Artificial Intelligence (AI)-based health indicators are crucial for reliable condition monitoring of rotating machinery. However, existing unsupervised anomaly detection methods commonly face challenges in accurately modeling the vibration signal distribution and setting robust detection thresholds. To overcome these limitations, this paper proposes a novel gear fault detection approach based on Generative Adversarial Networks (GANs), specifically employing the fast AnoGAN (f-AnoGAN) structure. The method effectively models vibration signals from healthy operating conditions and identifies anomalies based on deviations from this learned distribution. Additionally, a statistically driven threshold-setting procedure using the anomaly scores of healthy data is introduced, enhancing detection robustness and reliability. The proposed methodology is validated using experimental data from a gear accelerated degradation test, demonstrating superior performance in detecting gear pitting at an earlier stage and with greater consistency compared to conventional unsupervised detection methods.

This experimental study investigates the critical role and impact of additive concentration in enhancing the tribological performance of castor oil as a biolubricant for agricultural tractor engines. Friction and wear are major contributors to reduced engine efficiency, highlighting the need for effective lubrication strategies. While biolubricants like castor oil offer environmental benefits, they often require additives to achieve optimal performance. However, the concentration of these additives is crucial, as an imbalance can negatively impact the lubrication system, leading to a higher coefficient of friction, increased wear, and reduced engine efficiency and lifespan. This study examines the effects of varying concentrations of a mixture of propyl gallate (PG) and ionic liquid (IL) additives on the tribological performance of castor oil. The tribological behaviour of lubricated top compression piston ring and cylinder liner samples was evaluated under simulated engine conditions using a Bruker UMT Tribolab test rig, in accordance with the ASTM G181 standard. The experimental results revealed an influence of additive concentration on the coefficient of friction and wear behaviour. This emphasises the importance of optimising additive formulations to minimise engine wear and friction. Notably, a 0.5% volume concentration of the additive mixture led to a remarkable 34.8% reduction in the average coefficient of friction (COF) and a lower wear rate.

This paper presents the development of a prototype system for in-situ wear monitoring of helical gears using vision-based condition monitoring (VCM). The research addresses the challenge of monitoring gearbox wear, particularly pitting, an inherent failure mechanism in high-power applications such as wind turbines. A VCM system was integrated into an FZG gear test rig to automatically capture images of gear surfaces during operation, using an oil splash mitigation strategy to ensure high image quality. These images were processed using an image processing pipeline, incorporating a deep learning Feature Pyramid Network for automated annotation of wear defects, trained based on an iterative approach to reduce annotation effort during the training phase. Hereafter, this paper explores metrics related to pitting evolution, including pit area, height, width, and location on the gear surface, as well as insights these metrics give on pitting evolution. This framework’s ability to track the spatiotemporal development of gear wear provides valuable insights for condition monitoring and predictive maintenance in industrial applications

Mechanical components undergo various wear mechanisms during operation, leading to the development of different failure modes on their surface. Identifying the different types of failure modes is essential to understand the contributing conditions to component failure. However, the identification process heavily relies on qualitative assessment of the worn surfaces by human experts, which is time-consuming, demands a high level of specialization, and is inevitably subjective. In this context, assessing three-dimensional (3D) worn topography can improve the objectiveness of identifying the surface failure modes. This study focuses on classifying indentation, grooving, pitting, and adhesive failure modes using 3D topography metrics. Historical datasets of worn topographies are considered, including ball cratering, dry sand rubber wheel, seawater corrosion, and back-to-back gear tests. An original framework, combining topography measurement and metrics with an artificial neural network, is developed for classifying these samples. Topography metrics of surface motion orientation (Smo) and surface stratification ratio (Ssr) are employed to facilitate the classification task. Smo describes how the damage is oriented towards the motion direction, while Ssr quantifies the ratio between peaks and valleys of the worn topography. When combined, they reveal a unique morphological space SmoxSsr, with improved physical interpretability, where different surface failure modes can be located. These metrics (Smo and Ssr) serve as input features of an artificial neural network designed for the automated classification of surface failure modes. When applied to the historical datasets, the developed network achieved an overall accuracy of 94% in classifying the investigated failure modes. The proposed framework offers an effective and objective solution for identifying surface failure modes in metal contacts.

Gearbox failures in wind turbines significantly impact operational reliability and maintenance costs, particularly in offshore environments. Traditional condition monitoring (CM) methods, such as vibration and oil analysis, often fail to detect defects early due to limitations caused by the indirect measurement approach. This is further amplified by external influences, such as changing weather conditions, on system dynamics. This study presents a vision-based condition monitoring (VCM) framework for gear health assessment. The proposed system integrates a camera system within a back-to-back gear tester equipped and utilizes an automated auxiliary system to mitigate oil splash interference on image quality. The test rig was also equipped with accelerometers to compare visual and vibrational monitoring. The effectiveness of the VCM is evaluated through eight accelerated lifetime tests, inducing gear pitting, scuffing, and root cracks. Results demonstrate that visual monitoring enables early detection, straightforward qualitative analysis of gear defects, and quantification of damage progression by leveraging deep learning. Compared to vibrational monitoring, visual monitoring offers an alternative with improved diagnostic capabilities and reduced susceptibility to external factors, showing its potential for application in condition monitoring. These findings suggest that vision-based monitoring can enhance predictive maintenance strategies, reducing downtime and optimizing gearbox longevity in wind energy applications.

This study explores the in situ measurement of contact temperature in thermo-elastohydrodynamic lubrication (TEHL) within cylindrical roller thrust bearings (CRTBs) utilizing vapour-deposited resistive thin-film sensors. The sensors, optimized for compactness and high spatial resolution, were strategically embedded on the stationary bearing raceways near the outer, inner, and mean radius. This configuration enabled a precise measurement of temperature variations in both pure rolling and rolling–sliding regions of the CRTBs. The experimental results revealed a consistent decrease in temperature from the inner and outer radius zones towards the mean radius as the slip-to-roll ratio (SRR) decreased in these regions. Temperature profiles showed an early rise in the inlet zone attributed to thermal inlet shear. At higher speeds, a secondary temperature peak indicative of full-film lubrication was observed in the outlet zone immediately following the Hertzian contact. The study further shows the influence of surface pressure, shear rates, sliding friction, and circumferential speed on contact temperature dynamics, offering insights into their complex interplay. Additionally, viscosity variations due to different oil temperatures were found to critically affect the rate of temperature rise and the propensity for mixed friction phenomena. A higher viscosity resulted in an earlier onset of the temperature rise in the contact, while a lower viscosity and higher speeds promote mixed lubrication, leading to reduced contact film temperatures. These findings provide valuable insights into the behaviour of CRTB-lubricated contacts under various operating conditions and serve as crucial validation data for advanced TEHL computational models.

Fused filament fabrication is a rapidly growing 3D printing technique with the ability to produce functional components with complex shapes. The mechanical characteristics of 3D-printed parts are significantly influenced by various process parameters such as layer thickness, infill density, and nozzle temperature, which can influence part's parameters in conflicting ways. This research focuses on identifying the optimum settings for fused filament fabrication of acrylonitrile butadiene styrene. Specifically, the dimensional deviations, mechanical and abrasive wear properties of printed specimens are investigated. Experiments were designed using the Taguchi method with an L9 orthogonal array, to vary the three factors systematically. The results were analysed using analysis of variance, the Taguchi signal-to-noise ratio, and the regression analysis, with multi-response optimisation performed via desirability function analysis. The optimal balance of all three properties was achieved with infill density = 23%, layer thickness = 0.25 mm, and nozzle temperature = 240 degrees C. This work provides a systematic, statistically validated method for multi-criteria optimisation in fused filament fabrication, offering practical guidance for producing acrylonitrile butadiene styrene components that meet multiple performance requirements simultaneously.

This study evaluates the tribological properties of DIN 1.2740 hot tool steel against Super Cr13 martensitic stainless steel at 700 degrees C. The results show that the coefficient of friction (COF) ranged from 0.15 to 0.63, indicating moderate frictional interaction. The wear rate of DIN 1.2740 was observed to be low, suggesting good resistance to wear at high temperatures. The complex surface oxide layer that formed on the pin's top surface, significantly reducing the COF and acting as a solid lubricant at elevated temperatures. The oxide layer was also fragile and unable to withstand the high sliding velocities and high loads. The steel exhibited a high surface roughness when subjected to increasing normal loads and increasing sliding velocities.

Polyurethanes (PU) are widely utilized in marine environments, including tribological applications such as gears and coatings, due to their beneficial properties, including excellent chemical, water/saltwater resistance, UV stability, high strength-to-weight ratio, wear resistance, and vibration absorption. These characteristics make PU well-suited for reducing wear and friction in dynamic components, resisting chemical degradation in seawater, and ensuring long-term performance under variable thermal and mechanical conditions in harsh seawater environments. However, due to the wide variety of PU types with varying properties, their performance can differ significantly, making careful material selection essential for the intended application. This research aims to evaluate the tribological behavior of different PU materials in rack-and-pinion system designed for a wave energy converter (WEC developed by Dutch Wave Power). The study investigates the wear resistance, surface damage and mechanisms, wear debris generation and micro-geometry changes along with the friction characteristic in the contact interface. A representative laboratory wear test for the real-life application was identified after examining the operating tribosystem. Three PU compounds were selected following an initial material screening and subjected to wear testing under conditions replicating the rolling-sliding contact experienced in WEC gear systems. These tests were conducted using a wheel-on-wheel configuration tribometer, simulating real-world contact pressures and rolling velocities representative of mid-wave height scenarios. The contact stress conditions were determined from finite element simulations of the WEC rack-and-pinion system. Synthetic seawater lubrication was continuously supplied during tests and introduced in the contact to replicate the seawater environment. Key operational parameters, including rotational slip, friction force, and surface temperatures, were monitored throughout the experiments. Post-mortem investigations included weight measurements, 3D surface topography analysis, and microscopic imaging to assess surface damage, material degradation and wear debris generation. To further analyze the sliding friction phase of rolling-sliding contact, complementary pin-on-disk tests were performed in a seawater-lubricated environment. These tests revealed a decreased coefficient of friction in seawater compared to dry conditions. The adhesion effects originating from same-material pair contacts were mitigated by the lubrication efficiency and regime. The original surface roughness and the pressure–velocity values influenced this phenomenon, resulting in a uniform coefficient of friction. Elevated p v levels led to the failure of less rigid polyurethane materials. The results allowed for a ranking and performance comparison of the PU materials. Materials with lower Young’s modulus exhibited accelerated delamination from the core layer due to shear forces induced by their flexible response and deformation. Furthermore, inherent air voids in the cured PU acted as sub-surface initiation points for damage, contributing to pitting and delamination. Ensuring adequate Young’s modulus and optimizing production technologies are critical for improving material performance. This study provides valuable insights into wear mechanisms, surface degradation, and lifetime behavior of candidate materials for WEC applications. By enhancing material performance and durability, the operational efficiency and service life of WEC systems can be extended, while environmental pollution caused by delaminated debris can be minimized. These findings support the development of more sustainable PU materials, aiding manufacturers and researchers in meeting stricter environmental regulations.

The development of high-quality health indicators based on Artificial Intelligence (AI) for condition monitoring, reflecting the degradation process and trend, remains a key area of research. Unsupervised deep learning methods, such as deep autoencoders and variational autoencoders, are often employed to establish health indicators for rotating machinery. However, commonly used methods frequently face challenges in controlling and evaluating the quality of learned features that represent this distribution, which subsequently impacts the accuracy of the test data analysis and anomaly detection. Additionally, the empirical nature of threshold setting adds an element of uncertainty to detections. The research propose a novel approach for constructing gear health indicators and performing anomaly detection using Generative Adversarial Networks (GAN), with a particular emphasis on the f-AnoGAN structure. The research focuses on modeling the distribution of vibration signals acquired from healthy systems using adversarial learning. By comparing test samples against this modeled distribution, the degree of similarity or dissimilarity acts as an indicator of anomalies. Owing to the generative process of the GAN architecture (creating data from randomly sampled low-dimensional noise), GAN-based modeling overcomes the limitation of autoencoders by aiming to reconstruct the continuous distribution of systems in healthy conditions from a limited set of healthy (training) samples. In this way, it offers more generalizability than traditional model learning. Moreover, this study proposes a new method for establishing thresholds based on distribution fitting by the anomaly score of healthy data. The proposed f-AnoGAN-based model and thresholding technique is applied, tested and evaluated in a gear-pitting degradation dataset and result in more accurate and timely fault detection, markedly enhancing the ability to identify subtle faults in systems over traditional methods.

Knowledge of wear and associated damage mechanism that is prevalent during abrasive wear conditions using NbC-based cermets is lacking. In the current investigation, the abrasive wear response and associated damage mechanisms of cermets due to characteristics effect of grit particles such as size and hardness have been explored. The present study evaluates the abrasive wear response of NbC-12Ni-10Mo2C (NbC-Ni) cermet during two-body abrasive wear, which was experimentally simulated by a pin abrasion tester following the ASTM G132 standard. The WC-Co cemented carbide (WC-15.6Co) with similar hardness was used as a reference material in this study for a comprehensive comparison of materials. The investigated test parameters included different applied loads (4-16 N) and abrasive particle sizes (22-200 mu m) for a 30 m sliding distance at 0.15 m/s sliding velocity. Silicon carbide (SiC) and aluminium oxide (Al2O3) were used as abrasive counter bodies. Test results clearly show the particle size effect and the critical abrasive particle size (CPS) for the cermet lies between 82 mu m and 125 mu m for both abrasives (SiC, Al2O3). It is noticed that the wear rate shows three different trends as the particle size increases, initial increase then a steady state during critical particle size and becomes unpredictable. This effect reflects the transition of wear micro-mechanisms dominated from binder removal (below CPS) to fracture and fragmentations (beyond CPS). The wear mode transition map from plastic grooving to fracture-dominated failure (fragmentation and granular cracks) was created by correlating factors such as the severity of contact and specific wear rate with microscopic observations. The wear produced by SiC abrasives was about an order of magnitude higher (approximate to 18x) than with Al2O3 abrasives. In addition, the material comparison highlight that the abrasive wear rate of NbC-Ni cermet was about 37-86% (SiC) to 66-83% (Al2O3) higher than for the WC-Co cemented carbide, despite both cermets having similar micro-hardness. In addition, the present study illustrates that the abrasion of cermets is not only related to mechanical properties such as hardness and fracture toughness but is inherently related to composite chemical properties such as wettability and interfacial strength. This work provides new insight into the wear response of NbC-Ni cermets and WC-Co cemented carbides regarding different abrasive counterfaces, abrasive particle sizes and transition of abrasive wear mechanisms.

Rolling and grooving are typical phenomena observed in ball cratering tests. Despite extensive research, their impact on the wear rate remains a subject of debate. Besides, the identification of rolling and grooving is predominantly performed with qualitative analysis. Therefore, this investigation introduced a systematic methodology for the assessment of the worn surface topography. Ball cratering tests were performed with increasing load to induce the transition between rolling and grooving mechanisms. Several roughness metrics were analysed, among which the surface aspect ratio (Str) was found the most effective parameter for identifying the transition between rolling and grooving. Additionally, the transition was found to occur in a range of load conditions. Moreover, a segmented analysis was implemented and further revealed a propensity for grooving to manifest towards the centre and trailing edge of the wear crater. Finally, it was found no discernible difference in the wear rate between rolling and grooving conditions, and different hypotheses were discussed to explain this behaviour. The superposition of mechanisms and the occurrence of grooving by rolling was found plausible explanations for the similar wear rate. As consequence, an improved terminology for rolling and grooving was proposed. The term rolling refers to the micro abrasive mechanism, while grooving designates the resulting failure mode.

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.

Polyamide 11 (PA11) and copolyester (TPC-E) were compounded through melt extrusion with low levels (below 10%) of expanded graphite (EG), aiming at the manufacturing of a thermally and electrically conductive composite resistant to friction and with acceptable mechanical properties. Thermal characterisation showed that the EG presence had no influence on the onset degradation temperature or melting temperature. While the specific density of the produced composite materials increased linearly with increasing levels of EG, the tensile modulus and flexural modulus showed a significant increase already at the introduction of 1 wt% EG. However, the elongation at break decreased significantly for higher loadings, which is typical for composite materials. We observed the increase in the dielectric and thermal conductivity, and the dissipated power displayed a much larger increase where high frequencies (e.g., 10 GHz) were taken into account. The tribological results showed significant changes at 4 wt% for the PA11 composite and 6 wt% for the TPC-E composite. Morphological analysis of the wear surfaces indicated that the main wear mechanism changed from abrasive wear to adhesive wear, which contributes to the enhanced wear resistance of the developed materials. Overall, we manufactured new composite materials with enhanced dielectric properties and superior wear resistance while maintaining good processability, specifically upon using 4–6 wt% of EG.

Polymer seals are utilized in various engineering applications to prevent leakage and contamination. The study investigates the wear and friction behavior of PTFE-based dynamic rotary seals, targeting their usage in space applications. Pin-on-disc dry sliding wear tests were performed with 0.5 MPa contact pressure and 0.2 m/s sliding velocity combining different lip seal (PTFE, PTFE+GF+MoS2), packing (PTFE, PTFE+Aramid fiber+solid lubricant) and shaft materials (34CrNiMo6, PEEK) involving third-body lunar (LHS-1) and Martian regolith (MGS-1) simulants. To understand the different influences of extraterrestrial regolith simulants compared to commonly encountered abrasives on Earth, quartz sand was selected as a reference. Quartz soil resulted in lower wear rates but a similar coefficient of friction to other regoliths. In the case of lip seals, testing with LHS-1 on PEEK and testing with MGS-1 on steel resulted in the most severe wear. Post-mortem surface analysis revealed the effect of external abrasive particles on the wear process and the transfer layer formation. The surface analysis confirmed that both lunar and Martian regolith simulants resulted in significant embedded particles. Based on the wear performance results, the lip seals performed better, but installation with an external packing could further aid the tribosystem.

TiB2+TiB coatings were formed on Ti–6Al–4V through a molten-salt diffusional process at temperatures of 850 °C and 900 °C for 16 h. The thickness of the TiB layer increased by about two times at the higher process temperature, while the thickness of the TiB2 layer remained constant. Tribocorrosion rate of Ti–6Al–4V and the coated samples was evaluated in a reciprocating sliding under a normal load of 15 N in a phosphate buffer saline (PBS) solution for 3600–36000 cycles against an alumina ball. The results showed that the tribocorrosion rate of the borided samples decreased up to 56 times compared with Ti–6Al–4V after 36000 cycles. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) studies showed the presence of oxide-rich patches on the wear surface of Ti–6Al–4V with a thickness of up to 1 μm. TEM and atomic force microscopy (AFM) images also revealed the presence of a tribofilm with a thickness of up to 200 nm on the surface of the boride coating. In addition, X-ray photoelectron spectroscopy (XPS) analysis confirmed the tribofilm formed on the wear surface of coated samples contained B2O3/H3BO3 compound, resulting in a more stable fluctuation in coefficient of friction and open circuit potential during sliding. The SEM images of the alumina wear surface showed cracks and titanium transfer layers in contact with the borided layers and Ti–6Al–4V, respectively.

The present study has developed new insights into the wear transition mode of cermets and provides a better understanding of the role of abrasive characteristics in three-body abrasive wear. Two sintered and fully densified cermets, NbC–Ni (NbC–12Ni–10Mo2C) and WC-Co (WC-9.5Co) with similar micro-hardness (HV30 ≈ 13.5 GPa) were selected in this study. The abrasion response of cermets against different abrasive characteristics namely size (67–245 μm), hardness (silica, alumina and SiC), and shape (round and angular) was experimentally investigated according to the ASTM G65 standard. The test results showed that the specific wear rate (SWR) of the cermets increased significantly with increasing abrasive size and hardness. The size effect shows that the dominant wear micro-mechanisms shift from binder removal (rolling) to mixed binder-carbide extrusion (sliding) as the abrasives particle size changes from smaller (67 μm) to larger (245 μm). The hardness ratio between the abrasives and cermets (Ha/Hs) highlights that silica and alumina abrasives provide mild wear (Ha/Hs < 1.5), while SiC abrasives cause severe wear (Ha/Hs > 1.5). Both cermets exhibited similar SWR during mild wear, but NbC–Ni showed 7 times higher SWR than WC-Co during severe wear. The abrasives shape effect does not show a significant difference on the wear rate of the cermets.

The investigation in this article focuses on the rolling resistance torque and thermal inlet shear factor in tapered roller bearings (TRBs) through systematic experiments using a modular test setup. TRBs typically operate under Elastohydrodynamic Lubrication (EHL) conditions. At sufficiently high speeds, the majority of rolling friction is due to a significant shift of the pressure centre in the EHL contact. While at lower speeds, sliding friction in the roller-rib contact becomes dominant, which operates under mixed lubrication conditions. Limited literature exists on the impact of inlet shear heating on effective lubricant temperature (Tin_c) and rolling friction in TRBs. To fill this gap, experimental measurements of the total frictional torque under axial loading at different speeds and oil temperatures are performed. With existing models for different friction contributions described in the literature, the rolling resistance due to EHL has been determined for various operating conditions. The effects of dimension-less speed (U), material (G), and load (W) parameters have also been investigated. Under fully flooded conditions, it was observed that the influence of material (G) and load (W) parameters on rolling friction is minor, while the impact of velocity (U) is significant. In the context of rolling resistance, the heating due to shear of the lubricant in the inlet zone plays a significant role. For higher rotational velocities, the estimated rotational torque reduction resulting from inlet shear heating was found to be approximately 6–8%.

Gear failure modes and their underlying mechanisms are usually identified by visual inspection, which relies on the skills and experience of the human observer and hence is prone to subjectivity and bias. Therefore, it is essential to design and implement objective methods to improve the identification of gear failure modes. In the present study, the 3D topography of gear surfaces affected by different types of wear modes, i.e., micropitting, pitting, and scuffing, was measured by means of white light interferometry. The surfaces were evaluated in terms of height, spatial, and function roughness parameters, according to ISO 25178-2. Besides, a new roughness parameter, named surface motion orientation (Smo), was proposed. Three features were found relevant to identify the differences between the gear surfaces affected by different failure modes: the shape of asperities distribution, the severity of damage, and the surface texture orientation with respect to the motion direction. The combination of the roughness parameters selected to quantify each of these features (Ssk,Sq,Smo) resulted in an objective classification of the assessed gear failure modes.

Due to the current devastating environmental concerns caused by petroleum-derived lubricants in internal combustion (IC) engines (because of their toxicity, non-biodegradability and not environmental adaptability), and the increase in oil prices, as well as the degradation of the global crude oil reserves, researchers all over the world are working to develop innovative ideas for sustainable development in biomass-derived biodegradable lubricant oil which the perform equivalent or more than the commercial petroleum-based oils in engine lubrication. This review paper’s major purpose is to provide those researchers and particularly engineers interested in IC engine biolubricant oil derived from renewable biomass with appropriate information and perspective.