Sensors – The Eyes and Ears of Ship Automation – Part 2

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.

Our hope is that the next generation of microprocessor-based shipboard machinery control systems will incorporate these or similar algorithms for real-time sensor diagnostics and accommodation (software-generated signals used as substitutes for failed sensors).

Click the link below to download the white paper …

Sensors – the Eyes and Ears of Ship Automation – Part 2