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In-Service Diagnostics of a Highway Bridge from a Progressive Damage Case Study

机译:基于渐进式损坏案例研究的公路桥梁在役诊断

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摘要

Development of diagnostic and prognostic routines for application to in-service measurements from highway bridges necessitates analysis of experimental measurements from in-service highway bridges under natural or prescribed induced damage. This is generally limited to the unique opportunity of investigating end-of-service life bridges prior to reconstruction and consequently only a limited library of such case studies exist. This paper documents a field test of an end-of-service bridge span with prescribed progressive damage to a bearing as well as several diaphragm connections. Thirty dual-axis accelerometers were distributed across the bridge span with data acquisition and transmission facilitated by a real-time lossless wireless sensor network. A highway department service truck applied traffic excitation to the structure through routine passes on a consistent lane of traffic. Output-only system identification was applied to the baseline time history response to develop a state-space model of the bridge dynamics used for forward prediction in the form of a Kalman filter. Simple statistical evaluation of the prediction error in the model demonstrates the variance can be used to localize and generally quantify the degree of damage in the structure. The case study additionally illustrates the potential importance of monitoring lateral acceleration along the girders to permit identification of damage to elements, such as the diaphragms, that contributing primarily to the lateral and torsional response of primary structural members.
机译:发展用于在公路桥梁的在役测量中应用的诊断和预后例程,需要分析在自然或规定的诱发损伤下在役公路桥梁的实验测量结果。通常,这仅限于在重建之前研究使用寿命终止生命桥的独特机会,因此,仅存在有限的此类案例研究库。本文记录了服务终了的桥梁跨度的现场测试,对轴承以及几个膜片连接规定了渐进式损坏。跨桥跨度分布了30个双轴加速度计,实时无损无线传感器网络促进了数据采集和传输。公路部门的服务卡车通过常规通行在一致的行车道上将交通激励应用于结构。仅输出系统识别应用于基线时程响应,以卡尔曼滤波器的形式开发用于前向预测的桥梁动力学状态空间模型。对模型中的预测误差进行简单的统计评估表明,该方差可用于定位结构并总体上量化损伤程度。案例研究还说明了监视沿大梁的横向加速度的潜在重要性,以允许识别对主要是主要结构构件的横向和扭转响应的膜片等元件的损坏。

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