Intelligent cable inspection system

Abstract

The embodiment of the application discloses a kind of intelligent cable inspection systems, the system includes: complexity determination module is configured to receive the area image photographed in unmanned aerial vehicle inspection process, the area image is identified to obtain area complexity, the area complexity includes image complexity and line complexity;Parameter determination module is configured to determine the inspection parameter of the unmanned aerial vehicle according to the area complexity, the inspection parameter includes flight height, flight speed, flight direction and image shooting accuracy;Control module is configured to send the inspection parameter to the unmanned aerial vehicle, to control the unmanned aerial vehicle according to the inspection parameter to carry out the shooting of area image.The scheme improves the flight inspection efficiency of unmanned aerial vehicle, and possible line fault can be found more timely.

Description

TECHNICAL FIELD

[0001] The embodiment of the present application relates to the technical field of cable, in particular to an intelligent cable inspection system. BACKGROUND

[0002] In recent years, with the popularization of intelligent cable, the use range of cable is more and more wide. In order to ensure the normal operation of cable equipment, it is necessary to carry out regular inspection and patrol. Through regular inspection and patrol, defects and safety hazards in cable equipment can be found in time, so as to achieve the purpose of eliminating defects and reducing fault loss in time.

[0003] In the prior art, patent CN109002057A discloses an intelligent inspection unmanned aerial vehicle system for cable tunnel, specifically discloses that the system comprises an electronic circuit module, a multi-rotor unmanned aerial vehicle and a detection sensor module. The electronic circuit module comprises an electronic circuit, an ARM, a memory and a control program. The detection sensor module comprises a humidity sensor, an acceleration sensor, a gyroscope sensor, a laser, an image sensor, a temperature sensor and an ultrasonic sensor. The multi-rotor unmanned aerial vehicle comprises a sensor fixing support, a multi-rotor and an electronic circuit fixing position. The system realizes unmanned aerial vehicle inspection operation for cable tunnel, locates fault position, reduces the occurrence of cable disasters, ensures the reliable output of electric energy, avoids the harm to operators, and is beneficial to improving the automation degree of power transmission network safety monitoring and promoting the construction of smart grid. However, the inspection system disclosed in the above scheme has relatively single function, lacks reasonable determination of inspection parameters, has low inspection efficiency, and can only complete basic inspection function, which needs to be improved. SUMMARY

[0004] The embodiment of the present application provides an intelligent cable inspection system, solves the problem of low intelligent cable inspection efficiency in the prior art, improves the flight inspection efficiency of the unmanned aerial vehicle, and can discover possible line faults more timely.

[0005] In a first aspect, the embodiment of the present application provides an intelligent cable inspection system, which comprises:

[0006] A complexity determination module configured to receive regional images shot in the unmanned aerial vehicle inspection process, identify the regional images to obtain regional complexity, and the regional complexity comprises image complexity and line complexity.

[0007] A parameter determination module configured to determine the inspection parameters of the unmanned aerial vehicle according to the regional complexity, and the inspection parameters comprise flight height, flight speed, flight direction and image shooting accuracy.

[0008] A control module configured to send the inspection parameters to the unmanned aerial vehicle to control the unmanned aerial vehicle to shoot regional images according to the inspection parameters.

[0009] Optionally, the complexity determining module is configured to:

[0010] identify the area image, determine image complexity according to a clarity result and an object category result obtained by the identification; and identify a line of the area image, and determine line complexity according to a result of the line identification.

[0011] Optionally, the parameter determining module is configured to:

[0012] determine image shooting precision according to the image complexity, the image shooting precision including shooting zoom multiple and shooting resolution;

[0013] determine flight height, flight speed and flight direction of the unmanned aerial vehicle according to the line complexity.

[0014] Optionally, the parameter determining module is configured to: if an overlap index in the line complexity is greater than a preset overlap index value, determine a plurality of different flight directions according to line directions;

[0015] if a line identification index in the line complexity is greater than a preset identification index value, reduce the flight height and the flight speed of the unmanned aerial vehicle.

[0016] In a second aspect, an embodiment of the present application further provides an intelligent cable inspection method, comprising:

[0017] receiving area images shot in an unmanned aerial vehicle inspection process, identifying the area images to obtain area complexity, the area complexity including image complexity and line complexity;

[0018] determining inspection parameters of the unmanned aerial vehicle according to the area complexity, the inspection parameters including flight height, flight speed, flight direction and image shooting precision;

[0019] sending the inspection parameters to the unmanned aerial vehicle to control the unmanned aerial vehicle to shoot area images according to the inspection parameters.

[0020] Optionally, the identifying the area images to obtain area complexity comprises:

[0021] identifying the area images, determining image complexity according to a clarity result and an object category result obtained by the identification; and identifying a line of the area images, and determining line complexity according to a result of the line identification.

[0022] Optionally, the determining inspection parameters of the unmanned aerial vehicle according to the area complexity comprises:

[0023] determine an image shooting precision according to the image complexity, the image shooting precision comprising a shooting zoom factor and a shooting resolution;

[0024] determine a flight height, a flight speed and a flight direction of the UAV according to the line complexity.

[0025] Optionally, the determining of the flight height, the flight speed and the flight direction of the UAV according to the line complexity comprises:

[0026] if the overlap index in the line complexity is greater than a preset overlap index value, determining a plurality of different flight directions according to a line direction;

[0027] if a line recognition index in the line complexity is greater than a preset recognition index value, reducing the flight height and the flight speed of the UAV.

[0028] In a third aspect, an embodiment of the present application further provides an intelligent cable inspection device for determining an inspection parameter according to a region complexity, the device comprising:

[0029] one or more processors;

[0030] a storage device configured to store one or more programs,

[0031] when the one or more programs are executed by the one or more processors, the one or more processors implement the intelligent cable inspection method according to the embodiment of the present application.

[0032] In a fourth aspect, an embodiment of the present application further provides a storage medium storing computer executable instructions, the computer executable instructions being used to execute the intelligent cable inspection method according to the embodiment of the present application when executed by a computer processor.

[0033] In the embodiment of the present application, the complexity determination module is configured to receive a region image shot in a UAV inspection process, and to obtain a region complexity by recognizing the region image, the region complexity comprising an image complexity and a line complexity; the parameter determination module is configured to determine an inspection parameter of the UAV according to the region complexity, the inspection parameter comprising a flight height, a flight speed, a flight direction and an image shooting precision; and the control module is configured to send the inspection parameter to the UAV, so as to control the UAV to shoot the region image according to the inspection parameter. The present application solves the problem of low intelligent cable inspection efficiency in the prior art, improves the flight inspection efficiency of the UAV, and can discover possible line faults in a more timely manner. BRIEF DESCRIPTION OF DRAWINGS

[0034] Figure 1 a flowchart of an intelligent cable inspection method according to an embodiment of the present application.

[0035] Figure 2 A flow chart of another intelligent cable inspection method provided for the embodiment of the present application;

[0036] Figure 3 A module structure block diagram of an intelligent cable inspection system provided for the embodiment of the present application;

[0037] Figure 4 A structural schematic diagram of an intelligent cable inspection device provided for the embodiment of the present application, which determines the inspection parameters according to the complexity of the region. DETAILED DESCRIPTION

[0038] The embodiment of the present application will be further described in detail below in combination with the drawings and embodiments. It can be understood that the specific embodiments described herein are only used to explain the embodiment of the present application, but not to limit the embodiment of the present application. In addition, it should be noted that, in order to facilitate the description, only the parts related to the embodiment of the present application are shown in the drawings, but not all the structures.

[0039] Figure 1 A flow chart of an intelligent cable inspection method provided for the embodiment of the present application, specifically comprising the following steps:

[0040] Step S101, receiving the region image photographed in the process of unmanned aerial vehicle inspection, and obtaining the region complexity by identifying the region image, the region complexity including image complexity and line complexity.

[0041] In an embodiment, the cable line such as high-voltage cable is inspected by using unmanned aerial vehicle. In the process of inspection, the unmanned aerial vehicle photographs the region image by the camera carried by the unmanned aerial vehicle. For example, when the unmanned aerial vehicle flies above the cable, the region image of a certain region is photographed. As the unmanned aerial vehicle flies, the region image also changes accordingly.

[0042] In an embodiment, the scheme execution subject can be an intelligent cable control center platform. After receiving the region image photographed in the process of unmanned aerial vehicle inspection, the region complexity is obtained by processing. Optionally, the region complexity is obtained by identifying the region image. The region complexity is used to represent the complexity of the information contained in the photographed region. Specifically, the region complexity includes image complexity and line complexity. The image complexity refers to the clarity of the content contained in the image, such as whether the object contained in the image can be clearly distinguished. The lower the clarity, the higher the image complexity. The image complexity also refers to the complexity of the types of objects contained in the image, such as the more types, the higher the image complexity. The line complexity refers to the complexity of the line contained in the region image, such as the more lines, the higher the line complexity.

[0043] Optionally, the identifying the region image to obtain a region complexity comprises: identifying the region image to determine an image complexity according to a clarity result and an object category result obtained by the identifying; and performing line identification on the region image to determine a line complexity according to a result of the line identification. Specifically, when the unmanned aerial vehicle is at a high flight height, the corresponding image captured cannot clearly distinguish the cable and identify the condition of the cable, and thus the clarity result corresponds to a low clarity. Conversely, the clarity result corresponds to a high clarity. The object category result is the number of object categories identified from the image, such as cables, houses, trees, ground, or only cables and ground, and the more the number of categories, the higher the image complexity. When the region image is subjected to line identification, the number of cable lines is identified, such as 1 cable, 2 cables, or a plurality of complex cables, and the more the number of cables, the higher the line complexity.

[0044] In step S102, the inspection parameters of the unmanned aerial vehicle are determined according to the region complexity, and the inspection parameters include a flight height, a flight speed, a flight direction, and an image capturing accuracy.

[0045] In one embodiment, the inspection parameters of the unmanned aerial vehicle are determined according to the determined region complexity. Optionally, the inspection parameters include a flight height, a flight speed, a flight direction, and an image capturing accuracy.

[0046] Specifically, the determining the inspection parameters of the unmanned aerial vehicle according to the region complexity comprises: determining an image capturing accuracy according to the image complexity, the image capturing accuracy including a capturing zoom factor and a capturing resolution; and determining a flight height, a flight speed, and a flight direction of the unmanned aerial vehicle according to the line complexity. The image complexity and the line complexity can be divided into a plurality of levels, different levels of the image complexity correspond to different image capturing accuracies set, and different levels of the line complexity correspond to different flight heights, flight speeds, and flight directions of the unmanned aerial vehicle set.

[0047] For example, the higher the image complexity, the higher the image capturing accuracy, the image capturing accuracy including a capturing zoom factor and a capturing resolution. The higher the line complexity, the lower the flight height of the unmanned aerial vehicle, the slower the flight speed, and the flight direction changes from a single flight direction to a multi-angle back-and-forth flight direction.

[0048] Specifically, the determining the image capturing accuracy according to the image complexity can refer to the following table:

[0049] Clarity results Object class results Shooting zoom Shooting resolution High Less than 3 1：1 240P Low Less than 3 1：2 480p High More than 3 1：4 240P Low More than 3 1：8 480p

[0050] Specifically, determining the UAV's flight altitude, speed, and direction based on the route complexity includes: if the overlap index in the route complexity is greater than a preset overlap index value, then determining multiple different flight directions based on the route direction; if the route recognition index in the route complexity is greater than a preset recognition index value, then reducing the UAV's flight altitude and speed. The overlap index is determined by the degree of route overlap identified in the image, such as an overlap index of 60%.

[0051] When the overlap index is determined to be greater than a preset overlap index value (exemplarily 0.4), multiple different flight directions are determined based on the route direction, such as forward, reverse, and diagonal flight directions. The route recognition index refers to the number of routes identified in the image. For example, if two routes are identified, the route recognition index is 2; if four routes are identified, the route recognition index is 4. The preset recognition index value is exemplarily set to 3. That is, when the route recognition index in the route complexity is greater than the preset recognition index value, the UAV's flight altitude and speed are reduced; the specific reduction in flight altitude and speed is not limited.

[0052] Step S103: Send the inspection parameters to the UAV to control the UAV to take pictures of the area based on the inspection parameters.

[0053] After determining the inspection parameters, they are sent to the drone, which then takes pictures of the area based on these parameters. Finally, images that meet the recognition requirements are transmitted back, ensuring the drone's inspection efficiency.

[0054] As described above, by receiving regional images captured during UAV inspection, the complexity of the region is determined through image recognition, including image complexity and line complexity. Based on this complexity, inspection parameters for the UAV are determined, including flight altitude, flight speed, flight direction, and image capture accuracy. These parameters are then sent to the UAV to control it to capture regional images. This solves the problem of low efficiency in existing intelligent cable inspection technologies, improves the efficiency of UAV flight inspections, and enables more timely detection of potential line faults. This solution can adaptively adjust inspection parameters, and the determination of these parameters is based on the complexity of various settings, ensuring both inspection efficiency and the acquisition of satisfactory image information.

[0055] Figure 2 A flowchart of another intelligent cable inspection method provided in an embodiment of the present invention is shown below. Figure 2 As shown, a specific and complete example is given. Specifically, it includes:

[0056] Step S201, receiving the region image photographed in the process of unmanned aerial vehicle inspection, identifying the region image, determining the image complexity according to the clarity result and the object category result obtained by identification; performing line identification on the region image, and determining the line complexity according to the result of the line identification, wherein the region complexity includes the image complexity and the line complexity.

[0057] Step S202, determining the image shooting accuracy according to the image complexity, wherein the image shooting accuracy includes the shooting zoom factor and the shooting resolution; if the overlap index in the line complexity is greater than a preset overlap index value, determining a plurality of different flight directions according to the line direction; and if the line identification index in the line complexity is greater than a preset identification index value, reducing the flight height and the flight speed of the unmanned aerial vehicle.

[0058] Step S203, sending the inspection parameter to the unmanned aerial vehicle to control the unmanned aerial vehicle to shoot the region image according to the inspection parameter.

[0059] According to the above scheme, the region complexity is obtained by receiving the region image photographed in the process of unmanned aerial vehicle inspection and identifying the region image, wherein the region complexity includes the image complexity and the line complexity; the inspection parameter of the unmanned aerial vehicle is determined according to the region complexity, wherein the inspection parameter includes the flight height, the flight speed, the flight direction and the image shooting accuracy; and the inspection parameter is sent to the unmanned aerial vehicle to control the unmanned aerial vehicle to shoot the region image according to the inspection parameter, thereby solving the problem of low intelligent cable inspection efficiency in the prior art, improving the flight inspection efficiency of the unmanned aerial vehicle, and enabling possible line faults to be discovered more timely.

[0060] Figure 3 A module structure block diagram of an intelligent cable inspection system is provided for the embodiments of the present application, the intelligent cable is used to execute the intelligent cable inspection method provided by the above embodiments, and has the corresponding function modules and beneficial effects of the execution method. As shown in the figure, the system specifically includes: a complexity determination module 101, a parameter determination module 102 and a control module 103, wherein, Figure 3

[0061] The complexity determination module 101 is configured to receive the region image photographed in the process of unmanned aerial vehicle inspection, identify the region image to obtain the region complexity, and the region complexity includes the image complexity and the line complexity.

[0062] The parameter determination module 102 is configured to determine the inspection parameter of the unmanned aerial vehicle according to the region complexity, and the inspection parameter includes the flight height, the flight speed, the flight direction and the image shooting accuracy.

[0063] ​The control module 103 is configured to send the inspection parameter to the unmanned aerial vehicle to control the unmanned aerial vehicle to shoot the area image according to the inspection parameter.

[0064] According to the above scheme, the complexity determination module is configured to receive the area image shot in the unmanned aerial vehicle inspection process, identify the area image to obtain the area complexity, the area complexity includes the image complexity and the line complexity; the parameter determination module is configured to determine the inspection parameter of the unmanned aerial vehicle according to the area complexity, the inspection parameter includes the flight height, the flight speed, the flight direction and the image shooting accuracy; the control module is configured to send the inspection parameter to the unmanned aerial vehicle to control the unmanned aerial vehicle to shoot the area image according to the inspection parameter. The scheme improves the flight inspection efficiency of the unmanned aerial vehicle, and can discover possible line faults more timely.

[0065] In one possible embodiment, the complexity determination module is configured to:

[0066] Identify the area image, determine the image complexity according to the clarity result and the object type result obtained by identification; identify the line of the area image, and determine the line complexity according to the result of the line identification.

[0067] In one possible embodiment, the parameter determination module is configured to:

[0068] Determine the image shooting accuracy according to the image complexity, the image shooting accuracy includes the shooting zoom multiple and the shooting resolution;

[0069] Determine the flight height, the flight speed and the flight direction of the unmanned aerial vehicle according to the line complexity.

[0070] In one possible embodiment, the parameter determination module is configured to:

[0071] If the overlap index in the line complexity is greater than a preset overlap index value, a plurality of different flight directions are determined according to the line direction;

[0072] If the line identification index in the line complexity is greater than a preset identification index value, the flight height and the flight speed of the unmanned aerial vehicle are reduced.

[0073] Figure 4 A structural schematic diagram of an intelligent cable inspection equipment for determining an inspection parameter according to an area complexity provided by an embodiment of the present application is shown in FIG. 1. Figure 4 As shown in the figure, the equipment includes a processor 201, a memory 202, an input device 203 and an output device 204; the number of processors 201 in the equipment can be one or more, Figure 4The processor 201 in the device, the memory 202, the input device 203 and the output device 204 can be connected through a bus or other means, Figure 4 The memory 202 is a computer readable storage medium, which can be used to store software programs, computer executable programs and modules, such as program instructions / modules corresponding to the intelligent cable inspection method in the embodiment of the application. The processor 201 executes various functions and data processing of the device by running the software programs, instructions and modules stored in the memory 202, that is, implements the intelligent cable inspection method described above. The input device 203 can be used to receive input digital or character information, and generate key signal input related to user settings and function control of the device. The output device 204 can include a display device such as a display screen.

[0074] The embodiment of the application also provides a storage medium containing computer executable instructions, which are used to execute an intelligent cable inspection method when executed by a computer processor, and the method comprises:

[0075] Receiving regional image photographed in a UAV inspection process, identifying the regional image to obtain a regional complexity, the regional complexity including image complexity and line complexity;

[0076] Determining an inspection parameter of the UAV according to the regional complexity, the inspection parameter including flight height, flight speed, flight direction and image photographing accuracy;

[0077] Sending the inspection parameter to the UAV to control the UAV to photograph regional image according to the inspection parameter.

[0078] Optionally, the identifying the regional image to obtain the regional complexity comprises:

[0079] Identifying the regional image, determining the image complexity according to the clarity result and the object type result obtained by identification; identifying the regional image, determining the line complexity according to the result of the line identification.

[0080] Optionally, the determining the inspection parameter of the UAV according to the regional complexity comprises:

[0081] Determining the image photographing accuracy according to the image complexity, the image photographing accuracy including photographing zoom multiple and photographing resolution;

[0082] Determining the flight height, the flight speed and the flight direction of the UAV according to the line complexity.

[0083] Optionally, the determining the flight height, the flight speed and the flight direction of the unmanned aerial vehicle according to the line complexity comprises:

[0084] if the overlap index in the line complexity is greater than a preset overlap index value, determining a plurality of different flight directions according to the line direction;

[0085] if the line identification index in the line complexity is greater than a preset identification index value, reducing the flight height and the flight speed of the unmanned aerial vehicle.

[0086] It is worth noting that the embodiments of the intelligent cable inspection system device described above include various units and modules only according to the logical division of functions, but are not limited to the above division, as long as the corresponding functions can be realized. In addition, the specific names of each functional unit are only for easy mutual distinction, and are not intended to limit the protection scope of the embodiments of the present application.

[0087] Note that the above are only preferred embodiments of the present application and the technical principles applied. Those skilled in the art will understand that the embodiments of the present application are not limited to the specific embodiments described herein, and those skilled in the art can make various obvious changes, readjustments and substitutions without departing from the scope of the embodiments of the present application. Therefore, although the embodiments of the present application have been described in more detail through the above embodiments, the embodiments of the present application are not limited to the above embodiments, and can include more other equivalent embodiments without departing from the concept of the embodiments of the present application, and the scope of the embodiments of the present application is determined by the scope of the appended claims.

Claims

1. An intelligent cable inspection system, characterized in that, a complexity determination module configured to receive a region image captured during a UAV inspection process, identify the region image, determine an image complexity according to a clarity result and an object category result obtained through the identification, perform line identification on the region image, and determine a line complexity according to a result of the line identification; a parameter determination module configured to determine an image capturing precision according to the image complexity, the image capturing precision including a capturing zoom factor and a capturing resolution, determine a plurality of different flight directions according to a line direction if an overlap index in the line complexity is greater than a preset overlap index value, and reduce a flight height and a flight speed of the UAV if a line identification index in the line complexity is greater than a preset identification index value; a control module configured to send the inspection parameter to the UAV to control the UAV to capture a region image according to the inspection parameter.

2. The method of claim 1, wherein the method comprises: including: receiving a region image captured during a UAV inspection process, identifying the region image, determining an image complexity according to a clarity result and an object category result obtained through the identification, performing line identification on the region image, and determining a line complexity according to a result of the line identification; determining an image capturing precision according to the image complexity, the image capturing precision including a capturing zoom factor and a capturing resolution, determining a plurality of different flight directions according to a line direction if an overlap index in the line complexity is greater than a preset overlap index value, and reducing a flight height and a flight speed of the UAV if a line identification index in the line complexity is greater than a preset identification index value; sending the inspection parameter to the UAV to control the UAV to capture a region image according to the inspection parameter.

3. An intelligent cable inspection apparatus for determining inspection parameters based on the complexity of a region, the apparatus comprising: one or more processors; a storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, the one or more processors implement the intelligent cable inspection method of claim 2.

4. A storage medium storing computer executable instructions for executing the intelligent cable inspection method of claim 2 when executed by a computer processor.

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