Sensors are the eyes and ears of your automation. Their health is essential to all shipboard monitoring and control functions that require reliable data to synthesize decisions.
In Part 2 of this series, we present some advanced research involving two multivariate machine learning algorithms; nonlinear state estimation and support vector machines, both applicable to shipboard sensor diagnostics. Data collected from a ship’s main propulsion gas turbine engine is used in the case study.