Dynamic State Tracking of Overhead Powerlines With Real Time State Estimation: a Data-Driven Approach

Abstract This study focuses on laying the groundwork for the effective vibration suppression of power lines using mobile damping robots (MDR). Earlier research shows that effective vibration suppression is achieved by positioning the MDR at the anti-nodes of the power line. This study focuses on accurately estimating the dynamic state of the power line using a data-driven approach, hence identifying the position of the antinode. The entire dynamics of the vibration of the system is estimated from the displacement data of the power line using Dynamic Mode Decomposition (DMD) and the resulting system is stabilized with Tikhonov Regularization. The stabilized system is then used in conjunction with a Kalman Filter to accurately estimate the dynamic state of the power line using minimal displacement. All displacement data used in this study is acquired from a Galerkin model of the power line. This study shows that this method is a viable alternative to existing numerical methods which are often computationally expensive and time-consuming.