Search Results (49)

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

The control of lubricity induced by electric potential is appealing for numerous applications. On the other hand, the high polarity of ionic liquids facilitates the adsorption of equally charged molecules onto polar surfaces. This phenomenon and its consequences are well understood at the nanoscale; however, they have recently garnered significant attention at the macroscale. This study investigates the lubricity of trihexyltetradecylphosphonium dicyanamide, a phosphonium ionic liquid, when used as a neat lubricant in reciprocating sliding under electrically charged conditions. Two different polarities with the same potential were applied to the friction pair of bearing steel against bearing steel while monitoring electrical contact resistance. The lubricity was evaluated through measurements of friction, wear, surface morphology, and composition. It was found that the application of electric potential significantly alters the lubricity of the investigated ionic liquid where a positive potential applied to the ball resulted in the least damaging situation. The recorded electrical contact resistance enabled the monitoring of tribofilm formation during reciprocation. It was found that there was minimal to no separation between interacting surfaces when the ball was changing direction. Full article

In aerospace technology, angular contact ball bearings are required to exhibit extremely high operational precision, necessitating real-time monitoring of their wear status to conduct pre-failure analysis. Although extensive studies have been conducted on the wear characteristics of angular contact bearings, further in-depth research is still required to enhance the accuracy of bearing life predictions. To address the imprecision in wear life prediction for angular contact ball bearings, this article proposes a refined wear calculation model based on dynamic load distribution. The model calculates the dynamic load distribution between the inner and outer rings and the raceway under mixed lubrication conditions. Integrating the dynamic load distribution methodology with the wear calculation model, the dynamic contact characteristics of angular contact bearings can be more accurately characterized. Building on this foundation, a dynamic analysis model considering dynamic wear in the bearing contact zone is established. The vibration characteristics of bearings under varying loads are analyzed, and vibration experiments under different load conditions are conducted. Through vibration spectrum analysis, the influence patterns of wear characteristic frequency bands in the wear model on the pre-failure state of bearings are further elucidated. This study provides a theoretical basis for bearing wear life prediction analysis. Full article

Hydropower is important in the modern power system due to its ability to quickly adjust production. More frequent use of this ability may lead to increased maintenance needs, highlighting the importance of research in condition monitoring for hydropower. This study suggests a model approach for friction monitoring of the bearings inside the Kaplan turbine’s hub. The approach is developed for when normal and anomalous data exist. The study compares isolation forest (iForest), local outlier factor (LOF), one-class support vector machine (OC-SVM), and Mahalanobis distance (MD) for anomaly detection, where iForest and OC-SVM appear to be good choices due to their robust performance. A moving decision filter (MDF) is fed with the output from the anomaly detection models to classify the data as normal or anomalous. The parameters in the MDF are optimized with Bayesian optimization to increase the performance of the models. The approach is tested using data from two actual hydropower turbines. The study shows that the model approach works for both turbines. However, the parameter optimization must be performed separately for each turbine. Full article

Early fault detection in rotating machinery is crucial for optimizing maintenance and minimizing downtime costs, especially in medium-to-large-scale industrial applications. This study presents a multibody model developed in the Simulink^® Simscape environment to simulate the dynamic behavior of medium-sized spherical bearings. The model includes descriptions of the six degrees of freedoms of each subcomponent, and was validated by comparison with experimental measurements acquired on a test rig capable of applying heavy radial loads. The results show a good fit between experimental and simulated signals in terms of identifying characteristic fault frequencies, which highlights the model’s ability to reproduce vibrations induced by localized defects on the inner and outer races. Amplitude differences can be attributed to simplifications such as neglected housing compliancies and lubrication effects, and do not alter the model’s effectiveness in detecting fault signatures. In conclusion, the developed model represents a promising tool for generating useful datasets for training diagnostic and prognostic algorithms, thereby contributing to the improvement of predictive maintenance strategies in industrial settings. Despite some amplitude discrepancies, the model proves useful for generating fault data and supporting condition monitoring strategies for industrial machinery. Full article

In induction motor bearings, distributed faults are prevalent, often resulting from factors such as inadequate lubrication and particle contamination. Unlike localized faults, distributed faults produce complex and unpredictable motor signal behaviors. Although existing research predominantly addresses localized faults in mains-fed motors, particularly single-point defects, a comprehensive investigation into particle contamination in bearings of inverter-fed motors is essential for a more accurate understanding of real-world bearing issues. This paper conducts a comparative analysis of vibration, stator current, speed, and acoustic signals to detect particle contamination through signal analysis across three domains: time, frequency, and time-frequency. These domains are analyzed to assess and compare the characteristics of each monitored signal in the context of bearing wear detection. The data were collected from both steady-state and startup transients of an induction motor controlled by a variable frequency drive. The experimental results highlight the most significant characteristics of each monitored signal, evaluated across the different domains of analysis. The primary conclusion indicates that, in inverter-fed motors, sound and vibration signals exhibit abnormal levels when the bearing is damaged but the related-fault signature becomes complicated. Additionally, the findings demonstrate that the analysis of startup stator current and speed signals presents the potential to detect distributed bearing damage in inverter-fed induction motors. Full article

This research addresses the issue of lubricant performance degradation in the main shaft bearings of wind turbines. Through multi-temperature accelerated aging tests, the static thermal degradation patterns were elucidated, and an aging model was developed. Initially, 176 samples were prepared at temperatures of 80 °C, 100 °C, 120 °C, and 140 °C using the static thermal degradation method, with 44 samples at each temperature point. Subsequently, key parameters such as the quality change rate, penetration, oil separation rate, and evaporation amount of the lubricant were systematically measured. Ultimately, the mathematical aging model of the lubricant was derived by fitting the aging kinetics model. The results indicate that as aging time and temperature increase, the degradation characteristics of the lubricant, such as quality change rate, penetration, oil separation rate, and evaporation amount, exhibit discernible patterns. The mathematical aging model was successfully fitted, with the maximum deviation generally within 20% of the error margin, meeting the established criteria. This research provides a theoretical foundation for the establishment of a lubricant condition monitoring system in wind farms. Predicting the performance inflection point of the lubricant can effectively prevent unplanned bearing shutdowns resulting from lubrication failures, thereby offering significant engineering value in enhancing the operational reliability of wind turbine units. Full article

The present paper deals with a review on bearing currents in electrical machines, with major emphasis on mechanisms, impacts, and mitigation strategies. High-frequency common-mode voltages from the inverter-driven system have been found to be the main reason for bearing current leading to motor bearing degradation and eventual failure. This paper deals with bearing currents—electrical discharge machining (EDM) currents, circulating bearing currents, and rotor-to-ground bearing currents—and the various methods of their generation and effects that are harmful to the bearings and lubricants of a motor. Mitigation techniques, among which the following have been taken into account, are studied in this context: the optimization of PWM modulation, and the use of shaft grounding brushes, insulated bearings, and passive or active filters. Finally, advantages, limitations, and implementation challenges are discussed. A review comparing three-phase and dual three-phase inverters showed that, due to the increased degree of freedom in modulation strategies, it is possible to eliminate common-mode voltages through active modulation techniques. Such added flexibility will reduce the risk of bearing currents effectively. It also highlights future research directions in bearing current suppression, including the development of multi-phase motor systems, real-time monitoring technologies with artificial intelligence, and the use of new insulation materials for the enhancement of bearing reliability. The results obtained should guide future research and engineering practices in suppressing bearing currents to improve motor durability with high performance. Full article

The diesel engine on a ship is crucial as it serves as the primary power source, significantly influencing both the vessel’s efficiency and safety. Monitoring metal wear particles found in lubricating oil is essential for assessing the lubrication condition of mechanical equipment onboard and anticipating potential failures. Analyzing these metal wear particles allows us to gauge the wear status of bearing pairs within the machinery, thereby providing a technical foundation for routine maintenance activities. However, under real operating conditions, it can be challenging to prevent multiple metal particles from simultaneously passing through sensors. To address this issue, this research introduces an innovative three-coil induction sensor that employs a variable-frequency excitation technique to explore how induction and eddy currents interact. The findings indicate that when the excitation frequency changes, the peak value of the signal from 337 μm iron particles only increases by 3.35 times, while the peak value of the signal from 340 μm copper particles increases by 22.69 times. Consequently, this study recommends using changes in excitation frequency to differentiate between mixed metal particles made of various materials. Full article

Oscillating grease-lubricated slewing bearings are used in several applications. One of the most demanding and challenging is the rotor blade bearings of wind turbines. They allow the rotor blades to be turned to control the rotational speed and loads of the complete turbine. The operating conditions of blade bearings can lead to lubricant starvation of the contacts between rolling elements and raceways, which can result in wear damages like false brinelling. Variable oscillating amplitudes, load distributions, and the grease properties influence the likelihood of wear occurrence. Currently, there are no methods for rating this risk based on existing standards. This work develops an empirical methodology for assessing and quantifying the risk of wear damage. Experimental results of small-scale blade bearings show that the proposed methodology performs well in predicting wear damage and its progression on the raceways. Ultimately, the methods proposed here can be used to incorporate on-demand lubrication runs of pitch bearings, which would make turbine operation more reliable and cost-efficient. Full article

Super-precision bearing lubrication condition is essential for equipment’s overall performance. This paper investigates a monitoring method of bearing lubrication using multi-sensors based on graph data. An experiment was designed and carried out, establishing a dataset including vibration, temperature, and acoustic emission signals. Graph data were constructed based on a priori knowledge and a graph attention network was employed to conduct a study on monitoring bearing lubrication abnormalities and discuss the influence of a missing sensor on the monitoring. The results show that the designed experiments can effectively respond to the degradation process of bearing lubrication, and the graph data constructed based on a priori knowledge show a good effect in the anomaly monitoring process. In addition, the multi-sensor plays a significant role in monitoring bearing lubrication. This work will be highly beneficial for future monitoring methods of bearing lubrication status. Full article

Bearings are one of the main components of induction motors, machines widely employed in today’s industries, making their monitoring a primordial task; however, most systems focus on measuring one physical magnitude to detect one kind of fault at a time. This research tackles the combination of two common faults, grease contamination and outer race damage, as lubricant contamination significantly impacts the life of the bearing and the emergence of other defects; as a contribution, this paper proposes a methodology for the diagnosis of this combination of faults based on a proprietary data acquisition system measuring vibration and current signals, from which time domain statistical and fractal features are computed and then fused using LDA for dimensionality reduction, ending with an SVM model for classification, achieving 97.1% accuracy, correctly diagnosing the combination of the contamination with different severities of the outer race damage, improving the classification results achieved when using vibration and current signals individually by 7.8% and 27.2%, respectively. Full article

The traction motor is a crucial component of high-speed electric multiple units, and its operational reliability is directly impacted by the temperature increase in the bearings. To accurately predict and simulate the temperature change process of traction motor bearings during operation, a fluid–solid–thermal simulation analysis model of grease-lubricated deep groove ball bearings was constructed. This model aimed to simulate the temperature rise of the bearing and the grease flow process, which was validated through experiments. The results from the simulation analysis and tests indicate that the temperature in the contact zone between the bearing rolling element and the raceway, as well as the ring temperature, initially increases to a peak and then gradually decreases, eventually stabilizing once the bearing’s heat generation power and heat transfer power reach equilibrium. Furthermore, the established fluid–solid–thermal coupling simulation analysis model can accurately predict the amount of grease required for effective lubrication in the bearing cavity, which stabilizes along with the bearing temperature. The findings of this research can serve as a theoretical foundation and technical support for monitoring the health status of high-speed EMU traction motor bearings. Full article

The traction behavior in cryogenic solid-lubricated ball bearings (CSLBBs) of liquid rocket engines (LREs) has a significant effect on the dynamic response of the bearing–rotor system. To reveal the fault mechanism of CSLBBs, a tribo-dynamic model is proposed in this paper that considers the solid-lubricated traction, six-DOF motion of the ball and contact collisions between the ball and the cage. The modified traction model uses fan-shaped and arched sections to discretize the contact area to eliminate the meshing error. The newly developed fault model, called ‘geometrical-frictional defects’, can more realistically represent solid-lubrication coating defects. The results show that the frictional excitation can significantly increase bearing vibration by increasing the traction force on the raceway. The change in the amplitude of the bearing vibration and its derivative can be used as a reference to determine the depth of defects. The width of the defect can be diagnosed by monitoring the double-pulse time interval and spectrum of the bearing vibration signal. This research may provide some theoretical guidance for the design and condition monitoring of CSLBBs. 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