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Compressive membrane action can considerably improve the load bearing capacity of concrete slabs and beams in case of excessive loaded due to an accidental event. Currently, only limited research has been focusing on compressive membrane action in prestressed concrete elements, or on concrete elements with large cavities, such as precast concrete hollow core slabs. Therefore, a novel real-scale test setup has been developed in order to assess this effect in precast hollow core slabs, and how it can enhance the load-carrying capacity in accidental events. In parallel with these tests, a numerical finite element model has been developed in order to perform a more detailed structural analysis of this phenomenon, and to study the influence of various input parameters. The details of this test setup are briefly explained, and some relevant experimental test results are provided. Considering the experimental findings and validated numerical model, this contribution aims to quantify the influence of compressive membrane action on the structural reliability of precast concrete hollow core slabs. To this end, probabilistic models for the most important material and geometric variables are gathered, and the structural reliability is assessed using Latin Hypercube sampling. Overall, the results indicate that considering the formation of compressive membrane action strongly influences the variability of the ultimate load-carrying capacity of precast concrete hollow core slabs. [ABSTRACT FROM AUTHOR]

Assessment of the influence of human activities on recent, current, and future global and regional climate conditions and extremes has advanced sufficiently to provide a reasonable measure of its impact across the globe. The lack of concurrent adaptation of the design base for load bearing structures results mainly from the absence of a clear signal that climate change will have a significant effect on the climate actions that are accounted for in the structural design basis. The recent IPCC assessment of the physical science basis of climate change reports significant advances in observing and projecting changes in weather and climate extremes due to human influences. This provides an opportunity to reassess projections of future climate action conditions. Whilst the IPCC assessment confirms previous indications that, for example extreme wind will respond moderately globally, improvements in understanding and projecting changes show that trends will be overshadowed by uncertainties. The implication is that the design base will need to account for increasing uncertainties as climate actions are projected into the future, over the service life of existing structures, as well as those designed to current standards. The design base consequently in advance need to reflect continuous changes of existing structures. [ABSTRACT FROM AUTHOR]

Copyright of Technisches Messen is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A three-dimensional vehicle-axle box bearing coupling model is established. The model can calculate the contact force in three directions and obtain the dynamic response of axle box bearing under the real vehicle running environment. The load distribution on the double row tapered roller bearing and the vehicle is analyzed, and the co-simulation is conducted by comprehensively considering the force transmission between vehicle and bearing. Taking into account the great impact of defects on the bearing, three different types of bearing defects are added into the model, respectively. The simulation results verify the effectiveness of the model. The model is also verified by using the rolling and vibrating test rig of single wheelset. It is concluded that the simulation results show good agreement with experimental results. The influence of track irregularity on the system motion state is studied by using axis trajectory and vibration RMS (Root Mean Square value). The results show that the influence of track irregularity and wheel flat scar on axle box bearing cannot be ignored. The RMS of acceleration will change greatly due to the existence of defects. Wheel flat scar will greatly interfere with the extraction of bearing defect, but it can be selected at high speed and low frequency to monitor the existence of wheel flat scar, and select low speed and high frequency to monitor the existence of bearing defect. The research results are helpful to the detection of wheel flat scar and axle box bearing defect. [ABSTRACT FROM AUTHOR]

Copyright of Experimental Technology & Management is the property of Experimental Technology & Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The studies of the nonlinear dynamics of the protective bearing-rotor system in the past 30 years were reviewed. Firstly, The development history of the local collision model was sorted out. the development of the system structure model from the two aspects of the rotor and the back-up bearing was summarized, and the characteristics of each model were given . Secondly, the main reason for back-up bearing-rotor system damage-backward whirl was analyzed. Then the relationship between the drop response results and the system structure and parameters was expoualded from three aspects of rotor structure, bearing structure and bearing parameters. Finally, some general guidelines for the design and selection of back-up bearings' structure and parameters were summarized, and some issues which was worth further study were pointed out. [ABSTRACT FROM AUTHOR]

The technology of fault diagnosis helps improve the reliability of wind turbines. Difficulties in feature extraction and low confidence in diagnostic results are widespread in the process of deep learning-based fault diagnosis of wind turbine bearings. Therefore, a probabilistic Bayesian parallel deep learning (BayesianPDL) framework is proposed and then achieves fault classification. A parallel deep learning (PDL) framework is proposed to solve the problem of difficult feature extraction of bearing faults. Next, the weights and biases in the PDL framework are converted from deterministic values to probability distributions. In this way, an uncertainty-aware method is explored to achieve reliable machine fault diagnosis. Taking the fault signal of the gearbox output shaft bearing of a wind turbine generator in a wind farm as an example, the diagnostic accuracy of the proposed method can reach 99.14%, and the confidence in diagnostic results is higher than other comparison methods. Experimental results show that the BayesianPDL framework has unique advantages in the fault diagnosis of wind turbine bearings. [ABSTRACT FROM AUTHOR]

We present a compressed air motor, completely built by laser powder bed fusion. To highlight the fully functional integration by additive manufacturing, the rotor, stator, bearings, turbine, gas inlet and outlet were all built in a single print job. The material used was Inconel 718, and the motor was 44 mm tall and 12 mm in diameter. With the rotation axis of the motor in print in the direction of the laser powder bed fusion process, no build supports are needed, and thus the rotor and stator are fully moveable against each other. Plain bearings were used to position the rotor inseparably inside the stator, with a bearing gap of 0.2 mm, resulting in stable rotation. The idle rotation speed of the motor was measured with a digital laser measuring device as a function of air pressure and inlet size. With linear behavior between the rotation speed and gas pressure of up to 5.5 bar, the motor can be easily controlled. With varying gas inlet sizes, the idle rotation speed of the compressed air motor is also varied. A maximum rotation speed of 90,000 rpm was achieved at 1.5 mm gas inlet size and 3 bar gas pressure. [ABSTRACT FROM AUTHOR]

The working principle of the motor can cause unbalanced magnetic pull (UMP) between stator and rotor unavoidably. Previous research about nonlinear vibration excited by UMP was focused on the rotor supported by traditional mechanical bearings or gas bearings. However, the magnetic levitation rotor is particular due to the low rigidity provided by the active magnetic bearing (AMB). UMP amplifies rotor vibration in the resonant zone and further excites the nonlinear electromagnetic force, thus producing different vibration phenomena. The paper calculates rotor orbit, spectra analysis, and time-history plot with numerical methods and studies the influence of the rotation speed, eccentricity, key control parameters, and UMP on rotor dynamics in detail. Results illustrate displacement response spectra of the magnetic levitation rotor are quite different from previous research results. The appearing frequency components are inducted by universal formulas in this paper. Furthermore, research shows a slight adjustment of the control parameters affect significantly harmonic components and vibration characteristics. The research results have practical reference significance for fault diagnosis, feature recognition, and controller optimization of the AMB-rotor system. [ABSTRACT FROM AUTHOR]

Induction motors are complex energy conversion systems across the domains of dynamics, electricity, and magnetism. Most existing models mainly consider unidirectional coupling, such as the effect of dynamics on electromagnetic properties, or the effect of unbalanced magnetic pull on dynamics, while in practice it should be a bidirectional coupling effect. The bidirectionally coupled electromagnetic-dynamics model is beneficial to the analysis of induction motor fault mechanisms and characteristics. This paper proposes a coupled electromagnetic-dynamic modeling method that introduces unbalanced magnetic pull. By using the rotor velocity, air gap length, and unbalanced magnetic pull as the coupling parameters, the coupled simulation of the dynamic and electromagnetic models can be effectively realized. Simulation results for bearing faults show that the introduction of magnetic pull induces a more complex dynamic behavior of the rotor, which in turn leads to modulation in the vibration spectrum. The fault characteristics can be found in the frequency domain of the vibration and current signals. Through the comparison between simulation and experimental results, the effectiveness of the coupled modeling approach and the frequency domain characteristics caused by the unbalanced magnetic pull are verified. The proposed model can help to obtain a variety of information that is difficult to measure in reality and can also serve as a technical basis for further research on nonlinear characteristics and chaos in induction motors. [ABSTRACT FROM AUTHOR]

Copyright of Bearing is the property of Bearing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Subtractive manufacturing processes are usually accompanied by the occurrence of tiny flakes and swarf, which later on cause severe wear and damage, especially in moving components such as rolling or sliding bearings, pistons, etc. However, up until now, such detrimental effects have hardly been investigated. One reason is the lack of a definition of a typical design of debris particle. Therefore, the main goal of the project described in this paper was to elaborate a draft that defines standardized test particles. It had to be evaluated whether test particles could be adequately reproduced and whether they would reveal significant damage potential. Taking into account future mass fabrication, Micro Powder Injection Molding (MicroPIM) was chosen as a production method. Five different 3D designs of geometrically defined test particles were developed. The maximum size of each design was 1167 mm in green state; however, all samples shrank in size during sintering. Specially tailored feedstocks containing 42CrMo4 steel powders were used and the related molding, debinding and sintering procedures were developed. All particle geometries and related mold inserts were developed using a commercial software routine for the layout of runner systems, gate locations and ejector positions. The damage potential of the test particles was evaluated based on trials using journal bearing and shift valve test rigs. Although only a moderate degree of damage potential could be ascertained up until now, it can be expected that the artificial swarf will enable standardized wear test procedures to be developed. [ABSTRACT FROM AUTHOR]

Thin-film sensors were used to measure the oil film pressure distribution at the piston pin-bore interface in order to ascertain the stress distribution on the piston pin of a gasoline engine during actual operation. Thin-film sensors have been manufactured by a sputtering method to a total film thickness of about 3–6 μm. The features of thin-film sensors have been utilized to successfully measure the oil film pressure on engine main bearings, connecting rod bearings and piston skirts of both diesel and gasoline automotive engines. However, as engine lubrication conditions have become more severe year by year, it has become necessary to develop thin-film pressure sensors with higher durability. The use of diamond-like carbon (DLC) coating for the protective film of the thin-film sensor has enabled accurate measurement of oil film pressure under engine operating conditions. The AVL EXCITETM Power Unit was used in simulations with the application of elastic fluid lubrication theory. The calculated values were compared with measured data, and a comparison was made of the effect of the model constraint condition. [ABSTRACT FROM AUTHOR]

Machinery or instruments are subjected to external forces from a base in many cases. It can have a negative influence on manufacturing accuracy, tightness, wear of machine parts, work safety etc. Therefore, it is necessary to perform suitable passive elastic bearings of machinery to eliminate external vibration from the base. An application of suitable vibro-isolating materials is one way of the vibration elimination. The aim of the paper is to study vibration damping properties of different materials by means of a non-destructive method of forced mechanical oscillations. Different factors influencing transfer damping of mechanical vibration were investigated in this work, e.g., material type and its thickness, excitation frequency of mechanical oscillations, size of mass load and effect of material composition. These factors were subsequently evaluated. Finally, suitable recommendations for passive damping of mechanical vibration were described. [ABSTRACT FROM AUTHOR]

Because the signal of water pump bearing is seriously disturbed by noise and the fault evolution is complex, it is difficult to describe the performance degradation trend of water pump bearing in a timely and accurate manner using the traditional performance degradation index (PDI). In this paper, a new Cluster Migration Distance (CMD) algorithm is proposed. The extraction of the indicator includes the following four steps: First, the relevant blind separation is used to extract the useful signal of the monitored bearing from the mixed signal; secondly, the impact component is further enhanced by wavelet packet analysis. Then, the redundancy of the original feature vectors is eliminated using our previously proposed KJADE (Kernel Joint Approximate Diagonalization of Eigen-matrices) method. Finally, the newly proposed CMD index is computed as PDI. By calculating the offset trajectory of the feature cluster centroid in the continuous running process of the bearing, CMD can aptly deal with the complex and variable features in the fault evolution process of the water pump bearing. The whole-life monitoring data of a 220 KW water pump system are processed. The results show that the proposed CMD index has better early-warning ability and monotonicity than the traditional kurtosis index. [ABSTRACT FROM AUTHOR]

Aiming at noise problem of two-stage gearbox, this paper uses the panel acoustic contribution analysis (PACA) and response surface methodology to conduct structural-borne acoustics analysis and multi-objective optimization of gearbox. Using this optimization, optimal layout and parameters of the added ribs can be determined. The dynamic model of a spur gear-shaft-bearing system is built in consideration of the time-varying mesh stiffness, the time-varying bearing stiffness, and the flexibility of the shaft, while dynamic load of the bearing is obtained through solving the model. The dynamic load of bearings is considered as excitation to analyze the vibration and noise radiation characteristics of housing. Furthermore, acoustic transfer vector, modal acoustic contribution and PACA are used to select the region with the most acoustic contribution. The variable ribs structure model (VRSM) is established in this region. Finally, the VRSM are adopted to optimize the housing. The optimization model based on the peak sound pressure level (PSPL) and the ribs mass (Rm) is established by using response surface method. Through multi-objective optimization, the variable in VRSM can be modified or deleted to reduce the radiated noise of the gearbox. The optimization results demonstrate that the PSPL after optimization is decreased by 4.88 dB at frequency of 3130 Hz. At the same mass, the noise reduction effect of VRSM is 12% higher than that of standard rib. Therefore, the optimization effect of the housing structure is obvious. PACA-VRSM-RSM- NSGA-II technology provides a new research scheme for reducing the vibration and noise of the gearbox. [ABSTRACT FROM AUTHOR]

Based on Newton's second law and the thermal network method, a mechanical thermal coupling model of the bearing rotor system of high-speed trains is established to study the interaction between the bearing vibration and temperature. The influence of lubrication on the vibration and temperature characteristics of the system is considered in the model, and the real-time relationship between them is built up by using the transient temperature field model. After considering the lubrication, the bearing outer ring vibration acceleration and node temperature considering grease are lower, which shows the necessity of adding the lubrication model. The corresponding experiments for characteristics of vibration and temperature of the model are respectively conducted. In the envelope spectrum obtained from the simulation signal and the experimental signal, the frequency values corresponding to the peaks are close to the theoretical calculation results, and the error is very small. In the three stages of the temperature characteristic experiment, the node temperature change of the simulation model is consistent with the experiment. The good agreement between simulation and experiments proves the effectiveness of the model. By studying the influence of the bearing angular and fault size on the system node temperature, as well as the change law of bearing lubrication characteristics and temperature, it is found that the worse the working condition is, the higher the temperature is. When the ambient temperature is low, the viscosity of grease increases, and the oil film becomes thicker, which increases the sliding probability of the rolling element, thus affecting the normal operation of the bearing, which explains the phenomenon of frequent bearing faults of high-speed trains in the low-temperature area of Northeast China. Further analysis shows that faults often occur in the early stage of train operation in the low-temperature environment. [ABSTRACT FROM AUTHOR]

The rolling bearing is one of the important parts of rotating machinery, while the degree of dependence on the machine is becoming heavier nowadays. Therefore, it is always necessary to monitor its operating status and diagnose faults. To better analyze the bearing vibration signal from the time domain and frequency domain and reduce information loss, we propose a model that decomposes the original bearing vibration signal with a length of 1024 by a two-layer wavelet packet. For the analysis, four low-frequency and high-frequency feature vectors of a length of 1024 are obtained as the input for the analysis model. The proposed model uses frequency subbands to automatically extract features from network input and then fuse the features. The accuracy of the model on a single load on the Case Western Reserve University (CWRU) dataset is 98−100%, which shows the diagnostic effect is satisfactory. [ABSTRACT FROM AUTHOR]

In the present work, an exact analytical solution is presented to investigate the frequency response and stability of a very complex asymmetric rotor-disk-bearing system considering the shear deformation and rotary inertia despite the unbalance. The system consists of eighteen disks, a rotor, and three bearings, and all components of the system are considered elastic. Also, disks are modeled as Timoshenko beam elements and in fact, their bending flexibility is considered. But, because of their high ratios of diameter to length of them, they are practically rigid in the presented model. Here the bearings are modeled with springs and dampers. In other words, the rotor-disk system is assumed to be on oil-lubricated bearings as viscoelastic supports. Timoshenko's beam theory based on the Hamiltonian principle is used to derive governing equations of the problem. Then, to confirm the equations, the results were compared with those obtained by other researchers, and a good agreement was found. The natural frequencies of the rotor-disk-bearing system were also obtained in the free vibration case and the orbit shapes were then plotted according to each frequency. Finally, the influences of different parameters including bearing stiffness and damping, internal damping of structure, mass unbalance for forced vibration case on displacement amplitude and rotation were analyzed. [ABSTRACT FROM AUTHOR]

Copyright of Bearing is the property of Bearing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, a dual membrane restrictor design was proposed to improve the stiffness performance of the compensated hydrostatic bearing. Theoretical models for the proposed dual membrane restrictors were derived. Analysis of these models showed that a high stiffness region could be achieved at the desired loading region through the proper selection of the design parameters. A series of simulations were conducted to study the variations in the design parameters on the stiffness and clearance variations. It was found that the dimensionless membrane stiffness in the inlet restrictor, K m i * , was the most dominant parameter for the performance of the compensated bearing system. The main advantages of the proposed dual membrane restrictor are the increase in flexibility by providing high stiffness at the desired loading region; and improving the stiffness performance of the bearing system especially at the desired loading region. [ABSTRACT FROM AUTHOR]

Detecting motor bearing faults by stator currents is of great importance as it improves the adaptability of measurement means to different environments and reduces the number of sensors. Therefore, many studies have been conducted to investigate bearing faults by constructing motor models, most of which have used signal models to simulate the dynamics of the bearings. However, the signal model may be exposed to the issue that the nonlinearities in the bearing operation are neglected, thus oversimplifying the coupling effects between the electromagnetic and dynamics models. Hence, a coupled electromagnetic–dynamic modeling method for induction motors based on multiple coupled circuit theory and the rotor-bearing dynamics model is proposed in this study to implement the coupled simulation of electromagnetic and dynamic models. The air gap length and rotor velocity are used as coupled parameters for the calculation of stator–rotor mutual inductance and ball contact deformation, respectively. The simulation results show that the proposed model can effectively implement the electromagnetic–dynamic coupled and reflect the bearing fault characteristics in the current signal. Experiments were conducted on induction motors with typical winding configurations under laboratory conditions. The comparison results verify the effectiveness of the proposed modeling method. [ABSTRACT FROM AUTHOR]

A turbo compressor was investigated to ensure the operational reliability of the charging of fuel cell systems. This study investigated air-lubricated herringbone bearings to support the high-speed rotating shaft. For reliable operation of the rotor bearing system, stable operation in the whole speed range (up to 120 krpm), as well as low lift-off speed, is an important issue. Some publications containing guidelines for an optimized design in terms of stability and lift-off behavior date back to the 1970s, with some simplifying assumptions (such as narrow groove theory and small eccentricity analysis). Many publications have addressed the calculations, as well as the optimization of herringbone-grooved bearings; however, general design guidelines are still missing in the view of the authors. Although the investigations related to bearings for the support of a lightweight rotor for a special compressor of a fuel cell unit, this study could also indicate favorable bearing designs for other high-speed applications. Here, the compressible Reynolds equation was solved in the whole solution domain using a conservative finite difference scheme, and the corresponding bearing characteristics were determined. In a perturbation analysis, the linearized dynamic coefficients of the herringbone bearing are calculated. To compare the suitability and performance of the various herringbone-grooved bearing designs, especially at high speed, the simple model of a Jeffcott rotor airborne with two identical herringbone-grooved journal bearings (HGJBs) was used. The geometrical parameters of the HGJBs were varied, and their effects on bearing characteristics and stability were evaluated. Recommendations concerning favorable geometrical bearing parameters for a sufficiently high stability threshold speed and reasonable low lift-off speed were the result of the parameter study. [ABSTRACT FROM AUTHOR]

Rotor parts have been the central components of "intelligent emergency water supply and water purification integrated equipment in mountainous areas and remote disaster areas". However, various failure modes can inevitably occur, due to high-speed and heavy-duty conditions for a long time in the field. The fault characteristic frequency is also easily submerged by the strong noise, depending mainly on the inner structure of the equipment. There is a high similarity in the fault vibration signals of rotor parts, such as impeller, bearing, and gear. The existing fault identification cannot quickly and accurately detect the fault mode. In this study, an improved adaptive fault identification model was proposed to realize the intelligent fault diagnosis of multi-stage high-pressure lift pumps using a one-dimensional convolutional neural network and long-term memory network (CNN-LSTM). In the CNN network, the last set of convolutional layers used for the feature extraction was then connected to the global mean pooling layer, in order to reduce the number of model parameters and integrate feature information. Relu activation function was then selected for the gradient disappearance, compared with the Sigmoid function. As such, the activation function of the pooling layer was changed to the Relu function in the CNN network. After that, the LSTM time series network was embedded to integrate the one-dimensional CNN and LSTM into a framework structure. Finally, the Softmax function was used as the classification output of the network model. The fault identification was as follows. First, the vibration signal was collected to preliminarily de-noise through CEEMD, where the de-noised data was divided into time series of equal length. Then, the data set was divided into the training, test, and validation set. Secondly, the optimal initial parameters of the model were obtained by Bayesian optimization. The model parameters were also fine-tuned layer by layer using back propagation. The model performance was evaluated by the validation set. Third, the test set was input into the trained model to calculate the evaluation index. The fault identification experiment of multistage high-pressure pumps was carried out to verify the improved fault identification model. Four typical faults were selected to identify: spalling of rotor bearing outer ring, fracture of bearing inner ring, blockage of the impeller, and broken tooth of the gear. The analysis results show that the improved model performed better to separate fault modes, thereby realizing the accurate identification of the health status of multistage high-pressure pumps. The identification accuracy of the improved model for the four fault modes was close to 100%, indicating higher accuracy of identification and feasibility. An adaptive intelligent fault identification model was fully utilized for the multistage high-pressure water pump. Two neural networks were integrated to adaptively extract the features from the time series data and fault sample information, where the 1D-CNN output was used as the LSTM input. There was no need the feature extraction using prior knowledge. The interference of inappropriate features was also reduced for end-to-end fault identification and classification. Consequently, the superior overall performance was achieved in the improved model, where the structure was much simpler, the iteration was faster, better generalization ability, the higher resistance to the noise. High accuracy was reached more than 97%. Anyway, the improved model can be expected to serve as the fault identification network for the multistage high-pressure numerical key fault of rotor bearings, wheels, and gears. [ABSTRACT FROM AUTHOR]

The aim of this paper is to gain insight into the nonlinear vibration feature of a dynamic model of a gas turbine. First, a rod fastening rotor-bearing coupling model with fixed-point rubbing is proposed, where the fractal theory and the finite element method are utilized. For contact analysis, a novel contact force model is introduced in this paper. Meanwhile, the Coulomb model is adopted to expound the friction characteristics. Second, the governing equations of motion of the rotor system are numerically solved, and the nonlinear dynamic characteristics are analyzed in terms of the bifurcation diagram, Poincaré map, and time history. Third, the potential effects provided by contact degree of joint interface, distribution position, and amount of contact layer are discussed in detail. Finally, the contrast analysis between the integral rotor and the rod fastening rotor is conducted under the condition of fixed-point rubbing. [ABSTRACT FROM AUTHOR]

Conveyor belts are used in many industries, from food to mining and power generation. These conveyors consist of many subsystems, and these systems, like any mechanical system, are prone to failure. The failure of these systems can cause the conveyor to be stopped and repaired, and during this downtime, production is lost. Thermal cameras are the most using method to diagnose the faults in bearing that produce the heating than the healthy bearing. Acoustic gear and accelerometer are used to capture the idler sound and vibration to detect the current health of the idler. But, these diagnosis methods need an engineering presence near the belt and monitoring purposes. However, these sensors can be monitored by only a few idlers nearby, and the installation cost of these makes the monitoring system infeasible. A predictive maintenance framework and mathematical modelling of a belt conveyor have been proposed to identify the faults before the severe damage of the belt. The experimental results showed that the in-belt monitor could identify a faulty bearing even before failure occurred. This allows all the defective bearings to be identified and the needed stock can be purchased ahead of a planned outage, and all the faulty bearings can be replaced. One large, scheduled outage can be organized to replace all defective bearings and bearings showing signs of failure soon, reducing the number of short power failures that punctuate the conveyor feed. This form of monitoring is insufficient for estimating the remaining service life of the faulty bearings. [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]

A new in-situ rotary magnetorheological honing (RMRH) approach has been developed in this study to fine-finish the machined inner surface of cylindric workpieces with increased productivity and dimensional accuracy. A single in-situ honing tool is used for performing both traditional as well as magnetorheological (MR) honing. The tool is fabricated based on the designed tool through magnetostatic analysis. In this work, the final MR finished surface is achieved up to 60 nm from the original machined surface roughness of 510 nm with the expense of 40 min of traditional honing and 60 min of MR finishing. Also, the great improvement in surface waviness is confirmed through the final surface waviness is achieved as 50 nm from the initial surface waviness of 1460 nm. The improvement in circularity is confirmed through the circularity test performed in this work. The improvement in surface texture has been analyzed through the scanning electron microscope images. As a result of the finishing capability of the currently designed in-situ tool, it is useful in a variety of industrial applications such as oil pipes, bearings, hydraulic cylinders, cylindrical molds, cylindrical barrels of injection molding machines, compressor bodies, valve bodies, etc. [ABSTRACT FROM AUTHOR]

The successful applications of deep transfer learning to intelligent fault diagnosis testify to a positive correlation between transferable feature similarity and knowledge transferability across diagnostic tasks. This correlation makes feature similarity possible to assess diagnostic knowledge transferability. Therefore, researchers have attempted various measures for feature similarity, and distance metrics have been adopted as an objective measure for feature distribution discrepancy. However, the commonly used distance metrics cannot address the joint distribution discrepancy (JDD) due to the difficulty in fitting conditional distributions of target domain samples. To overcome the problem, we resort to explore cluster-conditional distributions instead and propose an optimal transport-embedded joint distribution similarity measure (OT-JDSM) that is implemented in two steps. First, a cluster-true label propagation spreads labels from a small number of labeled target domain samples to the whole. Second, the JDD of transferable features is produced via an efficient solution of optimal transport. OT-JDSM is demonstrated on synthetic examples and 144 transfer diagnosis tasks that are created by public and private bearing datasets. The results show that OT-JDSM of transferable features has a stronger correlation with diagnostic knowledge transferability than other distance metrics. Moreover, the OT-JDSM gain can quantify the transfer performance of diagnostic models on tasks. [ABSTRACT FROM AUTHOR]

Bearings and cylindrical roller bearings to be specific have found application in rotating machinery due to their high load-bearing ability. The dynamic performance of the bearing is greatly influenced by the contact stress, displacement, stiffness and temperature developed during service. Hence, this study employs finite element analysis software, Abaqus to determine the thermo-mechanical behaviour of a typical healthy cylindrical roller bearing of a power generation airflow root blower subjected to a dynamic load of 160 kN at 2850 r/min (300 rad/s). The contour plots and results obtained from the analysis show that the maximum temperature developed in the bearing during operation is 118.5 °C and the maximum contact stress of 896.6 MPa was developed on the outer ring, at the point of contact between the balls and the outer ring, thus making the outer ring more prone to failure as compared to the other components of the bearing during operation. [ABSTRACT FROM AUTHOR]

Ultrahigh molecular weight polyethene (UHMWPE) is employed as a bearing material in a range of applications due to its improved elasticity, compatibility, and impact resistance, processing conditions for a suitable surface texture are necessary. Surface texture processing on microchannels using lasers is always associated with the effect of heat damage on the polymer specimen surface. This study aims to explore the use of polydimethylsiloxane (PDMS) and polyacrylic acid (PAA) in the form of liquid gel coatings in order to reduce heat damage to surfaces during the laser processing of ultrahigh molecular weight polyethene (UHMWPE). First, PDMS and PAA were coated on the surface of the UHMWPE material specimen, and then texturing was performed using a laser diode and cleaned using the ultrasonic method. Second, the dimensions and texture profiles of all the samples from this study were measured using a confocal microscope and open source software. In addition, the effect of adding liquid gel on the surface at 150 µm thickness and laser power parameters was determined. The results show that the PDMS and PAA liquid gel layers help regulate the dimensional bulge of the fabricated microchannels at laser powers below 6 watts, compared to those produced without the coating. [ABSTRACT FROM AUTHOR]

Copyright of Bearing is the property of Bearing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Machine accuracy of workpiece is dependent on a number of factors including the machine spindle nose position. Recently, the application of thermal phenomenon especially in electrospindle has been of great interest. Thermal displacement of the spindle nose affects the accuracy of machining and it also depends largely on the amount of power loss in the bearings. This paper presents the angular contact bearing model which takes into account the stiffness of spring stacking. The result show what effect does the stiffness of the spring stacking have on axial force, contact forces and displacements of angular contact bearing. Moreover, omission in the analysis of the stiffness of the spring stacking result in errors in the estimation of the position on the spindle nose due to the deformation of the elastic spring. [ABSTRACT FROM AUTHOR]

More layers in a convolution neural network (CNN) means more computational burden and longer training time, resulting in poor performance of pattern recognition. In this work, a simplified global information fusion convolution neural network (SGIF-CNN) is proposed to improve computational efficiency and diagnostic accuracy. In the improved CNN architecture, the feature maps of all the convolutional and pooling layers are globally convoluted into a corresponding one-dimensional feature sequence, and then all the feature sequences are concatenated into the fully connected layer. On this basis, this paper further proposes a novel fault diagnosis method for a rotor–journal bearing system based on SGIF-CNN. Firstly, the time-frequency distributions of samples are obtained using the Adaptive Optimal-Kernel Time–Frequency Representation algorithm (AOK-TFR). Secondly, the time–frequency diagrams of the training samples are utilized to train the SGIF-CNN model using a shallow information fusion method, and the trained SGIF-CNN model can be tested using the time–frequency diagrams of the testing samples. Finally, the trained SGIF-CNN model is transplanted to the equipment's online monitoring system to monitor the equipment's operating conditions in real time. The proposed method is verified using the data from a rotor test rig and an ultra-scale air separator, and the analysis results show that the proposed SGIF-CNN improves the computing efficiency compared to the traditional CNN while ensuring the accuracy of the fault diagnosis. [ABSTRACT FROM AUTHOR]

This paper is the second in a two-part study on lubrication in wind turbine main bearings. Where Part 1 provided an introductory review of elastohydrodynamic lubrication theory, this paper will apply those ideas to investigate lubrication in the double-row spherical roller main bearing of a 1.5MW wind turbine. Lubrication is investigated across a "contact conditions dataset" generated by inputting main-bearing applied loads, estimated from hub loads generated using aeroelastic simulation software, into a Hertzian contact model of the main bearing. From the Hertzian model is extracted values of roller load and contact patch dimensions, along with the time rate of change of contact patch dimensions. Also included in the dataset are additional environmental and operational variable values (e.g. wind speeds and shaft rotational speeds). A suitable formula for estimating film thickness within this particular bearing is then identified. Using lubricant properties of a commercially available wind turbine grease, specifically marketed for use in main bearings, an analysis of film thickness across the generated dataset is undertaken. The analysis includes consideration of effects relating to temperature, starvation, grease thickener interactions and possible non-steady effects. Results show that the studied main bearing is at risk of operating under mixed lubrication conditions for a non-negligible proportion of its operational life, indicating that further work is required to better understand lubrication in this context and implications for main-bearing damage and operational lifetimes. Key sensitivities and uncertainties within the analysis are discussed, along with recommendations for future work. [ABSTRACT FROM AUTHOR]

Bearings are important components of most machinery and their working conditions influence the operation of the entire machinery. Even if bearings are being used under excellent conditions, sooner or later material fatigue will occur. Besides other things poor operating environment contaminated or peculiarly moist areas and improper handling practices cause premature failures. This article focuses on vibration analysis methods for detecting bearing failures and presents a special lifetime test procedure. [ABSTRACT FROM AUTHOR]

In the coupling state of rotor unbalance fault and bearing defect fault for rotor system, the signals contain multiple fault components, and the fault diagnosis of the rotor system needs to contain comprehensive multidimensional feature quantities. However, irrelevant feature information in the multi-dimensional feature quantities increases the complexity of classification calculation and affects the efficiency and accuracy of diagnosis. In order to eliminate redundant and irrelevant features in the feature information, and achieve the goal of fewer diagnostic features and good diagnostic results, this paper proposes an adaptive feature selection based on the maximum information coefficient FF-FC-MIC (Feature-to-Feature and Feature-to-Category Maximum Information Coefficient) method. Firstly, the sparse representation algorithm is used to reconstruct the original signal to improve the signal-to-noise ratio, and the multi-dimensional feature quantity of the reconstructed signal is calculated; Secondly, calculate the correlation between features and features through MIC to obtain a feature set of weak correlation between features; thirdly, use MIC to calculate the correlation between features and signal categories to obtain a feature set with strong correlation between features and signals; Finally, the FF-FC-MIC feature selection method is used for feature adaptive selection and input into SVM to complete fault diagnosis. The method is analyzed by simulation signals and the real experiment signals. The results show that the method can effectively remove redundant and disclosed features in the coupling fault, reducing the characteristic dimension to reduce the fault classification time, and improve classification accuracy. Different experimental cases and various feature selection comparison methods further verify the accuracy and applicability of the proposed method. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to reveal the influence of dimples on the tribological properties of the "washers-cage-rollers" system of rolling element bearing (REB) under starved lubrication. Design/methodology/approach: A fiber laser marking system was used to prepare dimples patterns on the raceways of the shaft washers of cylindrical roller thrust bearings (CRTBs). The friction and wear properties of dimples textured CRTBs with different diameter of dimples (200 µm, 250 µm, 300 µm) and depth of dimples (4 µm, 8 µm, 12 µm) were researched through a vertical universal wear test rig using a customized tribo-pair under starved lubrication. The surface stresses and the influence mechanism of dimple units on the tribological behavior of REBs were also compared and discussed. Findings: Although the surface stresses on the raceways of dimples textured bearings are significantly higher than that of the smooth group, the coefficients of friction and wear losses of them are all reduced under starved lubrication. When the effective volume of dimples is between 1.13 and 2.25 and the depth of dimples is smaller than 12 µm, the tribological properties of dimples textured CRTBs are significantly improved. In this work, when the diameter of dimples is 250 µm, and the depth of dimples is 8 µm, the textured bearings can provide the excellent friction-reduction ability and outstanding wear resistance. Originality/value: This work is a valuable reference for the raceway design and optimization of REBs. [ABSTRACT FROM AUTHOR]

Dynamic characteristics of the asymmetric rotor system supported in axial-grooved gas-lubricated bearings are studied. In order to solve nonlinear dynamic response of rotor system effectively, a hybrid numerical model is established by coupling the motion equation of rotor with the rational function model of the gas film forces. The rational function model of the gas film forces of gas-lubricated bearing is established based on vector fitting theory. By using the hybrid numerical model, the repeated calculations of the unsteady Reynolds equation and gas film forces are avoided; the continuous rotor trajectory and the dynamic gas film forces can be calculated simultaneously; and for the rotor system supported in the same bearings, the computing cost can be saved effectively. The nonlinear dynamic responses of asymmetric rotor system supported in axial-grooved gas-lubricated bearings are investigated by trajectory diagrams, frequency spectrum, Poincaré maps, and time series. The bifurcations are analyzed by the bifurcation diagrams with different rotating speeds and mass eccentricities. The dynamic behaviors of the asymmetric rotor system appear complex nonlinear dynamic phenomenon and specific bifurcation characteristics. [ABSTRACT FROM AUTHOR]

A great percentage of breakdowns in the rotary machines are caused by faulty gears and bearings generating high costly downtime. The diagnosis of gears and bearings combined faults using conventional frequency methods is difficult because of the presence of a high level of noise in the signal or a disturbance emanating from other sources in/out of the machine. This manuscript develops an improved approach for gears and bearings simple/combined faults automated diagnosis using an optimized wavelet packet transform (OWPT), for signal denoising and fault features extraction, combined with pattern recognition neural networks (PRNN) for fault classification. We applied this improved approach on acceleration signals acquired from a test rig simulating an industrial rotary machine; then, these acquired signals were processed using OWPT, based on the best choice of the wavelet packet and the level of decomposition using minimum Shannon entropy and maximum energy to Shannon entropy ratio criteria. The results gave us the bi-orthogonal 3.1 (bior3.1) as the best mother wavelet among 41 wavelet families being tested and the 6th level as the best decomposition level. These two found parameters are used for the extraction of time-domain features, which are used as input data to train neural networks after data normalization. The results showed that the proposed method could detect any type (simple/combined) and size (small "incipient," mean and large) of gears and bearig faults in non-stationary operations with the presence of high noise. In addition, the automation of the classification process could be generalized to any kind of faults in the machine such as misalignment, electrical faults, and rotor damage. [ABSTRACT FROM AUTHOR]

Torpedo anchors (TAs) are regarded as one of the most efficient mooring solutions for taut mooring systems, and end-bearing TAs are a new type of TA that primarily relies on end-bearing plates at the tail to generate a pile-end resistance to improve their pulloutbearing capacity (P). Therefore, the estimation of the pullout capacity of the end-bearing TA is vital for the design of offshore floating facilities. In this study, pullout model tests were conducted to investigate the P of conventional and end-bearing TAs and examine the effects of factors such as the embedment depth (h), the relative density (Dr), the pullout angle (α), and the area (A) of the bearing plates on P. The test results show that, under oblique pullout loading, the P on the conventional TA increased slowly as displacement increased, while there was a peak on the load–displacement curve of each end-bearing TA with a relatively large A. The end-bearing TAs considerably outperformed the conventional TAs in terms of the P. In addition, increasing h, Dr, and A significantly increased the P of the end-bearing TAs. However, increasing h and Dr slightly decreased the ability of the bearing plates to increase the P of the end-bearing TAs. These research results can provide a guideline for TA installation in deep-sea engineering. [ABSTRACT FROM AUTHOR]

Featured Application: The current work is suitable for diagnosing induction motor failures online. It is highly applicable to bearing fault diagnosis and may be useful for industries. The demand for the condition monitoring of induction motors is increasing in various fields, such as industry, transportation, and daily life. Bearing faults are the most common faults, and many fault diagnosis methods have been proposed using artificial pitting as the fault factor in most cases. However, the validity of a fault diagnosis method for other kinds of faults does not seem to be evaluated. Considering onsite scenarios and other possibilities of faults, this paper introduces scratches on the outer raceways of bearings. A study was performed on the detection of several kinds of bearing scratches using a proposed method that was based on an auto-tuning convolutional neural network. The developed approach was also compared with other diagnostic methods for validation. The results showed that the proposed technique provides the possibility of diagnosing several kinds of scratches with acceptable accuracy rates. [ABSTRACT FROM AUTHOR]