Electric equipment thermal fault diagnosis method and system and electronic device

A technology of power equipment and diagnostic methods, applied in the direction of electric radiation detectors, biological neural network models, neural architectures, etc., can solve problems such as error-prone, high professional knowledge and experience requirements, and low work efficiency

Active Publication Date: 2018-01-19
SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI +1
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Problems solved by technology

This diagnostic method can only recognize one infrared image at a time, which has low work effi

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  • Electric equipment thermal fault diagnosis method and system and electronic device
  • Electric equipment thermal fault diagnosis method and system and electronic device
  • Electric equipment thermal fault diagnosis method and system and electronic device

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[0058] In order to make the objectives, technical solutions and advantages of the present invention clearer, the following further describes the present invention in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, but not to limit the present invention.

[0059] The concept of deep learning is derived from artificial neural networks, and its research significance lies in the establishment and simulation of neural networks in the human brain, and the mechanism that imitates the human brain is used to understand and process various data for analysis and learning. Deep learning forms a more abstract high-level representation attribute category or feature by combining low-level features to discover distributed feature representations of data. The convolutional neural network model is a kind of deep learning method. The convolutional neural network m...

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Abstract

The invention relates to an electric equipment thermal fault diagnosis method and system and an electronic device. The method comprises the following steps: collecting an infrared image of electric equipment and constructing a convolutional neural network model on the basis of the infrared image; inputting a to-be-detected infrared image into the convolutional neural network model; identifying a temperature scale and electric equipment in the infrared image through the convolutional neural network model; generating an RGB value and temperature reference table on the basis of RGB values of pixels points of the identified temperature scale and upper and lower bounds of the temperature scale, extracting an RGB value of the identified electric equipment, comparing the extracted RGB value withRGB values in the RGB value and temperature reference table, and obtaining a temperature result of the identified electric equipment; carrying out diagnosis on the temperature result through a power grid system diagnosis standard, and determining whether thermal faults of the electric equipment occur. The electric equipment is identified in a highly efficient and accurate manner through the convolutional neural network model, the temperature is read accurately through the RGB value, and a power grid system is improved in intelligent level.

Description

technical field [0001] The invention relates to the technical field of grid system fault detection, in particular to a thermal fault diagnosis method, system and electronic equipment of electric power equipment. Background technique [0002] The substation is an important part of the power grid system, and the safe and stable operation of the power equipment in the substation is an important factor to ensure the reliability of power supply. Due to the long-term operation of power equipment and the influence of environmental factors, various failures often occur, usually in the form of overall or partial abnormal heating. Therefore, monitoring the temperature state of power equipment, and analyzing and diagnosing it according to the temperature state is of great significance for discovering hidden accidents, taking early measures to avoid vicious consequences, and ensuring safe and reliable operation of the power grid. [0003] Infrared thermal imaging technology is a non-co...

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Application Information

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IPC IPC(8): G01J5/10G06N3/04
Inventor 胡金星秦皓莫文雄张志亮王书强孙煜华吴永欢张文斐
Owner SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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