Lubricants, Volume 12, Issue 2 (February 2024) – 36 articles

Chemical–mechanical planarization (CMP) is used to smoothen the topographies of a rough surface by combining several functions of tribology (friction, lubrication), chemistry, and electrochemistry (corrosion, wear, tribo-corrosion). The surface layer of interest is structurally weakened by the chemical and/or electrochemical reactions of selected additives in a polishing slurry, and the modified surface is flattened by the abrasion of a polishing pad with or without abrasive particles. The chemically active CMP slurry also serves as a lubricant for polishing and enables planarization at a microscopic level while avoiding the formation of defects at the processed surface. Applications of CMP are wide-ranging in various material-processing technologies and, specifically, it is a critical manufacturing step of integrated circuits. The CMP of metals is a significant part of this processing scheme and is associated with highly complex tribo-electrochemical mechanisms that are now additionally challenging due to various new requirements of the advanced technology nodes. The present review examines the current statuses of experimental strategies for collecting important mechanistic details of metal CMP that are necessary to design and assess CMP consumables. Both traditional and underexplored experimental techniques are discussed with illustrative results, including many previously unpublished findings for certain CMP systems of current interest. Full article

Ensuring precise prediction, monitoring, and control of frictional contact temperature is imperative for the design and operation of advanced equipment. Currently, the measurement of frictional contact temperature remains a formidable challenge, while the accuracy of simulation results from conventional numerical methods remains uncertain. In this study, a PINN model that incorporates physical information, such as partial differential equation (PDE) and boundary conditions, into neural networks is proposed to solve forward and inverse problems of frictional contact temperature. Compared to the traditional numerical calculation method, the preprocessing of the PINN is more convenient. Another noteworthy characteristic of the PINN is that it can combine data to obtain a more accurate temperature field and solve inverse problems to identify some unknown parameters. The experimental results substantiate that the PINN effectively resolves the forward problems of frictional contact temperature when provided with known input conditions. Additionally, the PINN demonstrates its ability to accurately predict the friction temperature field with an unknown input parameter, which is achieved by incorporating a limited quantity of easily measurable actual temperature data. The PINN can also be employed for the inverse identification of unknown parameters. Finally, the PINN exhibits potential in solving inverse problems associated with frictional contact temperature, even when multiple input parameters are unknown. Full article

An optimisation model for small datasets was applied to thixocasted/compocasted composites and hybrid composites with hypereutectic Al-18Si base alloys. Composites were produced with the addition of Al₂O₃ (36 µm/25 nm) or SiC (40 µm) particles. Based on the design of experiment, tribological tests were performed on the tribometer with block-on-disc contact geometry for normal loads of 100 and 200 N, a sliding speed of 0.5 m/s, and a sliding distance of 1000 m. For the prediction of the tribological behaviour of composites, artificial neural networks (ANNs) were used. Three inputs were considered for ANN training: type of reinforcement (base alloy, Al₂O₃ and SiC), amount of Al₂O₃ nano-reinforcement (0 and 0.5 wt.%), and load (100 and 200 N). Various ANNs were applied, and the best ANN for wear rate (WR), with an overall regression coefficient of 0.99484, was a network with architecture 3-15-1 and a logsig (logarithmic sigmoid) transfer function. For coefficient of friction (CoF), the best ANN was the one with architecture 3-6-1 and a tansig (hyperbolic tangent sigmoid) transfer function and had an overall regression coefficient of 0.93096. To investigate the potential of ANN for the prediction of two outputs simultaneously, an ANN was trained, and the best results were from network 3-5-2 with a logsig transfer function and overall regression coefficient of 0.99776, but the predicted values for CoF in this case did not show good correlation with experimental results. After the selection of the best ANNs, the Taguchi grey multi-response optimisation of WR and CoF was performed for the same combination of factors as the ANNs. For optimal WR and CoF, the combination of factors was as follows: composite with 3 wt.% Al₂O₃ micro-reinforcement, 0.5 wt.% Al₂O₃ nano-reinforcement, and a load of 100 N. The results show that developed ANN, the Taguchi method, and the Taguchi grey method can, with high reliability, be used for the optimisation of wear rate and coefficient of friction of hypereutectic Al-Si composites. Microstructural investigations of worn surfaces were performed, and the wear mechanism for all tested materials was light abrasion and adhesion. The findings from this research can contribute to the future development of hypereutectic Al-Si composites. Full article

The oil–air lubrication method is specifically employed for high or ultra-high-speed spindle rolling bearings. Under high-speed conditions, the air curtain formed inside the bearing cavity obstructs oil delivery, thereby limiting further increases in spindle rotation speed. To enhance oil delivery capability, a guiding-structured nozzle has been developed to concentrate the jet flow and improve penetration through the air curtain. Tests were conducted on an oil–air lubricated bearing test bench to investigate the impact of nozzle structures and oil types on torque and temperature rise. The results demonstrate that compared to conventional nozzles, the guiding-structured nozzle requires smaller optimal amounts of oil supply, indicating its superior ability to deliver oil. Further examination of oil jet patterns and droplet distributions confirms that the guiding-structured nozzle provides a more concentrated jet flow with uniform distribution and smaller droplet sizes in diameter. These characteristics contribute to highly efficient oil delivery. Additionally, synthetic oils reduce droplet size, torque, and temperature rise in mixed lubrication regimes due to their formation of an anti-friction absorption layer on rubbing surfaces. Full article

White etching layers (WELs) and brown etching layers (BELs), formed on the upper layer of bearing raceways generally lead to surface crack initiation and propagation and significantly affect the stable operation of precision bearings. In this study, the microstructure features of WELs and BELs from two failure bearings have been characterized and analyzed. The BEL mainly consists of quenched martensite with higher hardness values. The bainite simultaneously exists at the boundary of the BEL/matrix. Owing to the relative roll and slip, temperature increases and rapid decreases are the main formation mechanisms of the BEL in this study (thermal-induced effect). The WEL can be only found on one sample, and elongated and coarse grains are found in this region. It can be speculated that the WEL may originate from the surface region temperature increasing again and then slowly decreasing. Cracks can initiate at the boundaries of the WEL/BEL/matrix. The crack propagation behaviors are significantly affected by the properties of the WEL and BEL microstructure. It is difficult for the cracks to propagate from a softer WEL into a harder BEL. Thus, the depth of cracks in the WEL is shallower. However, because of the brittle nature of quenched martensite in the BEL, cracks can easily propagate downward under contact stress. Thus, the depth of cracks can exceed 100 μm easily. The formation mechanisms of the WEL/BEL and crack propagation behaviors have been further proved and discussed in this study. Full article

This research shows the antifriction and antiwear synergies between a phosphonium ionic liquid (IL) and f-WS₂ and f-SiO₂ nanoparticles (NPs) as additives of a base oil with low viscosity (PAO6). Mass concentrations of 0.1 wt% nanoadditives and 1% IL were selected to formulate the nanolubricants. Pure sliding and rolling–sliding friction tests were performed at 120 °C, finding great friction reductions in comparison with the PAO6 base oil, specifically for the double hybrid nanolubricant (PAO6 + 1 wt% IL + 0.1 wt% f-WS₂ + 0.1 wt% f-SiO₂). Regarding the wear produced, the greatest antiwear behavior was also achieved for the double hybrid nanolubricant (width reduction of 48% and worn area decrease of 84%). Furthermore, by means of Raman microscopy and roughness examination of the worn surfaces, it can be proposed that the lubrication mechanism of doubled hybrid nanolubricants could be supported by the adsorbed tribofilm (IL and f-WS₂) as well as the mending effects (f-WS₂ and f-SiO₂). Full article

The finite element method(FEM) is a powerful tool for studying friction and wear. Compared to experimental methods, it has outstanding advantages, such as saving financial costs and time. In addition, it has been widely used in friction and wear research. This paper discusses the application of the FEM in the study of friction and wear in terms of the finite element modeling methods, factors affecting wear behavior, wear theory, and the practical application of the method. Finally, the latest progress of finite element simulation wear research is summarized, and the future research direction is proposed. Full article

Recent green manufacturing demands have boosted the development of new biodegradable lubricants to replace petroleum-based lubricants. In this regard, water-based lubricants have been at the vanguard of recent research for a wide range of industrial applications, including metalworking fluids (MWFs). In this work, we present an experimental investigation on the performance of novel green MWFs based on aqueous nopal mucilage solutions. For this, fully biodegradable solutions with different mucilage concentrations (2.29, 4.58, and 6.85 mg/mL) were evaluated in terms of rheological, tribological, thermal stability, and turning (minimum quantity lubrication) performance and compared to a commercial semisynthetic oil-based MWF (Cimstar 60). Mucilage solutions exhibited viscoelastic shear-thinning behavior, which was enhanced along with mucilage concentration. The solution with the highest mucilage content studied resulted in the lowest wear, friction, and temperature in comparison to the other solutions and neat water in extreme pressure four-ball tests and a similar level of lubricity as compared to the commercial MWF in cutting tests. This performance is associated with the enhanced viscosity and elasticity of the solution, as well as the contents of lipids with fatty acids in the mucilage. Overall, the present results reveal the relevance of the viscoelastic behavior of the lubricant, elasticity in particular, in lubrication processes and point to nopal mucilage as an effective green additive to produce innocuous MWFs. Full article

Most asymmetrical lateral forces occur in the reciprocating piston mechanism, which is widely applied as a major component of power equipment. When this lateral force greatly acts on the piston, it comes into contact with the cylinder. To prevent this negative phenomenon, lubrication characteristic evaluation and control technology are necessary. In this study, a boundary lubrication model considering the elastic deformation of the contact surface was adopted to perform a lubrication analysis of a piston hydraulic pump widely used in the aviation and plant industries. The piston/cylinder mechanism was analyzed in terms of contact force, characteristic thickness, and power loss while varying various design and operating parameters (friction coefficient, clearance, profiling shape, operating speed, and pressure). In the overall bearing capacity to withstand the tilt of the piston, the bearing capacity ratio due to contact at the interface increased more steeply than the bearing capacity ratio in the fluid lubrication area. Profiling of the piston head played a positive role in reducing power loss but also increased piston tilt. This trend appeared more clearly as the head profiling degree of processing Increased. Lastly, the effects of variable operating speed and pressure were examined. High operating speed caused low contact force, and high operating pressure caused high contact force. Through this study, it was possible to predict the lubrication performance and power loss of reciprocating piston pumps used in the field more realistically through appropriate boundary lubrication modeling. Full article

This study explored the crucial relationship between base fluids and polyamide, a prevalent polymer in electric vehicle (EV) components, with the aim of enhancing the longevity and performance of EVs in the context of thermal management by immersion cooling. Focusing on polyalphaolefin and polyol ester as base fluids, an immersion test was conducted to assess their interaction with polyamide 6 using adapted ASTM standards. The results revealed the significant influences of both fluids on the physical properties and chemical structure of polyamide. Polyol ester demonstrated a lesser impact on the chemical and mechanical properties of polyamide 6. Full article

For over two decades, ionic liquids have been among the most exciting lubrication topics. Ionic liquids were investigated by using them as neat lubricants and lubricity-enhancing additives. However, new and unique features were revealed by introducing new ionic liquids. This paper compares the tribological properties of two ionic liquids with the same trihexyltetradecylphosphonium [P 6,6,6,14] cation and different anions—dicyanamide [DCN] and bis(2,4,4-trimethylpentyl)phosphinate. The widely investigated 1-Butyl-3-methylimidazolium hexafluorophosphate [BMIM] [PF6] ionic liquid was used as a reference. The lubricity was comprehensively investigated using two testing modes: reciprocation in a ball-on-plate tribometer and continuous sliding in a ball-on-disc tribometer. The tests were performed at temperatures of 30 and 80 °C. The friction, wear, and film thickness were evaluated, and a worn surface analysis was conducted. It was found that in the case of reciprocation, anion has a significant effect on the lubricity. The difference was particularly evident when the results at two temperatures were compared. The ability to build a low-friction tribo-film was suggested as the primer source of lubricity. In the case of continuous sliding, the differences were not as noticeable. In this case, viscosity was assigned to be the leading property. Full article

Magnesium (Mg) and graphene in alloy formulations are of paramount importance for lightweight engineering applications. In the present study, ZE10 Mg-alloy-based nanocomposites reinforced with graphene nanoplatelets (GNPs) having a thickness of 10–20 nm were fabricated via ultrasound-assisted stir casting. The effect of GNP contents (0.25, 0.5, and 1.0 wt.%) on the microstructure, Vickers hardness, and tensile properties of nanocomposites was investigated. Further, tribological studies were performed under a ball-on-disc sliding wear configuration against a bearing ball counterbody, at room and elevated temperatures of 100 °C and 200 °C, to comprehend temperature-induced wear mechanisms and friction evolution. It was revealed that the GNP addition resulted in grain coarsening and increased porosity rate of the Mg alloy. While the composites exhibited improved hardness by 20–35% at room temperature and 100 °C, a minor change was observed in their hardness and tensile yield strength values at 200 °C with respect to the GNP-free alloy. A notable improvement in lowering and stabilizing friction (coefficient of friction at 200 °C~0.25) and wear values was seen for the self-lubricating GNP-added composites at all sliding temperatures. The worn surface morphology indicated a simultaneous occurrence of abrasive and adhesive wear mode in all samples at room temperature and 100 °C, while delamination and smearing along with debris compaction (tribolayer protection) were the dominant mechanisms of wear at 200 °C. Inclusively, the results advocate steady frictional conditions, improved wear resistance, and favorable wear-protective mechanisms for the Mg alloy–GNP nanocomposites at room and elevated temperatures. Full article

In this article, we focus on utilising electrical impedance spectroscopy (EIS) for the assessment of global and contact impedances in roller bearings. Our primary objective is to establish a quantitative prediction of lubricant film thickness in elasto-hydrodynamic lubrication (EHL) and investigate the impedance transition from ohmic to capacitive behaviour as the system shifts from boundary lubrication to EHL. To achieve this, we conduct measurements of electrical impedance, bearing and oil temperature, and frictional torque in a cylindrical roller thrust bearing (CRTB) subjected to pure axial loading across various rotational speeds and supply oil temperatures. The measured impedance data is analysed and translated into a quantitative measure of lubricant film thickness within the contacts using the impedance-based and capacitance-based methods. For EHL, we observe that the measured capacitance of the EHL contact deviates from the theoretical value based on a Hertzian contact shape by a factor ranging from 3 to 11, depending on rotational speed, load, and temperature. The translation of complex impedance values to film thickness, employing the impedance and capacitance method, is then compared with the analytically estimated film thickness using the Moes correlation, corrected for inlet shear heating effects. This comparison demonstrates a robust agreement within 2% for EHL film thickness measurement. Monitoring the bearing resistance and capacitance via EIS across rotational speeds clearly shows the transition from boundary to mixed lubrication as well as the transition from mixed lubrication to EHL. Finally, we have observed that monitoring the electrical impedance appears to have the potential to perform the run-in of bearings in a controlled way. Full article

This article presents the results of an analysis of the influence of friction process parameters on the coefficient of friction of steel sheets 1.0347 (DC03), 1.0338 (DC04) and 1.0312 (DC05). A special tribometer was designed and manufactured in order to simulate the friction phenomenon occurring in the blankholder area in deep drawing operations. Lubricant was supplied to the contact zone under pressure. The value of the coefficient of friction was determined under various contact pressures and lubrication conditions. Multi-layer artificial neural networks (ANNs) were used to predict the value of the coefficient of friction. The input parameters considered were the kinematic viscosity of lubricants, contact pressure, lubricant pressure, selected mechanical properties and basic surface roughness parameters of sheet metals. The value of the coefficient of friction of 1.0312 steel sheets was predicted based on the results of friction tests on 1.0347 and 1.0338 steel sheets. Many ANN models were built to find a neural network that will provide the best prediction performance. It was found that to ensure a high performance of ANN prediction, it is necessary to simultaneously take into account all the considered roughness parameters (Sa, Ssk and Sku). The predictive performance of the ‘best’ network was greater than R² = 0.98. The lubricant pressure had the greatest impact on the coefficient of friction. Increasing the value of this parameter reduces the value of the coefficient of friction. However, the greater the contact pressure, the smaller the beneficial effect of pressure-assisted lubrication. The third parameter of the friction process, the kinematic viscosity of the oil, exhibited the smallest impact on the coefficient of friction. Full article

Water-lubricated bearings can effectively solve the pollution problem caused by lubricant leakage and are used in offshore engineering equipment for this reason. Aiming at the problems of unclear and undefined micro-interface lubrication mechanisms of water-lubricated bearings, this paper investigates the influence of non-parallel micro-cavities on the micro-interface lubrication mechanism of bearings. Based on a single micro-cavity model, the lubrication mechanism of micro-cavities is studied in this paper. Lubrication models of the non-parallel contact friction pairs model are built, and the effect of the non-parallelism on the lubrication performance of the micro-cavities is obtained using the computational fluid dynamics method. The results show that, under the same Reynolds number and cavitation pressure, the wedge effect caused by the non-parallelism causes the pressure at the inlet to rise, thus increasing the load-carrying capacity. The existence of non-parallelism limits the rise of the high pressure of the inertia effect on the micro-cavities and reduces the load-carrying capacity. The presence of non-parallelism decreases the area of the negative pressure proportion and increases the proportion of the positive pressure zone inside the micro-cavities, thus increasing the load-carrying capacity. Full article

Part of the gas phase within the bearing emanates from the gaseous lubricating medium generated by the phase transition of the liquid lubricant under low pressure, while the remaining portion originates from the expansion of gases, such as air, present in the lubricant. This study delves into the impact of vapor and gas cavitation on the stability of the rotor-journal bearing system. Utilizing computational fluid dynamics (CFD), a 3D transient lubrication model is developed for the rotor-journal bearing system. This model integrates a combined cavitation approach, encompassing both vaporous and gaseous cavitation phenomena. Based on a new structured dynamic mesh method, the journal orbits are obtained when the journal moves in the rotor-journal bearing system. In vaporous and gaseous cavitation, shear stress and non-condensable gases (NCG) are incorporated successively. Compared with the combined cavitation model, the basic cavitation model journal orbit amplitude is significantly larger than the combined cavitation model. The carrying capacity of journal bearings under the basic cavitation model is overestimated, leading to a more conservative prediction for system stability. Full article

Human joint prostheses experience wear failure due to the complex interactions between Ultra-High-Molecular-Weight Polyethylene (UHMWPE) and Cobalt-Chromium-Molybdenum (CoCrMo). This study uses the wear classification to investigate the gradual and progressive abrasive wear mechanisms in UHMWPE. Pin-on-disc tests were conducted under simulated in vivo conditions, monitoring wear using Acoustic Emission (AE). Two Machine Learning (ML) frameworks were employed for wear classification: manual feature extraction with ML classifiers and a contrastive learning-based Convolutional Neural Network (CNN) with ML classifiers. The CNN-based feature extraction approach achieved superior classification performance (94% to 96%) compared to manual feature extraction (81% to 89%). The ML techniques enable accurate wear classification, aiding in understanding surface states and early failure detection. Real-time monitoring using AE sensors shows promise for interventions and improving prosthetic joint design. Full article

Atomic force microscopes are used, besides their principal function as surface imaging tools, in the surface manipulation and measurement of interfacial properties. In particular, they can be modified to measure lateral friction forces that occur during the sliding of the tip against the underlying substrate. However, the shape, size, and deformation of the tips profoundly affect the measurements in a manner that is difficult to predict. In this work, we investigate the contribution of these effect to the magnitude of the lateral forces during sliding. The surface substrate is chosen to be a few-layer AB-stacked graphene surface, whereas the tip is initially constructed from face-centered cubic gold. In order to separate the effect of deformation from the shape, the rigid tips of three different shapes were considered first, namely, a cone, a pyramid and a hemisphere. The shape was seen to dictate all aspects of the interface during sliding, from temperature dependence to stick–slip behavior. Deformation was investigated next by comparing a rigid hemispherical tip to one of an identical shape and size but with all but the top three layers of atoms being free to move. The deformation, as also verified by an indentation analysis, occurs by means of the lower layers collapsing on the upper ones, thereby increasing the contact area. This collapse mitigates the friction force and decreases it with respect to the rigid tip for the same vertical distance. Finally, the size effect is studied by means of calculating the friction forces for a much larger hemispherical tip whose atoms are free to move. In this case, the deformation is found to be much smaller, but the stick–slip behavior is much more clearly seen. Full article

White Etching Cracks (WEC) have become a subject of extensive research in material science, chemistry and lubrication, and even operational mathematics by AI learning. Initially reported in the 1960s and considered an exotic anomaly, the failures gained importance with the global rise of wind energy power and the automotive industry. Unexpectedly high failure rates in various bearing applications have led to the need for a deeper understanding and prevention of WEC. It has come a long way from materials inspection, to parametrically studying WECs on test rigs, to the understanding that WEC is a stand-alone phenomenon and sparingly related to common failures in bearing technology. It has been commonly accepted that WEC drivers have multiple dimensions, e.g., material, contact mechanics, chemistry, and electricity. The impact of these factors on WEC failures is frequently studied using test rigs at the component level, such as the FE8 test rig. The FE8 has been utilized in numerous investigations due to its ability to replicate WEC failures without requiring artificial electricity or hydrogen charging by using specific lubricant chemistry and operating conditions. However, through intensive testing, it was observed in this study that a standard material in an FE8 rig component demonstrated a profound influence on WEC formation. This paper presents the details of the testing and analysis, aiming to investigate the mechanisms of interactions between the hose material and the low reference lubricant. The results demonstrate that the chemistry of the component material plays an important role in WEC formation. This finding may have significant impact in WEC studies, especially when the FE8 rig is used. Full article

Vacuum-sliding electrical contacts find extensive application in aerospace components, yet they face limitations related to inadequate lubrication performance. In this study, we analyzed the design of an emerging conductive lubricant material, NbSe₂. A series of NbSe₂-Ti films with varying doped Ti contents were prepared through magnetron sputtering technology. We investigated the correlation between the sputtering current and composition, microstructure, mechanical properties, and current-carrying tribological properties of the films. The results indicate that under vacuum and current-carrying conditions, the NbSe₂-Ti films demonstrate significant advantages over existing electrical-contact lubrication materials. Compared with electroplated gold films, the NbSe₂-Ti films reduced the coefficient of friction from 0.25 to 0.015, thereby improving the wear life by more than six times. This result demonstrates that magnetron-sputtered NbSe₂ film can be used as a lubricant for space current-carrying sliding contacts. Full article

To develop an angular contact ball bearing with low power consumption, a heat generation calculation model for angular contact ball bearings has been established based on bearing quasi dynamics, elastohydrodynamic lubrication theory, heat transfer theory, and Kirchhoff’s law of energy conservation, considering the effects of roundness error, bearing preload, centrifugal effect, and thermal expansion. The correctness of the model is verified through experiments. The influence of different operating conditions and roundness errors on the thermal characteristics of angular contact ball bearings is analyzed. The results of the calculation indicate that when the roundness error order is equal to the number of balls n/2 ± 2 (where n = 1, 2, 3, …), the overall heat generation of the bearing is lower than that without considering the roundness error. When the roundness error order is equal to (2n − 1)/4 ± 2 (where n = 1, 2, 3, …), the overall heat generation of the bearing is higher than that without considering the roundness error. At the same rotating speed, the overall heat generation fluctuates as the roundness error order changes, and the trend becomes more pronounced as the rotating speed increases. The maximum overall heat generation is achieved when the roundness error order equals (2n − 1)/4 times (where n = 1, 2, 3, …) the number of balls. When the roundness error order is equal to n/2 times the number of balls (where n = 1, 2, 3, …), the bearing’s overall heat generation is minimal. The variation in the total heat generated by the bearing is directly proportional to the amplitude of the roundness error. With the increase in roundness error harmonic order, the bearing integral heat generation shows a periodic change, and the change period has a mapping relationship with the number of balls. Full article

For wind turbine applications, there is a cyclic load-varying process between rolling elements and raceways in pitch bearings. This kind of motion can also lead to radial fretting. However, this is seldom addressed under grease-lubricated conditions in the literature. In this study, grease-lubricated point contact problems have been investigated experimentally under cyclic load-varying conditions. The findings revealed that as the load-varying range diminishes, the variation in grease film distribution becomes more subtle and the rate of discharge of thickener fiber clusters in the stick zone decelerates. This is due to the fact that the rate of change in the Hertz contact radius is reduced and the migration of grease is weakened during the unloading process. Due to the large apparent viscosity of grease with a high soap content, entrapped grease is not easily discharged during loading, and the thickness of the film in the stick zone progressively increases as the soap content of the grease is augmented. This also causes the variable load zone to wear out more easily. As the grease is subjected to repeated loading and unloading, there is a gradual reduction in film thickness, and larger thickener fiber clusters tear, resulting in a flattened form and shear thinning. Grease containing sulphur–phosphorus additives demonstrates a superior effect on reducing fretting wear within the large variable load range but generally proves effective for smaller load-varying ranges. This study may offer insights into the degradation of grease under variable load motion and methods to prevent radial fretting wear. Full article

Leaf spring calipers are a kind of pipe detector that installs strain gauges on the detecting arm, and the strain gauges measure the geometrical dimensions of the inner wall of the pipe by detecting the bending strain of the leaf spring and the sensors of the leaf spring caliper are set up on the detecting arm, so it has higher detecting accuracy and smaller structural dimensions. Leaf spring calipers are widely used because of their outstanding advantages, but their detection arms are worn out, and their detection accuracy increases with the detection distance. In this paper, we establish a wear model of the detection arm for the operation of the leaf spring caliper in crude oil and refined product pipelines, and according to the model, we build a wear test system for the detection arm. The wear test system of the inspection arm simulates the wear between the inspection arm made of G61500 (UNIFIED NUMBERING SYSTEM) material and the pipe made of X80 (API SPEC 5L) material. The wear pattern of the inspection arm in crude oil and refined oil pipelines is investigated by adding lubricating media with similar physical parameters to crude oil and refined oil, such as light mineral oil, SAE 5W-30 lubricant, 600XP 680 lubricant. The experimental results are analyzed to explore the wear performance of the leaf spring caliper arm, and the prediction algorithm is used to predict the wear pattern of the leaf spring after lubrication. The results show that the average error between the predicted and actual values meets the accuracy requirements, and the wear prediction model of the detection arm can be used as a correction algorithm for the wear error of the leaf spring caliper to improve the detection accuracy. Full article

Diamond-like carbon (DLC) film has gained widespread popularity as a versatile and important solid lubricant material in the field of tribology. Among various types of DLC films, hydrogen-rich DLC (a-C:H) film as a high-performance material has greatly enhanced anti-friction and anti-wear. However, despite its remarkable capabilities, the surface chemical properties and tribological performance of a-C:H film are significantly influenced by the surrounding environment, in special atmospheric conditions. Its super-slip mechanism involves the participation of hydrogen atoms, which can weaken the normal electron number of the outermost layer of a-C:H film. What is more, it is essential to investigate tribofilms in a vacuum or inert gas environment to ascertain the appropriate tribological properties of a-C:H film, which helps in mitigating oxidation effects. When non-doped DLC films are subjected to friction in a dry nitrogen or argon environment, they create sp³-C-rich transfer films on the contact surface, resulting in macroscopic super-slip effects. This paper aims to introduce and discuss the diverse nanostructures of in situ tribofilms in a-C:H film, focusing on the working environment, and explore the prospective application directions of a-C:H film. Full article

The transient lubrication conditions of rolling bearings are different in gearboxes and bearing testers. It has been observed that samples of qualified rolling bearings tested in rolling bearing testers often fail and do not meet lifespan requirements when employed in other lubrication conditions. This may be caused by different factors affecting the bearing in testing and applying lubrication. Needle roller bearings were selected for this study to investigate the causes of this phenomenon in terms of lubrication. Based on the computational fluid dynamics (CFD) method, fluid domain models for the same type of rolling bearings with different lubrication conditions were established. The transient flow fields of rolling bearings with oil jet lubrication in a tester and splash lubrication in a planetary gearbox were simulated. The air–oil transient distribution of rolling bearings in two kinds of lubrication was analyzed. The results indicate that the rotational speed significantly affected the oil jet lubrication of the needle roller bearing. The average oil volume fraction rose by 0.2 with the increase in the bearing speed from 1200 r/min to 6000 r/min and by 0.06 with the increase in the oil jet velocity from 8 m/s to 16 m/s. The splash lubrication of the bearings in the planetary gearbox was directly related to the immersion depth of the rolling bearings in the initial position. Meanwhile, the splash lubrication of the bearings was also affected by other factors, including the initial layout of the planetary gears. The increase in speed from 1200 r/min to 6000 r/min made the average oil volume fraction of splash lubrication decrease by 4.4%. The average oil volume fraction of the bearings with splash lubrication was better than that with oil jet lubrication by an average of 41.9% when the bearing speed was in the low-speed stage, ranging from 1200 r/min to 3600 r/min. On the contrary, the bearings with oil jet lubrication were better than those with splash lubrication by an average of 31.8% when the bearing speed was in the high-speed stage, ranging from 4800 r/min to 6000 r/min. Full article

This paper proposes a dynamic-projection-integrated particle-filtering-based identification strategy for the friction characteristic curve of a train wheelset under the slipping fault condition. This strategy aims to achieve the identification of the fault friction characteristic curve (FFCC) in the early slipping fault stage. First, a multi-dimensional integrated particle-filtering (MDIPF)-based parameters correction method is proposed. The MDIPF constructs an error particle state transition model encompassing multi-dimensional parameters, which integrates inter-particle correlation to facilitate error fusion during the state transition process. Then, a dynamic projection domain (DPD)-based particle refinement method is proposed. The DPD constructed the contraction factors to dynamically fine-tune the particle projection domain. Finally, a multi-level evaluation-based identification method for the FFCC is proposed. And the dynamic-projection-integrated particle-filtering-based identification strategy is validated, which can actualize the rapid and accurate identification of the FFCC. Full article

This study delves into the drag-reducing properties of nickel plating coatings applied to hydraulic pipelines. To investigate the drag reduction characteristics of pipeline coatings, we designed a specialized experimental apparatus to conduct deceleration experiments. The primary objective was to systematically assess the drag reduction effect of varying coating thicknesses on liquid flow within the pipeline. Chemical nickel plating was employed for preparing drag reduction coatings with diverse thicknesses, achieved through precise adjustments in the composition and operating conditions of the plating solution. In the design of the experimental apparatus, careful consideration was given to crucial parameters such as the inner diameter of the pipeline, the inlet flow rate, and the control of experimental variables. It quantitatively assesses how varying coating thicknesses, flow velocities, and pipeline diameters impact the pipelines’ resistance to flow. By meticulously measuring the pressure differential across the pipeline, the research evaluates the extent of drag reduction afforded by the coatings and simultaneously elucidates the underlying mechanisms. Findings indicate a peak drag reduction rate of 5% under conditions of a 20 µm-thick nickel coating, 5 m/s flow velocity, and a 10 mm pipeline diameter. This study aims to comprehend how coatings affect linear losses along the pipeline, thereby establishing the groundwork for optimizing drag reduction technology. These outcomes highlight the coatings’ potential to mitigate linear losses due to shear stress during fluid transport, offering a viable solution to enhance hydraulic pipeline efficiency with significant industrial implications. Full article

Tool wear prediction can ensure product quality and production efficiency during manufacturing. Although traditional methods have achieved some success, they often face accuracy and real-time performance limitations. The current study combines multi-channel 1D convolutional neural networks (1D-CNNs) with temporal convolutional networks (TCNs) to enhance the precision and efficiency of tool wear prediction. A multi-channel 1D-CNN architecture is constructed to extract features from multi-source data. Additionally, a TCN is utilized for time series analysis to establish long-term dependencies and achieve more accurate predictions. Moreover, considering the parallel computation of the designed architecture, the computational efficiency is significantly improved. The experimental results reveal the performance of the established model in forecasting tool wear and its superiority to the existing studies in all relevant evaluation indices. Full article

A dedicated test bench is employed to record acoustic emission signals from dry gas seals under various operating conditions. Time-domain and frequency-domain analysis methods are utilized to process and analyze the acoustic emission signals during start/stop, stable operation, and two common fault states (end-face defects and compensation spring failure). Furthermore, feature recognition research is conducted. A method for identifying the operational states of seals (low-speed friction, gradual detachment, stable operation) based on the root mean square (RMS) was established, with transition points at speeds of 100 and 1000 RPM, respectively. Additionally, spectral analysis is conducted using Fourier transform to determine the frequency band of acoustic emission signals (240–320 kHz) generated during contact wear of dry gas seals. Investigation into two typical faults of dry gas seals reveals that the RMS value of the acoustic emission signal gradually increases with the rotational speed during the operation of dry gas seal end-face defects. This is attributed to the insufficient dynamic pressure effect on the end face, resulting in long-term wear and tear. When the dry gas seal compensates for spring failure, the RMS value of the acoustic emission signal initially increases, then decreases, and finally increases again as the speed increases. It reaches the stable operating inflection point when the end-face speed is 800 r/min. Full article

In this work, ball-on-disk wear experiments were carried out on different wear parameters such as sliding speed, sliding distance, normal load, temperature, and oil film thickness. In total, 81 different sets of wear depth data were obtained. Four different machine learning (ML) algorithms, namely Random Forest (RF), K-neighborhood (KNN), Extreme Gradient Boosting (XGB), and Support Vector Machine (SVM) were applied to predict wear depth. By analyzing the performance of several ML algorithms, it is demonstrated that ball bearing wear depth can be estimated by ML models by inputting different parameter variables. A comparative analysis of the performance of the different models revealed that XGB was more accurate than the other ML models at anticipating wear depth. Further analysis of the attribute of feature importance and correlation heatmap of the Pearson correlation reveals that each input feature has an effect on wear. Full article