Insulator defect identification and positioning device and method based on capsule network

Abstract

Insulator defect identification and positioning device and method based on capsule network, Deep learning model is established. Target detection based on capsule network structure is adopted. Parameters of convolution layer, capsule layer and decision layer of capsule network are initially configured. Existence and posture of insulators are detected by training set and patrol image training, and parameters of decision layer are predicted. The original machine patrols the image to be discriminated, outputs the specific position of the insulator through the capsule network, segments the image and extracts the image for standby, and calls the insulator feature extraction module to the segmented image. The extracted insulator characteristic string is divided into upper and lower parts, and theinsulator characteristic map obtained after the threshold value division is scanned line by line, the pixel points of each line are counted, the maximum connecting area where the insulator is locatedis determined, the main axis direction of the insulator is calculated, the insulator is rotated to the horizontal direction, and the abnormal position of the insulator is obtained. The invention greatly improves the efficiency of insulator defect identification, and provides reliable technical support for the power network maintenance department.

Description

technical field [0001] The invention relates to the technical field of transmission line maintenance in a smart grid, in particular to an insulator defect identification and positioning device and method based on a capsule network. Background technique [0002] Capsule network is a new and popular neural network architecture that has a profound impact on deep learning, especially in the field of computer vision. A capsule network is composed of capsules rather than neurons. A capsule is a small group of neurons that can learn to inspect a specific object (say, a rectangle) within a certain area of ​​an image. Its output is a vector (for example, an 8-dimensional vector). The length of each vector represents the estimated probability of the presence or absence of the object, and its orientation (e.g. in 8-dimensional space) records the pose parameters of the object (e.g., precise position, rotation, etc.). If the object changes slightly (e.g., moves, rotates, changes size,...

AI Technical Summary

Problems solved by technology

[0009] The purpose of the present invention is to provide a device and method for identifying and locating insulator defects based on a capsule network, which can solve the problem of the poor robustness of the existing defect identification algorithm for insulators based on machine patrol images under the complex background interference brought by various geographical environments problems, can greatly improve the efficiency of insulator defect identification, and provide reliable technical support for power grid maintenance departments

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