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This paper presents a simulation method that is used to study subcritical vibrations of a tube roll in a paper machine. This study employs asymmetric 3D beam elements based on the Timoshenko beam theory. An asymmetric beam model accounts for varying stiffness and mass distributions. Additionally, a detailed rolling element bearing model defines the excitations arising from the set of spherical roller bearings at both ends of the rotor. The results obtained from the simulation model are compared against the results from the measurements. The results indicate that the waviness of the bearing rolling surfaces contributes significantly to the subcritical vibrations while the asymmetric properties of the tube roll have only a fractional effect on the studied vibrations. [ABSTRACT FROM AUTHOR]

Abstract  A skew of a paper transferred by rubber rollers in printers is simulated by FEM software. Effects of an imbalance of preload, an imbalance distribution of coefficient of friction and a front tension on the paper skew are investigated and how to determine the skew direction are shown. A simulation model is composed of a feed roller, a preload roller and a paper. The feed roller is rotated forcibly by a certain degree at every calculation step and a deformation, displacement and strain of the paper and rollers are calculated. A series of calculation results is shown as a motion simulation. The results show that the paper skews to the smaller preload side, to the smaller coefficient of friction side, or to the opposite side of the front tension. Further, effects of a skew prevention guide plate is simulated. [ABSTRACT FROM AUTHOR]

Rolling element bearing failures in paper mill machines are considered in relation to their critical role in the machine function. The paper discusses these failures according to what becomes damaged and how, and relates them to the vibration spectra and their develop ment over the lives of the bearings. Interpretations of some variations in the vibration signature, i.e. relating vibration amplitude changes and frequency shifts to the deterioration processes involved, are proposed and discussed. The literature was found mainly to confirm this analysis . A new approach to envelope alarming is presented and shown theoretically (logically) to offer later renewal with fewer failures, and therefore lower cost and higher productivity. Deficiencies in data coverage and quality, and the feedback of case study results, are discussed. A model to improve maintenance experience is proposed and discussed. Using vibration to monitor component conditions, the accurate prediction of remaining life requires (a) enough vibration measurements, (b) numerate records of operating conditions, (c) better discrimination bet ween frequencies in the spectrum and (d) correlation of (b) and (c). This is because life prediction depends on the amplitudes of (and) the frequencies generated by the component damage. Much money could be saved because some of the present policies utilize as little as half of the useful life of a bearing. [ABSTRACT FROM AUTHOR]

The article describes the use of magnets, paper clips and a ball bearing in teaching molecular geometries. The materials can be used to demonstrate how the valence-shell electron air repulsion model (VSEPR) may be applied to predict molecular geometries. The practical advantages of using magnetic models than other models include the easy addition or removal of magnets in comparing domain geometry and molecular geometry.

Abstract: A paper-based wet friction material lubricated with automatic transmission fluids (ATFs) produces plateau and positive slope regions in the friction–sliding velocity diagram. This feature observed at less than 1mm/s of sliding velocity is discussed in this paper. The relationship between the friction and contact pressures of less than 5MPa was determined by a reciprocating friction test rig lubricated with mineral oil including phosphoric acid ester, one of the additives for ATFs. The real contact area for dry condition was also determined by optical interferometry. The consistency of the real contact pressure dependency of the shear strength of the boundary film was indicated at pressures of less than 1GPa obtained by steel-on-steel boundary friction (oiliness) test. This suggests that the generation of the positive slope region is due to thin film lubrication. To the plateau region, possibility of application of the phase transition model is considered. [Copyright &y& Elsevier]

The paper industry is a highly automated industry that includes many different production steps, in which a variety of machine components are used. In a paper machine, where the pulp is being transformed into paper, rotating components such as bearing-mounted rollers play an important part in driving the wire with the pulp through the process. In this type of industry with a serial layout, the failure of a single roller or bearing could lead to the stoppage of several production steps, with costly consequences as a result. To ensure and optimise asset availability, a condition-based maintenance (CBM) strategy could be implemented. However, CBM is dependent on an appropriate condition monitoring (CM) technique to detect a physical phenomenon that defines the state of critical components or systems. For the development of CM techniques, it is therefore important to understand and model the physical behaviour of the system in question. In this paper, the behaviour of a roller in a paper machine is analysed using the finite element method (FEM). The physical model was compared with vibration measurements collected from an online monitoring system and an experimental modal analysis. [ABSTRACT FROM AUTHOR]

Multiphysics models were used to simulate the deformational characteristics experienced by paper under metering blades. Paper is found to slip microscopically at the backing roll interface and subsequently buckle either side of the blade during metering operations. Micro-slippage of the paper at the interface is a linear function of the separation height incurred during buckling. The effects of altering the static coefficient of friction as well as the properties of the backing roll material are studied. Increasing the coefficient of static friction reduces the extent of buckling while a non-linear relationship is found to arise on increasing the elastic modulus of the backing roll material. The mechanisms involved in micro-buckling deformation are explicated herein. [Copyright &y& Elsevier]

Abstract: Paper-based friction materials are widely used for oil-immersed clutches in automatic transmissions for passenger cars. It is known that repetition of engagements of the clutches causes wear of the friction materials leading to running-in with an increase in contact area. Observation of the contact of a typical paper-based friction material has been made by contact microscopy using the reflection of polarized light. The results have shown that contact is made at the top of its particulate and fibrous constituents, and comparison with the results of laser microscopy has revealed that the contact area observed by the contact microscopy is the contour contact area. An analysis has been made to describe this behavior by employing a mechanical model in which spherical and columnar asperities are supported by an elastic halfspace and wear under the loads they support. Analytical results describe the observed change in the contour contact area and demonstrate applicability of the model to wear of composite materials. [Copyright &y& Elsevier]

In order to improve the precision of machining and reduce the processing cost of paper honeycomb core, a new method is presented to fix the honeycomb core work piece to the working platform using magnetic and frictional forces. In this method, iron powder is used as a medium instead of the traditional adhesive-based material to achieve the bonding between the work piece and the working platform. Iron powder is poured into honeycomb cells until it reaches the desired height using a numerically controlled iron powder feeder system. In addition, a magnetic working platform is manufactured and placed on top of the station of the milling machine. The magnetic field produced by the magnetic working platform is leaded to the iron powder while the magnetic field control system switches on. More precisely, the mutual magnetic attraction between the iron powders located in different cells of the honeycomb and between the iron powder and the platform is generated. While cuffing force is applied to the work piece, two types of friction force occur. One is between the iron powder and the wall of the honeycomb cells, and other one is between the work piece and the working platform. Once the resultant friction force balances the machining load, the work piece will be then fixed to the platform. In this paper, a new bonding system based on the new method is introduced and demonstrated. [ABSTRACT FROM AUTHOR]

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As a key mechanism of belt conveyor, the health status and working state of its parts have a profound impact on whether the belt conveyor can run normally and safely. In the composition of the standard belt conveyor, the number of rollers is numerous and scattered. At the same time, under the complex environment of the work site, the fault detection of each roller is particularly difficult. In order to solve the above problems, a diagnosis method based on thermal infrared image features is proposed to detect the faults of each roller mechanism in the belt conveyor. Firstly, the position of the idler is identified based on the YOLOv4 identification method, and then the sticking resistance and bearing damage of the idler are detected based on the temperature difference discrimination method. In this paper, the target recognition method based on YOLOv4 is used to identify the position of the roller, and the recognition accuracy is 93.8%, which meets the requirements of the project. The infrared image obtained by the dual-spectrum camera is used to distinguish the fault of the idler in the coal mine. The temperature of the bearing and surface of the normal roller increases rapidly within 10 minutes of operation, and the temperature changes slightly after 10 minutes of operation. The bearing damaged idler has a greater friction effect at the bearing, so the temperature at the bearing rises faster, and there is a temperature difference of about 7°C between the bearing and the normal roller. The surface temperature of the idler in the blocking state is also fast for about 20 minutes, and there will be a temperature difference of about 8°between the surface of the idler and the normal roller. In this paper, it is determined that the temperature rise coefficients of the roller surface and bearing under normal conditions are 24% 28% and 18% 22% respectively. It is determined that the threshold value of the temperature rise coefficient in the blocking state and the damaged state is 30% and 25% respectively, that is, when the surface temperature rise coefficient of the roller is detected to be more than 30%, it is determined that the card resistance fault occurs, when the temperature rise coefficient at the roller bearing is detected > 25%, the bearing damage fault is judged. [ABSTRACT FROM AUTHOR]

This tutorial reviewpresents our strategy to control the rotation in a molecular rotary motor, and the family of star-shaped ruthenium complexes designed to perform such a task. The molecules have a piano-stool structure with a “stator” meant to be grafted on a surface, and a “rotor” bearing redox-active groups, so that addressing the molecule with nano-electrodes would trigger rotation. [ABSTRACT FROM AUTHOR]

Der vorliegende Aufsatz stellt ein Konzept für den Entwurf und die Herstellung von gefalteten schalenförmigen Tragstrukturen aus zementbasierten Verbundwerkstoffen vor, das in Anlehnung an die japanische Papierfaltkunst Origami entwickelt wurde. Die räumlichen Tragstrukturen werden durch Faltung von ebenen Elementen mit vorgegebenen Faltlinien hergestellt. Ziel ist die Entwicklung einer Entwurfs- und Herstellmethodik für dünnwandige Faltwerke mit einfachen oder doppelt gekrümmten Geometrien, die als segmentierbare Hüll- und Konstruktionselemente mit optimierten mechanischen Eigenschaften eingesetzt werden können. Wegen der hohen Variabilität der Formen und der großen Anzahl von Freiheitsgraden der Faltstrukturen ist eine Unterstützung mit numerischer Simulation in allen Phasen des Entwurfs und der Herstellung unabdingbar. Gegenüber der traditionellen Herstellung von Schalentragwerken mithilfe aufwendiger gekrümmter Schalungen verspricht die Methodik ein hohes Potenzial an Wirtschaftlichkeit. Insbesondere durch die Verwendung von modernen, zementbasierten Verbundwerkstoffen werden durch das Konzept neue Anwendungsfelder erschlossen, die sich durch geringen Materialverbrauch, einen hohen Ausnutzungsgrad des Werkstoffs sowie eine einfache systematische Herstellung auszeichnen. Oricrete - design and manufacturing methodology for folded plate structures made of novel cementitious composites The present paper shows an approach for the design and production of folded plate structures made out of novel cementious composite materials. The idea of the approach is derived from the Japanese art of paper folding, origami. The spatial structures are obtained by folding of planar elements provided with prescribed crease lines. The aim of the present work is the development of a design and manufacturing method for the production of free-form structural members with optimized mechanical properties applicable as façade and load bearing segments. Due to the high variability of forms and the large amount of degrees of freedom of the fold patterns, a support by numerical simulation in all phases of design and production is required. The method has a high potential to reduce the production costs compared to traditionally fabricated shell structures with complex curved formworks. New fields of application for cementious composite materials can be entered that are characterized by low material consumption, a high exploitation of the material and a systematic manufacturing process. [ABSTRACT FROM AUTHOR]

Bearings are one of the critical components of rotating machinery, and their failure can cause catastrophic consequences. In this regard, previous studies have proposed a variety of intelligent diagnosis methods. Most existing bearing fault diagnosis methods implicitly assume that the training and test sets are from the same distribution. However, in real scenarios, bearings have been working in complex and changeable working environments for a long time. The data during their working processes and the data used for model training cannot meet this condition. This paper proposes an improved adversarial transfer network for fault diagnosis under variable working conditions. Specifically, this paper combines an adversarial transfer network with a short-time Fourier transform to obtain satisfactory results with the lighter network. Then, this paper employs a channel attention module to enhance feature fusion. Moreover, this paper designs a novel domain discrepancy hybrid metric loss to improve model transfer learning performance. Finally, this paper verifies the method's effectiveness on three datasets, including dual-rotor, a Case Western Reserve University dataset and the Ottawa dataset. The proposed method achieves average accuracy, surpassing other methods, and shows better domain alignment capabilities. [ABSTRACT FROM AUTHOR]

Wind turbine energy generators operate in a variety of environments and often under harsh operational conditions, which can result in the mechanical failure of wind turbines. In order to ensure the efficient operation of wind turbines, the detection of any abnormality in the mechanics is particularly important. In this paper, a method for detecting abnormalities in the bearings of wind turbine energy generators, based on the cascade deep learning model, is proposed. First, data on the mechanics of wind turbine generators were collected, and the correlation between the data was studied in order to select the parameters related to the bearing temperature. Then, the logical relationship between the observation parameters and the target parameters was established based on a one-dimensional convolutional neural network (CNN) and a long short-term memory (LSTM) network, and the difference between the predicted temperature and the actual temperature was assessed using the root mean square error evaluation model. Finally, a numerical example was used to verify the operational data from a wind farm unit in northwest China. The results show that the CNN-LSTM model proposed in this paper can detect abnormalities earlier in the state of the main bearing than the LSTM model, and the CNN-LSTM model can detect abnormalities in the main bearing that the LSTM network cannot find. [ABSTRACT FROM AUTHOR]

The bearing is the core component of the gearbox transmission system. Once it is damaged during operation, it will cause the shutdown of the mechanical equipment for maintenance. It has important application significance to carry out fault detection and remaining useful life (RUL) prediction. Whereas, some bottlenecks, such as the noise interference of state characteristics, the excessive dependence of supervised learning on prior samples, and the practical RUL online calculation, restrict the industrial application of RUL prediction for rotating machinery equipment. To overcome the above problems, this paper introduces the discrete wavelet transform (DWT) to decrease the noise of the vibration acceleration signal obtained, and then uses the sliding average method to weaken the transient excitation. To make the state characteristics of the monitored bearing trendy, linear, and monotonic, this paper proposes a new set of state interpret indicators: energy and cumulative summation feature (CSF) to reflect the bearing health status. Based on the available bearing health information, the fault boundary threshold is established through the 3 σ criteria, which serves as the basis for first predicting time (FPT) detection. Once the FPT point is determined, this paper applies CSF to replace the original vibration acceleration amplitude as the degradation indicator, which has better linearity and monotonicity than amplitude-based indicators, and which is conducive to the implementation of simple structure curve fitting to carry out the overall RUL prediction. Comparing with existing methods, such as relevance vector machine (RVM), deep belief network (DBN), and particle filtering (PF)-based methods, the experimental results demonstrate that the proposed method has the best RUL prediction efficiency and the fastest convergence. [ABSTRACT FROM AUTHOR]

Purpose: As a critical component of the wind turbine drive train, the bearings are easy to fail under the complex environment of variable working conditions and loads in long-term operation. So it is essential to carry out a study targeting at fault diagnosis on it to improve the safety and reliability of the whole wind turbine operating. Methods: This paper presents a kind of bearing fault diagnosis method for wind turbines based on convolutional neural network (CNN) and sparrow search algorithm (SSA) optimized extreme learning machine (ELM). First, the wavelet time-frequency diagram (WTD) is constructed by using the continuous wavelet transform (CWT) to the original vibrational signal of the wind turbine bearing. Then, the WTD is input into deep learning CNN for extracting features. Finally, the SSA-ELM classifier is constructed by searching the optimal parameters of ELM with SSA, and the extracted features are put into SSA-ELM to identify different fault types. Results: The proposed CWT-CNN-SSA- ELM method is experimentally validated by two bearing datasets and compared with other methods. The result shows that the method has better diagnosis capability. Conclusion: In this paper, a wind turbine bearing fault diagnosis method based on CNN and SSA-ELM is proposed. The approach is able to well extract fault features and classify and identify the bearing data under variable working conditions and time-varying speed with good generalization ability. [ABSTRACT FROM AUTHOR]

There is still a lack of effective lubrication condition monitoring methods in the field of diesel engines. The paper proposes a novel thermoelectric approach to divide the lubrication state of bearings. First, the generation mechanism of thermoelectric potential on bearings is clarified. Then, both experimental and simulation studies are done, and a strong correlation between lubrication and thermoelectric potential is shown. The film thickness and temperature are further confirmed as significant factors influencing thermoelectric potential. Generally, the thermoelectric potential increases with temperature. However, a small film thickness ratio (when the film thickness ratio is less than 4) will suppress the thermoelectric potential. Three typical lubrication states of bearings are distinguished through thermoelectric potential and supported by the Stribeck curve results. Moreover, the significant influence of lubrication on the bearing is confirmed through the analysis of surface morphology and composition. [ABSTRACT FROM AUTHOR]

Purpose: The accuracy of the machining process is significantly impacted by the performance of hydrostatic bearings. This paper aims to analyze the influence of micro-textured on the performance of the hydrostatic bearing, and the performance of the bearing is improved by designing the arrangement of micro-textured. Design/methodology/approach: Different designs have been used while creating micro-textured bearings. The finite element models of bearing with smooth and micro-textured were established and solved using the computational fluid dynamics method. The arrangement scheme of the micro-textured was evaluated by comparing the influence of the distribution position and arrangement of the micro-textured on the bearing performance. Findings: To improve the performance of the bearing, the bearing capacity was significantly increased, and the friction coefficient of the bearing was decreased when the micro-textured was distributed in the form of an obtuse angle arrangement in the maximum pressure area of the bearing. The experimental findings validate the analysis method. Originality/value: In this paper, the effect of irregularly arranged micro-textured on bearing performance is investigated to improve the bearing capacity and lubrication status. [ABSTRACT FROM AUTHOR]

Selected slewing bearings and their application have been described in this article. Basic causes of the damage pitch surfaces of slewing bearings have been analyzed and examples of the damage have been presented as well. Special attention was paid to these kinds of damage which appeared most often in the case of the pitch surfaces of the bearings and those ones which very often cause premature exchange of the bearing and its scrapping. On the basis of the conducted studies it was stated that the main cause of the damage to the pitch surfaces of the bearings is the excessive load of rolling elements. Based on the results of the conducted analysis, actions limiting the occurrence of the damage to the pitch surfaces of the bearings, which lead to their premature exchange, have been proposed. One of the suggested actions, limiting the premature exchange of bearings, is the necessity of exceptionally thorough design and selection of the slewing bearings, including the conditions of their foundation. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to study the clearance compatibility of active magnetic bearing (AMB) and gas bearing (GB) to achieve a single-structured hybrid gas-magnetic bearing (HGMB), which uses a single bearing structure to realize both the functions of gas bearing and magnetic bearing. Design/methodology/approach: Because the radial clearance size of the AMB is typically ten times larger than that of the GB, radial clearance compatibility of GB and AMB needs to maximize the radial clearance of GB by adjusting structural parameters. Parametric analysis of structural parameters of GB is explored. Furthermore, a general structural design principle based on static analysis, rotordynamic performance and system stability is established for the single-structured HGMB. Findings: Load capacity is vastly reduced due to the enlarged radial clearance of the GB. A minimum clearance needs to be ensured by increasing the bearing diameter or width to compensate for the reduced load capacity, yet indirectly raising the bearing load. Increased bearing load is conducive to stability, yet it raises the risk of rotor abrasion. In addition, excessively large bearing diameter leads to system instability, and inappropriate bearing width affects critical speeds. A general structural design principle is established and the designed HGMB–rotor processes optimal performances. Originality/value: A single-structured HGMB is proposed to address the urgent demand for high-speed, cryogenic turboexpanders with frequent starts/stops. This design applies a single-bearing structure to realize the characteristics of both GB and AMB, greatly simplifying the implementation, reducing air friction loss and raising critical speeds. This paper provides a fresh perspective on the development of cryogenic turboexpanders for hydrogen liquefaction. It theoretically validates the feasibility and provides a design guide for a single-structured HGMB system. [ABSTRACT FROM AUTHOR]

Due to their unique structural design, portal cranes have been extensively utilized in bulk cargo and container terminals. The bearing fault of their drive motors is a critical issue that significantly impacts their operational efficiency. Moreover, the problem of imbalanced fault samples has a more pronounced influence on the application of novel fault diagnosis methods. To address this, the paper presents a new method called bidirectional gated recurrent domain adversarial transfer learning (BRDATL), specifically designed for imbalanced samples from portal cranes' drive motor bearings. Initially, a bidirectional gated recurrent unit (Bi-GRU) is used as a feature extractor within the network to comprehensively extract features from both source and target domains. Building on this, a new Correlation Maximum Mean Discrepancy (CAMMD) method, integrating both Correlation Alignment (CORAL) and Maximum Mean Discrepancy (MMD), is proposed to guide the feature generator in providing domain-invariant features. Considering the real-time data characteristics of portal crane drive motor bearings, we adjusted the CWRU and XJTU-SY bearing datasets and conducted comparative experiments. The experimental results show that the accuracy of the proposed method is up to 99.5%, which is obviously higher than other methods. The presented fault diagnosis model provides a practical and theoretical framework for diagnosing faults in portal cranes' field operation environments. [ABSTRACT FROM AUTHOR]

The paper aims to obtain the expression of the velocity of lubricating fluid in the hydrodynamic journal bearings by analytical method. In the classical short-bearing theory, the fluid flow was studied by ignoring the effect of centrifugal force of the lubricating fluid film. However, the self-oscillation of the shaft of high-power motors does not follow the rules in classical hydrodynamic lubrication theory. To explain this phenomenon, a modified form of Reynolds equation, in which the influence of centrifugal force of the lubricant is not ignored, is established. The study aims to establish the modified Reynolds equation by including the effect of centrifugal forces for the case of the short bearing type. Integration of the Navier-Stokes equations, yield the expressions for the components of velocity of the lubricating fluid in the gap. The oil's pressure in the hydrodynamic journal bearing is obtained by solving the modified Reynolds equation. The numerical results are considered in the case of the stable equilibrium position of the motion of the shaft, i.e. the symmetry axis of the shaft does not move. The plots of the velocity components in the tangential axial direction are displayed too. The theoretical results of a parabolic velocity distribution similar to that of a Newtonian fluid, derived from a Bingham plastic flow model. The flow in the gap, which are obtained by analytical method, are completely consistent with its boundary conditions and its physical properties. Further, with these results, the paper as a lemma to solve the dynamics problem in floating ring bearing with the influence of the centrifugal force of the lubricant. [ABSTRACT FROM AUTHOR]

The automotive industry requires effective evaluation methods for the quality control of automobile parts and bearings. The ISO standard defines the calculation of roughness parameters from the material ratio curve ("MRC") and material ratio curve on normal probability paper ("MPC") as effective methods for evaluating surfaces with excellent lubrication and frictional characteristics. ISO 4287 specifies the slice method as a calculation method for the MRC. The analysis time of the slice method is long due to the large amount of calculation required. Therefore, ISO 21920-2 specifies the use of the sort method. The sort method reduces the analysis time significantly due to the small amount of calculation required. A previous study revealed that errors occur in the MRC using the sort method compared to the slice method. However, the previous study concluded that the errors were acceptable compared to the time cost. In addition, the plateau surface is a surface with excellent sliding properties. The roughness parameters of the plateau surface have to be calculated from the MPC. However, in the case of expression on normal probability paper, the difference between MRCs calculated by the sort and slice methods increases as both ends approach. Therefore, the results of roughness parameters calculated by each MPC are expected to be different. This study reports the results of an investigation into the effect that increasing differences have on the roughness parameters. We aim to contribute to the establishment of a highly effective evaluation method by verifying the validity of using the sort method in the calculation of the MPC. [ABSTRACT FROM AUTHOR]

The advent of Industry 4.0 has ushered in a new era of technological advancements, particularly in integrating information technology with physical devices. This convergence has given rise to smart devices and the Internet of Things (IoT), revolutionizing industrial processes. However, despite the push towards predictive maintenance, there still is a significant gap in fault prediction algorithms for electrical machines. This paper proposes a signal spectrum-based machine learning approach for fault prediction, specifically focusing on bearing faults. This study compares the effectiveness of traditional neural network algorithms with a novel approach integrating fuzzy logic. Through extensive experimentation and analysis of vibration spectra from various mechanical faults in bearings, it is demonstrated that the fuzzy-neuro network model outperforms traditional neural networks, achieving a validation accuracy of 99.40% compared to 94.34%. Incorporating fuzzy logic within the neural network framework offers advantages in handling complex fault combinations, showing promise for applications requiring higher accuracy in fault detection. While initial results are encouraging, further validation with more complex fault scenarios and additional fuzzy layers is recommended to fully explore the potential of fuzzy-neuro networks in fault prediction for electrical machines. [ABSTRACT FROM AUTHOR]

Reports on the Rockwell Automation's publishing of a white paper detailing the causes and solutions to motor-bearing current concerns for induction motors driven by inverters.

In recent years, most research on bearing fault diagnosis has assumed that the source domain and target domain data come from the same machine. The differences in equipment lead to a decrease in diagnostic accuracy. To address this issue, unsupervised domain adaptation techniques have been introduced. However, most cross-device fault diagnosis models overlook the discriminative information under the marginal distribution, which restricts the performance of the models. In this paper, we propose a bearing fault diagnosis method based on envelope spectrum and conditional metric learning. First, envelope spectral analysis is used to extract frequency domain features. Then, to fully utilize the discriminative information from the label distribution, we construct a deep Siamese convolutional neural network based on conditional metric learning to eliminate the data distribution differences and extract common features from the source and target domain data. Finally, dynamic weighting factors are employed to improve the convergence performance of the model and optimize the training process. Experimental analysis is conducted on 12 cross-device tasks and compared with other relevant methods. The results show that the proposed method achieves the best performance on all three evaluation metrics. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive review of mitigation approaches, with a specific focus on geometric modifications, to mitigate shaft voltage and bearing current in electric drives. While existing literature extensively covers inverter-based and coupling path-based methods, the potential of geometric modifications has been relatively underexplored. The geometric modification approach offers a cost-effective and weight-saving solution that can be incorporated during the early design phase of the machine. The review begins by outlining various mitigation techniques applied at the victim machine, including bearing insulation, ceramic ball bearings, shaft grounding, and more. Subsequently, it delves into the machine geometric modification approach, examining methods related to winding design, stator and rotor iron geometry, rotor surface insulation, and stator slot wedge modifications. The paper highlights the practical relevance of geometric modifications, emphasizing their advantages over conventional methods. The review paper aims to shed new light on the potential of geometric modifications in mitigating shaft voltage and bearing current in electric drives. By providing valuable insights into this approach, researchers and engineers can develop robust and efficient electric drive systems, advancing the field of electrical machine design and operation. [ABSTRACT FROM AUTHOR]

The prognosis of wind turbine failures in real operating conditions is a significant gap in the academic literature and is essential for achieving viable performance parameters for the operation and maintenance of these machines, especially those located offshore. This paper presents a framework for estimating the remaining useful life (RUL) of the main bearing using regression models fed operational data (temperature, wind speed, and the active power of the network) collected by a supervisory control and data acquisition (SCADA) system. The framework begins with a careful data filtering process, followed by creating a degradation profile based on identifying the behavior of temperature time series. It also uses a cross-validation strategy to mitigate data scarcity and increase model robustness by combining subsets of data from different available turbines. Support vector, gradient boosting, random forest, and extra trees models were created, which, in the tests, showed an average of 20 days in estimating the remaining useful life and presented mean absolute error (MAE) values of 0.047 and mean squared errors (MSE) of 0.012. As its main contributions, this work proposes (i) a robust and effective regression modeling method for estimating RUL based on temperature and (ii) an approach for dealing with a lack of data, a common problem in wind turbine operation. The results demonstrate the potential of using these forecasts to support the decision making of the teams responsible for operating and maintaining wind farms. [ABSTRACT FROM AUTHOR]

In this paper, the vibration control of the multivariable model of rotor bearing systems is considered for investigation. Some simply structured controllers that can suppress vibrational disturbances are tested for their robustness via the H∞ optimality criteria. Initially, intelligent optimisation techniques are used to minimize the H∞ mixed-sensitivity norm of the Linear Fractional Transformation (LFT) of the simple two-term PI controllers acting on the rotor system models. This results in some controllers that can suppress the vibration but with a slow oscillatory response. After this, an appropriate interpretation of the Bode plot singular values of the combined sensitivity and control effort matrix is used to explain the performance shortcomings of this controller. Moreover, the existing simply structured controllers in the literature exhibiting a faster performance are examined by using singular value plots. It is shown that when the maximum singular value of the control effort matrix drops below the 0 db line, the performance will be boosted. Finally, the H∞ controllers are designed by using the robust control toolbox in MATLAB. This resulted in rapid disturbance rejection, with the vibration amplitude diminishing to zero after 0.3 s due to double-step disturbances. However, these controllers in the frequency domain have an order of eight and may not be realizable to be implemented in practice. It is concluded that examining the Bode plot of the maximum singular value of the control effort matrix is a useful tool for evaluating performance in the frequency domain. However, designing robust controllers by toolboxes in the time domain can lead to superb performance with higher-order controllers. [ABSTRACT FROM AUTHOR]

In recent years, the trend towards larger wind turbines and higher power densities has led to increasing demands on planet gear bearings. The use of sliding bearings instead of rolling bearings in planetary bearings makes it possible to increase the power density with lower component costs and higher reliability. Therefore, the use of planet gear sliding bearings in wind turbine gearboxes has become more common. However, the flexible structure and complex load conditions from the helical tooth meshes lead to highly complex elastic structure deformation that modifies the lubricant film thickness and pressure distribution and, thus, has to be considered in the calculation of the bearing's load-carrying capacity. This paper introduces a highly time-efficient calculation procedure that is validated with pressure measurement data from a three-stage planetary gearbox for a multi-megawatt wind energy plant. The investigations focus on three main objectives: (i) analyses of experimental and predicted results for different load cases, (ii) validation of the results of planet gear sliding bearing code, and (iii) discussion on mandatory modeling depths for the different planet stages. Results indicate the necessity of further research in this field of applications, particularly for the third-stage bearings. [ABSTRACT FROM AUTHOR]

Aiming to resolve the problem where the reliability of gearbox bearings of wind turbines is easily affected by random impact, this paper puts forward a reliability evaluation method for the competitive failure of gearbox bearings of wind turbines considering the fault incubation point. Firstly, we use Weibull distribution to simulate the fault latent process of wind turbine gearbox bearings. Secondly, a natural degradation model of gearbox bearing is established based on the Wiener process. Then, we model the random impact arrival frequency and impact intensity through a homogeneous Poisson process and normal distribution, respectively. Finally, based on considering the fault incubation point, the natural degradation of the bearing, the instantaneous degradation caused by impact, and the decline in the impact resistance of the bearing, a reliability evaluation model of gearbox bearings of wind turbines is established. A high-speed bearing of a gearbox from a wind farm in northern China is selected for simulation analysis. The results show that the proposed method can better describe the reliability decline process of the gearbox bearings of wind turbines, which has a specific guiding significance for the maintenance of wind turbines. [ABSTRACT FROM AUTHOR]

Dynamic coefficients of a bearing are basic elements of rotor dynamics analysis. At present, there are still some issues in the calculation of the dynamic coefficient of air foil bearing. In this paper, the dynamic coefficients of the air foil bearing are calculated by time-domain identification. This method does not need to linearize the system equations, so it is generally applicable to different models for air foil bearings. Using the established method, this paper verified the calculation results using the foil model with axial uniform deformation for the first time, and the influence of the foil model on the dynamic coefficients was studied. The calculation results of the foil models with axial uniform deformation and axial independent deformation have significant differences. Furthermore, the accuracy of the dynamic coefficient method for different disturbance amplitudes was compared. The results indicate that the dynamic coefficient method has good accuracy over a large disturbance range. [ABSTRACT FROM AUTHOR]

The application of the existing complex network in fault diagnosis is usually modelled based on the time domain, resulting in the loss of sign frequency-domain features, and the extracted topology features of network are too macroscopic and insensitive to local changes within the network. This paper proposes a new method of local feature extraction based on frequency complex network (FCN) decomposition and builds a new complex network structure feature on this basis, namely, subnetwork average degree. The variation law of signals in frequency domain is obtained with the aid of the structural features of complex network. The local features that are sensitive to local changes of the network are applied to characterize the whole network, with flexible application and without limitation in mechanism. The average degree of subnetwork could be regarded as feature parameters for rolling bearing fault diagnosis and degradation state recognition. Analysis on the experimental data and bearing life cycle data shows that the method proposed in this paper is effective, revealing that the extracted features have effective separability and high accuracy in fault recognition and the degradation detection of the life cycle of rolling bearings combined with neural networks. Moreover, the proposed method has reference value for the processing and recognition of other nonstationary signals. [ABSTRACT FROM AUTHOR]

The lubrication of the mechanical components reduces friction, and increases the efficiency and the reliability. However, the interaction of moving components with the lubricant leads to power losses due to viscous and inertial effects. Nowadays, the study of lubricant behavior can be carried out through computational fluid dynamics (CFD) simulations. Nevertheless, the modeling of the computational domain within complex mechanical systems (e.g., ordinary, planetary and cycloidal gearboxes, roller bearings, and pumps) requires the exploitation of specific CFD techniques. In the last decades, many mesh-based or meshless approaches have been developed to deal with the complex management of the topological changes of the computational domain or the modeling of complex kinematics. This paper aims to collect and to classify the scientific literature where these approaches have been exploited for the study of lubricated mechanical systems. The goal of this research is to shed a light on the current state of the art in performing CFD analysis of these systems. Moreover, the objective of this study is to stress the limits and the capabilities of the main CFD techniques applied in this field of research. Results show the main differences in terms of accuracy achievable and the level of complexity that can be managed with the different CFD approaches. [ABSTRACT FROM AUTHOR]

Intelligent fault diagnostic systems are fast becoming key instruments in industrial applications. This paper presents a recognition system for diagnosing bearing defects in induction motors. The proposed scheme is comprised of five steps, namely signal segmentation, feature extraction and reduction, fault classification and the decision fusion. First, the vibration signal is segmented into successive equal-length intervals, which are considered as patterns in a recognition problem. The objective is to predict the defect mode (class) for each pattern. Then, the time- and the frequency-domain features are extracted from each interval. At the next step, a small set of distinctive and informative features is found by resorting to different feature reduction techniques to guarantee well-organized learning and immediate and accurate classification. Then, in the fourth step, various classifiers are trained to learn to distinguish between the faulty and healthy states. To make the final decision, different combinations of classifiers are considered using the voting and stacking techniques to enhance the overall performance of the recognition system. Evaluation of the proposed diagnostic scheme on the standard CWRU bearing defect database demonstrates that this system attains reasonable performance measures, validating the ideas put forward in this paper. [ABSTRACT FROM AUTHOR]

In order to ensure quality maintenance of rotary machinery, proper interpretation of the malfunction causes is required. The behaviour of the mechanical components of the machinery is often reflected in vibrations responding to the action of internal as well as external forces. The paper focuses on the issues of the application of the tools of technical diagnostics in verification of the technical condition of two-stage bevel-spur gearbox operating in difficult conditions of paper industry. Pinion bearing dismantled from malfunctioned gearbox was analysed. After repair, measurements were performed in order to determine the dynamic properties of the bearings. The values measured on the machine after repair were compared in two operating modes - depending on motor rotation speed. The acquired values of dynamic parameters and temperature (after repair) were in correlation to the condition found on the malfunctioned bearing (after dismantling form the malfunctioned gearbox). [ABSTRACT FROM AUTHOR]

Flaking failure caused by surface cracks of silicon nitride ceramic bearings has been investigated from the viewpoint of the ring crack model. However, the relation between surface and subsurface cracks under rolling contact fatigue is not fully understood. In this investigation subsurface cracks branching from an initial surface crack were observed in detail, and the process of flaking failure was investigated. The specimens were observed prior to the separation of the surface layers and it was found that the initial surface cracks grew vertically to the surfaces and did not curve as predicted by the ring crack model. Subsurface cracks branched from the single surface cracks and grew in a direction parallel to the surface. They grew in both the same and opposite directions to the ball movement, with small upward and downward branches. These subsurface cracks grew prior to the semi-circular surface cracks. From these observations it was concluded that the flaking failures are not caused directly by surface cracks, but by subsurface cracks that branch from them. [ABSTRACT FROM AUTHOR]

Purpose: The normal operation of a rotor system is generally vulnerable to misalignment between gas foil bearing (GFB) and rotor. However, most theoretical and experimental researches about the characteristics of GFBs have ignored this phenomenon. Therefore, the main purpose of this paper is to evaluate the static and dynamic performance of GFBs considering misalignment. Design/methodology/approach: The shaft is allowed to misalign in two directions. Then the variations of bearing load, friction force, restoring moment, stiffness and damping coefficients are thoroughly explored. The hydrodynamic pressure on the gas film is modeled with compressible Reynolds equation, and the deformation of the flexible bearing is calculated with finite element method. Small perturbation method is used to obtain the displacement and moment dynamic coefficients. Findings: The film thickness and pressure distribution distort when misalignments appear. The inclination of GFBs can enhance the restoring moment to withstand the imposed misalignment. Furthermore, the simulation phenomenon demonstrates the misalignment around load direction should be avoided as much as possible, while a small value misalignment around another direction is allowed. Originality/value: The value of this paper is the exploration of the influence of misalignments on the static and dynamic performance of the Generation II journal GFB. Peer review: The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2019-0418/ [ABSTRACT FROM AUTHOR]

This paper studies the rating lives of wind turbine main bearings, as determined by the IEC 61400‐1 and ISO 281 standards. A critical review of relevant bearing life theory and turbine design requirements is provided, including discussion on possible shortcomings such as the existence (or not) of the bearing fatigue load limit and the validity of assuming linear damage accumulation. A detailed exploratory case study is then undertaken to determine rating lives for two models of main bearing in a 1.5 MW wind turbine. Rating life assessment is carried out under different conditions, including various combinations of main bearing temperature, wind field characteristics, lubricant viscosity, and contamination levels. Rating lives are found to be sufficiently above the desired 20‐year design life for both bearing models under expected operating conditions. For the larger bearing, operational loads are shown to be below or close to the bearing fatigue load limit a vast majority of the time. Key sensitivities for rating life values are temperature and contamination. Overall, the results of this study suggest that an ISO 281 rating life assessment does not account for reported rates of main bearing failures in 1 to 3 MW wind turbines. It is recommended that a similar analysis be undertaken for ISO/TS 16281 rating lives, along with further efforts to identify principal root causes of main bearing failures in future work, possibly leading to a new application standard specific to this component. It is also recommended that the impacts of partial wake impingement on main bearing rating lives are investigated. [ABSTRACT FROM AUTHOR]

Purpose: The most common cause of CNC machine failure is the bearing faults that influence the performance of the manufacturing system. The detection and the diagnosis of bearing defects are crucial to the reliable functioning of revolving machinery. This paper suggests an intelligent vibration-based condition and fault diagnostic technique for the identification of bearing faults in CNC machine. Investigational vibration data obtained for various bearings and operational requirements were analyzed to create a structure for the monitoring and classification of bearing defects to determine the health of the machine. Methods: Fault diagnosis was made using Hybrid Signal Decomposition (HSD) methodology for the decomposition of the vibration signal. Vibration features derived from the received decomposed raw signal were chosen using the key component review to eliminate redundant features using Principal Component Analysis (PCA). Subsequently, these related features were input into Discrete AdaBoost and Gentle AdaBoost and compared to traditional Machine Learning (ML) algorithms for the classification of various bearing faults in CNC machine tools. Results: The proposed Gentle AdaBoost is outperformed with 100% classification accuracy by Discrete AdaBoost and other machine learning algorithms. Experimental outcomes suggest that the proposed approach has an immense capacity to prevent unplanned and unnecessary device shutdowns due to loss of bearings in the CNC machine. Conclusion: The success rate achieved using Gentle AdaBoost outperformed Discrete AdaBoost and other traditional machine learning algorithms, the performance rate obtained for defining various bearing states dependent on vibration signals. [ABSTRACT FROM AUTHOR]

Due to the advantages of low friction, high accuracy, and pollution-free characteristics, aerostatic bearings are widely used in precision and ultra-precision equipment machines. In order to improve the stability, this paper proposes a novel aerostatic bearing with damper modules to suppress the vibration on the bearing surface. A hermetically squeeze film damper (HSFD) constructed by sheet damper module (SDM) is applied to aerostatic bearings for acquiring good stability. The appropriate stiffness range of HSFDs can be obtained for meeting different air film thicknesses and excitation frequencies by theoretical calculations. Various stiffness and damping characteristics can be acquired by adjusting the thickness of sheets in SDMs. In addition, an experimental device is established to identify the stiffness and damping behavior of dampers. In order to further gain insight to evaluate the performance of bearings, a simple test rig has also been set up to measure the vibration characteristics. Experimental results reveal that the damper concept yields high viscous damping characteristics an order of magnitude larger than aerostatic bearing without dampers, which leads to the vibration amplitude be obviously suppressed. The proposed aerostatic bearings with HSFDs can provide a better performance on damping and stability. • In order to improve the stability, this paper proposes a novel aerostatic bearing with damper modules to suppress the vibration of bearing surface. • A hermetically squeeze film damper (HSFD) constructed by sheet damper module (SDM) is applied to aerostatic bearings to acquire good stability. • Experimental results show that the damper concept yields high viscous damping characteristics an order of magnitude larger than aerostatic bearing without dampers, which leads to the vibration amplitude on bearing surface can obviously been decreased. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to investigate the influence of surface texture on the subsurface characteristics of contact interfaces under elastohydrodynamic lubrication condition. As a typical contact form of gears and bearings, the optimization of friction characteristics at the elastohydrodynamic lubrication (EHL) interface has attracted the attention of scholars. Laser surface texturing is a feasible optimization solution, but there have been concerns about whether the surface texture of high-pair parts will affect their fatigue life. Design/methodology/approach: To examine the impact of texture preparation on the subsurface characteristics of high-pair interfaces under EHL conditions, a point contact EHL model is developed that takes into account the effect of textured surface topography. The pressure and thickness of the oil film are calculated as input parameters under different loads and entrainment velocities. The finite element method is used to simulate the impact of textures with varying diameters, densities and depths on the subsurface characteristics of the elastohydrodynamic interface. According to ISO 25178, analyze the relationship between 3D topography parameters and subsurface characteristics and study the trend of friction characteristics and subsurface characteristics based on the results of the ball on disc friction tests. Findings: The outcomes suggest that under different rotational velocity and load conditions, the textured surfaces exhibit improved friction reduction effects; however, the creation of textures can result in significant subsurface plastic deformation and local peeling. The existence of texture makes the larger stress zone in the subsurface layer closer to the surface, leading to fatigue failure near the surface. Reasonable design parameters can help enhance the attributes of the subsurface. A smaller Sa and a Str greater than 0.5 can achieve ideal subsurface properties on the textured surface. Originality/value: This paper investigates the influence of surface texture on the friction and subsurface characteristics of EHL interfaces and analyzes the impact of surface texture on interface contact performance while achieving lubrication improvement functional characteristics. The results provide theoretical support for the optimization design and functional regulation of surface texture in EHL interfaces. Peer review: The peer review history for this article is https://publons.com/publon/10.1108/ILT-10-2023-0324/ [ABSTRACT FROM AUTHOR]

In the hydrodynamic step bearing, when the lubricating film thickness is as low as the adsorbed layer thickness on the surface, the adsorbed layer effect on the bearing pressure should be evident. Different interactions can be formed between the fluid and the static surface, in the bearing inlet and outlet zones, respectively. In this paper, the multiscale calculation was made for the pressures generated in this type of step bearing when the continuum film exists between the adsorbed layers. The calculation outcomes show that the hydrodynamic pressures and loads of the bearing for the S(strong)-M(medium)-S(strong) and S(strong)-W(weak)-S(strong) fluid-bearing surface interaction types exceed significantly those for the S(strong)-S(strong)-S(strong) fluid-bearing surface interaction type if the bearing clearance in the outlet zone is smaller than 100nm (and over 20nm). The results indicate that for higher hydrodynamic pressures in the bearing, the interaction between the fluid and the static surface in the outlet zone is stronger than that in the inlet zone. [ABSTRACT FROM AUTHOR]