Unmanned aerial vehicle inspection method and system for thermal boiler maintenance and storage medium

Abstract

The invention discloses an unmanned aerial vehicle inspection method and system for thermal boiler maintenance and a storage medium, and the method comprises the steps: obtaining video information images of a boiler and related equipment in real time through an airborne visual sensor, processing the obtained video information images by an image enhancement method based on active illumination, and forming a training set and a sample set; performing feature extraction operation on the obtained training set to obtain feature information of images of the boiler and the related equipment; creating a deep convolutional neural network image recognition model based on feature extraction, and using samples in the sample set for training; using a deep convolutional neural network image recognition model to recognize the sample set. according to the method, the problem that the boiler is difficult to quickly and effectively recognize due to the fact that manual field detection and unmanned aerial vehicle aerial photography detection are influenced by various factors when the collected images are detected in a boiler recognition method is solved.

Description

Technical field: [0001] The invention relates to the field of inspection control of power transmission lines, in particular to an inspection method, system and storage medium of an unmanned aerial vehicle for inspection and maintenance of thermal boilers. Background technique: [0002] Today's society is increasingly dependent on electricity supply. At present, boiler identification methods are mainly traditional manual on-site inspection and UAV aerial photography inspection. Manual inspection technology has high recognition accuracy, but information collection is difficult and inefficient; while using UAV for boiler inspection, although information collection is convenient, However, it is still necessary to manually inspect the collected images. Although this technology is more efficient than the traditional manual field inspection technology, it will also be affected by related factors, such as the influence of light when the drone is shooting the boiler and the long-term...

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is: to overcome the deficiencies of the prior art, the deep convolutional neural network image recognition model automatically recognizes the images collected by the drone, and at the same time uses the image enhancement method of active lighting to analyze the collected images Process to increase the recognition of boilers and related equipment in the image, and solve the problems of manual field detection and drone aerial photography detection in the boiler inspection identification method. When detecting the collected images, it will be affected by various factors, which makes it difficult for boilers to be fast and effective. Method, system, and storage medium for unmanned aerial vehicle inspection of thermal boiler inspection for identifying problems

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