The Implementation of Nonlinear Signal Techniques for Enhanced Monitoring of Marine Propulsion Systems

Abstract

The motor is a crucial component of a ship's propulsion system, playing a significant role in facilitating smooth maritime transportation operations. Various factors, including dynamic loads, speed variations, and unstable marine environmental conditions influence the performance of the propulsion motor. Under dynamic conditions, the ship's propulsion motor encounters challenges such as load fluctuations, vibrations, and other disturbances that can affect its efficiency and operational lifespan. Consequently, real-time monitoring of the motor's condition has become an urgent necessity to detect potential damage early and ensure the safety and reliability of the ship's operations. This study aims to develop a condition monitoring system for ship propulsion motors using nonlinear acoustic signals. These signals will be processed using appropriate algorithms for nonlinear signals' characteristics. The Short Time Fourier Transform (STFT) is identified as a suitable algorithm for processing nonlinear signals. The filtered signal results will provide insights into the condition of the ship's propulsion motor. Given the influence of vibrations and non-engine noise, careful consideration must be given to sensor placement to achieve high monitoring accuracy. The Completely Randomized Design (CRD) approach will be employed to determine the optimal sensor placement. Through precise signal processing, meticulous spectral analysis, and optimal sensor positioning, accurate information can be obtained. The research findings indicate that the motor monitoring system achieved an accuracy rate of 100% with the sensor positioned 110 cm from the test motor body.