This paper proposes a new belief rule-based (BRB) expert system for fault diagnosis of marine diesel engines. The expert system is the first of its kind that consists of multiple concurrently activated BRB subsystems, in which each subsystem has its distinctive outputs and uses the evidential reasoning approach for inference. This novel modeling approach can be applied to identify fault modes that may co-exist. In essence, the group of BRB subsystems is used to model the nonlinear relationships between the fault features and the fault modes in marine diesel engines. The initial BRB expert system can be established by using expert experience and then optimized by using the data samples accumulated during the operation of marine diesel engines. Due to limitations in knowledge and data collected, ignorance is also considered in some BRB subsystems. The proposed BRB expert system is applied to abnormal wear detection for a kind of marine diesel engine. The performance of the BRB expert system is investigated in comparison with that of artificial neural network (ANN) models, support vector machine (SVM) models, and binary logistic regression model with fivefold cross-validation. The results show that the BRB expert system can be used for fault diagnosis of marine diesel engines in a probabilistic manner, which outperforms the ANN models, SVM models, and the binary logistic regression model in terms of accuracy and stability, and can effectively identify concurrent faults.

Frictional vibration and noise caused by water-lubricated rubber stern tube bearings, which are generated under extreme conditions, severely threaten underwater vehicles’ survivability and concealment performance. This study investigates the effect of flaky and spherical MoS₂nanoparticles on tribological properties and damping capacity of water-lubricated rubber materials, with the aim of decreasing frictional noise. A CBZ-1 tribo-tester was used to conduct the sliding tests between rubber ring-discs and ZCuSn₁₀Zn₂ring-discs with water lubrication. These materials’ typical mechanical properties were analysed and compared. Coefficients of friction (COFs), wear rates, and surface morphologies were evaluated. Frictional noise and critical velocities of generating friction vibration were examined to corroborate above analysis. Results showed that spherical MoS₂nanoparticles enhanced rubber material’s mechanical and tribological properties and, in turn, reduced the friction noise and critical velocity. Flaky MoS₂nanoparticles reduced COF but did not enhance their mechanical properties, i.e., the damping capacity, wear resistance property; thus, these nanoparticles did not reduce the critical velocity obviously, even though increased the frictional noise at high load. The knowledge gained in the present work will be useful for optimizing friction pairs under extreme conditions to decrease frictional noise of water-lubricated rubber stern tube bearings.

Conventional, multimodal and nanostructured WC-12Co coatings with different WC sizes and distributions were prepared by high velocity oxy-fuel spray (HVOF). The micrographs and structures of the coatings were analyzed by scanning electron microscope (SEM), X-ray diffractometer (XRD) et al. The porosity, microhardness and fracture toughness of the WC-Co coatings were measured. The coating resistance to cavitation erosion (CE) was investigated by ultrasonic vibration cavitation equipment and the cavitation mechanisms were explored. Results show that there is serious WC decarburization in nanostructured and multimodal WC-Co coatings with the formation of W₂C and W phases. The nanostructured WC-Co coating has the densest microstructure with lowest porosity compared to the other two WC-Co coatings, as well as the highest fracture toughness among the three coatings. It was also discovered that the nanostructured WC-Co coating exhibits the best CE resistance and that the CE rate is approximately one-third in comparison with conventional coating.

Polymers are widely used in bearing applications. In the case of water-lubricated stern tube bearings, thermoplastic polyurethane (TPU)-based composites are used due to their excellent wear resistance, corrosion resistance, and tunable mechanical properties. Their tribological performance, however, depends on operating conditions. In this work, TPU was blended with carbon fiber, graphene platelet, and ultra-high molecular weight polyethylene (UHMWPE). Friction tests of TPU based-composites against copper countersurface were carried out in water to mimic the actual operating conditions of the bearing. Most of the resulting contacts were in the boundary lubrication regime, in which friction was attributed to both contact mechanics of asperities as well as water lubrication. Our results show that the viscoelasticity of TPU has a considerable impact on its tribological performance. Water lubrication at 50 °C promotes the softening of polymer surface material during sliding, resulting in higher fluctuation in the coefficient of friction and wear loss. This is attributed to the reduced thermomechanical properties. In addition, Schallamach waviness is observed on worn surface. The tribological properties of TPU are significantly improved by the inclusion of carbon fiber, graphene platelet, and UHMWPE. The formation of graphene transfer-layers and UHMWPE transfer film reduces friction and wear loss, while the inclusion of carbon fiber enhances wear resistance due to improved mechanical properties and load bearing capacity.

The main wear mechanism between the NBR pins and the 1Cr18Ni9Ti stainless steel rubbing pairs is severe adhesion tearing wear under the water-lubricated condition.