Power transmission line foreign matter detection method based on an improved Faster RCNN

A foreign object detection and power transmission line technology, applied in biological neural network models, image data processing, image enhancement, etc., can solve problems such as unsatisfactory detection, and achieve the effect of improving the effect, speed and accuracy

Inactive Publication Date: 2019-03-19
CHINA UNIV OF PETROLEUM (EAST CHINA)
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Problems solved by technology

[0007] In order to solve the problem of unsatisfactory detection of foreign objects (balloons, films, kites, etc.) in transmission lines in complex scenes, the purpose of the present invention is to provide a method for detecting foreign objects in transmission lines based on improved Faster RCNN

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  • Power transmission line foreign matter detection method based on an improved Faster RCNN
  • Power transmission line foreign matter detection method based on an improved Faster RCNN

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Embodiment Construction

[0024] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0025] Such as figure 1 As shown, the present invention is based on the improved Faster RCNN transmission line foreign matter detection method, including the following basic steps: preprocessing the foreign matter pictures collected, increasing the scale of the training set; sharing the convolutional network part in the Faster RCNN Improve the network; adjust the anchor size ratio in the RPN network in Faster RCNN; conduct end-to-end joint training on the impr...

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Abstract

The invention provides a power transmission line foreign matter detection method based on an improved Faster RCNN, and the method comprises the following steps: carrying out the preprocessing of a collected foreign matter image, and increasing the scale of a training set; carrying out network improvement on the shared convolutional network part in the Faster RCNN; adjusting the size ratio of the anchor in the RPN network in the Faster RCNN; performing end-to-end joint training on the improved network; and carrying out foreign matter detection on the picture by using the trained detection model, framing the position of the foreign matter and identifying the type of the foreign matter. The invention relates to a power transmission line foreign matter detection method based on an improved Faster RCNN, which combines image processing and deep learning, and adopts the improved Faster RCNN to improve the accuracy of power transmission line foreign matter detection.

Description

technical field [0001] The invention relates to image processing, artificial intelligence, and deep learning, and in particular to an improved FasterRCNN-based transmission line foreign object detection method. Background technique [0002] The power system is of great significance to our country. The transmission line network is the main component of the system. It is very important to maintain the safety of the transmission line. In recent years, there have been frequent incidents of endangering the safety of the power grid due to hanging kites, balloons, and falling plastic films all over the country. The entanglement of these foreign objects in the transmission line will shorten the limit discharge distance of high-voltage electricity, which will cause pedestrians and vehicles under the transmission line Threat. Therefore, it is of great significance to find foreign matter in time and accurately, and then take corresponding removal measures. [0003] At present, there a...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06N3/04
CPCG06T7/0002G06T2207/20081G06N3/045
Inventor 张卫山刘霞耿祖琨
Owner CHINA UNIV OF PETROLEUM (EAST CHINA)
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