Using Feature Extraction to Perform Equipment Health Monitoring on Ship-Radiated Noise

The current state of the art in hydroacoustics research employs a variety of feature extraction techniques with the goal of accurately classifying a ship based on its radiated noise. These techniques are capable of accuracy in excess of 95%. A question arises as to whether similar techniques could be applied to a known vessel to identify and monitor individual systems from the ship’s noise. In this paper, the fast orthogonal search algorithm is used as a basis for a feature extraction and classification algorithm. This algorithm is applied to real recordings of ship-radiated noise and is shown to be capable of identifying the running status of a subset of the ship’s systems, providing a proof of concept for the detection and monitoring of a ship’s systems based solely on the ships hydroacoustic noise.