Structural Condition Assessment under Varying Environmental Conditions

Vibration-based damage detection techniques, made possible by recent advances in sensor technology, rely mainly on identifying significant changes in dynamic characteristics of structures. In real structures, a practical difficulty occurs when damage-induced changes in dynamic properties of the structure are of the same order of magnitude as those due to operational/environmental variations (e.g. traffic load, temperature, humidity, wind, etc.). In other words, changes in global properties can also be induced by changing environmental conditions, which erroneously can be interpreted as the existence of damage. Therefore, obtaining an accurate estimate of the structural performance of the Memorial Bridge is perhaps one of the most challenging aspects of the “Living Bridge” project.

The south-span of the bridge is instrumented with various types of sensors responsible to provide raw data for remote monitoring of the bridge. The post-processing of information obtained from long-term monitoring of the bridge not only allows to investigate the impacts of ambient changes (e.g. temperature) on the bridge global parameters, but also it leads to achieve conclusive information to inform decisions with regard to the bridge structural performance. Since the Memorial Bridge has been newly reconstructed, the measurements, in the early age of the structure, can be used to train a valuable baseline model for future condition assessments. The use of statistical pattern recognition techniques has the advantage to derive objective decision making criteria for monitoring the actual state of the bridge. Additionally, analytical models can be developed as a basis for comparison purposes with monitoring data collected on the bridge (Milad Mehrkash). This exercise determines whether possible differences in the structural responses are due to induced changes in the bridge components (including possible occurrence of damage) or environmental variations. The latter will proactively assess and maintain the bridge performance, reduce long-term maintenance costs, and advance sustainable development of smart bridges around these issues. 

Written by: Vahid Shahsavari