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Automatic transmission line identification system and method based on multilayer convolutional neural network

A convolutional neural network, automatic recognition system technology, applied in character and pattern recognition, image data processing, instruments, etc., can solve problems such as time-consuming and laborious, and achieve the effect of operating ability.

Inactive Publication Date: 2018-04-20
ELECTRIC POWER RESEARCH INSTITUTE OF STATE GRID SHANDONG ELECTRIC POWER COMPANY +2
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Problems solved by technology

The disadvantage is that it is time-consuming and labor-intensive, and needs to be redesigned according to specific problems and tasks

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  • Automatic transmission line identification system and method based on multilayer convolutional neural network
  • Automatic transmission line identification system and method based on multilayer convolutional neural network
  • Automatic transmission line identification system and method based on multilayer convolutional neural network

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Embodiment Construction

[0037] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0038] In view of the time-consuming and laborious problem of extracting feature operators by traditional methods such as PAST, LOG, HOG, SIFT, SURF, and HARRIS, convolutional neural networks (CNN) are mainly used to identify two-dimensional graphics that are invariant to displacement, scaling, and other forms of distortion. Since the feature detection layer of CNN learns through training data, when using CNN, it avoids explicit feature extraction and learns implicitly from training data; moreover, because the neuron weights on the same feature map Same, so the network can learn in parallel, which is also a big advantage of the convolutional network over the network of neurons connected to each other.

[0039] Convolutional neural network has unique advantages in speech recognition and image processing with its special structure of local weight...

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Abstract

The invention discloses an automatic transmission line identification system and method based on a multilayer convolutional neural network. The system comprises an equipment picture database, a targetdetection module, a target tracking module and a target identification module; the equipment picture database stores image or video information of obstacles on a transmission line in a classified way, and marks images or videos; the target detection module locates an obstacle target on the line in the video or image, and provides object position information of the present frame; according to thedetected object position information as well as prior information of structuring of the detection target, the target tracking module tracks the target online; and the target identification module identify types of different equipment online in different scales, backgrounds, illumination and angles. The system and method have the advantages that good characteristics that reflect the target can be learned automatically via deep learning, artificial design or redesign is not needed, execution can be realized via once training, and only model optimizing and multiple offline training are needed.

Description

technical field [0001] The invention belongs to the technical field of power system operation and fault diagnosis, and in particular relates to a transmission line automatic identification system and method based on a multi-layer convolutional neural network. Background technique [0002] At present, the image database of the power system for traditional transmission lines has problems such as few categories, insufficient quantity, single structure and scene, and can only be identified for specific tasks. The obstacles on the line vary greatly, the scale changes greatly, and the influence of light is very obvious. Especially affected by multiple factors such as one meaning with multiple images, one image with multiple objects, one object with multiple states, and foreign objects similar to each other, there are still many unresolved problems in reliable image recognition technology on transmission lines, and there is still a big gap from practical application. Especially fo...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06T7/00G06T7/246
CPCG06T7/0008G06T7/246G06T2207/10016G06T2207/20081G06T2207/20084G06T2207/30184G06T2207/30164G06V20/38G06V20/42G06V20/46
Inventor 郭锐李振宇张峰李勇吴观斌许玮慕世友李超英傅孟潮李建祥赵金龙王万国
Owner ELECTRIC POWER RESEARCH INSTITUTE OF STATE GRID SHANDONG ELECTRIC POWER COMPANY
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