PERTANIKA JOURNAL OF SCIENCE AND TECHNOLOGY

Damage to the bearings of a ship's propulsion motor represents a significant reason why ships experience operational disruptions. Therefore, it is important to detect and diagnose early on problems related to the bearings of a propulsion motor early on to reduce maintenance costs and prevent potential maritime accidents. Additionally, since bearings subjected to variable loading and speed in dynamic environments have the possibility for various types of damage to occur, an accurate, non-destructive detection method is required to allow for early indication of damage to bearings. A condition monitoring system based on acoustic signals was developed within this study to be able to monitor the health of the bearings of a propulsion motor without damaging them. A method called Short Time Fourier Transform (STFT) was used to analyse the time vs frequency characteristics of the acoustic signal generated by the motor during various operating conditions. The STFT analysis revealed unique spectral patterns that identified different forms of bearing damage, i.e., failure of the inner-race, outer-race, ball of the bearing, and cage. Testing of the system was conducted with a variety of combinations of speed and load to identify the reaction of the system to variations in operational conditions. Monitoring ship propulsion motors using the STFT algorithm has been proven to be suitable for processing non-linear data with a high accuracy of 97.5%. Development of this system will provide a safe and environmentally friendly way to monitor the operation of equipment at sea.