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Line inspection method and system based on unmanned aerial vehicle, and electronic equipment

A UAV and line technology, applied in neural learning methods, biological neural network models, fault detection by conductor type, etc., can solve problems such as inability to image processing technology.

Inactive Publication Date: 2022-02-25
HANGZHOU POLYTECHNIC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

During line inspection, many faults of the line cannot be monitored through images, for example, some faults occur inside the line, which cannot be well checked by some existing image processing technologies

Method used

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  • Line inspection method and system based on unmanned aerial vehicle, and electronic equipment
  • Line inspection method and system based on unmanned aerial vehicle, and electronic equipment
  • Line inspection method and system based on unmanned aerial vehicle, and electronic equipment

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Embodiment Construction

[0052] Hereinafter, exemplary embodiments according to the present application will be described in detail with reference to the accompanying drawings. Apparently, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments of the present application. It should be understood that the present application is not limited by the exemplary embodiments described here.

[0053] Scenario overview

[0054] As mentioned above, the existing drone cruise is based on analog video signals, and the video information captured by the drone is transmitted back to the online server, and fault prediction and inspection are performed based on image data. During line inspection, many faults of the line cannot be monitored through images. For example, some faults occur inside the line, which cannot be well checked by some existing image processing technologies. Therefore, a UAV-based line inspection method is expected.

[0055] That is t...

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Abstract

The invention relates to the field of line inspection, and particularly discloses a line inspection method and system based on an unmanned aerial vehicle and electronic equipment. According to the method, the core function of a line is current transmission, and the change of the current can cause the change of a magnetic field, so that the detected magnetic field values are processed, and a high-dimensional correlation mode between the magnetic field values of all points is mined based on a deep learning convolutional neural network, so that the electric transmission of a power transmission line is detected through the magnetic field value of each point on the power transmission line detected by an unmanned aerial vehicle during inspection. Through the mode, the detected magnetic field value can be prevented from being influenced by external factors, so that the final detection result is prevented from being influenced.

Description

technical field [0001] The present invention relates to the field of line inspection, and more specifically, relates to an unmanned aerial vehicle-based line inspection method, an unmanned aerial vehicle-based line inspection system and electronic equipment. Background technique [0002] In recent years, UAV technology has developed rapidly, and the use of UAVs for cruise detection has been widely used in various fields. China has a complex and huge power grid system, and the power grid distribution environment and scenarios are complex. Traditional manual inspection or online inspection cannot meet the inspection requirements of the entire power grid system. The application of UAV patrol monitoring to power grid inspection has a wide range of applications. market expectation. [0003] However, the existing drone cruise is based on analog video signals, and the video information captured by the drone is transmitted back to the online server, and fault prediction and inspect...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/08G06N3/04G06N3/08
CPCG01R31/085G06N3/08G06N3/045
Inventor 蔡吸礼黄煜栋
Owner HANGZHOU POLYTECHNIC
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