Development of a Multisensor Fusion Algorithm for Displacement Estimation

Abstract

While displacement is valuable information regarding the behavior of structures, measuring displacement from large civil structures is often challenging and costly. To overcome difficulties found in direct measurements such as LVDT and LASER-based methods, indirect displacement estimation approaches are alternatively developed using acceleration or strain that are relatively cost-effective and convenient to measure. However, these measurements have own characteristics that limit wider application of the indirect estimation. For example, as double integration of acceleration results in the low frequency drift in the estimated displacement, high-pass filters are often used to suppress the drift, assuming displacements are close to a zero mean process. These types of limitations can be resolved by employing fusion of different types of measurements. This study develops an indirect displacement estimation method based on the multimetric data (i.e., acceleration and strain) that can estimate non-zero mean, dynamic displacements. The approach is numerically validated using a simply supported beam with moving loads that produce non-zero mean displacements.