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Fluid Pressure over Curved Plate of Constant Width01:12

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When a curved plate of constant width is submerged in a liquid, the pressure acting normal to the plate varies continuously both in magnitude and direction. Calculating the magnitude and location of the resultant force at a point is often challenging for such cases. One of the methods to determine the resultant force and its location involves separately calculating the horizontal and vertical components of the resultant force. This complex calculation can be simplified by representing the...
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Cortical Bone Assessment Using Ultrasonic Guided Waves: A Reproducibility Study in a Healthy Population
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基于阶段阵列引导波和深度学习算法的曲面板的定量损害评估.

Qi Yuan1, Ying Wang2, Zhongqing Su3

  • 1School of Civil and Environmental Engineering, Harbin Institute of Technology (Shenzhen), Guangdong 518055, China; Department of Mechanical Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong Special Administrative Region.

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概括

本研究介绍了GW-SHMnet,这是一个使用阶段阵列引导波 (PAGW) 和深度学习的框架,用于在曲板块中准确评估损坏大小. 它使结构完整性的自主定量评估成为可能.

关键词:
卷积神经网络是一种卷积神经网络.曲的板块板块是一个曲线板块.深度学习是一种深度学习.导向波浪的导向波浪是指导波浪的导向波.阶段式数组是一个阶段式数组.定量评价 定量评价 定量评价 定量评价结构性健康监测 结构性健康监测

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科学领域:

  • 结构健康监测 结构健康监测
  • 非破坏性测试 不破坏性测试
  • 机器学习应用 机器学习应用

背景情况:

  • 阶段式阵列引导波 (PAGW) 显示出用于检测和定位曲板块中轻微损坏的前景.
  • 定量损害评估是具有挑战性的,因为难以提取损害大小敏感特征.

研究的目的:

  • 提出一个新的综合框架,GW-SHMnet,用于自主定量评估曲板的轻微损坏.
  • 为此目的,利用PAGW,有限元 (FE) 建模和深度学习.

主要方法:

  • 构建了一个FE模型来模拟PAGW在曲线板中的传播.
  • 在曲的板上使用PAGW实验验证实了FE模型.
  • 开发了一个全面的FE模拟数据库,用于培训和测试深度学习模型.
  • 采用深度学习进行自动特征提取以确定损坏大小.

主要成果:

  • GW-SHMnet框架证明了它的有效性,准确性和稳定性.
  • 成功启用了对轻微损害的自主定量评估.
  • 验证了深度学习在提取损坏敏感特征方面的能力.

结论:

  • 拟议的GW-SHMnet框架为曲板的定量损害评估提供了一个有效的解决方案.
  • 这种方法在复杂几何形状的结构健康监测领域取得了进展.
  • 整合PAGW,FE建模和深度学习提供了一个强大的工具来识别和量化结构损伤.