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A Discussion on the Merits and Limitations of Using Drive-by Monitoring to Detect Localised Damage in a Bridge

机译:运用行车监控技术检测桥梁局部损伤的优缺点探讨

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摘要

Given the large number of bridges that currently have no instrumentation, there are obvious advantages in monitoring the condition of a bridge by analysing the response of a vehicle crossing it. As a result, the last two decades have seen a rise in the research attempting to solve the problem of identifying damage in a bridge from vehicle measurements. This paper examines the theoretical feasibility and practical limitations of a drive-by system in identifying damage associated to localized stiffness losses. First, the nature of the damage feature that is sought within the vehicle response needs to be characterized. For this purpose, the total vehicle response is considered to be made of ‘static’ and ‘dynamic’ components, and where the bridge has experienced a localized loss in stiffness, an additional ‘damage’ component. Understanding the nature of this ‘damage’ component is crucial to have an informed discussion on how damage can be identified and localised. Leveraging this new understanding, the authors propose a wavelet-based drive-by algorithm. By comparing the effect of the ‘damage’ component to other key effects defining the measurements such as ‘vehicle speed’, the ‘road profile’ and ‘noise’ on a wavelet contour plot, it is possible to establish if there is a frequency range where drive-by can be successful. The algorithm uses then specific frequency bands to improve the sensitivity to damage with respect to limitations imposed by Vehicle-Bridge vibrations. Recommendations on the selection of the mother wavelet and frequency band are provided. Finally, the paper discusses the impact of noise and road profile on the ability of the approach to identify damage and how periodic measurements can be effective at monitoring localised stiffness changes.
机译:鉴于目前没有仪器的桥梁数量众多,通过分析车辆通过桥梁的响应来监视桥梁状况具有明显的优势。结果,在过去的二十年中,试图解决从车辆测量中识别桥梁损坏的问题的研究有所增加。本文研究了在确定与局部刚度损失相关的损伤方面的驾驶系统的理论可行性和实际局限性。首先,需要表征车辆响​​应中寻求的损坏特征的性质。为此,车辆的总响应被认为是由“静态”和“动态”组件组成的,而桥梁在刚度方面出现局部损失的情况下,会附加一个“损坏”组件。了解这种“损坏”成分的性质对于就如何识别和定位损坏进行深入的讨论至关重要。利用这种新的理解,作者提出了一种基于小波的驱动算法。通过将“损坏”分量的影响与定义测量值的其他关键影响(例如小波轮廓图上的“车辆速度”,“道路轮廓”和“噪声”)进行比较,可以确定是否存在频率范围偷渡成功的地方。然后,该算法使用特定的频带来提高针对车桥振动施加的限制的损坏敏感性。提供了关于选择母波和频带的建议。最后,本文讨论了噪声和道路轮廓对方法识别损坏的能力的影响,以及定期测量如何有效监视局部刚度变化。

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