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Unmanned aerial vehicle image transmission tower collapse identification method based on deep learning

A technology of deep learning and power transmission towers, applied in scene recognition, character and pattern recognition, computer components, etc., can solve the problems of power transmission tower lodging data scarcity, work mistakes, physical and psychological burden, etc., to avoid poor training effect , Improve efficiency and accuracy, avoid cumbersome and inefficient effects

Inactive Publication Date: 2019-09-17
FUZHOU UNIV
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AI Technical Summary

Problems solved by technology

[0004] However, due to the scarcity of power transmission tower lodging data, the identification of UAV image tower lodging has been lack of in-depth research
Considering that in the process of manual inspection, inspectors will be physically and psychologically burdened by looking at pictures or images for a long time, which will lead to work mistakes and seriously affect the work efficiency of power inspection
At the same time, due to the huge image data of drones, the cost of manual inspection is extremely high

Method used

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  • Unmanned aerial vehicle image transmission tower collapse identification method based on deep learning
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  • Unmanned aerial vehicle image transmission tower collapse identification method based on deep learning

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Embodiment Construction

[0025] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0026] It should be pointed out that the following detailed description is exemplary and is intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0027] It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combina...

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Abstract

The invention relates to an unmanned aerial vehicle image transmission tower collapse identification method based on deep learning. The unmanned aerial vehicle image transmission tower collapse identification method comprises the steps: firstly, making a training data set and a verification data set, wherein the data set comprises two types of unmanned aerial vehicle images which comprise vertical towers and collapsed towers under different backgrounds; then establishing a deep learning model, and respectively taking a Faster R-CNN network based on ResNet and a Yolov3 network based on Darknet-53 as basic network structures for deep learning target detection; and carrying out data enhancement, training the deep learning model, solidifying and testing a detection model, carrying out model fusion, and finally identifying the tower image by utilizing the fused model. According to the invention, a deep learning target detection method is utilized to realize identification and fault detection of the transmission tower in the inspection process.

Description

technical field [0001] The invention relates to the field of electric power operation and maintenance inspection, in particular to a method for identifying lodging of power transmission poles and towers based on deep learning images of unmanned aerial vehicles. Background technique [0002] With the advent of the information age, more and more industries, commerce, and agriculture depend on the existence of electricity. The scale of the power grid continues to expand, and the operation and maintenance of transmission lines has become an important work content of the power sector. After a long period of operation and use, the transmission lines of the distribution network will be damaged to varying degrees. Sudden severe weather conditions, such as strong winds, ice and snow, etc., will cause damage to the transmission tower or even collapse. As the main supporting force of the transmission line, once the tower is damaged, the surrounding power equipment will be damaged to v...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/32G06K9/62
CPCG06V20/13G06V10/25G06F18/214
Inventor 陈静吴莉江灏缪希仁林珍
Owner FUZHOU UNIV
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