Guobin Li

Abnormal vibration is one of the primary causes of high-pressure fuel pipe failure. To investigate the vibration characteristics of a high-pressure fuel pipe under combined diesel engine excitation and fuel pressure pulsation, a two-way fluid–structure interaction (FSI) model was established. A comparative analysis of the dry and wet modal characteristics was first performed. Based on the prescribed diesel engine vibration displacement, the vibration responses of the high-pressure fuel pipe with and without diesel engine excitation were compared. Furthermore, the effects of different engine loads (50 %, 75 %, and 100 %) and inlet pressure levels (36, 38, 40, 42, and 44 MPa) on the vibration energy distribution were investigated through spectral analysis. The results show that the natural frequencies of the high-pressure fuel pipe decrease under fluid-structure interaction, with the frequency reduction becoming more pronounced in higher-order modes. When diesel engine excitation is considered, the peak vibration displacement decreases slightly, while the vibration attenuation rate decreases, resulting in a longer vibration response duration. As the engine load increases, the vibration displacement increases, and the spectral components near the second and fourth wet modal frequencies become more pronounced under the full-load condition. Increasing the inlet pressure also leads to a progressive increase in the spectral amplitude, particularly near the fourth wet modal frequency. These findings provide theoretical support for vibration assessment and structural optimization of marine high-pressure fuel pipes.

Oil flow rate is a key indicator of energy-transfer efficiency and operating conditions in hydraulic systems, and microelectromechanical systems (MEMS) sensors offer a promising approach for its measurement because of their high sensitivity and integration potential. This paper proposes a differential-pressure flow sensor that integrates a piezoresistive MEMS pressure sensor with a variable-diameter pipe differential pressure generator (VDP-DPG) for hydraulic oil flow measurement. A flow rate-pressure difference model is established using the Navier-Stokes and Bernoulli equations, and key geometric parameters are optimized through numerical simulation. Under the prescribed size constraints, a 7° diffuser angle, a 5.0 mm inner-passage inlet diameter, and a 17.74° outer-passage contraction angle provide a favorable balance between pressure-difference output and pressure loss. Simulations at inlet velocities of 0.1-1.0 m/s reveal an approximately quadratic relationship between pressure difference and inlet velocity. Based on the optimized simulation results, an engineering prototype of the MEMS-integrated VDP-DPG is designed and fabricated. The prototype exhibits a sensitivity of 3.456 mV/kPa, and flow tests at 0.1-0.5 m/s show good agreement with the numerical trend, supporting the mathematical model and measurement principle. The results demonstrate the feasibility and potential of combining piezoresistive MEMS sensing with a VDP-DPG for hydraulic oil flow measurement.

Electrical slip rings are key components for power and signal transmission in rotating equipment, and degradation of sliding electrical contact is a major factor limiting their reliability. To analyze the sliding electrical contact behavior of slip rings, an elastoplastic contact framework incorporating thermal–mechanical–electrical coupling is developed. The semi-analytical method combined with discrete convolution-fast Fourier transform is employed to efficiently solve the coupled contact problem, while J₂ flow theory and radial return algorithm are adopted to determine plastic deformation. Based on the proposed model, the elastoplastic sliding electrical contact behaviors of smooth and sinusoidal surfaces are systematically investigated. The results show that plastic deformation increases the contact area, thereby reducing the electrical contact resistance, current density at the contact edge, and maximum temperature rise, although it may induce the residual stress. Reducing the asperity height of sinusoidal surfaces while maintaining multiple discrete micro contact spots can effectively lower the electrical contact resistance and interfacial temperature rise. The proposed model provides a useful theoretical tool for evaluating the thermal–mechanical–electrical performance of sliding electrical contact in slip rings.

Water-lubricated bearings play a vital role in marine propulsion systems, significantly influencing operational reliability and environmental sustainability. Accurate and real-time monitoring of lubrication states in these bearings is essential to guarantee the safe operation of marine vessels. Nevertheless, many existing monitoring approaches rely on laboratory-acquired static parameters, such as film thickness and pressure, which inadequately capture the dynamic lubrication variations encountered during actual navigation conditions. To overcome this limitation, an embedded cantilever-beam bouncing-ball triboelectric nanogenerator (CB-TENG) is developed as a self-powered sensor that converts water-film-induced micro-vibrations within a confined bearing clearance into electrical outputs. A coupled simulation framework parameterized by film thickness, together with comparative 30-min experiments under representative loads, demonstrates that fluid excitation alone can effectively drive the CB-TENG response and that the vibration/electrical characteristics depend measurably on lubrication conditions. As lubrication improves, the output evolves from low-amplitude, broadband and aperiodic fluctuations (boundary lubrication) to quasi-periodic oscillations with intermittent disturbances (mixed lubrication), and further to a stronger and more coherent near-resonant component with spectral energy concentrated around the structural natural-frequency band (hydrodynamic lubrication). Quantitative features derived from the time- and frequency-domain signals (e.g. RMS level and the spectral peak amplitude near the natural frequency) provide reproducible criteria for lubrication-state discrimination. The proposed CB-TENG offers a compact, passive, and self-powered route for in-situ condition monitoring of marine water-lubricated bearing systems.

Diesel engine is the main power source of ships, and its failure seriously affects safe navigation. Transfer learning is an effective method to solve cross-domain diagnosis of marine diesel engine. However, when facing large domain shifts, relying solely on cross-domain consistent semantic information cannot achieve high-precision diagnosis of the target task. A diagnostic method for diesel engine has been proposed. The shallow independent - deep sharing mechanism is first designed to fully consider the specificity and commonality of different domains. Then, the reliable alignment of different classes of source and target domains is achieved based on domain alignment theory and pseudo-label strategy. The performance of the framework is rigorously evaluated by two real-world cases and its applicability across subsystems is verified. The results demonstrate that the average accuracy of the framework is over 93%, outperforming other methods by more than 1.55%. Even in tasks with large domain distribution discrepancies, the framework also enables robust feature transfer.