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首页> 外文期刊>Australian Journal of Structural Engineering >Damage identification in timber bridges utilising the damage index method and neural network ensembles
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Damage identification in timber bridges utilising the damage index method and neural network ensembles

机译:利用损伤指数法和神经网络集成的木桥损伤识别

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摘要

Many of Australia's timber bridges are in aged and decayed conditions. In order to ensure the reliability of these structures and the safety of the public, condition assessment, damage detection and safety evaluation is necessary. This paper presents a damage identification procedure, which is based on global change of vibration characteristics of a structure. The developed method utilises the damage index (DI) method in combination with neural network techniques to identify damage in numerical and experimental timber beam structures. The neural network ensemble approach is utilised in order to respect important diversities of different modes and to integrate individual characteristics of vibrational mode separated damage features. The method considers field testing issues associated with measurement noise, limited number of sensor arrays and environmental fluctuations. The results of damage detection using the proposed approach demonstrate its ability to determine the location and severity of all present damage cases. The outcomes shoiv that the developed damage detection method is effective, robust and reliable.
机译:澳大利亚的许多木桥处于老化和腐烂的状态。为了确保这些结构的可靠性和公众的安全,必须进行状态评估,损坏检测和安全评估。本文提出了一种基于结构整体振动特性整体变化的损伤识别程序。所开发的方法结合了损伤指数(DI)方法和神经网络技术来识别数值和实验木梁结构中的损伤。使用神经网络集成方法是为了尊重不同模式的重要多样性,并整合振动模式分离的损伤特征的各个特征。该方法考虑了与测量噪声,有限数量的传感器阵列和环境波动相关的现场测试问题。使用所提出的方法进行损坏检测的结果表明,它能够确定所有当前损坏案例的位置和严重性。结果表明,开发的损伤检测方法是有效,可靠和可靠的。

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