Data Fusion of Accelerometers with Inclinometers for Reference-free High Fidelity Displacement Estimation
Abstract »Today, 40% of the US’s freight tonnage is carried by railroads and the demand for railroads is expected to double in 20 years. While use of railroads keeps increasing, operations of maintenance, repair and replacement (MRR) cannot respond to the aging infrastructure immediately due to limited resources. Since railroad bridges are under constant stress of train loads, the assessment of existing railroad bridges is required for sustainable, safe, reliable and continuous railroad operations. However, accurate measurement of bridge movements during operation is a challenging task. This paper proposes a new method fusing multi-metric measurement data obtained from accelerometers and inclinometers in real-time to provide quantitative information for data-driven structural health assessments. To study the performance of the proposed method, a cantilever beam representing pier bent is simulated in real-time. Measured responses at the tip of the beam are compared to the displacements estimated by the data fusion method. The results indicate that bridge responses can be accurately estimated even in the events where pseudo-static displacements due to non-symmetrical heavy train loading are dominant.