Insulator evaluation and classification method and device based on infrared image

Abstract

The invention discloses an insulator evaluation and classification method and device based on infrared images. The method comprises the steps of acquiring an insulator infrared spectrum sample library; cutting the obtained images of the insulator infrared spectrum sample library to obtain a normal insulator library as a positive sample and a deteriorated insulator library as a negative sample; graying the images in the positive sample and the negative sample; processing the image after graying processing by using a principal component analysis method; and training the image processed by the principal component analysis method and the characteristics of the insulator state by adopting a Bayesian algorithm to obtain a corresponding relationship between characteristic parameters and the insulator state and model prediction parameters, thereby realizing classification and identification of the insulator. According to the technical scheme of the invention, the method can adapt to a complexfield environment, achieves the automatic recognition and diagnosis of the insulator in the infrared image, effectively reduces the false detection, and improves the efficiency and accuracy.

Description

technical field [0001] The invention relates to the field of electrical testing, in particular to an infrared image-based insulator evaluation and classification method and a device thereof. Background technique [0002] Insulators are an important component of transmission lines. With the increase of operating years, the electrical or mechanical properties of some insulators exposed to outdoor operating lines will decline to varying degrees. The specific manifestations are: insulation performance decline, mechanical strength decline, the ceramic parts will crack or even break, resulting in a decrease in the resistance of the insulator, becoming a deteriorated insulator, increasing the possibility of flashover of the insulator string, and even causing the string of insulators to drop, leading to serious accidents such as wire falling off. Grid security poses a threat. [0003] Insulators are used in transmission lines and substations, and the operating environment of most i...

AI Technical Summary

Problems solved by technology

The spark fork method is a traditional detection method, which needs to be detected manually when the line is out of service. This detection method consumes a lot of manpower, material resources and time

Due to the backwardness of the detection means, it is susceptible to electromagnetic interference, even if the inspection is carried out once a year, there are still hidden dangers that cannot be completely eliminated, resulting in missed or false detections

Especially in recent years, due to the aggravation of environmental pollution, in the case of smog, the dirty particles covered on the surface of insulators have a great impact on the heating characteristics of insulators, and also greatly interfere with the online detection of deteriorated insulators

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