桥梁健康监测数据的挖掘和分析工作只有在整体数据质量符合基本要求的有效数据基础上进行,才能保障如模态参数识别、损伤识别和状态评估等后续工作的准确性.因此,基于量化改进的探索性分析方法(Exploratory Data Analysis,EDA)和相关性分析从数据完整性、准确性和一致性的角度建立了桥梁健康监测静、动态数据的质量评估方法.对某大跨度斜拉桥健康监测系统的静、动态数据进行质量评估,通过对比分析了不同评估质量的温度数据、静挠度数据和不同评估质量的主梁竖向加速度动力信号的模态参数识别的稳定图,验证了所提方法的正确性.结果表明,所提评估方法能够快速有效地判断数据质量的好坏,进而确保桥梁结构的服役性能评估和预测的准确性,有利于提高健康监测数据的可用性和效能.
Research on the Quality Assessment Method of Bridge Health Monitoring Data
The mining and analysis of bridge health monitoring data can only be carried out on the basis of effective data with overall data quality that meets the basic requirements,so as to ensure the accuracy of follow-up work such as modal parameter identification,damage identification and condition assessment.Therefore,based on the exploratory analysis method and correlation analysis of quantitative improvement,this paper establishes a quality assessment method for static and dynamic data of bridge health monitoring from the perspective of data completeness,accuracy and consistency.Finally,the quality evaluation of static and dynamic data of a long-span cable-stayed bridge health monitoring system is carried out,and the correctness of the proposed method is verified by comparing and analyzing the temperature data,static deflection data and the stability chart of modal parameter identification of the vertical acceleration dynamic signal of the main beam with different evaluation quality.The results show that the proposed evaluation method can quickly and effectively judge the quality of the data,so as to ensure the accuracy of the service performance assessment and prediction of the bridge structure,which is conducive to improving the availability and efficiency of health monitoring data.
health monitoringdata quality assessmentexploratory data analysismodal parameter identification
万方数据
维普
