Predictive Maintenance for Rudder Cavitation: An Early-Warning Detection System in Marine Engineering

The gradual erosion of steering components, which can compromise vessel manoeuvrability and structural integrity, makes rudder cavitation a significant threat to marine safety and operational efficiency. This paper addresses this important problem by reporting the development of an automated dual-node early-warning detection system that can identify and classify rudder cavitation states in a distributed shipboard network. The proposed methodology simulates an acoustic and vibration sensor network integrated with two parallel PIC16F84A microcontrollers. A local steering gear unit classifies cavitation intensity into normal, warning and severe states from discrete sensor data A synchronised remote bridge unit provides real-time repeater alarms and dynamic tracking of active watchkeeping personnel. The predictive maintenance approach relies on distributed sensor monitoring, enabling proactive interventions and increasing operational availability and safety of vessels. The system offers remote condition assessment on an ongoing basis to enable mariners to make well-informed decisions to avoid extensive damage, costly dry-dock repairs and long downtimes. The research presented herein describes the design of a fault-tolerant, embedded framework for real-time diagnostic purposes and its use in enhancing the maritime operational safety and updating the anticipatory maintenance procedures.