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Deep inspection method for automatic identification of ship corrosion area

A technology for automatic identification and ships, applied in neural learning methods, character and pattern recognition, instruments, etc., can solve the problems of limited number of images, large image recognition errors, large rust detection errors, etc., achieve high cost, shorten training time, The effect of training complexity reduction

Active Publication Date: 2021-07-02
青岛东坤蔚华科技有限公司
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Problems solved by technology

[0004] In view of the fact that rust does not have a specific regular shape and color, image recognition is performed only based on the shape and color, and the rust detection error is relatively large
In addition, for a specific ship, the number of images collected by the UAV is limited, and relying solely on the collected images to train a complex deep neural network will also lead to large image recognition errors

Method used

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  • Deep inspection method for automatic identification of ship corrosion area
  • Deep inspection method for automatic identification of ship corrosion area
  • Deep inspection method for automatic identification of ship corrosion area

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Embodiment Construction

[0072] The present invention will be described in further detail below.

[0073] In order to enable those skilled in the art to better understand the present invention. The present invention is described in further detail below.

[0074] In order to further illustrate the effectiveness of the technical method, the in-depth inspection system for automatic identification of ship corrosion areas proposed by the present invention will be further described in conjunction with the accompanying drawings in the embodiments of the present invention.

[0075] see figure 1 , an in-depth inspection method for automatic identification of ship corrosion areas. The method comprises the following steps:

[0076] S01: Taking a ship to be inspected for corrosion as an example, use a drone to take pictures of the ship, and collect as many images as possible of the ship's interior and hull, such as figure 2 .

[0077] S02: Flip, translate and add noise to the image collected by the drone, an...

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Abstract

The invention relates to a deep inspection method for automatic identification of a ship corrosion area, wherein the method comprises the steps: building a pre-training image identification model and a corrosion image automatic identification model, then labeling a large number of ship images, and training the corrosion image automatic identification model through a part of images with labels; inputting a plurality of to-be-detected ship images into the trained model, reserving the images marked with corrosion labels, and marking a corrosion area bounding box, wherein the marked images form a corrosion area positioning data set; establishing a corrosion area target detection model, and training the model by using part of the images in the corrosion area positioning data set; and finally, inputting a to-be-positioned rusted ship image into the trained corrosion area target detection model, outputting bounding box parameters of a corrosion area, and marking the position of the corrosion area by using a bounding box. According to the method, an integrated process from ship image acquisition to corrosion area automatic positioning is realized, a deep learning image recognition algorithm and a target detection algorithm are fused, and the method is very intelligent.

Description

technical field [0001] The invention relates to the field of ship corrosion area detection, in particular to an in-depth inspection method for automatic identification of ship corrosion areas. Background technique [0002] The traditional corrosion detection of warships is mostly on-site manual inspection, which often consumes a lot of time and energy, and even has potential safety hazards in high-risk areas of ships, which poses a potential threat to the personal safety of inspection workers. In order to reduce the time and labor cost of ship corrosion detection and promote the safe and efficient development of the work, it is necessary to focus on the current technological frontiers to improve the inspection process and reduce human intervention in the corrosion detection process as much as possible. [0003] At present, due to its low-cost and high-efficiency on-site performance, robot inspection has been initially applied in many scenarios such as construction sites and ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/32G06K9/54G06K9/62G06N3/04G06N3/08
CPCG06N3/084G06V20/00G06V10/25G06V10/20G06N3/047G06N3/045G06N3/044G06F18/214G06F18/2415
Inventor 王宇赫毛强强余梦琪刘帅辰汪远博孙鑫
Owner 青岛东坤蔚华科技有限公司
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