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Intelligent power plant electrical equipment fault diagnosis method based on width learning and temporal and spatial characteristics of infrared images

A technology of infrared images and electrical equipment, which is applied in image analysis, image data processing, electrical measurement, etc., and can solve the problems of limited quantitative analysis of infrared images

Active Publication Date: 2019-06-11
ZHEJIANG UNIV
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Problems solved by technology

[0003] The purpose of this invention is to propose a fast temperature soft sensor and its Fault Diagnosis Strategy of Target Power Equipment

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  • Intelligent power plant electrical equipment fault diagnosis method based on width learning and temporal and spatial characteristics of infrared images
  • Intelligent power plant electrical equipment fault diagnosis method based on width learning and temporal and spatial characteristics of infrared images
  • Intelligent power plant electrical equipment fault diagnosis method based on width learning and temporal and spatial characteristics of infrared images

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Embodiment Construction

[0064] The invention discloses a fault diagnosis method for electrical equipment in an intelligent power plant based on width learning and infrared image spatiotemporal features, aiming at analyzing the spatiotemporal attributes of infrared images, combining image texture information and temperature time series change information, and using width learning to complete electrical equipment. Troubleshooting. First of all, for the infrared precision inspection data in the power plant, fit the relationship between gray value and temperature value, and complete temperature soft measurement, so as to solve the problem of the special and uncommon image format of the infrared thermal imager, and the expensive and functional accompanying processing software. different question. Then, based on the optimal threshold segmentation method, the key target electrical equipment is extracted from the image, thus avoiding the interference of complex background on fault diagnosis. Aiming at the e...

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Abstract

The invention discloses an intelligent power plant electrical equipment fault diagnosis method based on width learning and temporal and spatial characteristics of infrared images. The method is characterized by analyzing temporal and spatial characteristics of the infrared images, combining image texture information and temperature temporal variation information, and completing electrical equipment fault diagnosis by using width learning. The method is capable of extracting target power equipment needed to be analyzed in each infrared image in extremely short time and giving corresponding temperature information, solving the defect that the infrared images can only be analyzed by using specially-equipped random software, deeply exploring temporal and spatial attributes of the infrared images, analyzing the infrared images at multiple dimensions and improving effectiveness and accuracy of the infrared diagnosis technique.

Description

technical field [0001] The invention belongs to the field of electrical equipment maintenance based on infrared diagnosis technology, in particular to a fault diagnosis method for electrical equipment in an intelligent power plant based on width learning and infrared image spatiotemporal features. Background technique [0002] Infrared fault diagnosis technology uses the principle of infrared thermal imaging to display the temperature distribution on the surface of the equipment to judge the internal conditions of the equipment. It has the characteristics of intuitive graphics, accurate judgment, safety and reliability, and high diagnostic efficiency. It has played an important role in the preventive maintenance of electrical equipment. Nowadays, many power groups are equipped with advanced infrared thermal imagers, which are used to detect voltage-induced or current-induced heating defects in power transmission and transformation equipment, such as poor lead contact of main ...

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Application Information

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IPC IPC(8): G01R31/00G01J5/00G06T7/00G06T7/11G06T7/136G06T7/45G06T7/62
Inventor 赵春晖王晶
Owner ZHEJIANG UNIV
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