Vibration and Grease Condition Monitoring in Rotating Marine Mechanical Equipment: A Review

Rotating mechanical equipment forms the operational backbone of marine vessels and offshore installations. Main propulsion machinery, shaft lines, thrusters, deck cranes, winches, pumps, fans, and electric motors all depend on rolling element bearings, gears, and couplings that must survive sustained loading in one of the harshest industrial environments on earth. Unplanned failure of such equipment at sea carries consequences that extend far beyond repair cost, including loss of propulsion, grounding risk, environmental damage, and threats to crew safety. Condition monitoring has therefore become central to modern marine maintenance strategy, and two complementary technologies dominate the field: Vibration analysis, which interrogates the dynamic response of the machine, and grease or lubricant condition monitoring, which interrogates the health of the tribological interface itself. This review surveys the state of the art in both domains as applied to marine rotating machinery. Vibration monitoring is examined from sensing hardware through signal processing, covering time domain statistical indicators, spectral and envelope analysis, time frequency decomposition, and the rapid rise of machine learning and deep learning diagnostics. Grease condition monitoring is reviewed with attention to grease degradation mechanisms in the marine environment, offline laboratory techniques such as spectroscopic, rheological, and wear debris analysis, and emerging online sensing approaches including dielectric, ultrasonic, and acoustic emission methods. The complementary nature of the two technologies is emphasised, and the enabling infrastructure surrounding them, including sensing networks, data architectures, cybersecurity, maintenance logistics, safety management, and programme economics, is reviewed by drawing on developments in adjacent asset intensive industries. The review closes by identifying practical challenges specific to ships, including non stationary operating profiles, sensor survivability, limited crew expertise, and data transfer constraints, and outlines future research directions in sensor fusion, digital twins, and prognostics for remaining useful life estimation.