Surface fatigue crack segmentation in steel box girder bridges using an improved Unet convolutional neural network

IF 2.6 3区工程技术 Q2 ENGINEERING, CIVIL

Structure and Infrastructure Engineering Pub Date : 2024-08-13 DOI:10.1080/15732479.2024.2390461

Tian Gao, Zhiyuan Yuanzhou, Bohai Ji, Junyuan Xia

引用次数: 0

Abstract

Despite the success of crack segmentation, the traditional segmentation strategy and networks are not necessarily suitable for fatigue cracks with unique visual features. Towards the indistinct cra...

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使用改进的 Unet 卷积神经网络分割钢箱梁桥的表面疲劳裂缝

尽管裂纹分割取得了成功，但传统的分割策略和网络并不一定适合具有独特视觉特征的疲劳裂纹。针对模糊不清的裂纹，我们可以通过...

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来源期刊

Structure and Infrastructure Engineering 工程技术-工程：机械

CiteScore

9.50

自引率

8.10%

发文量

131

审稿时长

5.3 months

期刊介绍： Structure and Infrastructure Engineering - Maintenance, Management, Life-Cycle Design and Performance is an international Journal dedicated to recent advances in maintenance, management and life-cycle performance of a wide range of infrastructures, such as: buildings, bridges, dams, railways, underground constructions, offshore platforms, pipelines, naval vessels, ocean structures, nuclear power plants, airplanes and other types of structures including aerospace and automotive structures. The Journal presents research and developments on the most advanced technologies for analyzing, predicting and optimizing infrastructure performance. The main gaps to be filled are those between researchers and practitioners in maintenance, management and life-cycle performance of infrastructure systems, and those between professionals working on different types of infrastructures. To this end, the journal will provide a forum for a broad blend of scientific, technical and practical papers. The journal is endorsed by the International Association for Life-Cycle Civil Engineering ( IALCCE) and the International Association for Bridge Maintenance and Safety ( IABMAS).