Abstract
There is a common perception when monitoring ocean waves, that data buoys, measuring parameters, such as significant wave height and dominant period, must have the characteristics of true wave followers, where the movement of the device is assumed to follow the free surface of the ocean. This presents an obstacle to using wave energy to power data buoys, as wave energy converters necessarily interact with passing waves to harness their energy. This study proposes a Kalman filter-based unknown input estimator to be used as a soft sensor to process readings from an existing motion sensor mounted a data buoy, taking into account the effects of an internal moonpool acting as an oscillating water column (OWC), including tests with an orifice plate to simulate a turbine power take-off (PTO). The estimator described in this article is tested against wave tank data in both regular and irregular waves, for a fully sealed moonpool, acting as a linear system. This article also describes how the Kalman filter can be extended to handle the nonlinearities introduced by fitting an orifice plate simulating an OWC turbine PTO, and tests this against regular wave data. The proposed sensor is found to accurately return values for significant wave height and zero-crossing period, as well as time series estimates of the free surface elevation, at 0.1 s time steps, for both linear and nonlinear system representations.