Showing papers on "Bearing (mechanical) published in 2014"

Motor Bearing Fault Diagnosis Using Trace Ratio Linear Discriminant Analysis

Abstract: Bearings are critical components in induction motors and brushless direct current motors. Bearing failure is the most common failure mode in these motors. By implementing health monitoring and fault diagnosis of bearings, unscheduled maintenance and economic losses caused by bearing failures can be avoided. This paper introduces trace ratio linear discriminant analysis (TR-LDA) to deal with high-dimensional non-Gaussian fault data for dimension reduction and fault classification. Motor bearing data with single-point faults and generalized-roughness faults are used to validate the effectiveness of the proposed method for fault diagnosis. Comparisons with other conventional methods, such as principal component analysis, local preserving projection, canonical correction analysis, maximum margin criterion, LDA, and marginal Fisher analysis, show the superiority of TR-LDA in fault diagnosis.

Localization and Circumnavigation of a Slowly Moving Target Using Bearing Measurements

Abstract: The problem of localization and circumnavigation of a slowly moving target with unknown speed has been considered. The agent only knows its own position with respect to its initial frame, and the bearing angle to the target in that frame. We propose an estimator to localize the target and a control law that forces the agent to move on a circular trajectory around the target such that both the estimator and the control system are exponentially stable. We consider two different cases where the agent's speed is constant and variable. The performance of the proposed algorithm is verified through simulations.

An advanced numerical model of elastomeric seismic isolation bearings

Abstract: SUMMARY The nuclear accident at Fukushima Daiichi in March 2011 has led the nuclear community to consider seismic isolation for new large light water and small modular reactors to withstand the effects of beyond design basis loadings, including extreme earthquakes. The United States Nuclear Regulatory Commission is sponsoring a research project that will quantify the response of low damping rubber (LDR) and lead rubber (LR) bearings under loadings associated with extreme earthquakes. Under design basis loadings, the response of an elastomeric bearing is not expected to deviate from well-established numerical models, and bearings are not expected to experience net tension. However, under extended or beyond design basis shaking, elastomer shear strains may exceed 300% in regions of high seismic hazard, bearings may experience net tension, the compression and tension stiffness will be affected by isolator lateral displacement, and the properties of the lead core in LR bearings will degrade in the short-term because of substantial energy dissipation. New mathematical models of LDR and LR bearings are presented for the analysis of base isolated structures under design and beyond design basis shaking, explicitly considering both the effects of lateral displacement and cyclic vertical and horizontal loading. These mathematical models extend the available formulations in shear and compression. Phenomenological models are presented to describe the behavior of elastomeric isolation bearings in tension, including the cavitation and post-cavitation behavior. The elastic mechanical properties make use of the two-spring model. Strength degradation of LR bearing under cyclic shear loading due to heating of lead core is incorporated. The bilinear area reduction method is used to include variation of critical buckling load capacity with lateral displacement. The numerical models are coded in OpenSees, and the results of numerical analysis are compared with test data. The effect of different parameters on the response is investigated through a series of analyses. Copyright © 2014 John Wiley & Sons, Ltd.

Bi-spectrum based-EMD applied to the non-stationary vibration signals for bearing faults diagnosis

Abstract: Empirical mode decomposition (EMD) has been widely applied to analyze vibration signals behavior for bearing failures detection. Vibration signals are almost always non-stationary since bearings are inherently dynamic (e.g., speed and load condition change over time). By using EMD, the complicated non-stationary vibration signal is decomposed into a number of stationary intrinsic mode functions (IMFs) based on the local characteristic time scale of the signal. Bi-spectrum, a third-order statistic, helps to identify phase coupling effects, the bi-spectrum is theoretically zero for Gaussian noise and it is flat for non-Gaussian white noise, consequently the bi-spectrum analysis is insensitive to random noise, which are useful for detecting faults in induction machines. Utilizing the advantages of EMD and bi-spectrum, this article proposes a joint method for detecting such faults, called bi-spectrum based EMD (BSEMD). First, original vibration signals collected from accelerometers are decomposed by EMD and a set of IMFs is produced. Then, the IMF signals are analyzed via bi-spectrum to detect outer race bearing defects. The procedure is illustrated with the experimental bearing vibration data. The experimental results show that BSEMD techniques can effectively diagnosis bearing failures.

Dynamic Modeling and Vibration Response Simulation for High Speed Rolling Ball Bearings With Localized Surface Defects in Raceways

Abstract: A dynamic model is developed to investigate vibrations of high speed rolling ball bearings with localized surface defects on raceways. In this model, each bearing component (i.e., inner raceway, outer raceway and rolling ball) has six degrees of freedom (DOFs) to completely describe its dynamic characteristics in three-dimensional space. Gyroscopic moment, centrifugal force, lubrication traction/slip between bearing component are included owing to high speed effects. Moreover, local defects are modeled accurately and completely with consideration of additional deflection due to material absence, changes of Hertzian contact coefficient and changes of contact force directions due to raceway curvature variations. The obtained equations of motion are solved numerically using the fourth order Runge–Kutta–Fehlberg scheme with step-changing criterion. Vibration responses of a defective bearing with localized surface defects are simulated and analyzed in both time domain and frequency domain, and the effectiveness of fault feature extraction techniques is also discussed. An experiment is carried out on an aerospace bearing test rig. By comparing the simulation results with experiments, it is confirmed that the proposed model is capable of predicting vibration responses of defective high speed rolling ball bearings effectively.

High-Frequency Induction Machine Modeling for Common Mode Current and Bearing Voltage Calculation

Abstract: In this paper, several inverter-fed induction machines with rated powers between 1.5 and 240 kW are modeled for calculating the common mode (CM) stator ground current and the capacitive bearing voltage. Simple methods to extract the parameters of the high-frequency machine model from the measured CM and differential mode impedances are presented. Furthermore, the most significant parameters are given for five different machine sizes between 1.5 and 240 kW rated power. Calculation examples are provided in comparison to the experimental results.

User's Manual for the Hydrate v1.5 Option of TOUGH+ v1.5: A Code for the Simulation of System Behavior in Hydrate-Bearing Geologic Media

Abstract: HYDRATE v1.5 is a numerical code that for the simulation of the behavior of hydrate-bearing geologic systems, and represents the third update of the code since its first release [Moridis et al., 2008]. It is an option of TOUGH+ v1.5 [Moridis, 2014], a successor to the TOUGH2 [Pruess et al., 1999] family of codes for multi-component, multiphase fluid and heat flow developed at the Lawrence Berkeley National Laboratory. HYDRATE v1.5 needs the TOUGH+ v1.5 core code in order to compile and execute. It is written in standard FORTRAN 95/2003, and can be run on any computational platform (workstation, PC, Macintosh) for which such compilers are available. By solving the coupled equations of mass and heat balance, the fully operational TOUGH+HYDRATE code can model the non-isothermal gas release, phase behavior and flow of fluids and heat under conditions typical of common natural CH4-hydrate deposits (i.e., in the permafrost and in deep ocean sediments) in complex geological media at any scale (from laboratory to reservoir) at which Darcy’s law is valid. TOUGH+HYDRATE v1.5 includes both an equilibrium and a kinetic model of hydrate formation and dissociation. The model accounts for heat and up to four mass components, i.e., water, CH4, hydrate, and water-soluble inhibitors such as salts or alcohols. These are partitioned among four possible phases (gas phase, liquid phase, ice phase and hydrate phase). Hydrate dissociation or formation, phase changes and the corresponding thermal effects are fully described, as are the effects of inhibitors. The model can describe all possible hydrate dissociation mechanisms, i.e., depressurization, thermal stimulation, salting-out effects and inhibitor-induced effects.

Fault diagnosis of rolling element bearing by using multinomial logistic regression and wavelet packet transform

Abstract: This paper is focused on comparison of effectiveness of artificial intelligence (AI) techniques in fault diagnosis of rolling element bearings. The features for classification are extracted through wavelet packet decomposition using RBIO 5.5 wavelet. The whole classification is done using two features: energy and Kurtosis. The data samples for classification are taken with reference to a healthy bearing, thus, minimizing the errors from the experimental set-up. Four bearing conditions such as bearing with outer race defect, inner race defect, ball defect and combined defect on outer race, inner race and ball have been used in this paper. Localized defects of micron level are induced through laser machining. The effectiveness of three AI techniques viz. ANN, SVM and multinomial logistic regression are compared. The results show that the Logistic Regression technique is the more effective than other two techniques as ANN and SVM.

Integration of EEMD and ICA for wind turbine gearbox diagnosis

Abstract: Gearbox failure becomes a major concern for reliability of wind turbine because of complex repair procedures, long downtime and high replacement costs. Prior studies showed that the majority of gearbox failures were initiated from bearing failures. Because of the low signal-to-noise ratio (mixture of bearing defect signals and gear meshing signals) and transient nature of bearing signals, it poses significant difficulty for bearing defect diagnosis in wind turbine gearbox at the incipient stage. To address it, this paper presents an effective fault component separation method that integrates ensemble empirical mode decomposition (EEMD; an adaptive signal decomposition method in time-frequency domain) with independent component analysis (ICA; a blind source separation technique), without requiring a priori information on the rotating speeds or bandwidth. The method firstly decomposes one-channel vibration measurements into a series of intrinsic mode functions as pseudo-multi-channel signals, by means of EEMD. ICA is performed on the intrinsic mode functions to separate bearing defect-related signals from gear meshing signals. Envelope spectrum analysis is performed on the bearing defect-related signals to identify bearing structural defects. The effectiveness of the developed method in separating bearing defect-related signals from gear meshing signals for more effective fault diagnosis in bearings is evaluated and confirmed, numerically and experimentally. Copyright © 2013 John Wiley & Sons, Ltd.

Fault diagnosis of rolling element bearings via discriminative subspace learning

Abstract: The trace ratio criterion based LDA method is utilized for fault diagnosis of rolling element bearingsTR-LDA is also extended to handle the nonlinear datasets confronted in real-world fault diagnosisWe evaluate the proposed method by visualizing and classifying the rolling element bearing fault dataSimulations results show the superiority of the method in fault diagnosis of rolling element bearings Rolling element bearings play an important role in ensuring the availability of industrial machines Unexpected bearing failures in such machines during field operation can lead to machine breakdown, which may have some pretty severe implications To address such concern, we extend our algorithm for solving trace ratio problem in linear discriminant analysis to diagnose faulty bearings in this paper Our algorithm is validated by comparison with other state-of art methods based on a UCI data set, and then be extended to rolling element bearing data Through the construction of feature data set from sensor-based vibration signals of bearing, the fault diagnosis problem is solved as a pattern classification and recognition way The two-dimensional visualization and classification accuracy of bearing data show that our algorithm is able to recognize different bearing fault categories effectively Thus, it can be considered as a promising method for fault diagnosis

Comparative analysis of textured and grooved hydrodynamic journal bearing

Abstract: Research is being focused on to find the influence of surface variations such as texturing or grooving on the bearing performances. Though, earlier it was restricted to the theoretical aspects alone, however, with the help of advance manufacturing techniques (laser surface texturing, etching, special grinding process, etc.), it has become possible to produce micro-textures or grooves on the surface of journal bearing. The objective of the present study is to numerically compare the influence of spherical texture and micro-grooving (longitudinal and transverse) on friction coefficient and average temperature of journal bearing at low and high eccentricity ratios. From the findings, it has been observed that the micro-grooving reduces the friction coefficient and average temperature is maximum in comparison with spherical texture.

Analysis and Design of a 300-W 500 000-r/min Slotless Self-Bearing Permanent-Magnet Motor

Abstract: Active magnetic bearings enable contactless operation and can therefore be used for supporting rotors spinning at high speeds. However, the rotational speed in conventional reluctance-force-based magnetic bearing topologies is limited, which is mainly due to high rotor losses and limited force control bandwidths. In this paper, a prototype of a self-bearing motor is presented, which overcomes several limitations of state-of-the-art high-speed magnetically levitated electric drive systems. Due to the employed magnetic bearing, the motor can be operated in high-purity or vacuum environments. An analytical mechanical and electrical bearing model is introduced and verified by measurements. Furthermore, a bearing inverter system is designed, and its controller performance is shown. Measurements of spinning levitated rotors up to speeds of 505 000 r/min verify the functionality of the overall system. To the authors' knowledge, this is the highest speed achieved by magnetically levitated electrical drive systems so far.

Numerical Assessment of Frictional Heating in Sliding Bearings for Seismic Isolation

Abstract: This article proposes a numerical investigation of the frictional heating developed in sliding bearings under high velocities and the influence of the relevant temperature rise on the mechanical characteristics of the device. A three-dimensional finite element model of the bearing is created and frictional heat generation is modelled through a thermal source inserted at the sliding surface of the bearing, with intensity dependent on the coefficient of friction, the contact pressure and the velocity. The friction value is adjusted step-by-step on surface temperature and velocity and used to update the thermal flux and the resisting force developed by the bearing. The numerical predictions of temperature histories and force–displacement loops are compared with the results of laboratory tests to validate the numerical approach. The procedure can help in preliminary studies for the selection of bearing materials accounting for their thermal stability and for the estimation of change of design properties of sl...

White-Etching Matter in Bearing Steel. Part II: Distinguishing Cause and Effect in Bearing Steel Failure

Abstract: The premature failure of large bearings of the type used in wind turbines, possibly through a mechanism called “white-structure flaking”, has triggered many studies of microstructural damage associated with “white-etching areas” created during rolling contact fatigue, although whether they are symptoms or causes of failure is less clear. Therefore, some special experiments have been conducted to prove that white-etching areas are the consequence, and not the cause, of damage. By artificially introducing a fine dispersion of microcracks in the steel through heat treatment and then subjecting the sample to rolling contact fatigue, manifestations of hard white-etching matter have been created to a much greater extent than samples similarly tested without initial cracks. A wide variety of characterization tools has been used to corroborate that the white areas thus created have the same properties as reported observations on real bearings. Evidence suggests that the formation mechanism of the white-etching regions involves the rubbing and beating of the free surfaces of cracks, debonded inclusions, and voids under repeated rolling contact. It follows that the focus in avoiding early failure should be in enhancing the toughness of the bearing steel in order to avoid the initial microscopic feature event.