Search Results (581)

This paper addressed the problem of oil diagnostics lubricants applied to the predictive maintenance of industrial gearboxes, proposing the integration of an artificial intelligence (AI) system into the process analysis. The main objective was to overcome the critical issues of the traditional method, characterized by long analysis times and a marked dependence on the subjective interpretation of operators. The method includes a detailed statistical analysis of the common ways to assess the condition of lubricants, such as optical emission spectroscopy, particle counting, measuring viscosity and density, and Fourier-transform infrared spectroscopy (FT-IR). These methods are then combined with an artificial intelligence model. Tested on commercial gearbox data, the proposed approach demonstrates agreement between IA and expert evaluation. The application has shown that it can effectively support diagnoses, reduce processing time by 60%, and minimize human errors. It also improves knowledge sharing through an increase in the stability and repetitiveness of diagnoses and promotes consistency and clarity in reporting. Full article

Ecotribology focuses on both saving energy resources and reducing environmental pollution. Considering environmental concerns, water-based nanolubricants have gained significant attention over conventional oil-based ones. Non-ecotoxic and highly environmentally friendly nanoadditives were chosen for nanolubricant synthesis, especially considering their use at elevated temperatures. In this study, hexagonal boron nitride nanosheets (hBNNSs) and titanium dioxide nanoparticles (TiO₂ NPs) were used to prepare water-based lubricants with glycerol and surfactant sodium dodecyl benzene sulfonate (SDBS) in water under ultrasonication. An Rtec ball-on-disk tribometer was used to investigate the tribological performance of the synthesised water-based lubricants containing different nano-hBN/TiO₂ concentrations, with dry and water conditions used as benchmarks. The results indicated that the water-based nanolubricant containing 0.5 wt% hBN and 0.5 wt% TiO₂ exhibited the best tribological performance at both ambient (25 °C) and elevated (500 °C) temperatures. This optimal concentration leads to a reduction in the coefficient of friction (COF) by 72.9% and 37.5%, wear of disk by 62.5% and 49%, and wear of ball by 74% and 69% at ambient and elevated temperatures, respectively, compared to that of distilled water. Lubrication mechanisms were attributed to the rolling, mending, tribofilm, solid layer formation, and synergistic effects of hBNNSs and TiO₂ NPs. Full article

Analyzing the two-phase flow behavior in bearing lubrication is crucial for understanding friction and wear mechanisms, optimizing lubrication design, and improving bearing operational efficiency and reliability. However, the complexity of oil–air two-phase flow in high-speed bearings poses significant research challenges. Currently, there is a lack of comparative studies employing different simulation strategies to address this issue, leaving a gap in evidence-based guidance for selecting appropriate simulation approaches in practical applications. This study begins with a comparative analysis between experimental and simulation results to validate the reliability of the adopted simulation approach. Subsequently, a comparative evaluation of different simulation methods is conducted to provide a scientific basis for relevant decision-making. Evaluated from three dimensions—adaptability to rotational speed conditions, research focuses (oil distribution and power loss), and computational economy—the findings reveal that FVM excels at medium-to-high speeds, accurately predicting continuous oil film distribution and power loss, while MPS, leveraging its meshless Lagrangian characteristics, demonstrates superior capability in describing physical phenomena under extreme conditions, albeit with higher computational costs. Economically, FVM, supported by mature software ecosystems and parallel computing optimization, is more suitable for industrial design applications, whereas MPS, being more reliant on high-performance hardware, is better suited for academic research and customized scenarios. The study further proposes that future research could adopt an FVM-MPS coupled approach to balance efficiency and precision, offering a new paradigm for multi-scale lubrication analysis in bearings. Full article

This study investigates the coefficient of friction (COF) and wear behavior in fretting regimes—stick, stick–slip, and gross sliding—under dry and oil-lubricated conditions. Fretting tests were conducted by increasing oscillation amplitude from a few micrometers to 48 µm. In dry conditions, displacement amplitude initially rose rapidly, stabilizing after about 5 million load cycles, indicating steady-state behavior. The friction ratio (FR) surged early, peaking between 0.7 and 1.0, before declining to stable values, suggesting a shift from adhesive to stable frictional interaction. The minimal slip amplitude confirmed the predominance of the stick regime. Conversely, in oil-lubricated conditions, displacement amplitude stabilized after an initial increase, achieving higher amplitudes than in dry tests. The FR started below 0.2, gradually increasing to a peak around 10,000 load cycles for higher oscillation amplitudes (e.g., 15 µm), reflecting the lubricant’s role in reducing metal-to-metal contact. COF curves in lubricated tests showed smoother transitions and lower peak values compared to dry tests. These findings highlight the lubricant’s effectiveness in minimizing adhesion and enhancing sliding efficiency, offering insights for optimizing material performance in engineering applications. Full article

This study presents a detailed experimental comparison of the rotordynamic and thermal performance of automotive turbochargers supported by two distinct hydrodynamic bearing configurations: fully floating ring bearings (FFRBs) and semi-floating ring bearings (SFRBs). While both designs are widely used in commercial turbochargers, they exhibit significantly different dynamic behaviors due to differences in ring motion and fluid film interaction. A cold air-driven test rig was employed to assess vibration and temperature characteristics across a range of controlled lubricant conditions. The test matrix included oil supply pressures from 2 bar (g) to 4 bar (g) and temperatures between 30 °C and 70 °C. Rotor speeds reached up to 200 krpm (thousands of revolutions per minute), and data were collected using a high-speed data acquisition system, triaxial accelerometers, and infrared (IR) thermal imaging. Rotor vibration was characterized through waterfall and Bode plots, while jump speeds and thermal profiles were analyzed to evaluate the onset and severity of instability. The results demonstrate that the FFRB configuration is highly sensitive to oil supply parameters, exhibiting strong subsynchronous instabilities and hysteresis during acceleration–deceleration cycles. In contrast, the SFRB configuration consistently provided superior vibrational stability and reduced sensitivity to lubricant conditions. Changes in lubricant supply conditions induced a jump speed variation in floating ring bearing (FRB) turbochargers that was approximately 3.47 times larger than that experienced by semi-floating ring bearing (SFRB) turbochargers. Furthermore, IR images and oil outlet temperature data confirm that the FFRB system experiences greater heat generation and thermal gradients, consistent with higher energy dissipation through viscous shear. This study provides a comprehensive assessment of both bearing types under realistic high-speed conditions and highlights the advantages of the SFRB configuration in improving turbocharger reliability, thermal performance, and noise suppression. The findings support the application of SFRBs in high-performance automotive systems where mechanical stability and reduced frictional losses are critical. Full article

Many low-temperature applications, such as rocket engines and liquefied natural gas (LNG) transport pumps, necessitate ultra-low-temperature operational environments. In these conditions, the properties of lubricating oils and greases are significantly influenced by temperature, leading to the widespread adoption of solid lubrication. Currently, there is no international research regarding the influence of bearing coatings on the subsurface stress distribution in raceways. The Lundberg–Palmgren (L-P) theory states that subsurface stress variations govern bearing lifespan. Therefore, this paper utilizes existing formulas and Python programming to calculate the subsurface stress field of the inner raceway in a MoS₂ solid-lubricated angular contact ball bearing. Furthermore, it analyzes the impacts of factors such as coating material properties, slide-to-roll ratio, traction coefficient, and load on its subsurface stress field. The results reveal that for solid-lubricated ball bearings, as the load increases, the maximum subsurface stress shifts closer to the center of the contact area, and the maximum subsurface shear stress becomes more concentrated. As the traction coefficient increases, the stress on the XZ-plane side increases and its position moves closer to the surface, while the opposite trend is observed on the other side. Additionally, the maximum value of the subsurface von Mises stress is approximately 0.64P₀, and the maximum value of the orthogonal shear stress component τ_yz in the subsurface is approximately 0.25P₀. Full article

To address the unclear coupling mechanism between thermal elastohydrodynamic lubrication (TEHL) and dynamic behaviors in planetary gear systems, a novel tribo-dynamic model for dual-star planetary gears considering TEHL effects is proposed. In this model, a TEHL surrogate model is first established to determine the oil film thickness and sliding friction force along the tooth meshing line. Subsequently, the dynamic model of the dual-star planetary gear transmission system is developed through coordinate transformations of the dual-star gear train. Finally, by integrating lubrication effects into both time-varying mesh stiffness and time-varying backlash, a tribo-dynamic model for the dual-star planetary gear transmission system is established. The study reveals that the lubricant film thickness is positively correlated with relative sliding velocity but negatively correlated with unit line load. Under high-speed conditions, a thickened oil film induces premature meshing contact, leading to meshing impacts. In contrast, under high-torque conditions, tooth deformation dominates meshing force fluctuations while lubrication influence diminishes. By establishing a test bench for the planetary gear transmission system, the obtained simulation conclusions are verified. This research provides theoretical and experimental support for the design of high-reliability planetary gear systems. Full article

In order to improve the lubrication efficiency in the bearing cavity, this study establishes a simulation model of the fluid domain of the bearing cavity based on the computational fluid dynamics (CFD) method and systematically studies the flow characteristics of the lubricant and its lubrication mechanism in the high-speed rotary bearing. In the process of high-speed bearing operation, the lubricant is subject to the combined effect of centrifugal force and contact pressure, gradually spreads to both sides of the steel ball, and forms a stable oil film after injection from the nozzle. However, due to the influence of high pressure distribution in the contact area, the actual formation of the oil film coverage is relatively limited. In order to further optimize the lubrication effect, this study focuses on investigating the influence law of different injection speeds and rotational speeds on the bearing air curtain effect. The results of the study show that when the air curtain effect is enhanced, there will be significant shear interference on the trajectory of the lubricant, which is manifested in the phenomenon of “buckling” at the end of the lubricant, thus reducing the lubrication efficiency. To address this problem, this study innovatively proposes the air curtain obstruction coefficient K as a quantitative evaluation index, and through numerical simulation, it is found that the lubricant can effectively overcome the air curtain obstruction and achieve a better lubrication coverage when the value of K is reduced to below 0.4. Based on this finding, the study further confirmed that the lubrication efficiency of bearings can be significantly improved under different operating conditions by rationally regulating the injection rate. Full article

Tapered roller bearings are extensively utilized in the aerospace industry owing to their superior load-carrying capacity and extended service life. However, the majority of research conducted by scholars on the subject of bearing lubrication has focused on ball and cylindrical roller bearings. There is a paucity of research on the internal lubricants and air distribution of tapered roller bearings under oil jet lubrication conditions. This paper presents a computational fluid dynamics (CFD) simulation model specifically designed for the oil jet lubrication of tapered roller bearings. The flow field inside the bearing cavity is analyzed under various operating conditions, and the impact of different parameters on lubrication performance is quantitatively assessed using the oil return efficiency as a metric. Additionally, an experimental test stand for the jet lubrication of tapered roller bearings was developed. The simulated oil return efficiency was compared with experimental data, revealing discrepancies within 10%, thereby validating the accuracy of the CFD model. The findings suggest that directing the oil jet toward the smaller end of the bearing, appropriately increasing the nozzle flow rate, and utilizing positive jetting can significantly improve the lubrication performance of tapered roller bearings. Full article

Lubricant condition analysis is a valuable diagnostic tool for assessing engine performance and ensuring the reliable operation of diesel engines. While traditional diagnostic techniques—such as Fourier transform infrared spectroscopy (FTIR)—are constrained by slow response times, high costs, and the need for specialized personnel. In contrast, dielectric spectroscopy, impedance analysis, and soft computing offer real-time, non-destructive, and cost-effective alternatives. This review examines recent advances in integrating these techniques to predict lubricant properties, evaluate wear conditions, and optimize maintenance scheduling. In particular, dielectric and impedance spectroscopies offer insights into electrical properties linked to oil degradation, such as changes in viscosity and the presence of wear particles. When combined with soft computing algorithms, these methods enhance data analysis, reduce reliance on expert interpretation, and improve predictive accuracy. The review also addresses challenges—including complex data interpretation, limited sample sizes, and the necessity for robust models to manage variability in real-world operations. Future research directions emphasize miniaturization, expanding the range of detectable contaminants, and incorporating multi-modal artificial intelligence to further bolster system robustness. Collectively, these innovations signal a shift from reactive to predictive maintenance strategies, with the potential to reduce costs, minimize downtime, and enhance overall engine reliability. This comprehensive review provides valuable insights for researchers, engineers, and maintenance professionals dedicated to advancing diesel engine lubricant monitoring. Full article

Mechanical components are more difficult to detect at the initial state of failure. To solve this problem, this paper models and simulates the characteristics of an electrostatic oil-line sensor (OLS) wear particles carried in the lubricating oil path are detected. In this study, an OLS that monitors the charge in an oil line using the principle of electrostatic induction is modeled and simulated. The sensor characteristics are simulated and tested using finite element simulation. The sensor efficiency, spatial sensitivity, and length-to-diameter ratio are simulated based on the point charges at different locations. The simulation results show that the sensitivity exhibits different trends when the point charge is inside and outside the probe. The length-to-diameter ratio is proportional to the sensor efficiency, the spatial sensitivity distribution law of multiple charges is consistent with that of a point charge, and the relative deviation rate between the mathematically calculated values and the simulated values is less than 3% under the same conditions. In conclusion, the finite element simulation results of the electrostatic oil line sensor constructed in this study are consistent with the theoretical model calculations and can be used in future mechanical fault diagnosis. Full article

Worm gears are used in various mechanical constructions, especially in heavy industrial plants, where they are exposed to high operating loads, large torques, and high temperatures, particularly in conditions where it is necessary for the input and output shafts to be at an angle of 90°. Regarding tribological optimization, the application of carbon nanotube in lubricants can lead to significant improvements in the performance characteristics of worm gears, both in terms of increasing efficiency and reducing the coefficient of friction and wear, as well as minimizing mechanical losses, noise, and vibrations. The objective of this study is for the research results, through the use of oil with varying percentages of carbon nanotube additives (CNTs), to contribute to the optimization of worm gears by improving efficiency, extending service life, and reducing vibrations—both within the gearbox itself and within the industrial facility where it is applied. The research methodology involved laboratory testing of a worm gear using lubricants with varying concentrations of carbon nanotube. During the experiment, measurements of efficiency, vibrations, and noise levels were conducted in order to determine the impact of these additives on the operational performance of the gear system. The main contribution of this research is reflected in the experimental confirmation that the use of lubricants with optimized concentrations of carbon nanotube significantly enhances the operational performance of worm gears by increasing efficiency and reducing vibrations and noise, thereby enabling tribological optimization that contributes to improved reliability, extended service life, and enhanced workplace ergonomics under demanding industrial conditions. Furthermore, experimental investigations have shown that the efficiency of the gearbox increases from an initial value of 0.42–0.65, which represents an increase of 54%, the vibrations of the worm gear decrease from an initial value of 5.83–2.56 mm/s², which represents an decrease of 56%, while the noise was reduced from 87.5 to 77.2 dB, which represents an decrease of 12% with the increasing percentage of carbon nanotube additives in the lubricant, up to a maximum value of 1%. However, beyond this experimentally determined threshold, a decrease in the efficiency of the tested worm gearbox, as well as an increase in noise and vibration levels was recorded. Full article

The anodic oxide layer’s porosity is considered a functional feature, acting as a reservoir of lubricants. This feature enables the design of self-lubricating systems that effectively reduce friction and wear. To improve the tribological performance of Al₂O₃ anodic coatings on EN AW 5251 aluminium alloys, this paper presents a modification of the coating with tungsten disulfide (IF-WS₂) nanopowder and its effect on coating resistance. The wear properties of Al₂O₃/IF-WS₂ coatings in contact with a cast iron pin were investigated. The results include the analysis of the friction coefficient in the reciprocating motion without oil lubrication at two loads, the analysis of the wear intensity of the cast iron pin, the characterisation of wear scars, and the analysis of SGP parameters. Two-level factorial analysis showed that load and nanomodification significantly affected the load-bearing parameter Rk. Incorporation of the modifier, especially under higher loads, reduced the Rk value, thus improving the tribological durability of the contact pair. Both load and nanomodification had a notable impact on the coefficient of friction. The use of IF-WS₂-modified coatings reduced the coefficient, and higher loads further enhanced this effect, by approximately 9% at a load of 0.3 MPa and 15% at a load of 0.6 MPa, indicating improved lubricating conditions under greater contact stress. Full article

This study investigates the dynamic relationship between bearing gearbox condition indicators (BGCIs) and the lubrication oil temperature within the framework of health and usage monitoring system (HUMS) applications. Using the dynamic autoregressive distributed lag (DARDL) simulation model, we quantified both the short- and long-term responses of condition indicators to shocks in oil temperature, offering a robust framework for a counterfactual analysis. To complement the time-domain perspective, we applied a wavelet coherence analysis (WCA) to explore time–frequency co-movements and phase relationships between the condition indicators under varying operational regimes. The DARDL results revealed that the ball energy, cage energy, and inner and outer race indicators significantly increased in response to the oil temperature in the long run. The WCA results further confirmed the positive association between oil temperature and the condition indicators under examination, aligning with the DARDL estimations. The DARDL model revealed that the ball energy and the inner race energy have statistically significant long-term effects on the oil temperature, with p-values < 0.01. The adjusted R² of 0.785 and the root mean square error (MSE) of 0.008 confirm the model’s robustness. The wavelet coherence analysis showed strong time–frequency correlations, especially in the 8–16 scale range, while the frequency-domain causality (FDC) tests confirmed a bidirectional influence between the oil temperature and several condition indicators. The FDC analysis showed that the oil temperature significantly affected the BGCIs, with evidence of feedback effects, suggesting a mutual dependency. These findings contribute to the advancement of predictive maintenance frameworks in HUMSs by providing practical insights for enhancing system reliability and optimizing maintenance schedules. The integration of dynamic econometric approaches demonstrates a robust methodology for monitoring critical mechanical components and encourages further research in broader aerospace and industrial contexts. Full article

This study explores the machinability of Incoloy 800HT (high temperature) under a sustainable lubrication approach, employing a twin-nozzle minimum quantity lubrication (MQL) system with groundnut oil as a green cutting fluid. The evaluation focuses on key performance indicators, including surface roughness, tool flank wear, power consumption, carbon emissions, and chip morphology. Groundnut oil, a biodegradable and nontoxic lubricant, was chosen to enhance environmental compatibility while maintaining effective cutting performance. The Taguchi L₁₆ orthogonal array (three factors and four levels) was utilized to conduct experimental trials to analyze machining characteristics. The best surface quality (surface roughness, Ra = 0.514 µm) was obtained at the lowest depth of cut (0.2 mm), modest feed (0.1 mm/rev), and moderate cutting speed (160 m/min). The higher ranges of flank wear are found under higher cutting speed conditions (320 and 240 m/min), while lower wear values (<0.09 mm) were observed under lower speed conditions (80 and 160 m/min). An entropy-integrated multi-response optimization using the MOORA (multi-objective optimization based on ratio analysis) method was employed to identify optimal machining parameters, considering the trade-offs among multiple conflicting objectives. The entropy method was used to assign weights to each response. The obtained optimal conditions are as follows: cutting speed = 160 m/min, feed = 0.1 mm/rev, and depth of cut = 0.2 mm. Optimized outcomes suggest that this green machining strategy offers a viable alternative for sustainable manufacturing of difficult-to-machine alloys like Incoloy 800 HT. Full article