Underwater pier disease identification method based on deep learning and sonar imaging

A deep learning and disease identification technology, applied in image enhancement, image analysis, image data processing, etc., can solve the problems of low degree of automation, easy misjudgment, high cost, etc., to improve accuracy and automation, and automate High-level, low-cost effects

Inactive Publication Date: 2020-05-08
SOUTHEAST UNIV
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  • Application Information

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Problems solved by technology

The underwater part of the bridge pier has been subjected to harsh environments such as erosion and corrosion for a long time, which may cause defects such as defects, cracks, and exposed ribs or even damage underwater, which will seriously affect the service life and even the bearing capacity of the bridge.
At present, ...

Method used

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  • Underwater pier disease identification method based on deep learning and sonar imaging
  • Underwater pier disease identification method based on deep learning and sonar imaging
  • Underwater pier disease identification method based on deep learning and sonar imaging

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Embodiment Construction

[0020] The present invention will be described in further detail below in conjunction with the accompanying drawings. Such as figure 1 As shown, a method for identifying underwater pier diseases based on deep learning and sonar imaging includes the following steps:

[0021] 1. Use side-sound sonar equipment to obtain pictures of underwater pier diseases and pictures of normal conditions to form a data set, and set each picture to a size of 1200x1200pixel; the pictures of diseases mainly include pictures of defects, pictures of cracks and pictures of exposed tendons.

[0022] 2. Use the data enhancement method to expand the data set and label each picture; the data enhancement method here uses random rotation and random cropping, and the label is marked with a rectangular frame, and the form of the label frame is in the form of an xml file record it.

[0023] 3. Divide the data set into training test set, verification set and test set according to the ratio of 8:1:1.

[0024...

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Abstract

The invention provides an underwater pier disease identification method based on deep learning and sonar imaging, and the method comprises the steps: obtaining a prepared underwater pier scanning picture through employing underwater side sonar equipment, wherin the underwater pier scanning picture comprises a disease and no-disease picture; increasing the number of data sets by using an image enhancement method; marking the data set, marking a disease area with a rectangular frame, and storing coordinate information; dividing the data set into a training test set, a verification set and a testset; establishing a yolov3 model in the deep learning target detection network, and performing training to obtain a training model; and controlling side sonar equipment to scan along the underwater pier part on the water surface to obtain a scanning picture, and performing automatic underwater pier disease identification by using the trained yolov3 model. The method is high in efficiency and lowin cost, and has more obvious advantages of automation and real-time performance compared with a traditional manual diving method and a sonar manual screening method.

Description

technical field [0001] The invention relates to the field of interaction technology between civil engineering and artificial intelligence, in particular to a method for identifying underwater pier diseases based on deep learning and sonar imaging. Background technique [0002] The bridge pier is the main load-bearing component of the bridge pier, and most of the load of the bridge structure is transmitted to the foundation through the pier. Any loss of bearing capacity of a bridge pier will lead to the overall instability and destruction of the bridge pier. Therefore, the safety of the bridge pier must be highly valued. The underwater part of the bridge pier has been subjected to harsh environments such as erosion and corrosion for a long time, which may cause defects such as defects, cracks, and exposed ribs or even damage underwater, which will seriously affect the service life and even the bearing capacity of the bridge. At present, the detection methods of underwater pi...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T5/00G06T5/20
CPCG06T5/002G06T5/20G06T7/0004G06T2207/20081G06T2207/20084G06T2207/30132
Inventor 吴刚侯士通董斌
Owner SOUTHEAST UNIV
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