An aerial photograph image tower identification card fault diagnosis method based on depth learning

A technology of deep learning and fault diagnosis, applied in neural learning methods, character and pattern recognition, instruments, etc., can solve problems such as line tower changes, bending, damage, etc., and achieve the effect of improving robustness

Active Publication Date: 2019-02-22
FUZHOU UNIV
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Problems solved by technology

[0003] In recent years, unmanned aerial vehicle inspection has gradually become one of the main means of inspection and maintenance of transmission lines. The necessity of automatically detecting tower signs in aerial images and performing fault diagnosis has become increasingly prominent: sign records the information of current poles and towers , is an effective auxiliary positioning method. If the identification plate can be detected during the inspection process of the UAV, the inspection image of the transmission line and the image of ...

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  • An aerial photograph image tower identification card fault diagnosis method based on depth learning
  • An aerial photograph image tower identification card fault diagnosis method based on depth learning
  • An aerial photograph image tower identification card fault diagnosis method based on depth learning

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[0024] The technical solution of the present invention will be specifically described below in conjunction with the accompanying drawings.

[0025] The present invention provides a method for diagnosing the fault of a pole and tower identification plate based on deep learning, comprising the following steps:

[0026] Step S1. Establish a tower signage detection image library and its label library: including tower signboards in various scenarios, the signage types are pole number plates and warning signs, and the images are complete high-definition aerial images according to the pixel width of the picture not exceeding 1024 or The image pixel height is not less than 900 regular proportional scaling;

[0027] Step S2. Establish a tower leg detection image library and its tag library: including tower legs with identification plates in various scenarios, the image is a complete high-definition aerial image according to the picture pixel width not exceeding 1024 or the picture pixe...

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Abstract

The invention relates to an aerial photograph image tower identification card fault diagnosis method based on depth learning. The method comprises the following steps of: establishing a pole and toweridentification card detection image library and a tag library thereof; estalbihsing the image library and tag library of tower leg detection; establishing a tower identification card status classification image library and its label library; establishing the deep learning object detection mode Faster R-CNN, including the basic network NasNet, a zone Proposal Network and a Fast R-CNN detection network; establishing a depth-learning image classification model ResNet; traninig the established detection model or classification model on the prepared galleries, and performing data enhancement on the input data of each iteration in the training process, including random rotation, random fill-in cropping and random grayscale. According to the relative position of the detected tag and the tower leg, the fault of tower tag falling off is diagnosed. If there is no tag falling off, the state of the tag is diagnosed by using the classification model.

Description

technical field [0001] The invention belongs to the fields of high-voltage transmission line inspection technology, image recognition technology, and machine learning technology, and in particular relates to a method for diagnosing faults of tower identification plates based on aerial photography images based on deep learning. Background technique [0002] The tower identification plate is an important component in the transmission line operation and maintenance management system, which is installed on each base tower of the overhead transmission line. The pole number plate in the identification plate shows the line name, line number and pole tower number. The inspection and maintenance personnel can know the basic information of the pole tower through the pole number plate, which is convenient for subsequent maintenance work. The warning signs in the signboards display prohibited behaviors and safety reminders, warn staff and non-staff of relevant safety information, and co...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V2201/09G06N3/045G06F18/24G06F18/214
Inventor 缪希仁刘欣宇江灏陈静
Owner FUZHOU UNIV
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