Insulator fault detection and fault rating method based on image analysis

Abstract

The invention discloses an insulator fault detection and fault rating method based on image analysis. The method comprises the steps of preprocessing a to-be-processed image; detecting the edge of the insulator; carrying out region segmentation by utilizing an improved region growth algorithm; and determining a fault by detecting the shape characteristics of the insulator area and the edge, and carrying out fault rating. According to the method, fault detection can be effectively carried out on the overhead line system insulator, the calculation amount of the algorithm is small, the area growth algorithm with the background point as the starting point is used, interference of the surface texture of the insulator is avoided, and the fault detection accuracy is guaranteed. The missing detection rate is 0.5% or below, the fault detection accuracy is 95% or above, and the actual engineering requirements are met. The invention particularly provides a feasible scheme for image analysis-based fault detection with insufficient negative samples, provides an index for judging the fault level, and is helpful for making reasonable response to consideration of factors of comprehensive safety and economy in engineering.

Description

technical field [0001] The invention belongs to the technical field of image processing and analysis, and in particular relates to a fault detection method for a catenary insulator. Background technique [0002] The catenary is an important part in the construction of electrified transmission lines. It is erected on the lines along the railway line through the pillar equipment along the line. Electric locomotives mainly obtain the electrical energy required for operation through the transmission of the catenary, so it is very important to ensure the good working condition of the catenary at all times. In the catenary system, the insulator is one of the important parts of the suspension device in addition to the mechanical support. Because the working environment of insulators needs to be exposed to the atmospheric environment for a long time, and also needs to withstand strong electric fields and strong mechanical stress for a long time, the probability of failure is high, ...

AI Technical Summary

Problems solved by technology

Damage to the ceramic body of the insulator will reduce its insulation strength. If it is not found and replaced for a long time, it will cause the porcelain bottle to break and cause other unpredictable failures in the circuit

At present, the traditional manual detection has low efficiency, high work intensity, and high risk factor. The electric field method cannot detect some external insulation defects that do not affect the electric field. These detection methods do not have certain practicability

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