通过整合数字信号特征和深度学习,用于桥梁结构的地震反应的快速识别方法
Zhaoxu Lv1, Youliang Ding2,3, Junxiao Guo2,3
1Jiangsu Xiandai Road & Bridge Co., Ltd., Nanjing 210018, China.
Sensors (Basel, Switzerland)
|January 25, 2025
概括
这项研究引入了一种新的方法,用于识别桥梁地震反应,使用信号处理和深度学习. 这种方法提高了在地震期间识别结构行为的准确性和效率.
科学领域:
- 结构工程 结构工程
- 地震分析 - - 地震分析
- 人工智能的人工智能
背景情况:
- 桥梁结构容易受到地震事件的影响,因此需要准确的方法来监测它们的反应.
- 传统的地震响应识别方法在准确性和效率方面面临挑战.
- 深度学习为先进的结构性健康监测提供了潜力.
研究的目的:
- 提出一种综合方法,用于在桥梁结构中识别地震响应.
- 利用信号处理和深度学习来提高准确性和效率.
- 在现实场景中验证拟议方法的有效性.
主要方法:
- 使用短时间能量方法来提取非平滑的信号段.
- 应用短时间里叶变换,连续波束变换和Mel频率的角质系数进行光谱分析.
- 使用长短期内存 (LSTM) 和ResNet50网络进行特征矩阵分类.
主要成果:
- 信号处理有效地提取结构响应特征.
- 神经网络中的过度装配显著减少.
- 综合方法在地震响应识别方面实现了高精度和效率.
结论:
- 信号处理和深度学习的整合为桥梁地震响应识别提供了强大的解决方案.
- 与现有技术相比,这种方法提供了更好的准确性和效率.
- 这些发现有助于先进的结构健康监测和桥梁的抗震能力.
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