obtained through real-time communication, ensuring the instant update of the data and avoiding the accumulation of errors caused by delays; in step S1.3, the coordinates in the micro-radar coordinate system are converted into the coordinates in the substation cloud stereo coordinate system through the coordinate transformation formula, unifying the coordinate reference frame and simplifying the subsequent processing process. In step S1.3.3, the position is corrected by presetting the hovering point, which effectively reduces the cumulative error of the flight path and ensures that the UAV can fly accurately according to the preset path. Compared with the existing technology, the S1 step significantly improves the positioning accuracy of the UAV in the substation, and solves the problem of inaccurate positioning of the traditional method in complex environments; the introduction of hovering points for position correction ensures that the UAV can adjust the flight path in time, avoids the accumulation of deviations caused by external interference, and improves the reliability and safety of the inspection task; through the coordinate transformation formula, the position data in different coordinate systems are unified, the path planning and position correction process are simplified, and the overall performance of the system is improved; the use of multiple positioning devices enhances the robustness of the system. Even if a device fails, other devices can still ensure the normal operation of the system, improving the stability and reliability of the system. These improvements are not only innovative in technology, but also show significant advantages in practical applications, which are functions that cannot be achieved by simple combinations of existing technologies.

[0036] S2: Generate UAV flight nodes based on flight coordinate data, and determine the connection relationship between flight nodes according to preset path planning rules. The flight nodes include position coordinate information and action control information.

[0037] S2.1: Based on the flight coordinate data, the take-off point, inspection point, travel point and landing point are selected in the three-dimensional model of the substation, and the information of these nodes is stored in the database.

[0038] Specifically, this step uses the flight coordinate data obtained in step S1 to select the take-off point, inspection point, travel point and landing point in the pre-built three-dimensional model of the substation. These nodes include position coordinate information (X, Y, Z), and these node information is stored in the database to provide a basis for subsequent path planning.

[0039] S2.2: According to the preset path planning rules, use the algorithm to determine the connection relationship between the flight nodes to form the preliminary flight path of the drone; if multiple devices are on the same y-axis, first inspect the devices on the same y-axis, then inspect other devices in turn according to the distance on the x-axis, and generate an intermediate point between every two nodes for adjustment and correction.

[0040] Specifically, this step uses an algorithm (such as Dijkstra algorithm or A* algorithm) based on a preset path planning rule to determine the connection relationship between flight nodes and form a preliminary flight path for the UAV.

[0041] If multiple devices are on the same y-axis, first inspect the devices on the same y-axis, and then inspect other devices in turn according to the distance on the x-axis. In order to ensure the smoothness and controllability of the path, an intermediate point is generated between every two nodes for the adjustment and correction of the drone.

[0042] S2.3: If there are obstacles or non-flyable areas in the preliminary flight path, the detour path is recalculated based on the three-dimensional model of the substation, and the feasibility and safety of the final flight path are ensured by adding new detour nodes or adjusting the positions of existing nodes.

[0043] Specifically, this step enhances the robustness of path planning by introducing conditional judgment. If obstacles or non-flyable areas are detected in the preliminary flight path, the system will recalculate the detour path based on the 3D model of the substation. The system will identify all possible detour paths based on the 3D model of the substation and ensure the feasibility and safety of the final flight path by adding new detour nodes or adjusting the positions of existing nodes. This dynamic path adjustment mechanism can effectively respond to various emergencies in complex environments.

[0044] Preferably, step S2 realizes efficient path planning and dynamic path adjustment by combining the three-dimensional model of the substation and real-time flight coordinate data. This method not only improves the efficiency and safety of drone inspections, but also solves the problem that traditional path planning methods are difficult to cope with complex environments and emergencies. By generating intermediate points for adjustment and correction, the smoothness and controllability of the flight path are ensured; and the dynamic path adjustment mechanism based on the three-dimensional model further enhances the robustness and adaptability of the system. These improvement measures have significantly improved the reliability and efficiency of drone inspection tasks in actual application scenarios, providing solid technical support for the automated inspection of substations.

[0045] S3: When the UAV is flying according to the flight node, the UAV position data is collected according to the preset frequency. When the UAV reaches the preset flight node, the spatial position is measured and corrected, and abnormal data is filtered according to the preset rules.

[0046] S3.1: When the UAV is flying according to the flight node, the position data of the UAV is collected at a preset frequency (such as 5 Hz), and the position data is transmitted to the ground control station in real time.

[0047] It should be noted that this step continuously collects the position data of the UAV at a preset frequency (such as 5Hz) and transmits this data to the ground control station in real time. This high-frequency collection method can capture the dynamic changes of the UAV in a timely manner and provide accurate data support for subsequent spatial position measurement and correction. Real-time transmission to the ground control station can realize remote monitoring and management, and improve the response speed and operation efficiency of the system.

[0048] S3.2: When the UAV reaches the preset flight node, the spatial position is measured through micro radar and other sensors, and the position of the UAV is corrected according to the measurement results; if there is a deviation between the measurement results and the preset flight node coordinates, the position correction program is started to adjust the attitude and speed of the UAV to ensure that it accurately reaches the preset position.

[0049] It should be noted that this step uses micro radar and other sensors to perform precise spatial position measurement when the drone reaches the preset flight node. By comparing with the pre-set flight node coordinates, if there is a deviation, the position correction program is started. Specifically, the system will adjust the attitude (such as pitch, roll, yaw angle) and speed of the drone according to the measurement results to ensure that the drone can accurately reach the preset position. This periodic correction mechanism reduces cumulative errors and improves the accuracy of the overall path. For example, during the inspection of a 500kv substation, when the drone arrives at a certain equipment inspection point, precise measurements are performed through the micro radar to ensure that the drone can accurately hover at the predetermined position, thereby improving the accuracy and reliability of the inspection.

[0050] S3.3: Filter abnormal data according to preset rules. If the data change value exceeds 50%, it will be regarded as invalid data and eliminated. At the same time, if the data change value exceeds the threshold for multiple consecutive times, the emergency shutdown procedure will be triggered to ensure the safety of the drone.

[0051] It should be noted that this step filters the collected location data through preset rules. Specifically, if the data change value between two adjacent collections exceeds 50% (that is, the data change is significant), it is considered to be abnormal data and is eliminated, and does not participate in the guidance of the flight path and position correction. In addition, if the data change value exceeds the threshold for multiple consecutive times, the emergency shutdown procedure is triggered to prevent the risk of flight loss of control due to data anomalies. This double filtering mechanism effectively eliminates abnormal data caused by sensor failure, external interference and other factors, and ensures the reliability and consistency of the data. For example, when the drone encounters strong winds or other external interference during flight, the system can quickly identify and eliminate abnormal data to ensure the safe operation of the drone.

[0052] In summary, the present invention significantly improves the positioning accuracy of the UAV in the substation through multi-point reference and real-time data update, and solves the problem of inaccurate positioning of the traditional method in a complex environment. The present invention introduces a hovering point for position correction, ensures that the UAV can adjust the flight path in time, avoids the accumulation of deviations caused by external interference, and improves the reliability and safety of the inspection task. The present invention combines the Dijkstra algorithm and the A* algorithm to not only form an efficient preliminary flight path, but also dynamically adjust the path when encountering obstacles, ensuring the feasibility and safety of the path. This multi-level path planning mechanism solves the problem that path planning is inflexible and difficult to deal with sudden obstacles in the prior art. The present invention effectively eliminates abnormal data caused by factors such as sensor failure and external interference through a multi-level data filtering mechanism, and enhances the robustness and safety of the system. In particular, through preset rules and multi-level filtering mechanisms, the continuity and reliability of data are ensured, and the risk of flight out of control due to data anomalies is prevented.

[0053] Embodiment 2 is an embodiment of the present invention, which provides a system for autonomous flight path control of low-altitude drones in a substation, including:

[0054] An acquisition module is used to acquire the real-time spatial coordinate system constructed by at least three substation positioning devices, and fuse the real-time spatial coordinate system with the pre-established substation three-dimensional coordinate system to obtain the flight coordinate data of the UAV;

[0055] A generation module generates UAV flight nodes based on the flight coordinate data and determines the connection relationship between the flight nodes according to the preset path planning rules;

[0056] The correction module is used to collect the drone's position data at a preset frequency while the drone is flying according to the flight nodes, perform spatial position measurement and correction when the drone reaches the preset flight nodes, and filter abnormal data according to preset rules.

[0057] Example 3, reference Figure 2, is an embodiment of the present invention, which is different from the previous embodiment in that: if the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0058] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0059] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0060] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0061] Example 4 is an embodiment of the present invention, which provides a method for autonomous flight path control of low-altitude UAVs in substations. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0062] There are three key points for autonomous flight of low-altitude drones in substations: 1. Coordinate system conversion; 2. Path planning; 3. Position correction.

[0063] First, the coordinate system is converted.

[0064] The substation uses multiple micro radars as signal sources, and communicates with multiple (at least 3) micro radars in real time through the sensors carried by the drone body, and calculates the three-dimensional coordinates (i.e. the spatial position of the drone) through an algorithm; the substation conducts a full-station lidar scan in advance, constructs a full-station model, and generates a substation site cloud three-dimensional coordinate system.

[0065] There are multiple (e.g. 12, A0-A11) micro radars in the substation, with A0 as the dot (0, 0, 1; 1 is the micro radar installation height of 1 meter). The dot (0, 0, 0) in the substation cloud stereo coordinate system is measured and characterized as (15.21, 13.41, 0) in the micro radar coordinate system.

[0066] The patrol point coordinates of the patrol object device 1 are selected from the system as (25.21, 26.41, 8), the two sets of coordinate systems are merged, and the output flight path planning point coordinates are (40.42, 39.82, 7), which are pushed to the drone.

[0067] X coordinate 40.42 = 15.21 + 25.21;

[0068] Y coordinate 39.82 = 13.41 + 26.41;

[0069] Z coordinate 7=8-1.

[0070] Second, path planning.

[0071] 1. Algorithm planning premise. The take-off point, inspection point, travel point, and landing point are selected in advance on the model (each inspection channel has a pre-set take-off point and landing point, and the positions of the take-off point and landing point are on the same x-axis or y-axis as the inspection point in the channel) and these data are stored in the database; at the same time, the system binds the equipment to the inspection point.

[0072] 2. Web-based operation process. (1) Enter the autonomous flight path planning function, add a task, fill in the inspection task name, select the inspection equipment, drone, operator and other information. (2) Start the flight and start monitoring the real-time coordinates of the drone. You can view the real-time position, coordinates, altitude and other information of the drone on the home page or real-time monitoring page.

[0073] Path planning process (taking 500kv as an example)

[0074] (1) Multiple devices are on the same y-axis.

[0075] Confirmation of take-off point: The two devices selected in the above figure are on the same y-axis, and the corresponding inspection point coordinates are (-41.63, -84.79, 7) and (-63.98, -84.79, 7). In the 500kv main area, the y-coordinate of the take-off point is the same as the inspection point, so the take-off point is determined to be (63.7, -84.79, 3).

[0076] The inspection order is determined as follows: the equipment on the same y-axis as the take-off point is inspected first. If there are equipment on a different y-axis, the equipment on the same y-axis is inspected first, and then other equipment is inspected in sequence according to the distance along the x-axis. In the figure above, (-41.63, -84.79, 7) is inspected first, and then (-63.98, -84.79, 7) is inspected.

[0077] Intermediate point generation: If the distance between the current point and the inspection point or the travel point exceeds 10 meters, an intermediate point is generated every 10 meters for the adjustment and correction of the drone. In this example, several intermediate points are generated from the take-off point to the first inspection point, such as: (53.7, -84.79, 3), (53.7, -84.79, 3), (53.7, -84.79, 3)...

[0078] Landing point confirmation: After the last inspection point is inspected, the nearest crossing point is selected. After the crossing is completed, the corresponding landing point is selected according to the crossing end point. In this example, the crossing starting point is (-72.93, -84.79, 7) and the crossing end point is (-72.93, -91.44, 7).

[0079] Landing point (63.7, -91.44, 3).

[0080] Detailed path confirmation: Based on the above steps, the detailed path is:

[0081] Step 1: (63.70, -84.79, 3.00)

[0082] Step 2: (53.70, -84.79, 3.00)

[0083] Step 3: (43.70, -84.79, 3.00)

[0084] Step 4: (33.70, -84.79, 3.00)

[0085] Step 5: (23.70, -84.79, 3.00)

[0086] Step 6: (13.70, -84.79, 3.00)

[0087] Step 7: (3.70, -84.79, 3.00)

[0088] Step 8: (-6.30, -84.79, 3.00)

[0089] Step 9: (-16.30, -84.79, 3.00)

[0090] Step 10: (-26.30, -84.79, 3.00)

[0091] Step 11: (-36.30, -84.79, 3.00)

[0092] Step 12: (-41.63, -84.79, 7.00)

[0093] Step 13: (-51.63, -84.79, 7.00)

[0094] Step 14: (-61.63, -84.79, 7.00)

[0095] Step 15: (-63.98, -84.79, 7.00)

[0096] Step 16: (-72.93, -84.79, 7.00)

[0097] Step 17: (-72.93, -84.79, 7.00)

[0098] Step 18: (-72.93, -91.44, 7.00)

[0099] Step 19: (-62.93, -91.44, 7.00)

[0100] Step 20: (-52.93, -91.44, 7.00)

[0101] Step 21: (-42.93, -91.44, 7.00)

[0102] Step 22: (-32.93, -91.44, 7.00)

[0103] Step 23: (-22.93, -91.44, 7.00)

[0104] Step 24: (-12.93, -91.44, 7.00)

[0105] Step 25: (-2.93, -91.44, 7.00)

[0106] Step 26: (7.07, -91.44, 7.00)

[0107] Step 27: (17.07, -91.44, 7.00)

[0108] Step 28: (27.07, -91.44, 7.00)

[0109] Step 29: (37.07, -91.44, 7.00)

[0110] Step 30: (47.07, -91.44, 7.00)

[0111] Step 31: (57.07, -91.44, 7.00)

[0112] Step 32: (63.70, -91.44, 3.00)

[0113] Instruction generation: The currently designed instruction format is x1, y1, z1, x2, y2, z2, action code; the action code is: 0-none, 1-photograph, 2-hover, 90: rotate 90 degrees clockwise, 180: rotate 180 degrees clockwise, 270: rotate 270 degrees clockwise.

[0114] Generate corresponding instructions based on the path in the previous step. If the height of the current point is different from that of the next point, the height needs to be adjusted. If the current point is an inspection target, the angle needs to be rotated. According to the above rules, the generated instructions are as follows:

[0115] 63.7,-84.79,3.0,53.7,-84.79,3.0,0; 53.7,-84.79,3.0,43.7,-84.79,3.0,0; 43.7,-

[0116] 84.79,3.0,33.7,-84.79,3.0,0；33.7,-84.79,3.0,23.700000000000003,-

[0117] 84.79,3.0,0；23.700000000000003,-84.79,3.0,13.700000000000003,-

[0118] 84.79,3.0,0；13.700000000000003,-84.79,3.0,3.700000000000003,-

[0119] 84.79,3.0,0；3.700000000000003,-84.79,3.0,-6.299999999999997,-84.79,3.0,0；-

[0120] 6.299999999999997,-84.79,3.0,-16.299999999999997,-84.79,3.0,0；-

[0121] 16.299999999999997,-84.79,3.0,-26.299999999999997,-84.79,3.0,0；-

[0122] 26.299999999999997,-84.79,3.0,-36.3,-84.79,3.0,0；-36.3,-84.79,3.0,-41.63,-

[0123] 84.79,3.0,0；-41.63,-84.79,3.0,-41.63,-84.79,7.0,0；-41.63,-84.79,7.0,-41.63,-

[0124] 84.79,7.0,270；-41.63,-84.79,7.0,-41.63,-84.79,7.0,2；-41.63,-84.79,7.0,-41.63,-

[0125] 84.79,7.0,90；-41.63,-84.79,7.0,-51.63,-84.79,7.0,0；-51.63,-84.79,7.0,-61.63,-

[0126] 84.79,7.0,0；-61.63,-84.79,7.0,-63.98,-84.79,7.0,0；-63.98,-84.79,7.0,-63.98,-

[0127] 84.79,7.0,270；-63.98,-84.79,7.0,-63.98,-84.79,7.0,2；-63.98,-84.79,7.0,-63.98,-

[0128] 84.79,7.0,90；-63.98,-84.79,7.0,-72.93,-84.79,7.0,0；-72.93,-84.79,7.0,-72.93,-

[0129] 84.79,7.0,0；-72.93,-84.79,7.0,-72.93,-91.44,7.0,90；-72.93,-91.44,7.0,-

[0130] 62.93000000000001,-91.44,7.0,0；-62.93000000000001,-91.44,7.0,-

[0131] 52.93000000000001,-91.44,7.0,0；-52.93000000000001,-91.44,7.0,-

[0132] 42.93000000000001,-91.44,7.0,0；-42.93000000000001,-91.44,7.0,-

[0133] 32.93000000000001,-91.44,7.0,0；-32.93000000000001,-91.44,7.0,-

[0134] 22.930000000000007,-91.44,7.0,0；-22.930000000000007,-91.44,7.0,-

[0135] 12.930000000000007,-91.44,7.0,0；-12.930000000000007,-91.44,7.0,-

[0136] 2.930000000000007,-91.44,7.0,0；-2.930000000000007,-

[0137] 91.44,7.0,7.069999999999993,-91.44,7.0,0;7.069999999999993,-

[0138] 91.44,7.0,17.069999999999993,-91.44,7.0,0;17.069999999999993,-

[0139] 91.44,7.0,27.0699999999999993,-91.44,7.0,0;27.069999999999993,-

[0140] 91.44,7.0,37.069999999999999,-91.44,7.0,0;37.069999999999999,-

[0141] 91.44,7.0,47.069999999999999,-91.44,7.0,0;47.069999999999999,-

[0142] 91.44,7.0,57.06999999999999,-91.44,7.0,0;57.069999999999999,-91.44,7.0,63.7,-

[0143] 91.44,7.0,0;63.7,-91.44,7.0,63.7,-91.44,3.0,0;

[0144] (2) Multiple devices are not on the same y-axis.

[0145] Confirmation of take-off point: The two devices selected in the above figure are not on the same y-axis, and the corresponding inspection point coordinates are (58.35, -178.6, 6) and (58.35, -120.62, 6). In this case, the take-off point is set to the point with a larger y value to start the inspection, so the take-off point is set to (63.7, -120.6, 3).

[0146] Inspection order is determined: As in the above example, the equipment in the same row as the take-off point is inspected first. If there are equipment on different y-axis, the equipment on the same y-axis is inspected, and then other equipment is inspected in sequence according to the distance on the x-axis. In the above figure, (58.35, -120.62, 6) is inspected first, and then (58.35, -178.6, 6) is inspected.

[0147] Intermediate point generation: Same as the above example, if the distance between the current point and the inspection point or the travel point exceeds 10 meters, an intermediate point will be generated every 10 meters for the adjustment and correction of the drone.

[0148] Landing point confirmation: Same as the above example, after the last inspection point is inspected, the nearest travel point is selected. After the travel is completed, the corresponding landing point is selected according to the travel end point. In this example, the travel start point is (51.82, -178.6, 6), the travel end point is (51.82, -185.25, 6) and the landing point is (63.7, -185.25, 3).

[0149] Detailed path confirmation: Based on the above steps, the detailed path is:

[0150] Step 1: (63.70, -120.62, 3.00)

[0151] Step 2: (58.35, -120.62, 6.00)

[0152] Step 3: (51.82, -120.62, 6.00)

[0153] Step 4: (51.82, -178.60, 6.00)

[0154] Step 5: (58.35, -178.60, 6.00)

[0155] Step 6: (51.82, -178.60, 6.00)

[0156] Step 7: (51.82, -178.60, 6.00)

[0157] Step 8: (51.82, -185.25, 6.00)

[0158] Step 9: (61.82, -185.25, 6.00)

[0159] Step 10: (63.70, -185.25, 3.00)

[0160] Instruction generation: The rules are the same as the above example, and the generated content is as follows:

[0161] 63.7,-120.62,3.0,58.35,-120.62,3.0,0; 63.7,-120.62,3.0,58.35,-120.62,6.0,0; 58.35,-120.62,6.0,51.82,-120.62,6.0,90; 51.82,-120.62,6.0,51.82,-178.6,6.0,90; 51.82,-178.6,6.0,58.35,-178.6,6.0,0; 58.35,-178.6,6.0, 51.82,-178.6,6.0,0; 51.82,-178.6,6.0,51.82,-178.6,6.0,0; 51.82,-178.6,6.0,51.82,-185.25,6.0,90; 51.82,-185.25,6.0,61.82,-185.25,6.0,0; 61.82,-185.25,6.0,63.7,-185.25,6.0,0; 61.82,-185.25,6.0,63.7,-185.25,3.0,0.

[0162] Finally, position correction.

[0163] Before the drone flies, the flight speed, altitude and other requirements are set. During the actual flight of the drone, due to the slight differences in the drone's own mechanical parts and the instability of wind speed and direction during flight, the actual flight path and the planned path may deviate slightly, so the flight space position correction is required. A safe position correction method is used: "A number of three-dimensional hovering points are set in the path planning, and the hovering point positioning measurement and correction are achieved. After the correction is completed, the next path flight is executed, thereby reducing the cumulative error."

[0164] In addition, the flight speed of the drone (2 meters / 1 second) has been set, and the data refresh frequency during the flight is set to 5hZ. Therefore, the flight distance of the drone in 1 second (or 1hZ, i.e. 0.2 seconds to fly 0.4 meters) can be calculated to be 2 meters, which is the change value of the coordinate data. When the data change value exceeds 50%, the system defaults to filtering out invalid data and does not participate in guiding flight and position correction.

[0165] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for autonomous flight path control of low-altitude UAVs in substations, characterized in that: include: Acquire a real-time spatial coordinate system constructed by at least three substation positioning devices, and fuse the real-time spatial coordinate system with a pre-established substation stereoscopic coordinate system to obtain flight coordinate data of the UAV; Generate UAV flight nodes based on the flight coordinate data, and determine the connection relationship between the flight nodes according to a preset path planning rule; When the UAV flies according to the flight node, the UAV position data is collected according to the preset frequency. When the UAV reaches the preset flight node, the spatial position is measured and corrected, and abnormal data is filtered according to the preset rules.

2. The method for autonomous flight path control of low-altitude UAVs in substations according to claim 1, characterized in that: The calculation process of the flight coordinate data includes the following steps: At least three positioning devices are arranged in the substation as signal sources; Acquiring spatial position data of the drone through real-time communication between the positioning device and the sensor carried by the drone; The spatial position data is fused with the pre-established substation three-dimensional coordinate system to obtain the flight coordinate data of the UAV.

3. The method for autonomous flight path control of low-altitude UAVs in a substation as claimed in claim 2, characterized in that: The spatial position data is integrated with the pre-established substation three-dimensional coordinate system, including the following steps: Based on the real-time communication data between the sensors carried by the drone and multiple micro-radars in the substation, the three-dimensional coordinates of the drone in the micro-radar coordinate system are calculated; The three-dimensional coordinates in the micro-radar coordinate system are converted into the coordinates in the substation cloud three-dimensional coordinate system. The flight coordinates of the UAV in the substation cloud three-dimensional coordinate system are obtained after performing coordinate transformation based on the known position of the micro-radar coordinate system point corresponding to the substation cloud three-dimensional coordinate system and the micro-radar coordinate system coordinate value of the target device. If there is a deviation between the flight coordinates of the drone in the cloud stereo coordinate system of the substation and the coordinates on the preset planned path, the position correction program is started to perform positioning measurement and correction through the hovering point set in the path planning; if the deviation exceeds the preset threshold, the drone is adjusted to the nearest hovering point and the flight coordinates are recalculated until the deviation is within the allowable range, and the next path flight is continued.

4. The method for autonomous flight path control of low-altitude UAVs in a substation as claimed in claim 3, characterized in that: The flight node includes position coordinate information and action control information.

5. The method for autonomous flight path control of low-altitude UAVs in a substation as claimed in claim 4, characterized in that: Generating a UAV flight node based on the flight coordinate data and determining the connection relationship between the flight nodes according to a preset path planning rule comprises the following steps: Based on the flight coordinate data, node information is selected in the three-dimensional model of the substation, and the node information is stored in the database; the nodes include take-off points, inspection points, travel points and landing points; According to the preset path planning rules, the connection relationship between the flight nodes is determined to form the initial flight path of the drone; if multiple devices are on the same y-axis, the devices on the same y-axis are inspected first, and then other devices are inspected in turn according to the distance on the x-axis, and an intermediate point is generated between every two nodes for adjustment and correction; If there are obstacles or non-flyable areas in the preliminary flight path, the detour path is recalculated based on the three-dimensional model of the substation by adding new detour nodes or adjusting the positions of existing nodes.

6. The method for autonomous flight path control of low-altitude UAVs in a substation as claimed in claim 5, characterized in that: When the drone is flying according to the flight node, the drone position data is collected according to a preset frequency, and when the drone reaches the preset flight node, the spatial position is measured and corrected, and abnormal data is filtered according to preset rules, including the following steps: While the UAV is flying according to the flight nodes, the position data of the UAV is collected at a preset frequency, and the position data is transmitted to the ground control station in real time; When the drone reaches the preset flight node, the spatial position is measured through micro radar and other sensors, and the position of the drone is corrected according to the measurement results; if there is a deviation between the measurement result and the preset flight node coordinates, the position correction program is started to adjust the attitude and speed of the drone to ensure that it reaches the preset position accurately; Filter abnormal data according to preset rules.

7. The method for autonomous flight path control of low-altitude UAVs in a substation as claimed in claim 6, characterized in that: The preset rule is that if the data change value exceeds 50%, it is regarded as invalid data and is discarded; at the same time, if the data change value exceeds the threshold for multiple consecutive times, an emergency shutdown procedure is triggered to ensure the safety of the drone.

8. A system for autonomous flight path control of low-altitude UAVs in substations, based on the method for autonomous flight path control of low-altitude UAVs in substations according to any one of claims 1 to 7, characterized in that: include, An acquisition module is used to acquire a real-time spatial coordinate system constructed by at least three substation positioning devices, and fuse the real-time spatial coordinate system with a pre-established substation three-dimensional coordinate system to obtain flight coordinate data of the UAV; A generation module, which generates UAV flight nodes based on the flight coordinate data and determines the connection relationship between the flight nodes according to a preset path planning rule; The correction module is used to collect the drone position data at a preset frequency when the drone is flying according to the flight node, perform spatial position measurement and correction when the drone reaches the preset flight node, and filter abnormal data according to preset rules.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for autonomous flight path control of a low-altitude UAV in a substation described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for autonomous flight path control of a low-altitude UAV in a substation described in any one of claims 1 to 7 are implemented.

Images