DE102023113683A1 - Machine-assisted inspections of energy infrastructure - Google Patents

Abstract

The invention relates to a method for checking energy infrastructures (6) with an automated use of at least one drone (4), which comprises a first test track (10) and at least one further test track (20). Each test track (10, 20) has a starting position (11, 21) of the drone and at least one further position (12, 13, 14), (22, 23, 24) of the drone (4) in order to take at least one image of at least one object (40, 50) with a high-resolution camera. Each test track (10, 20) is predefined, each test track (10, 20) is precise and each test track (10, 20) is repeatable in time and/or place.

Description

The invention relates to a method for checking energy infrastructures with an automated mission of at least one drone, which comprises a first predefined test track and at least one further predefined test track, wherein each test track has a starting position of the drone and at least one further position of the drone for capturing at least one image of at least one object with a high-resolution camera.

The energy infrastructure includes a network for the transmission and distribution of electrical energy, in particular mainly so-called overhead lines. An overhead line is an electrical line whose current-carrying conductors are routed through the air outdoors and are usually only insulated from each other and from the ground by the ambient air. The conductors are usually carried by overhead line masts to which they are attached with insulators. The overhead line mast is a system or a structure for suspending an overhead electrical line, in particular a distribution mast and/or a transmission mast.

A constant energy supply from the energy infrastructure is essential for a modern and civilized life. Maintaining the systems reduces the risk of interruptions in the energy supply and ensures the expected security of supply. Inspections are used to identify problems early, before failures can occur. This is why energy infrastructure systems are usually inspected at regular intervals to identify potential sources of danger. Overhead lines are inspected as standard by walk-throughs and/or flights at fixed intervals. Power lines and masts, the suspensions on the masts and the buildings in the vicinity of the power lines are regularly inspected from the air by helicopter flights.

Out of US 4,818,990 is known a surveillance system that utilizes a unique remotely controlled drone with twin counter-rotating propellers equipped with electric field sensing, thermal infrared imaging, video imaging, acoustics and corona discharge detection equipment. The compact, remotely controlled drone flies along a power corridor and is maintained at a fixed distance from an external phase conductor, using onboard electric field detection circuitry, video/infrared imagery and an RF/laser altimeter. The contra-rotating configuration of the twin-turbocharged propellers mounted on coaxial vertical shafts provides an extremely stable platform unlike conventional manned helicopters currently used for routine right-of-way patrols. Two counter-rotating, saucer-shaped auxiliary propellers provide a level of stability far superior to that of a conventional helicopter, especially in gusty winds. The onboard sensors and video cameras enable power utilities to economically implement priority road monitoring, infrared sensor inspection of frayed conductors or damaged splices, acoustic/corona sensor detection of cracked insulators, critical thermally limited span monitoring and other monitoring functions.

The US 2015/0353196 A1 shows an aircraft with an electromagnetic field sensor, an adjustable electromagnetic reference field strength, a comparator, a parachute, a parachute release and an inspection camera for inspecting an overhead power line corridor with masts, phase conductors and shielding wires. The electromagnetic reference field strength is set before flight to establish the minimum electromagnetic field strength before the parachute release triggers the parachute. The electromagnetic reference field strength corresponds to a radius and thus a virtual tunnel outside of which the airframe cannot fly without releasing the parachute, regardless of the state of the autopilot, the GPS signal or the radio link.

Occasionally, insulator chains that separate the power lines from the equipment need to be replaced, as do the spacers that ensure there is enough space between the lines. But aging trusses and masts also need to be replaced or repaired.

As a rule, a very crude methodology of manual and ground-based inspection of systems has been used so far. Here, an inspection and observation of masts and visible parts of the lines must be carried out from at least three directions using stabilized binoculars.

A relatively new option is the possibility of additional inspection from the air using a helicopter or an unmanned aerial vehicle. In this case, the construction of the systems, especially the top of the trusses and the mast head, must be examined in detail and documented photographically. When taking photographs, particular attention must be paid to the correct alignment of the Camera and the resolution of the image material for the time-delayed evaluation.

Defects identified should be recorded with several photos from different perspectives. Documentation of the mast designation or another conclusive assignment of the location of the defect is relevant for the assignment. It is often a challenge to depict a defect in such a way that it can be clearly identified and its severity assessed.

Aerial inspection using a helicopter or unmanned aerial vehicle is usually performed manually by pilots. As a result, images are usually inconsistent in terms of angle and image quality. In addition, the manual shooting process depends on the pilot's skills and is relatively slow and time-consuming.

The aim of the present invention is to provide a method for checking energy infrastructures that records relevant system components repeatedly and in a time-saving manner using high-resolution images. The images should be suitable for evaluation independent of location and time. In addition, the inspection should be able to be automated.

This object is achieved according to the invention by a method for checking energy infrastructures according to the main claim and a system according to the subordinate main claim. Preferred embodiments emerge from the subclaims, the description, the exemplary embodiments and the drawings.

According to the invention, each test section is predefined, each test section is precise, each test section is repeatable in time and/or location.

The term energy infrastructure includes, for example, distribution masts, transmission masts and lines. In addition, the term energy infrastructure can also include all so-called renewable energies, such as solar fields, wind turbines and solar towers. The invention is described below using distribution masts as an example, but can be applied to all energy infrastructures.

For example, the positions in the first test section relative to each other are within a tolerance range compared to the positions in the other test section relative to each other, wherein the deviations in the x- or y- or z-direction are less than 500 cm, preferably less than 100 cm, in particular less than 20 cm in the spatial orientation.

A mission includes at least one test track to check an energy infrastructure installation, in particular distribution towers, during which images of the installation are taken.

For example, a mission may also include two test tracks or a plurality of test tracks of installations of the same type or of installations of different types.

Preferably, a test track comprises at least one position at a short spatial distance from an object at which the drone stops its flight movement to take an image.

For example, a test track includes all positions for checking an object from which images are generated to assess the condition of the object.

In a preferred embodiment of the invention, the test section comprises at least one position above the object from which at least one image of the object is generated from a bird's eye view, with the camera and the gimbal pointing directly downwards.

A drone is an unmanned aerial vehicle that can be operated and navigated autonomously by a computer or remotely from the ground without a crew on board.

The remote control of the drone is realized, for example, by an application-based control in the form of a controller. This controller can therefore be supplemented with additional applications via a download.

Ideally, the controller is Android-based.

The drone also has a high-resolution camera and/or many sensors that can be aligned in all dimensions, especially with the help of a gimbal. A gimbal is a motorized gimbal that serves to make the movements of an optical device, usually a camera, less jerky and more fluid.

The drone has a variety of sensors, such as yaw rate sensors, acceleration sensors, a compass and an air pressure sensor as well as a GPS sensor.

In addition, the drone can have collision protection based on the detection of obstacles.

For example, the images captured by the high-resolution camera have a resolution of at least 5472 x 3648 pixels and are preferably stored in JPEG format with minimal compression at most and preferably uncompressed. In addition, the metadata of each image preferably includes the GPS coordinates, the gimbal tilt, roll and pan of the camera, and the date and time of the capture.

The camera is also suitable for creating thermal images. The images have a resolution of at least 640 x 640 pixels.

Ideally, the existing energy infrastructures, especially the distribution masts, are already known in terms of location, type and size. The operators of such energy infrastructures usually already have high-resolution, three-dimensional maps, which were created, for example, using lidar measurements.

Alternatively, the data for creating detailed maps of the distribution masts can also be collected by drone or helicopter flight using lidar technology and then made available.

An energy infrastructure operator preferably defines areas of assets that are to be inspected for preventive maintenance. Based on the high-resolution, three-dimensional maps and the defined inspection areas, the platform generates a mission, e.g. with a Smart Mission Planner as part of the platform.

The platform is a space that is accessible from all energy infrastructure operator platforms as well as from all drone control controllers or from all drone parts via at least one application-independent interface and at least one connection interface. Accessibility can be achieved via all currently known forms of data transmission.

The platform is, for example, a place or space in a cloud that can be connected from all locations worldwide.

The Smart Mission Planner is a part of the platform that can create a 3D model of a test track or a mission from the input data. The Smart Mission Planner works with GPS-based data, for example.

At the same time, the platform's Smart Mission Planner creates the necessary digital data that must be submitted to infrastructure authorities for approval of energy infrastructure reviews. The platform transmits the approval data directly to the approval authority, for example, and implements the approval data when the approval is granted.

To carry out the inspection of the distribution booms, the order is transferred to a drone pilot, preferably from an inspection company, and passed on to an application-based controller to control the drone.

In an advantageous embodiment of the invention, the mission is loaded from the control unit onto the drone so that the drone can fly the mission with the test tracks in automatic flight mode.

For example, the drone is controlled directly via the controller. High-quality drones with controllers that are trained to operate on the basis of Android have proven particularly useful here.

In an alternative variant of the invention, if the data connection is sufficiently stable, e.g. on any known mobile radio basis, the drone can also be controlled directly in real time via the connection interface of the platform.

In geodesy, real-time kinematics is a method for the precise determination of position coordinates using satellite navigation methods, which is used in the method according to the invention with the drone.

On site at the energy infrastructure facilities, the drone pilot starts the drone flight after the local conditions, such as the weather, are suitable for a drone flight. To start the mission, the drone records an arbitrary point and holds the position for comparison with the mission's GPS data.

This point for comparing the GPS data can be, for example, just above the ground immediately after takeoff or, for example, above the first cooling point at a distance of 2 - 3 m above the cooling point.

After comparing the GPS data, the drone automatically flies at least one test section of the mission. It stops the flight at each position defined in the test section, points the camera at the respective component of the object and takes at least one high-resolution image.

The mission can, for example, also include several test tracks, with the drone pilot Flight between the test routes can be carried out manually. The drone moves from a first position to the next position along a geometric straight line on the shortest connection.

Within a test section or a connecting section, the drone preferably moves from a first position to the next position along a geometric straight line on the shortest connection.

In an advantageous embodiment of the invention, the drone automatically flies at least one connecting route between the test routes as part of the mission.

For example, an entire area of energy infrastructure facilities can be inspected automatically using drone flight. The automated drone works through the inspection routes and connection paths one after the other. Such a fully automated drone flight is only limited by the power supply for the flight and/or the capacity for image capture. In this embodiment, the drone pilot's task is limited to starting the mission and receiving the drone at the end of the mission.

Advantageously, the recorded images of the systems or components of the energy infrastructure systems have a resolution of at least 5472 x 3648 pixels. The resolution therefore corresponds to 5K, for example.

In an advantageous embodiment of the invention, the images are stored uncompressed in JPEG format.

In addition, the metadata of each image includes, among other things, the GPS coordinates, the gimbal tilt, the rotation and pan of the camera, the date and time of the capture.

In the simplest version of the invention, the drone creates an image above an energy infrastructure object, for example at nadir. In the case of a power distribution mast and/or a transmission mast, the image includes the top of the mast, the cross arms, the suspensions, the insulators and the power lines.

In an advantageous embodiment of the invention, at least one image is taken of each installation in each of the five positions. Detailed images are taken, for example, of each power line suspension, each cross arm and also of the foundation of the mast and the mast itself. Ideally, each collection of images of the installations is supplemented by an image that is directed from above at the apex of the installation.

Additionally or alternatively, the power lines between the distribution towers can also be checked using image and/or video analysis.

The method according to the invention for inspecting distribution booms with an automated use of at least one drone offers a previously unattained quality and repeatability of the images generated, which can be used for condition-based maintenance of the systems.

This repeatability of the quality and recording perspective is achieved, for example, in the case of identical systems, by the fact that the identical test path and the identical camera settings can be realized through the process.

Furthermore, when a test section of the same object is repeated at a different time, the method according to the invention enables ideal repeatability of the quality and perspective of the images.

When an inspection flight is repeated at a later point in time on an identical system in the form of a previously defined test section, the positions of the test sections relative to one another are within a tolerance range, with the deviations in the x-, y- or z-direction being less than 500 cm, preferably less than 100 cm, in particular less than 20 cm in the spatial orientation.

The deviations of the positions in a temporal repetition of the test sections from the positions which exactly correspond to the positions of the first test section are less than 500 cm, preferably less than 50 cm, in particular less than 10 cm, in the x- or y- or z-direction.

The deviations of the positions in a temporally and/or spatially offset repetition of a test section, which correspond exactly to the positions of a first test section, are less than 500 cm in the x- or y- or z-direction, preferably less than 100 cm, in particular less than 10 cm.

When repeating an entire operation consisting of a sequence of at least two test sections and, if necessary, at least one connecting section, the positions of each test section relative to the positions of a previous test section lie within a tolerance range, with the deviations being less than 500 cm in the x- or y- or z-direction, preferably less than 100 cm, in particular less than 20 cm in spatial orientation.

The deviations of the positions in a temporally and/or spatially offset repetition of a test section in each mission are less than 5 cm, preferably less than 2 cm, in particular less than 1 cm, in the x-, y- or z-direction.

In a preferred variant of the invention, the relative distance and direction from a previous position is used as a basis for the movement of a drone to a next position within a test track and/or within a mission.

The test section and/or the connecting section are defined relative to the starting position. The starting position is determined by comparing it with the exact GPS position. The calculations of the relative distance and direction are crucial for further movement and stopping at positions of the drone.

So the coordinates of the test track are recalculated based on a base point set at the beginning of a mission. The altitude, heading, latitude and longitude of this base point are recorded by the drone's sensors. For the next position, the altitude is added or subtracted from the base altitude, and the new longitude and latitude are calculated as the distance to the base point.

The coordinates of the first position of the mission are preferably assigned to the coordinates of the base point.

For example, vectors are determined as a basis for the flight movement of the drone starting from the starting position.

In another variant of the invention, vectors are determined as the basis for the flight movement of the drone starting from each position and thus any other position can be reached with a vector.

Ideally, the speed of the drone correlates with the vector determination of the platform.

In an alternative variant of the invention, the mission is based on absolute GPS positions and the linking of these GPS positions.

In the alternative embodiment of the invention, the absolute GPS positions are used in combination with the flight altitude to determine the image capture positions and the flight movement of the drone. In this way, the image capture position or the current and variable flight position are not based on the position of the drone relative to the previous position.

This determines the individual position for creating images of the energy infrastructure assets, especially the distribution masts, as well as the angle and the camera orientation in correlation to absolute GPS data. The positions based on GPS data are linked to vectors.

Mission-wide inspection of multiple objects involves a series of inspection routes based on GPS coordinates to determine the location of each object and its associated positions for image acquisition.

Regardless of the execution of the automated mission, the drone inspection flight mission is initiated by recording any position for comparison and location with the mission's GPS data.

In a particularly advantageous embodiment of the invention, the drone stops its flight movement in order to take at least one image, wherein the camera is directed at a component of the object during the stationary flight position.

For example, at least one image is taken per position. Depending on the requirements of the inspection, two or more images may be taken from the same and/or slightly different directions.

Ideally, the GPS coordinates are stored together with the image data for each image and additionally linked to the image configuration in a flight log.

In an advantageous variant of the invention, at least one image and the data are transmitted to the platform via the drone controller.

In an alternative variant of the invention, the drone is controlled directly via the platform, and the image data is also transmitted directly to the platform in real time.

In an alternative variant of the invention, the data can also be received directly from the drone via the connection interface of the platform.

Preferably, the platform generates a 3D model of a mission for a drone flight based on GPS data obtained from previously collected melted precise position data of at least one object were obtained, and depending on the definition of an inspection corridor.

In an expedient embodiment of the invention, the platform sends the data of the predefined automated test track or mission to the controller for controlling the drone, wherein the controller loads the data into the drone.

Ideally, the platform contains at least one application programming interface for communication with the drone, with the monitoring center and with the platforms of the energy infrastructure operators and, if necessary, with other defined interaction partners.

Preferably, the platform also generates operational information from at least one test track for the approval of the system test by the responsible monitoring body.

At the same time, the platform uses a connection interface to transfer the flight log data to the corresponding monitoring point on the distribution mast.

The system according to the invention for inspecting distribution booms comprises at least one drone with an orientable high-resolution camera, a controller with application-based control and a platform which is suitable for automatically flying the drone along at least one test route of a mission predefined by the platform and for taking at least one image of a component of a system.

According to the invention, the drone is designed to follow an automated mission comprising a first test track and at least one further test track, wherein each test track has a starting position of the drone and at least one further position of the drone for taking at least one image of at least one object with the high-resolution camera, each test track is predefined, each test track is precise, each test track is repeatable regardless of time and/or location.

For example, the platform includes a processor that, in a machine learning phase, determines a predictive model for the probability of failure and thus the ideal time for servicing components of the system that require maintenance. This capability of the platform is also known as artificial intelligence.

The platform's AI examines the images taken by the drone and creates a damage analysis and a recommendation for action. The images and analyses are made available to the operator of energy infrastructure systems via an application-independent interface.

Ideally, the drone's high-resolution camera produces images that can be analyzed by the AI or the prediction model. The prediction model is able to identify components to be tested through pattern analysis and pattern recognition.

In an alternative embodiment of the invention, the drone flight mission is automated through the use of AI via at least one application-independent interface. This allows the drone to be controlled directly in real time via the platform.

Such precision in drone flight and image generation is previously unknown and not achievable by a pilot in manual operation. The advantageous precision can only be achieved through an automated flight program.

The repeatability of the images according to the invention, which depict components of energy infrastructure systems, in particular distribution towers, and were generated at different times and/or from identical systems at different locations, is particularly advantageous and particularly favorable with regard to condition-based maintenance.

Typically, a typical manual drone inspection for a simple energy infrastructure asset takes at least 200 seconds, assuming the pilot is particularly experienced and well-versed in the acquisition requirements. With the method and system according to the invention, this time period can be reduced to less than 30 seconds for a comparable inspection.

In a mission with multiple test tracks connected to connecting tracks, the inspection times and the overall flight times of the drone can be advantageously reduced.

Further advantages and features of the invention will become apparent from the description of an embodiment with reference to the drawings and from the drawings themselves.

• : Schematische Darstellung eines Einsatzes, bei dem jede Prüfstrecke über die Zeit wiederholbar ist,
• : Schematische Darstellung eines Einsatzes, bei dem jede Prüfstrecke ortsunabhängig wiederholbar ist,
• eine schematische Darstellung der Toleranzbereiche während eines Einsatzes,
• eine beispielhafte Überprüfung in einer Draufsicht,
• eine Darstellung des Systems und der Methode zur Überprüfung von Energieinfrastrukturanlagen.

This shows

• : Schematic representation of an application in which each test section is repeatable over time,
• : Schematic representation of an application in which each test section is repeatable regardless of location,
• a schematic representation of the tolerance ranges during an operation,
• an exemplary inspection in a plan view,
• a description of the system and method for checking energy infrastructure facilities.

1 shows an exemplary object 40 of the energy infrastructure in the power pole version as well as a schematic representation of an inspection flight 10, 20 of a drone. The object 40 has at least one cross arm 41 for attaching a power line to an insulator.

shows an application in which each test section is repeatable over time.

To start the mission, which includes a test track 10, 20, the drone records an arbitrary point and records the position for comparison with the GPS data of the mission. In the embodiment shown, the starting position 11, 21 is directly above the object 40. At this point, an image is created from above looking downwards.

The drone then flies to other positions 12, 13, 14, stops the flight, points the camera at a component of the object 40 and takes at least one image.

The first test section 10 comprises the positions 11, 12, 13, 14. The positions 11, 12, 13, 14 form a three-dimensional pattern.

The other test section 20 includes the positions 21, 22, 23, 24. The positions 21, 22, 23, 24 form a three-dimensional pattern.

When the inspection flight 10 is repeated at a later time in the form of the inspection flight 20, in which the goods 40 are identical, the positions 11, 12, 13, 14 in the first test section 10 are within a tolerance range 61, 62, 63, 64 compared to the positions 21, 22, 23, 24 in the other test section 20, whereby the deviations in the x- or y- or z-direction are less than 20 cm in spatial orientation.

The deviations of the positions 21, 22, 23, 24 during a repetition of the test section 20 to the positions 11, 12, 13, 14 of the first inspection flight 10 are less than 10 cm in the x- or y- or z-direction.

This results in highly comparable images of energy infrastructure asset components when an inspection is repeated at different times. This repeatability is very beneficial for the evaluation of the image files, regardless of whether the evaluation is carried out by a human and/or an AI.

shows an example of two systems 40, 50 of the energy infrastructure in the distribution boom design variant as well as a schematic representation of an operation for checking the energy infrastructure, in which the distribution booms are locally tested one after the other using two test sections 10, 20.

In 1 shows an application in which each test section is a repeatable position. The first test section 10 comprises the positions 11, 12, 13, 14. The positions 11, 12, 13, 14 form a three-dimensional pattern. The other test section 20 comprises the positions 21, 22, 23, 24. The positions 21, 22, 23, 24 form a three-dimensional pattern.

The mission includes the test sections 10, 20, which are carried out directly one after the other and are connected to each other via a connecting path 2. At the start, the drone records an arbitrary point and records the position for comparison with the GPS data of the mission. In the embodiment shown, the starting position 11 is directly above the object 40. At this point, an image is created from above looking downwards.

After the starting position 11, the drone flies to another position 12, 13, 14, stops the flight, points the camera at a component of the system 40, in this embodiment the component is designed as a cross member 41 and generates at least one image, for example of the suspension and the insulator of the power line.

During use, the drone automatically connects the test sections 10, 20 with a connecting path 2. The test section 20 begins with position 21 above the object 50. At position 21, the drone creates an image from above looking downwards. After position 21, the drone flies to another position 22, 23, 24, stops the flight, points the camera at a component of the system 50, in this embodiment the component is designed as a cross member 51 and creates at least one image, for example of the suspension and the insulator of the power line.

In the embodiment shown, the systems 40 and 50 are identical in construction and design. In this respect, the test track 20 is a repetition of the inspection flight 10 at a later time at a different location. The positions 11, 12, 13, 14 in the first test section 10 relative to each other within a tolerance range 61, 62, 63, 64 compared to the positions 21, 22, 23, 24 in the other test section 20, wherein the deviations in the x- or y- or z-direction are smaller than 20 cm in the spatial orientation.

In a mission with multiple test sections 10, 20, this results in excellently comparable images of components of identical distribution booms. This repeatability is very advantageous for both manual and automatic evaluation of the image files.

shows two examples of energy infrastructure systems 40 and 50 in the distribution mast variant, as well as a schematic representation of two missions. In each mission, the inspection of the distribution mast is carried out one after the other, both spatially and temporally. The later mission represents the repetition of the first mission at a later point in time and shows the exact repeatability of the inspection of objects 40, 50 of the energy infrastructure with a temporal offset.

The mission includes test sections 10, 20, which are carried out in direct succession and are connected to each other via a connecting path 2. At the start, the drone takes up any position and records it for comparison with the GPS data of mission 1. In the embodiment shown, the starting position 11 is directly above the object 40. The execution of the mission corresponds to the 2 embodiment shown.

When repeating the mission as a subsequent mission, the positions 91, 92, 93, 94 in the first test section 10 are within a tolerance range 81, 82, 83, 84 relative to the positions 11, 12, 13, 14 of the first test section 10 of the first mission, with the deviations in the x- or y- or z-direction being less than 10 cm in spatial orientation.

The deviations of the positions 21, 22, 23, 24, in a temporally and spatially offset repetition of the test section 10 as test section 20 in each mission, amount to less than 20 cm in the x- or y- or z-direction.

When repeating a mission with multiple test sections 10, 20, this leads to very easily comparable images of components of structurally identical energy infrastructure systems, especially at different points in time. This repeatability is very advantageous for the evaluation of image files for the condition-based maintenance of energy infrastructure systems, especially distribution masts.

4 shows an exemplary inspection with a test track 10 of a use of a system 40 as part of the energy infrastructure in a plan view.

The system 40 is designed as a distribution mast, which has the task of suspending several power lines 5.

To start the mission with the test track 10, the drone 4 takes up any position and saves it for comparison with the GPS data of the mission. In the embodiment shown, the starting position 11 is directly above the object 40. At position 11, an image of the system 40 is then created from above looking downwards.

The drone 4 then flies along the test track 10 to another position 12, 13, 14 and 15 along a geometric straight line on the shortest connection. At positions 12, 13, 14 and 15, the drone 4 stops the flight, points the camera at at least one component of the object 40 and creates three images with different camera orientations on the object 40. The test track 10 is terminated by assuming the starting position 11.

5 shows a representation of the system and the procedure for checking the systems 40, 50 of the energy infrastructure 6. The existing systems 40, 50 of the energy infrastructure 6 are usually known in terms of their location, type and size. High-resolution, three-dimensional maps are often already known, which were recorded, for example, using a Lidar measurement. Alternatively, this data 111 can also be generated by drone flights using Lidar technology.

An operator of the energy infrastructure 6 preferably defines areas of systems 40, 50 that are to be inspected for preventive maintenance. Based on the high-resolution, three-dimensional maps and the defined inspection areas provided by the platform 7 of the operator of the energy infrastructure 6, the platform 8, as part of the system, creates a mission using the Smart Mission Planner 9.

At the same time, the Smart Mission Planner 9 of the platform 8 generates the necessary digital data, which is submitted to the infrastructure authorities for review of the energy infrastructure 6 for approval. For example, the platform 8 transmits the approval data 101 directly to the approval authority 100 and, if approved, implements the approval data 101 in the mission 1.

To carry out the inspection of the energy infrastructure 6, the order is given to a drone pilot, preferably from an inspection company 103, for example, and transmitted to an application-based controller 102. In an advantageous embodiment of the invention, the controller 102 is based on an Android operating system. In the embodiment shown, the mission 104 is loaded from the controller 103 onto the drone 4.

On site, the drone pilot starts the drone flight after the local conditions, e.g. the weather, have been deemed suitable for the drone flight. At the start of the mission, the drone records a random point and holds the position for comparison with the GPS data of the mission. This point can be, for example, just above the ground immediately after takeoff or, for example, above the first system 40 at a distance of 2 - 3 m above system 40.

After comparing the GPS data, the drone 4 automatically flies the test routes 10, 20 of the mission. It stops the flight at each position 11, 12, 13, 14, 15 defined in the test routes 10, 20, points the camera at the respective component of the system 40, 50 and takes at least one high-resolution image.

In the embodiment shown, the captured images have a minimum resolution of 5472 x 3648 pixels (equivalent to 5K with a 3:2 aspect ratio in landscape mode) and are stored in JPEG format with minimal compression at best, preferably uncompressed. In addition, the metadata of each image includes GPS coordinates, gimbal tilt, camera roll and pan, date and time of capture, among other things.

In the illustrated embodiment of the invention, three images of each power line suspension, each crossbeam, the foundation of the mast and the mast itself are taken for each installation 40, 50, supplemented by an image looking down on the installation from above.

In the embodiment shown, the transmission 105 of the images and data to the platform 8 takes place via the controller 103 after the data and images 106 have been transmitted from the drone 4 to the controller 103. In an alternative variant of the invention, the data can also be received directly from the drone 4 via the connection interface 107 of the platform 8.

At the same time, the platform 8 takes over the transmission 108 of the flight log data to the corresponding monitoring point 100 of the energy infrastructure 6 via the connection interface 107.

In the embodiment shown, the platform 8 has a processor with machine learning elements for executing a prediction model for the failure of systems or components of the systems 40, 50 of the energy infrastructure 6. At the same time, the prediction model provides a suggestion for the condition-based maintenance of system components. This capability of the platform 8 is also referred to as artificial intelligence.

The AI of the platform 8 checks the images taken by the drone 4 and creates a damage analysis and a recommendation for action. The images and analyses 110 are made available to the platform 7 via an application-independent interface 109 for the operator of the systems 40, 50 of the energy infrastructure 6.

QUOTES INCLUDED IN THE DESCRIPTION

This list of documents listed by the applicant was generated automatically and is included solely for the better information of the reader. The list is not part of the German patent or utility model application. The DPMA accepts no liability for any errors or omissions.

Cited patent literature

• US 4,818,990 [0004]
• US 2015/0353196 A1 [0005]

Claims (9)

Method for checking energy infrastructures (6) with an automated use of at least one drone (4), with a first test track (10) and at least one further test track (20), wherein each test track (10, 20) has a starting position (11, 21) of the drone and at least one further position (12, 13, 14), (22, 23, 24) of the drone (4) for recording at least one image of at least one object (40, 50) with a high-resolution camera, characterized in that each test track (10, 20) is predefined, each test track (10, 20) is precise, each test track (10, 20) is repeatable in time and/or location. procedure according to claim 1 , characterized in that the positions (11, 12, 13, 14) in the first test section (10) relative to one another in comparison to the positions (21, 22, 23, 24) in the other test section (20) relative to one another are within a tolerance range (61, 62, 63, 64) (81, 82, 83, 84), wherein the deviations in the x- or y- or z-direction are less than 500 cm, preferably less than 100 cm, in particular less than 20 cm in the spatial orientation. procedure according to claim 1 or 2 , characterized in that the drone moves from a first position to the next position along a geometric straight line on the shortest connection. Method according to at least one of the preceding claims, characterized in that the drone (4) stops in each position and the high-resolution camera is precisely aligned with a component of the object (40, 50) in order to record at least one image with a resolution of at least 5472 x 3648 pixels. Method according to at least one of the preceding claims, characterized in that the relative distance and direction from a previous position is the basis for the movement of the drone (4) to the next position. Method according to at least one of the preceding claims, characterized in that the mission is based on absolute GPS positions, the location of each object (40, 50) and/or each position being identified by GPS data. Method according to at least one of the preceding claims, characterized in that a platform (8) generates a 3D model of the mission for a drone flight (4) on the basis of GPS data obtained from previously collected precise position data (111) of the object (40, 50) and the definition of a test corridor. System for inspecting distribution booms (6), comprising: - a drone (4) with a high-resolution camera that can be aligned - an application-related controller (103) - a platform (8), characterized in that the drone (4) is suitable for an automated mission with a first test track (10) and at least one further test track (20), wherein each test track (10, 20) has a starting position (11, 21) of the drone and at least one further position (12, 13, 14), (22, 23, 24) of the drone (4) for taking at least one image of at least one object (40, 50) with the high-resolution camera, each test path (10, 20) is predefined, each test path (10, 20) is precise, each test path (10, 20) is repeatable in time and/or place. system according to claim 8 , characterized in that the platform (8) comprises at least one application programming interface (107, 109).

Images