基于动力指纹与数据融合的桥梁损伤识别

Bridge Damage Identification Based on Dynamic Fingerprint and Data Fusion

为了实现对损伤进行精确定位,提出了利用柔度对角变化率与协调模态置信因子这两个动力指纹指标进行数据融合的方法。首先获取结构的模态参数,然后利用模态参数来构建柔度对角变化率与协调模态置信因子,最后根据数据融合理论将两个指标进行融合,获得新的损伤因子DI来进行损伤定位。为了验证该方法的有效性,通过一个简支梁桥有限元模型的算例进行数值分析,讨论了不同损伤程度及损伤位置对损伤识别产生的影响。结果表示,对动力指纹方法的两个损伤因子进行数据融合后的损伤识别结果准确率高,能够精确识别损伤位置。

A data fusion method was proposed using dynamic fingerprint indicators:flexibility change rate and enhanced coordinate modal assurance criteria so as to achieve the purpose of damage localization.Firstly,the modal parameters of the structure are obtained,and then the flexibility matrix and enhanced coordinate modal assurance criteria are constructed with the modal parameters.Finally,the indicators are fused to obtain a new damage index DI for damage localization based on data fusion theory.To verify the effectiveness of the method,the influence of different damage degrees and locations on damage identification was discussed through numerical analysis of a finite element model of a simply supported beam bridge.The results show that high accuracy of damage identification can be achieved with data fusion using two damage factors in dynamic fingerprint method,and the damage can be identified with the proposed method.