Aerial image insulator real-time detection method based on deep learning

Abstract

The invention relates to an aerial image insulator real-time detection method based on deep learning. The aerial image insulator real-time detection method based on deep learning includes the steps: handing a task of extracting characteristics to a deep convolutional neural network, extracting the deep characteristic information which is more comprehensive and can preferably describe an insulator,and inputting the deep characteristic information into a detector to perform prediction inference to obtain a detection result. For the aerial image insulator real-time detection method based on deeplearning, the whole process is an end-to-end quick detection channel; a target frame is obtained after the image is input; the efficiency of subsequent automatic fault diagnosis is improved; and theaerial image insulator real-time detection method based on deep learning is conductive to reducing the retrieval pressure and intensity when the line patrol staff retrieves the mass line patrol data at present. And at the same time, the aerial image insulator real-time detection method based on deep learning also utilizes the idea of transfer learning to transfer the knowledge obtained from the past task to the current target task, so as to enable the trained model to have inheritability; whenever new data is added into an image library, the target model can continue to train new data on the basis of a source model, so as to quickly achieve the expected effect and enable the old version of model not to be of no use at all because of updating of data; and the detection model can become moreand more powerful following increase of data as time goes on.

Description

technical field [0001] The invention relates to the field of high-voltage transmission line inspection technology and image recognition technology, and in particular to a real-time detection method for insulators based on aerial photography images based on deep learning. Background technique [0002] The inspection of transmission lines is one of the important means to ensure the safe and reliable operation of the power system. The power sector has to invest a lot of manpower and material resources in inspections every year. Traditional manual line inspection has problems of high risk, high cost, and low efficiency. The emergence of drones provides a new means of line inspection for the power sector. However, the current method of using UAVs for line inspection work is that the pilots control the UAVs, fly around the key components of the transmission line to take pictures, and the professionals on the ground analyze them on the spot, or bring the data back to the inspection...

AI Technical Summary

Problems solved by technology

The transmission line covers a wide range, and the landforms along the way are complex and diverse. In the aerial image, the distinction between the insulator and the background is low. At the same time, the shooting angle and environmental conditions of the UAV are relatively random. The existing algorithms cannot meet the requirements of fast detection of insulators. sex, accuracy requirements

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