Research on Geometric Parameter Prediction Algorithm for Oil and Gas Pipeline Defects-Reference-Cited by-同舟云学术

Research on Geometric Parameter Prediction Algorithm for Oil and Gas Pipeline Defects

Published:2023-10-27 Issue:3 Volume:7 Page:34-39
ISSN:2771-3032
Container-title:Academic Journal of Science and Technology
language:
Short-container-title:AJST

Author:

Liu Yijun,Wu Wei,Ren Xiaolin,Qin Le,Wang Yukun

Abstract

Aiming at the problem of insufficient feature extraction of magnetic leakage signals by traditional neural networks, this paper proposes an attention depth convolutional neural network model (ECA-VGG16), which adds an attention mechanism combined with convolutional neural network on the basis of deep convolutional neural network VGG16, so that the neural network can focus on the key information of the input data, further improve the ability of the grid to extract image data features, and realize the accurate expression of defect features.

Publisher

Darcy & Roy Press Co. Ltd.

Reference20 articles.

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