A Classification Method of Power Image Based on Deep Learning

A technology of deep learning and classification methods, applied in the fields of instruments, character and pattern recognition, computer parts, etc., can solve problems such as failure of training models

Active Publication Date: 2017-12-12
STATE GRID CORP OF CHINA +1
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Problems solved by technology

[0005] In some existing deep learning-based processing platforms, such as the invention patent with application number 201310739026.3 and the invention patent with application number 201410138343.4, there are obvious limitations in processing large-scale image data similar to electric equipment: that is, when a When the same type of training data is continuously input for a period of time, the training model will fail

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  • A Classification Method of Power Image Based on Deep Learning
  • A Classification Method of Power Image Based on Deep Learning
  • A Classification Method of Power Image Based on Deep Learning

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Embodiment Construction

[0077] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0078] A method for classifying electric power images based on deep learning, comprising the following steps:

[0079] Step S1: class-by-class emission of the input image;

[0080] The invention adopts an out-of-sequence transmission mechanism in the data preprocessing stage, which can effectively solve the failure problem of the training model. The preprocessing launch mechanism is attached figure 2 shown.

[0081] There are two caches used in this mechanism.

[0082] The first buffer is used to store the latest 256 pictures to be processed, and the control unit will select the appropriate data type from it, and input it into the second buffer to wait for transmission.

[0083] In the second cache, the images are sorted according to the type label. For example, taking five kinds of training pictures as an example, the queue is 0, 1, 2, 3, 4, 0, 1,...

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Abstract

The invention discloses a method for classifying electric power images based on deep learning. The buffer area is used to store several images to be processed, and several images are selected from the first buffer area to be stored in the second buffer area, and the images in the second buffer area are queued for transmission; the power image is extracted; Enhance the image after region extraction; adjust the size of the enhanced image, and format the image to meet the input of the classifier; input the data into the classifier and select a different training set The size and training speed are tested multiple times, and the classification accuracy and efficiency are compared and analyzed, and the optimal training parameters are selected to obtain the best training effect. Compared with the traditional technology, the present invention has obvious advantages, the convergence speed of training is faster and the accuracy rate is higher.

Description

technical field [0001] The invention relates to a power image classification method based on deep learning. Background technique [0002] As the lifeblood of the national economy and security, the safe operation of the power grid has always been the core and essential requirement of the power grid. In order to ensure the safety of the high-voltage power transmission and transformation grid, a large number of sensors have been deployed in the power transmission and transformation system. However, the function of a sensor with a single function cannot fully meet the needs of power grid security. In recent years, an important auxiliary solution is to use monitoring equipment to collect video images, manually evaluate the status of power transmission and transformation equipment, and take corresponding measures to solve the fault. However, manually classifying huge streaming media files will consume a lot of manpower and time, and the efficiency is also very low, which makes th...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/66G06K9/62
CPCG06V10/32G06F18/2321G06F18/214G06F18/241
Inventor 杜修明杨祎郭志红陈玉峰祝永新印俊张锦逵孙英涛冯新岩
Owner STATE GRID CORP OF CHINA
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