Sudu Ambegedara Amila, Sun Jie, Janoyan Kerop, Bollt Erik
Department of Mathematics, Clarkson University, 8 Clarkson Ave, Potsdam, New York 13699-5815, USA.
Department of Civil and Environmental Engineering, Clarkson University, Potsdam, New York 13699-5710, USA.
Chaos. 2016 Nov;26(11):116312. doi: 10.1063/1.4967920.
Damage detection of mechanical structures such as bridges is an important research problem in civil engineering. Using spatially distributed sensor time series data collected from a recent experiment on a local bridge in Upper State New York, we study noninvasive damage detection using information-theoretical methods. Several findings are in order. First, the time series data, which represent accelerations measured at the sensors, more closely follow Laplace distribution than normal distribution, allowing us to develop parameter estimators for various information-theoretic measures such as entropy and mutual information. Second, as damage is introduced by the removal of bolts of the first diaphragm connection, the interaction between spatially nearby sensors as measured by mutual information becomes weaker, suggesting that the bridge is "loosened." Finally, using a proposed optimal mutual information interaction procedure to prune away indirect interactions, we found that the primary direction of interaction or influence aligns with the traffic direction on the bridge even after damaging the bridge.
桥梁等机械结构的损伤检测是土木工程中的一个重要研究问题。利用从纽约州北部一座当地桥梁最近的实验中收集的空间分布式传感器时间序列数据，我们研究了使用信息论方法进行非侵入式损伤检测。有几个发现如下。首先，代表传感器测量加速度的时间序列数据更符合拉普拉斯分布而非正态分布，这使我们能够为熵和互信息等各种信息论度量开发参数估计器。其次，当通过拆除第一个横隔板连接的螺栓引入损伤时，用互信息测量的空间上相邻传感器之间的相互作用变弱，这表明桥梁“松动”了。最后，使用提出的最优互信息相互作用程序来消除间接相互作用，我们发现即使在桥梁受损后，相互作用或影响的主要方向仍与桥上的交通方向一致。
