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Adaptive Regression for Damage Detection in Bridges Under Environmental Influence

机译:环境影响下桥梁损伤检测的自适应回归

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Many of Vibration-based structural health monitoring (SHM) often uses vibrationcharacteristics to detect damage. It has been acknowledged that changes in vibrationcharacteristics can also happen due to environmental factors. Especially for civilstructures it is impossible to test in isolation from natural environment. Theseenvironmental factors are seen to significantly affect modal frequencies and caneasily mask changes caused by damage. In this study we propose a technique thattreats temperature variations as embedded parameter and helps to define acorrelation structure between modal frequencies. The proposed method utilizes thecorrelation between structural frequencies to represent the healthy state of thestructure. Damage is detected by measuring deviation of the recorded frequencyfrom the healthy state. The proposed damage detection strategy is tested usingsimulation result for a simply supported T-beam section bridges.
机译:许多基于振动的结构健康监测(SHM)经常使用振动 检测损坏的特征。已经认识到振动的变化 由于环境因素,特性也会发生。特别是民用 结构是不可能与自然环境隔离进行测试的。这些 环境因素被认为会极大地影响模态频率,并可能 容易掩盖由损坏引起的变化。在这项研究中,我们提出了一种技术, 将温度变化视为嵌入式参数,并有助于定义 模态频率之间的相关结构。所提出的方法利用了 代表健康状态的结构频率之间的相关性 结构体。通过测量记录频率的偏差来检测损坏 从健康状态开始。建议的损坏检测策略使用以下方法进行测试 简支T型钢截面桥的仿真结果。

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