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Modal-parameter identification and vibration-based damage detection of a damaged steel truss bridge

机译:受损钢桁架桥梁的模态参数识别和基于振动的损伤检测

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Bridge damage detection has become increasingly important, but few related techniques have been tested in situ on real bridges. For this study, a field experiment was conducted on an actual simply supported steel truss bridge with four artificial damage scenarios applied sequentially. Preliminary results of modal-parameter identification and vibration-based damage detection are then presented. For each scenario, modal frequencies and mode shapes of the bridge were identified with high precision and accuracy using a stabilization diagram-aided multivariate autoregressive analysis of vehicle-excited bridge vibrations. Changes in the identified modal parameters attributable to the artificial damage were observed. For modal frequencies, they decreased as damage causing high stress redistribution was applied, signifying a global stiffness loss. For mode shapes, both symmetric and anti-symmetric ones were distorted when the damage was applied asymmetrically, but no distortion was observed when damage was applied symmetrically. Moreover, a damage detection approach in an order of feature extraction and discrimination was verified to be practicable if the damage-sensitive feature was properly selected. Multiple modal frequencies, specifically the first three and four modal frequencies, were effective features because they were highly sensitive not only to the presence but also to the severity of the artificial damage. Multiple modal assurance criteria (MAC) values and coordinate modal assurance criteria (COMAC) values were also effective features that were sensitive to damage scenarios examined herein if sufficient modes were considered. However, neither a single frequency nor a single MAC value was as effective as multiple ones because each was sensitive to certain specific damage scenarios only. When damping ratios were taken as features, most of their combinations were slightly sensitive to the asymmetric damage, but none of those combinations, neither single nor multiple damping ratios, was sensitive to the symmetric damage. (C) 2016 Elsevier Ltd. All rights reserved.
机译:桥梁损坏检测变得越来越重要,但是很少有相关技术在真实桥梁上进行现场测试。对于本研究,在一个实际的简单支撑的钢桁架桥上进行了现场试验,并依次应用了四种人工破坏方案。然后给出了模态参数识别和基于振动的损伤检测的初步结果。对于每种情况,使用稳定图辅助的车辆激励桥梁振动的多元自回归分析,可以高精度和准确地识别桥梁的模态频率和模式形状。观察到归因于人为损害的已确定模态参数的变化。对于模态频率,由于施加了导致高应力重新分布的损伤,它们降低了,这表明整体刚度损失。对于模态形状,非对称地施加损伤时,对称和反对称形状都会变形,但是对称地施加损伤时,则不会观察到变形。此外,如果正确选择了损伤敏感特征,那么按特征提取和判别顺序的损伤检测方法被证明是可行的。多个模态频率,特别是前三个和四个模态频率,是有效的功能,因为它们不仅对人为损坏的存在而且对人为破坏的严重性高度敏感。如果考虑了足够的模式,则多个模式保证标准(MAC)值和协调模式保证标准(COMAC)值也是有效的功能,这些功能对此处检查的损坏情况敏感。但是,单个频率或单个MAC值都没有多个频率有效,因为每个频率仅对某些特定的损坏情况敏感。当以阻尼比为特征时,它们的大多数组合对不对称损伤都比较敏感,但是这些组合中,无论是单个还是多个阻尼比,都对对称损伤不敏感。 (C)2016 Elsevier Ltd.保留所有权利。

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