Zhao Han-Wei, Ding You-Liang, Li Ai-Qun
Key Laboratory of Concrete and Pre-Stressed Concrete Structures of the Ministry of Education, Southeast University, Nanjing 210096, China.
Beijing Advanced Innovation Center for Future Urban Design, Beijing University of Civil Engineering and Architecture, Beijing 100044, China.
Sensors (Basel). 2022 Apr 23;22(9):3247. doi: 10.3390/s22093247.
Real-time representation of the current performance of structures is an important task for perceiving potential danger in in-service bridges. Methods driven by the multisource sensing data of structural health monitoring systems are an effective way to achieve this goal. Due to the explicit zero-point of signals, the live load-induced response has an inherent advantage for quantitatively representing the performance of bridges. Taking a long-span cable-stayed railway-highway combined bridge as the case study, this paper presents a representation method of in-service performance. First, the non-stationary sections of train-induced response are automatically extracted by wavelet transform and window with threshold. Then, the data of the feature parameter of each non-stationary section are automatically divided into four cases of train load according to the calculational theory of bridge vibration under train effect and clustering analysis. Finally, the performance indexes for structural deformation and dynamics are determined separately, based on hierarchical clustering and statistical modeling. Fusing the real variability of massive data from monitoring and the knowledge of mechanics of theoretical calculations, accurate and robust indexes of bridge deflection distribution and forced vibration frequency are obtained in real time. The whole process verifies the feasibility of the representation of bridge in-service performance from massive multisource sensing data. The presented method, framework, and analysis results can be used as a reference for the design, operation, and maintenance works of long-span railway bridges.
实时呈现结构的当前性能是感知在用桥梁潜在危险的一项重要任务。由结构健康监测系统的多源传感数据驱动的方法是实现这一目标的有效途径。由于信号具有明确的零点，活载引起的响应在定量表征桥梁性能方面具有固有优势。本文以一座大跨度斜拉铁路 - 公路两用桥为例，提出了一种在用性能的表征方法。首先，通过小波变换和带阈值的窗口自动提取列车引起的响应的非平稳段。然后，根据列车作用下桥梁振动的计算理论和聚类分析，将每个非平稳段的特征参数数据自动划分为列车荷载的四种情况。最后，基于层次聚类和统计建模分别确定结构变形和动力学的性能指标。融合监测得到的海量数据的实际变异性和理论计算力学知识，实时获得准确且稳健的桥梁挠度分布和强迫振动频率指标。整个过程验证了从海量多源传感数据表征桥梁在用性能的可行性。所提出的方法、框架和分析结果可为大跨度铁路桥梁的设计、运营和维护工作提供参考。
