An unmanned aerial vehicle fault detection method, device, equipment and medium

Abstract

The application discloses a kind of unmanned plane fault detection method, device, equipment and medium.The method comprises: obtaining the position of the lead to be detected, and obtaining at least one lead wiring image collected by unmanned plane corresponding to the position of the lead to be detected;Each lead wiring image corresponding to the position of the lead to be detected is identified, and the lead wiring mode corresponding to the position of the lead to be detected is obtained;According to the lead wiring mode, the position of the inductor coil of unmanned plane is adjusted, so that the inductor coil of unmanned plane can detect at least one lead to be detected corresponding to the position of the lead to be detected, and the lead detection current corresponding to each lead to be detected is obtained;According to the lead detection current corresponding to each lead to be detected, the fault calculation result is calculated;According to the position of the lead to be detected and the fault calculation result, the fault detection information corresponding to the unmanned plane is determined.The application embodiment can improve the accuracy and efficiency of unmanned plane fault detection.

Description

Technical Field

[0001] This invention relates to the field of data detection technology, and in particular to a method, apparatus, equipment and medium for detecting drone faults. Background Technology

[0002] With the rapid development of technology, the types of power equipment are gradually increasing, and low-voltage overhead lines are also increasing to ensure the normal operation of power equipment. However, due to factors such as long-term outdoor high-load operation, unsafe accidents may occur in these lines, thus requiring timely inspection of line safety.

[0003] Currently, faults in the power lines are being checked section by section using clamp meters at height.

[0004] However, the large number of low-voltage overhead lines makes manual inspections inaccurate and prone to causing safety accidents. Summary of the Invention

[0005] This invention provides a method, apparatus, equipment, and medium for detecting drone faults, in order to improve the accuracy of drone fault detection.

[0006] In a first aspect, embodiments of the present invention provide a method for detecting faults in unmanned aerial vehicles (UAVs), the method comprising:

[0007] Obtain the position of the conductor to be detected, and obtain at least one conductor wiring image captured by the UAV corresponding to the position of the conductor to be detected;

[0008] The wiring images of each wire corresponding to the position of the wire to be detected are identified to obtain the wiring pattern of the wire corresponding to the position of the wire to be detected.

[0009] Adjust the position of the UAV induction coil according to the wiring method so that the UAV induction coil can detect at least one wire to be detected corresponding to the position of the wire to be detected, and obtain the wire detection current corresponding to each wire to be detected.

[0010] The fault calculation results are obtained based on the wire detection current corresponding to each wire to be tested.

[0011] Based on the location of the conductor to be tested and the fault calculation results, the corresponding fault detection information of the UAV is determined.

[0012] Secondly, embodiments of the present invention also provide a UAV fault detection device, the device comprising:

[0013] The image acquisition module is used to acquire the position of the conductor to be detected, and to acquire at least one conductor wiring image acquired by the UAV corresponding to the position of the conductor to be detected;

[0014] The image recognition module is used to recognize the wiring images of each wire corresponding to the position of the wire to be detected, and to obtain the wiring pattern of the wire corresponding to the position of the wire to be detected.

[0015] The current detection module is used to adjust the position of the UAV induction coil according to the wiring method, so that the UAV induction coil can detect at least one wire to be detected corresponding to the position of the wire to be detected, and obtain the wire detection current corresponding to each wire to be detected.

[0016] The current calculation module is used to calculate the fault calculation result based on the wire detection current corresponding to each wire to be tested.

[0017] The information confirmation module is used to determine the corresponding fault detection information of the UAV based on the location of the conductor to be detected and the fault calculation results.

[0018] Thirdly, embodiments of the present invention also provide a drone fault detection device, the drone fault detection device comprising:

[0019] At least one processor; and

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

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

[0022] According to another aspect of the present invention, a computer-readable storage medium is provided, which stores computer instructions for causing a processor to execute and implement the unmanned aerial vehicle (UAV) fault detection method of any embodiment of the present invention.

[0023] The technical solution of this invention acquires the location of the conductor to be detected and at least one conductor wiring image collected by the UAV corresponding to the location of the conductor to be detected. It then identifies each conductor wiring image corresponding to the location of the conductor to be detected to obtain the conductor wiring pattern. Based on the conductor wiring pattern, it adjusts the position of the UAV's induction coil so that the UAV's induction coil can detect at least one conductor to be detected corresponding to the location of the conductor to be detected, obtaining the conductor detection current corresponding to each conductor to be detected. Based on the conductor detection current corresponding to each conductor to be detected, it calculates the fault calculation result. Based on the location of the conductor to be detected and the fault calculation result, it determines the fault detection information corresponding to the UAV. Different operations are performed for different conductor wiring patterns, refining the steps of UAV fault detection and improving the accuracy of UAV fault detection.

[0024] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is a flowchart of a method for detecting drone faults according to an embodiment of the present invention;

[0027] Figure 2 This is a structural diagram of the conductor installation of a low-voltage overhead line according to an embodiment of the present invention;

[0028] Figure 3 This is a structural diagram of a fault detection drone provided according to an embodiment of the present invention;

[0029] Figure 4 This is a structural diagram of a fault detection drone provided according to an embodiment of the present invention;

[0030] Figure 5 This is a flowchart of a method for detecting drone faults according to an embodiment of the present invention;

[0031] Figure 6 This is a structural diagram of a drone fault detection device according to an embodiment of the present invention;

[0032] Figure 7 This is a structural diagram of a drone fault detection device provided in an embodiment of the present invention. Detailed Implementation

[0033] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0034] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0035] The acquisition, storage, and application of wire wiring images and other related technologies in the technical solutions of this invention comply with relevant laws and regulations and do not violate public order and good morals.

[0036] Example 1

[0037] Figure 1 This is a flowchart illustrating a drone fault detection method according to Embodiment 1 of the present invention. This embodiment of the invention is applicable to drone fault detection, and the method can be executed by a drone fault detection device, which can be implemented in hardware and / or software.

[0038] See Figure 1 The drone fault detection method shown includes:

[0039] S101. Obtain the position of the conductor to be detected, and obtain at least one conductor wiring image collected by the UAV corresponding to the position of the conductor to be detected.

[0040] The location to be detected can be the point in the conductor where current is to be measured. The conductor wiring image can be an image of the conductor installation structure of a low-voltage overhead line.

[0041] Specifically, the location of the wire to be detected can be obtained, the drone can be flown to the location of the wire to be detected, and the drone's camera can be controlled to capture multi-angle images of the wire wiring at the location of the wire to be detected, so that the images of each wire wiring can be identified in the subsequent process.

[0042] In one example, the drone is flown to location 1 of the wire to be inspected, and the drone's camera is used to capture 5 top-view images and 5 side-view images of the wire wiring at location 1.

[0043] S102. Identify the wiring images of each wire corresponding to the position of the wire to be detected, and obtain the wiring pattern of the wire corresponding to the position of the wire to be detected.

[0044] The wiring method can be either the wiring installation structure or the wiring method itself. There are typically two types of wiring installation structures: the first is a three-phase four-wire (horizontal) structure, such as... Figure 2 As shown on the left, another type is three-phase four-wire (vertical), such as... Figure 2 As shown on the right side of the middle section.

[0045] Specifically, images of different wiring patterns can be pre-collected using a drone. These images are then used to train a neural network to obtain a wiring pattern recognition model. The neural network includes, but is not limited to, feedforward neural networks, recurrent neural networks, convolutional neural networks, generative adversarial networks, graph neural networks, long short-term memory networks, and artificial neural networks. This embodiment of the invention does not impose any limitations on this. The wiring pattern recognition model can be stored in the drone for wiring pattern recognition, or it can be stored in the control system. After the drone collects wiring images, the images are transmitted to the control system, which then performs wiring pattern recognition.

[0046] In one example, after the drone collects 10 images of the wiring at location 1 of the conductor to be tested, it identifies these images and finds that the wiring pattern at location 1 of the conductor to be tested is three-phase four-wire (lateral).

[0047] S103. Adjust the position of the UAV induction coil according to the wiring method so that the UAV induction coil can detect at least one wire to be detected corresponding to the position of the wire to be detected, and obtain the wire detection current corresponding to each wire to be detected.

[0048] The location of the drone's induction coil can be the position of the induction coil installed on the drone. The wire detection current can be the current value of the wire to be detected corresponding to the induction coil detected by the drone's induction coil.

[0049] Specifically, there are four low-voltage overhead conductors: phase A, phase B, phase C, and phase D. Different wiring methods result in different conductor installation structures, and consequently, different positions for the drone's induction coils. The drone is equipped with an adjustable joystick, which houses four drone induction coils: phase A, phase B, phase C, and phase D coils. Each induction coil detects the current of its corresponding conductor. By adjusting the angle and position of the joystick according to the wiring method, the drone's induction coils are positioned to detect the current of their respective conductors, thus obtaining the current detection data for each conductor. Figure 2 The left side shows a three-phase four-wire (horizontal) configuration; the induction coil needs to be adjusted as follows. Figure 3 The operable lever shown is parallel to the plane containing the four wires to be tested. (As shown) Figure 2The image on the right shows a three-phase four-wire (vertical) configuration. The induction coil needs to be adjusted as follows: Figure 4 The operable lever shown is parallel to the plane containing the four wires to be tested.

[0050] S104. The fault calculation result is obtained based on the wire detection current corresponding to each wire to be tested.

[0051] The fault calculation result can be obtained from the current detected in the conductor, and can be used to determine the fault type of the conductor to be tested.

[0052] Specifically, overhead lines are one of the most common power transmission methods in power systems, and low-voltage power transmission to users is also primarily achieved through overhead lines. However, as low-voltage overhead lines operate outdoors for extended periods, factors such as material aging, external damage, and prolonged high-load operation can easily lead to leakage current in the conductors. Leakage not only damages electrical equipment and causes power loss, but more seriously, it can cause electric shock accidents to passersby, resulting in injury or death. Therefore, it is necessary to detect leakage current in the conductors under test, which can be done by measuring the current value of the conductors being tested. Furthermore, low-voltage lines often experience three-phase imbalance due to uneven user loads, which can easily lead to single-phase overload and cascading power accidents. Therefore, it is necessary to detect the three-phase imbalance between the current values ​​of the conductors under test. The fault calculation results are obtained based on the current values ​​of the conductors under test.

[0053] S105. Based on the location of the conductor to be tested and the fault calculation results, determine the corresponding fault detection information of the UAV.

[0054] Among them, the fault detection information can be a descriptive information about the fault condition of the conductor detected at the location of the conductor to be tested.

[0055] Specifically, fault detection is performed on each conductor position to be tested, and the fault calculation results corresponding to each conductor position are obtained. Based on the fault calculation results, the fault type corresponding to each conductor position is determined, and the faulty conductor position and fault type are identified as the fault detection information corresponding to the UAV.

[0056] The technical solution of this invention acquires the location of the conductor to be detected and at least one conductor wiring image collected by the UAV corresponding to the location of the conductor to be detected. It then identifies each conductor wiring image corresponding to the location of the conductor to be detected to obtain the conductor wiring pattern. Based on the conductor wiring pattern, it adjusts the position of the UAV's induction coil so that the UAV's induction coil can detect at least one conductor to be detected corresponding to the location of the conductor to be detected, obtaining the conductor detection current corresponding to each conductor to be detected. Based on the conductor detection current corresponding to each conductor to be detected, it calculates the fault calculation result. Based on the location of the conductor to be detected and the fault calculation result, it determines the fault detection information corresponding to the UAV. Different operations are performed for different conductor wiring patterns, refining the steps of UAV fault detection and improving the accuracy of UAV fault detection.

[0057] Example 2

[0058] Figure 5 This is a flowchart illustrating a UAV fault detection method according to Embodiment 2 of the present invention. Based on the above embodiments, this embodiment optimizes and improves the UAV fault detection operation.

[0059] Furthermore, the step of "calculating the fault calculation result based on the wire detection current corresponding to each wire to be tested" is refined to "obtain at least one fault detection type; calculate the wire detection current corresponding to each wire to be tested based on each fault detection type to obtain the fault calculation result", in order to improve the operation of UAV fault detection.

[0060] It should be noted that for parts not described in detail in the embodiments of the present invention, please refer to the descriptions in other embodiments.

[0061] See Figure 5 The drone fault detection method shown includes:

[0062] S501. Obtain the position of the conductor to be detected, and obtain at least one conductor wiring image collected by the UAV corresponding to the position of the conductor to be detected.

[0063] S502. Identify the wiring images of each wire corresponding to the position of the wire to be detected, and obtain the wiring pattern of the wire corresponding to the position of the wire to be detected.

[0064] S503. Adjust the position of the UAV induction coil according to the wiring method so that the UAV induction coil can detect at least one wire to be detected corresponding to the position of the wire to be detected, and obtain the wire detection current corresponding to each wire to be detected.

[0065] S504. Obtain at least one fault detection type.

[0066] Among them, the fault detection type can be the type of fault detection performed on the wire to be tested.

[0067] Specifically, at least one fault detection type is acquired, and the acquisition method includes, but is not limited to, mouse selection or keyboard input; this embodiment of the invention does not impose any restrictions on this. Fault detection types include leakage current detection and current balance detection.

[0068] S505. Calculate the conductor detection current corresponding to each conductor to be tested according to each fault detection type to obtain the fault calculation result.

[0069] Specifically, different fault detection types require different fault calculation methods. The appropriate fault calculation method is found for each fault detection type, and the result is obtained by applying the method corresponding to that fault type.

[0070] S506. Based on the location of the conductor to be tested and the fault calculation results, determine the corresponding fault detection information for the UAV.

[0071] This invention refines the operation of UAV fault detection by acquiring at least one fault detection type, calculating the wire detection current corresponding to each wire to be detected based on each fault detection type, obtaining the fault calculation result, and performing different fault calculation operations according to different fault detection types, thereby improving the accuracy of UAV fault detection.

[0072] Optionally, the fault detection type is leakage current detection. Based on each fault detection type, the wire detection current corresponding to each wire to be tested is calculated to obtain the fault calculation result, including: identifying at least one wire color from the wiring image of each wire; filtering among the wires to be tested for each wire color to obtain the target wire corresponding to the wire color and the wire detection current corresponding to the target wire; adding the wire detection currents of the target wires corresponding to each wire color to obtain the total wire current; obtaining a preset current threshold; and comparing the total wire current with the preset current threshold to obtain the fault calculation result.

[0073] The target conductor can be the conductor whose color corresponds to the conductor being detected. The total conductor current can be the sum of the detected currents of the conductors corresponding to the target conductors. The preset current threshold can be a pre-set threshold for the total conductor current.

[0074] Specifically, low-voltage conductors are colored in four ways: phase A is yellow, phase B is green, phase C is red, and the N line (neutral line) is light purple. Each conductor's wiring image is identified to obtain at least one conductor color. For each color, the conductors to be tested are filtered to obtain the target conductor and its corresponding current. The currents of the target conductors for each color are summed to obtain the total conductor current. A preset current threshold is obtained, typically set to 0. If the sum of the currents collected from conductors in the same area within the same time period is not zero, a leakage current is detected. The total conductor current is compared with the preset current threshold of 0 to obtain the fault calculation result.

[0075] By identifying the wiring images of each conductor, at least one conductor color is obtained. For each conductor color, the conductors to be tested are filtered to obtain the target conductor corresponding to the conductor color and the conductor detection current corresponding to the target conductor. The conductor detection currents of the target conductors corresponding to each conductor color are added together to obtain the total conductor current. A preset current threshold is obtained. The total conductor current is compared with the preset current threshold to obtain the fault calculation result. The conductors to be tested can be further filtered to ensure the accuracy of the total conductor current and improve the accuracy of UAV fault detection.

[0076] Optionally, the fault detection type is current balance detection type; according to each fault detection type, the conductor detection current corresponding to each conductor to be tested is calculated to obtain the fault calculation result, including: arranging and combining each conductor to be tested to obtain at least one conductor group, a conductor group including two conductors to be tested and the conductor detection current corresponding to each conductor to be tested; for each conductor group, subtracting the conductor detection current corresponding to the two conductors to be tested in the conductor group to obtain the conductor current difference value corresponding to the conductor group; obtaining the current difference threshold; for each conductor group, subtracting the conductor current difference value corresponding to the conductor group from the current difference threshold value to obtain the fault calculation result.

[0077] In this context, a conductor group can be two conductors to be tested and the corresponding conductor detection currents for each conductor. The conductor current difference can be the difference between the conductor detection currents of the two conductors to be tested within a conductor group. The current difference threshold can be a threshold value for the conductor current difference.

[0078] Specifically, the conductors to be tested are arranged and combined to obtain at least one conductor group. Each conductor group includes two conductors to be tested and the corresponding conductor detection current. For each conductor group, the larger of the conductor detection currents of the two conductors to be tested in the group is subtracted from the smaller of the conductor detection currents to obtain the conductor current difference for the group. A current difference threshold is then obtained. For each conductor group, the conductor current difference is subtracted from the current difference threshold. If the conductor current difference is less than the current difference threshold, it indicates that the difference between the conductor detection currents of the two conductors to be tested in the group is small, and the current is relatively balanced, so no alarm is triggered. If the conductor current difference is greater than or equal to the current difference threshold, it indicates that the difference between the conductor detection currents of the two conductors to be tested in the group is large, and the current is unbalanced, so an alarm is triggered. The alarm method can be information alarm, email alarm, telephone alarm, sound alarm, smoke alarm, or light alarm.

[0079] By arranging and combining the various conductors to be tested, at least one conductor group is obtained. Each conductor group includes two conductors to be tested and the conductor detection current corresponding to each conductor. For each conductor group, the conductor detection currents corresponding to the two conductors to be tested in the conductor group are subtracted to obtain the conductor current difference value corresponding to the conductor group, and the current difference threshold is obtained. For each conductor group, the conductor current difference value corresponding to the conductor group is subtracted from the current difference threshold to obtain the fault calculation result. Fault detection is performed through multi-dimensional data, which improves the accuracy of UAV fault detection.

[0080] Optionally, obtaining the position of the conductor to be tested includes: obtaining the low-voltage conductor segment to be tested and the starting position of the conductor segment; obtaining a preset acquisition distance; and dividing the low-voltage conductor segment to be tested from the starting position of the conductor segment according to the preset acquisition distance to obtain at least one position of the conductor to be tested corresponding to the low-voltage conductor segment to be tested.

[0081] The low-voltage conductor segment to be tested can be a segment of the conductor to be fault-detected, and the conductor between two poles constitutes a low-voltage conductor segment to be tested. The starting point of the conductor segment can be the position of the pole from which the drone is prepared to begin fault detection within the low-voltage conductor segment to be tested.

[0082] Specifically, the process involves acquiring the low-voltage conductor segment to be tested, determining the direction of fault detection for that segment, identifying the starting pole of the low-voltage conductor segment based on the fault detection direction, and defining the position of the starting pole as the starting point of the conductor segment. The preset acquisition distance can be the interval between each time the drone detects the conductor current position.

[0083] In one example, the low-voltage conductor segment 1 to be tested is acquired, and its location is from (0, 0) to (2, 5, 0). The starting position of the conductor segment is (0, 0). The preset acquisition distance is 1 meter. Based on the preset acquisition distance, the low-voltage conductor segment to be tested is divided into (0, 0) to (1, 0), (1, 0) to (2, 0), and (2, 0) to (2.5, 0) starting from the starting position of the conductor segment, according to the preset acquisition distance. The three positions of the conductor to be tested corresponding to the low-voltage conductor segment 1 are (0.5, 0), (1.5, 0), and (2.25, 0).

[0084] By acquiring the low-voltage conductor segment to be tested and its starting position, and obtaining a preset acquisition distance, the low-voltage conductor segment to be tested is divided from its starting position according to the preset acquisition distance, thus obtaining at least one conductor position corresponding to the low-voltage conductor segment to be tested. By repeatedly detecting the current of the same low-voltage conductor segment to be tested, the randomness of the detection is reduced, and the accuracy of UAV fault detection is improved.

[0085] Optionally, acquiring at least one wire routing image captured by a drone corresponding to the location of the low-voltage wire to be detected includes: identifying at least one drone shooting direction for the low-voltage wire segment to be detected; for each drone shooting direction, if the drone shooting direction is a top-down direction, flying the drone directly above the low-voltage wire segment to be detected to acquire at least one first wire image; if the drone shooting direction is a side-view direction, acquiring the camera deflection angle, flying the drone to a shooting position parallel to the low-voltage wire segment to be detected, and acquiring at least one second wire image according to the camera deflection angle; and determining each first wire image and each second wire image as a wire routing image.

[0086] The drone's shooting direction can be the direction in which the camera mounted on the drone captures the image. The first conductor image can be an image taken by the drone's camera looking down at the conductor to be inspected. The camera deflection angle can be the angle at which the camera is deflected. The second conductor image can be an image taken by the drone's camera looking from the side of the conductor to be inspected. The conductor routing image can be an image taken by the drone at the location of the conductor to be inspected.

[0087] Specifically, images of the low-voltage conductor segment to be detected are acquired, and these images are then identified to determine the top-view and side-view positions of the conductor segment. For each drone's shooting direction, if the drone is shooting from above, it flies directly above the conductor segment, and the camera is positioned to capture at least one first conductor image. If the drone is shooting from the side, the camera's deflection angle is determined, and the drone flies to a shooting position parallel to the conductor segment, with the camera deflected according to the deflection angle, capturing at least one second conductor image. All first and second conductor images are then identified as the conductor wiring images.

[0088] In one example, the low-voltage conductor segment to be detected is identified by a drone's camera direction, a left-side view direction, and a right-side view direction. For each drone camera direction, if the drone's camera direction is a top-down view, the drone is flown directly above the low-voltage conductor segment to collect five first conductor images. If the drone's camera direction is a left-side view, the camera is tilted at 30°, and the drone is flown to a shooting position parallel to the low-voltage conductor segment to the left, with the initial camera angle at 0°. Twenty second conductor images are then collected based on the camera tilt angles: tilted upwards and downwards by 30° and 60°, tilted to the left and 60°, and tilted to the right by 30° and 60°. If the drone's shooting direction is from the right-hand view, and the camera deflection angle is 30°, fly the drone to a shooting position parallel to the low-voltage conductor segment to be tested on the right side of the segment. With the initial camera angle at 0°, acquire 20 second conductor images at camera deflections of 30° and 60° upwards, 30° and 60° downwards, 30° and 60° to the left, and 30° and 60° to the right. These first and second conductor images are then used to define the conductor wiring images.

[0089] By identifying the low-voltage conductor segment to be tested, at least one drone shooting direction is obtained. For each drone shooting direction, if the drone shooting direction is from above, the drone is flown directly above the low-voltage conductor segment to be tested to collect at least one first conductor image. If the drone shooting direction is from the side, the camera deflection angle is obtained, and the drone is flown to a shooting position parallel to the low-voltage conductor segment to be tested, and at least one second conductor image is collected according to the camera deflection angle. Each first conductor image and each second conductor image is determined as the conductor wiring image. By collecting images of the test position from multiple angles, the accuracy of drone fault detection is improved.

[0090] Optionally, the position of the UAV's induction coil is adjusted according to the wiring method so that the UAV's induction coil can detect at least one wire corresponding to the position of the wire to be detected, and obtain the wire detection current corresponding to each wire to be detected. This includes: finding the coil rod adjustment method according to the wiring method; adjusting the UAV's coil rod according to the coil rod adjustment method so that each induction coil on the coil rod is parallel to each wire to be detected; for each induction coil, detecting the distance between the induction coil and the wire to be detected corresponding to the induction coil to obtain the detection distance; obtaining the detectable distance; for each induction coil, comparing the detection distance with the detectable distance to obtain the distance comparison result; adjusting the position of the corresponding induction coil of the UAV according to the distance comparison result of the induction coil, and controlling the opening and closing device of the corresponding induction coil to detect the wire to be detected, and obtaining the wire detection current corresponding to the wire to be detected.

[0091] The coil rod adjustment method can be the same as the adjustment method for the drone's induction coil. The detection distance can be the distance between the induction coil and the corresponding conductor to be detected, which can be obtained using a laser rangefinder. The detectable distance can be the distance between the induction coil capable of detecting current in the conductor and the conductor to be detected. The distance comparison result can be the result of comparing the detection distance and the detectable distance. The opening and closing device can be a device that clamps the induction coil to detect current in the conductor.

[0092] Specifically, the coil rod adjustment method is determined based on the wiring configuration. If the wiring configuration is three-phase four-wire (vertical), the coil rod adjustment method is to adjust the operable rod to be parallel to the plane containing each conductor to be tested. If the wiring configuration is three-phase four-wire (horizontal), the coil rod adjustment method is to adjust the operable rod to be parallel to the plane containing each conductor to be tested. For each induction coil, the distance between the induction coil and the corresponding conductor to be tested is detected to obtain the detection distance. For each induction coil, the detection distance is compared with the detection distance to obtain the distance comparison result. If the detection distance is less than or equal to the detection distance, the opening and closing device clamps the conductor to be tested for current detection. If the detection distance is greater than the detection distance, the position of the corresponding induction coil of the UAV is adjusted according to the distance comparison result, and the opening and closing device of the corresponding induction coil is controlled to detect the conductor to be tested, thereby obtaining the conductor detection current corresponding to the conductor to be tested.

[0093] By identifying the coil rod adjustment method based on the wire wiring pattern, and adjusting the drone's coil rod accordingly, each induction coil on the coil rod is aligned with the corresponding wire to be tested. For each induction coil, the distance between the induction coil and the corresponding wire is measured to obtain the detection distance. This detectable distance is then compared with the detectable distance for each induction coil to obtain a distance comparison result. Based on the distance comparison result, the position of the corresponding induction coil on the drone is adjusted, and the opening and closing device of the corresponding induction coil is controlled to detect the wire to be tested, obtaining the wire detection current. This method allows for real-time analysis and current acquisition based on different wire wiring patterns and wire positions, facilitating fault detection and improving the accuracy of drone fault detection.

[0094] Example 3

[0095] Figure 6 This is a schematic diagram of a drone fault detection device according to Embodiment 3 of the present invention. This embodiment of the invention is applicable to drone fault detection, and the device can execute a drone fault detection method. The device can be implemented in hardware and / or software.

[0096] See Figure 6 The UAV fault detection device shown includes: an image acquisition module 601, an image recognition module 602, a current detection module 603, a current calculation module 604, and an information confirmation module 605, wherein...

[0097] The image acquisition module 601 is used to acquire the position of the conductor to be detected, and to acquire at least one conductor wiring image acquired by the UAV corresponding to the position of the conductor to be detected;

[0098] Image recognition module 602 is used to recognize the wiring images of each wire corresponding to the position of the wire to be detected, and to obtain the wiring pattern of the wire corresponding to the position of the wire to be detected.

[0099] The current detection module 603 is used to adjust the position of the UAV induction coil according to the wiring method of the wire, so that the UAV induction coil can detect at least one wire to be detected corresponding to the position of the wire to be detected, and obtain the wire detection current corresponding to each wire to be detected.

[0100] The current calculation module 604 is used to calculate the fault calculation result based on the wire detection current corresponding to each wire to be tested.

[0101] The information confirmation module 605 is used to determine the fault detection information corresponding to the UAV based on the position of the conductor to be detected and the fault calculation results.

[0102] The technical solution of this invention acquires the location of the conductor to be detected and at least one conductor wiring image collected by the UAV corresponding to the location of the conductor to be detected. It then identifies each conductor wiring image corresponding to the location of the conductor to be detected to obtain the conductor wiring pattern. Based on the conductor wiring pattern, it adjusts the position of the UAV's induction coil so that the UAV's induction coil can detect at least one conductor to be detected corresponding to the location of the conductor to be detected, obtaining the conductor detection current corresponding to each conductor to be detected. Based on the conductor detection current corresponding to each conductor to be detected, it calculates the fault calculation result. Based on the location of the conductor to be detected and the fault calculation result, it determines the fault detection information corresponding to the UAV. Different operations are performed for different conductor wiring patterns, refining the steps of UAV fault detection and improving the accuracy of UAV fault detection.

[0103] Optional, the current calculation module 604 includes:

[0104] A type acquisition unit is used to acquire at least one fault detection type;

[0105] The fault calculation unit is used to calculate the conductor detection current corresponding to each conductor to be tested according to each fault detection type, and obtain the fault calculation result.

[0106] Optional, fault calculation unit, specifically used for:

[0107] The fault detection type is leakage current detection.

[0108] At least one wire color can be obtained by identifying the wiring images of each wire;

[0109] Based on the color of each wire, the target wires corresponding to each wire color are selected from the wires to be tested to obtain the wire detection current corresponding to the target wires.

[0110] The total current of the target wires corresponding to each wire color is obtained by summing the wire detection currents.

[0111] Obtain the preset current threshold;

[0112] The total current in the conductor is compared with a preset current threshold to obtain the fault calculation result.

[0113] Optional, fault calculation unit, specifically used for:

[0114] The fault detection type is current balance detection.

[0115] Arrange and combine the wires to be tested to obtain at least one wire group. A wire group includes two wires to be tested and the wire detection current corresponding to each wire to be tested.

[0116] For each conductor group, the conductor detection currents of the two conductors to be tested in the conductor group are subtracted to obtain the conductor current difference value of the conductor group.

[0117] Obtain the current difference threshold;

[0118] For each conductor group, the current difference between the conductors in the corresponding conductor group is subtracted from the current difference threshold to obtain the fault calculation result.

[0119] Optionally, the image acquisition module 601 includes:

[0120] The line segment acquisition unit is used to acquire the low-voltage conductor segment to be detected and the starting position of the conductor segment;

[0121] Distance acquisition unit, used to acquire preset acquisition distance;

[0122] The line segment division unit is used to divide the low-voltage conductor segment to be tested from the starting position of the conductor segment according to the preset acquisition distance, so as to obtain at least one position of the conductor to be tested corresponding to the low-voltage conductor segment to be tested.

[0123] Optionally, the image acquisition module 601 is specifically used for:

[0124] At least one drone shooting direction is obtained by identifying the low-voltage conductor segment to be detected;

[0125] For each drone's shooting direction, if the drone's shooting direction is from above, the drone will be flown directly above the low-voltage conductor segment to be detected to collect at least one first conductor image.

[0126] If the drone's shooting direction is a side view, obtain the camera deflection angle, fly the drone to a shooting position parallel to the low-voltage conductor segment to be detected, and collect at least one second conductor image according to the camera deflection angle.

[0127] Each first conductor image and each second conductor image are defined as conductor wiring images.

[0128] Optional, the current detection module 603 is specifically used for:

[0129] Find the coil rod adjustment method based on the wire wiring method;

[0130] Adjust the drone's coil rod according to the coil rod adjustment method to make each induction coil on the coil rod parallel to each wire to be detected;

[0131] For each induction coil, the distance between the induction coil and the corresponding wire to be tested is measured to obtain the detection distance;

[0132] Obtain the detectable distance;

[0133] For each induction coil, the detection distance is compared with the detectable distance to obtain the distance comparison result;

[0134] Based on the distance comparison results of the induction coil, the position of the induction coil of the UAV is adjusted, and the opening and closing device of the induction coil is controlled to detect the wire to be tested, so as to obtain the wire detection current of the wire to be tested.

[0135] The UAV fault detection device provided in this embodiment of the invention can execute the UAV fault detection method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the UAV fault detection method.

[0136] Example 4

[0137] Figure 7 A schematic diagram of the structure of a drone fault detection device 700 that can be used to implement an embodiment of the present invention is shown.

[0138] like Figure 7 As shown, the UAV fault detection device 700 includes at least one processor 701 and a memory, such as a read-only memory (ROM) 702 and a random access memory (RAM) 703, communicatively connected to the at least one processor 701. The memory stores computer programs executable by the at least one processor. The processor 701 can perform various appropriate actions and processes based on the computer program stored in the ROM 702 or loaded into the RAM 703 from the storage unit 708. The RAM 703 can also store various programs and data required for the operation of the UAV fault detection device 700. The processor 701, ROM 702, and RAM 703 are interconnected via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0139] Multiple components in the UAV fault detection device 700 are connected to the I / O interface 705, including: an input unit 706, such as a keyboard or mouse; an output unit 707, such as various types of displays or speakers; a storage unit 708, such as a disk or optical disc; and a communication unit 709, such as a network interface card (NIC), modem, or wireless transceiver. The communication unit 709 allows the UAV fault detection device 700 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0140] Processor 701 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 701 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 701 performs the various methods and processes described above, such as drone fault detection methods.

[0141] In some embodiments, the UAV fault detection method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 708. In some embodiments, part or all of the computer program may be loaded and / or installed on the UAV fault detection device 700 via ROM 702 and / or communication unit 709. When the computer program is loaded into RAM 703 and executed by processor 701, one or more steps of the UAV fault detection method described above may be performed. Alternatively, in other embodiments, processor 701 may be configured to perform the UAV fault detection method by any other suitable means (e.g., by means of firmware).

[0142] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0143] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0144] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0145] To provide user interaction, the systems and techniques described herein can be implemented on a drone fault detection device, which includes: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the drone fault detection device. Other types of devices can also be used to provide user interaction; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0146] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0147] A computing system can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system. It addresses the shortcomings of traditional physical hosts and VPS (Virtual Private Server) services, such as high management difficulty and weak business scalability.

[0148] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0149] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for detecting faults in unmanned aerial vehicles (UAVs), characterized in that, The method includes: The location of the conductor to be detected is obtained, as well as at least one conductor wiring image captured by the UAV corresponding to the location of the conductor to be detected; The wiring images of each wire corresponding to the position of the wire to be detected are identified to obtain the wiring pattern corresponding to the position of the wire to be detected. Adjust the position of the UAV induction coil according to the wire wiring method so that the UAV induction coil can detect at least one wire to be detected corresponding to the position of the wire to be detected, and obtain the wire detection current corresponding to each wire to be detected. Obtain at least one fault detection type; The fault detection current corresponding to each of the aforementioned fault detection types is calculated to obtain the fault calculation result; Based on the location of the conductor to be detected and the fault calculation results, the fault detection information corresponding to the UAV is determined.

2. The method according to claim 1, characterized in that, The fault detection type is a leakage current detection type; The step of calculating the conductor detection current corresponding to each conductor to be detected according to each of the fault detection types to obtain the fault calculation result includes: At least one wire color is obtained by identifying each of the wire wiring images; Based on the color of each wire, a selection is made among the wires to be detected to obtain the target wire corresponding to the wire color and the wire detection current corresponding to the target wire. The total current of the target wires corresponding to each of the wire colors is obtained by summing the wire detection currents. Obtain the preset current threshold; The total current in the conductor is compared with the preset current threshold to obtain the fault calculation result.

3. The method according to claim 1, characterized in that, The fault detection type is the current balance detection type; The step of calculating the conductor detection current corresponding to each conductor to be detected according to each of the fault detection types to obtain the fault calculation result includes: Arrange and combine the wires to be tested to obtain at least one wire group. A wire group includes two wires to be tested and the wire detection current corresponding to each wire to be tested. For each of the aforementioned conductor groups, the conductor detection currents of the two conductors to be detected corresponding to the conductor group are subtracted to obtain the conductor current difference value corresponding to the conductor group. Obtain the current difference threshold; For each of the aforementioned conductor groups, the current difference between the conductors corresponding to the conductor group is subtracted from the current difference threshold to obtain the fault calculation result.

4. The method according to claim 1, characterized in that, The step of obtaining the position of the conductor to be detected includes: Obtain the low-voltage conductor segment to be tested and the starting position of the conductor segment; Obtain the preset sampling distance; Based on the preset acquisition distance, the low-voltage conductor segment to be tested is divided from the starting position of the conductor segment according to the preset acquisition distance, thereby obtaining at least one conductor position corresponding to the low-voltage conductor segment to be tested.

5. The method according to claim 4, characterized in that, The step of obtaining at least one wire routing image captured by the UAV corresponding to the position of the wire to be detected includes: At least one drone shooting direction was identified from the low-voltage conductor segment to be detected; For each of the aforementioned drone shooting directions, if the drone shooting direction is a top-down direction, then the drone will fly directly above the low-voltage conductor segment to be detected to collect at least one first conductor image; If the drone's shooting direction is a side view, obtain the camera deflection angle, fly the drone to a shooting position parallel to the low-voltage conductor segment to be detected, and collect at least one second conductor image according to the camera deflection angle; Each of the first conductor images and each of the second conductor images are defined as conductor wiring images.

6. The method according to claim 1, characterized in that, The step of adjusting the position of the UAV induction coil according to the wire wiring method, so that the UAV induction coil can detect at least one wire corresponding to the position of the wire to be detected, and obtain the wire detection current corresponding to each wire to be detected, includes: Find the coil rod adjustment method based on the described wire wiring method; The coil rod of the UAV is adjusted according to the coil rod adjustment method so that each of the induction coils on the coil rod is parallel to each of the wires to be detected; For each of the aforementioned induction coils, the distance between the induction coil and the corresponding wire to be detected is measured to obtain the detection distance; Obtain the detectable distance; For each of the aforementioned induction coils, the detection distance is compared with the detectable distance to obtain a distance comparison result; Based on the distance comparison result corresponding to the induction coil, the position of the induction coil corresponding to the UAV is adjusted, and the opening and closing device corresponding to the induction coil is controlled to detect the wire to be tested, thereby obtaining the wire detection current corresponding to the wire to be tested.

7. A fault detection device for unmanned aerial vehicles (UAVs), characterized in that, The device includes: The image acquisition module is used to acquire the position of the conductor to be detected, and to acquire at least one conductor wiring image acquired by the UAV corresponding to the position of the conductor to be detected; The image recognition module is used to recognize the wiring images of each wire corresponding to the position of the wire to be detected, and to obtain the wiring pattern of the wire corresponding to the position of the wire to be detected. The current detection module is used to adjust the position of the UAV induction coil according to the wire wiring method, so that the UAV induction coil can detect at least one wire to be detected corresponding to the position of the wire to be detected, and obtain the wire detection current corresponding to each wire to be detected. The current calculation module is used to calculate the fault calculation result based on the wire detection current corresponding to each of the wires to be tested; The information confirmation module is used to determine the fault detection information corresponding to the UAV based on the position of the conductor to be detected and the fault calculation result; The current calculation module includes: A type acquisition unit is used to acquire at least one fault detection type; The fault calculation unit is used to calculate the conductor detection current corresponding to each conductor to be detected according to each of the fault detection types, and to obtain the fault calculation result.

8. A fault detection device for unmanned aerial vehicles (UAVs), characterized in that, The UAV fault detection equipment includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the UAV fault detection method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the unmanned aerial vehicle (UAV) fault detection method according to any one of claims 1-6.

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