Although hydraulic accumulators play a vital role in the hydraulic system, they face the challenges of being broken by continuous abnormal pulsating pressure which occurs due to the malfunction of hydraulic systems. Hence, this study develops anomaly detection algorithms to detect abnormalities of pulsating pressure for hydraulic accumulators. A digital pressure sensor was installed in a hydraulic accumulator to acquire the pulsating pressure data. Six anomaly detection algorithms were developed based on the acquired data. A threshold averaging algorithm over a period based on the averaged maximum/minimum thresholds detected anomalies 2.5 h before the hydraulic accumulator failure. In the support vector machine (SVM) and XGBoost model that distinguish normal and abnormal pulsating pressure data, the SVM model had an accuracy of 0.8571 on the test set and the XGBoost model had an accuracy of 0.8857. In a convolutional neural network (CNN) and CNN autoencoder model trained with normal and abnormal pulsating pressure images, the CNN model had an accuracy of 0.9714, and the CNN autoencoder model correctly detected the 8 abnormal images out of 11 abnormal images. The long short-term memory (LSTM) autoencoder model detected 36 abnormal data points in the test set.

The enlargement of ships has increased the relative hull deformation owing to draft changes. Moreover, design changes such as an increased propeller diameter and pitch changes have occurred to compensate for the reduction in the engine revolution and consequent ship speed. In terms of propulsion shaft alignment, as the load of the stern tube support bearing increases, an uneven load distribution occurs between the shaft support bearings, leading to stern accidents. To prevent such accidents and to ensure shaft system stability, a shaft system design technique is required in which the shaft deformation resulting from the hull deformation is considered. Based on the measurement data of a medium-sized oil/chemical tanker, this study presents a novel approach to predicting the shaft deformation following stern hull deformation through inverse analysis using deep reinforcement learning, as opposed to traditional prediction techniques. The main bearing reaction force, which was difficult to reflect in previous studies, was predicted with high accuracy by comparing it with the measured value, and reasonable shaft deformation could be derived according to the hull deformation. The deep reinforcement learning technique in this study is expected to be expandable for predicting the dynamic behavior of the shaft of an operating vessel.

The reliability of propulsion shafting systems is a major concern for ocean-going vessels because mid-ocean repairs can be time-consuming and spare parts must be available. To address this concern, vibration modeling and experimental measurements were conducted on a propulsion shafting system with a Z-drive propeller, with the objective of identifying the source of failure for the flexible rubber coupling connecting the diesel engine with the intermediate shaft. The torsional fluctuations in the flexible coupling dramatically increased and then abruptly ceased. The modeling results revealed that the frictional losses during power transmission through the universal joints could act as an excitation force for self-excited vibration. The coupling connected to the intermediate shaft did not have sufficient radial flexibility to dampen these vibrations. To avoid the effects of the self-excited torsional vibration, it is recommended that this coupling is replaced with one that is capable of absorbing the radial shaft displacement.

It is known that a ship’s shafting system can be adversely affected by hull deformation, variations in the engine power, the propeller load, and eccentric propeller thrusts, thereby increasingly affecting the behavior of the shaft’s movement. A deformed shafting system may also lead to a potential risk of bearing damage by causing a change in the local load of the rear part of the after-stern tube bearing of the propeller shaft. With this concern, a series of previous studies were focused on optimizing the effects of hull deformation by securing a proper level of propulsion shaft stability and optimizing the relative inclination angle and oil film retention based on a quasi-static state, that is, Rules for the Classification of Steel Ships and experiences of shipyards. However, despite our efforts to resolve this issue, marine accidents involving stern tube bearing damage have continued to occur under relatively unattended ship motions in a transient state, that is, a quasi-static state that can possibly cause sudden stern flow field changes. Therefore, to improve the stability of the propulsion shaft, it is necessary to understand ship motions and the conditions of shafting systems in a dynamic state and a transient state when the system is designed. From this point of view, this study investigated the effect of changes in eccentric propeller forces on the motion of the propeller shaft in a representative transient state of a 50,000 deadweight tonnage tanker by means of the strain gauge method and a displacement sensor. The research findings demonstrate that propeller thrust fluctuations have a direct effect on the shaft stability by significant changes in the shaft motion that can lead to unbalanced supporting loads on the stern tube bearing. These results clearly reproduce the cause of damage to the ship in which the accident occurred at a reliable level and will be a reference for establishing pragmatic guidelines for preventing damage to similar ships in the future.

The vessel speed reduction program (VSRP) was first introduced in the Port of Los Angeles in 2001 to improve air quality. In this study, an algorithm was developed to calculate ship emissions with a bottom-up approach based on ship activity using automatic identification system (AIS) data. The target vessel applied to the emission calculation was a vessel participating in Korea’s VSRP. Factors considered for the calculation of emissions were ship type, speed, gross tonnage, engine power, load, sulfur content of fuel, and fuel consumption rate by engine age. The algorithm is designed to calculate the reduction amount by VSRP by simultaneously calculating the emission amount of the actual speed and the emission amount of the cruise speed when not participating in VSRP. The emission results of ships that participated in the VSRP in 2020 revealed that their speed was reduced by 47% and carbon dioxide emissions by 71.9%. These results were verified through comparison with the fuel consumption report of the container fleet presented by the International Maritime Organization. Our findings can be used to monitor the air pollutant emissions of ships entering major ports in Korea and to develop policies envisaged at reducing the production and effect of greenhouse gases and air pollutants. Moreover, we recommend that this model be replicated in other countries for monitoring ship-induced emissions.

The injection timing of fuel in a diesel engine affects the combustion condition. Advanced fuel injection prolongs the ignition delay, positively impacting the increase in maximum combustion pressure and improving output. However, excessively advanced fuel injection can cause knocking. Moreover, premature ignition results in increased compression work when the maximum combustion pressure occurs before top dead center (TDC). This study aimed to diagnose and rectify starting failures, noise, and vibrations in a commercially operated ship engine by measuring the combustion pressure during low load operation. The target engine was a 4-stroke diesel, and the fuel injection system was mechanically controlled by a camshaft. The measured engine exhibited a 4.5 °CA error between the TDC, determined by the flywheel mark and the actual TDC. This discrepancy was influenced by excessively advanced fuel injection timing. It was confirmed that fuel injection and ignition were excessively advanced in all cylinders. After readjusting the engine by delaying the fuel injection timing by approximately 10 °CA, the combustion pressure was remeasured. The ignition was delayed by approximately 6.5 °CA at the same load, and the ignition intervals were uniformly adjusted. As the ignition timing was retarded, the compression work decreased and the expansion work increased in each cylinder, resulting in improved output across all cylinders. The amplitude of crankshaft angular velocity variation significantly decreased, improving uneven rotational force.