Ball Race Research Articles

Investigating the Effect of Vibration Signal Length on Bearing Fault Classification Using Wavelet Scattering Transform

Bearing condition monitoring and prognosis are crucial tasks for ensuring the proper operation of rotating machinery and mechanical systems. Vibration signal analysis is one of the most effective techniques for bearing condition monitoring and prognosis. In this study, the wavelet scattering transform, derived from wavelet transforms and incorporating concepts from scattering transform and convolutional network architectures, was utilized to extract quantitative features from vibration signals. The number of wavelet scattering coefficients obtained from vibration signals of different lengths varied due to the use of predefined wavelet and scaling filters in the wavelet scattering network. Additionally, these wavelet scattering coefficients are associated with different scattering paths within the corresponding wavelet scattering networks. Eight different lengths of vibration signals, associated with fifteen classes of rolling element bearing faults and conditions, were investigated using wavelet scattering feature extraction. The classes of rolling element bearing faults and conditions included normal bearings as well as ball and inner race faults with various fault diameters ranging from 0.007 inches to 0.028 inches. For the specific dataset validated, the computational results indicated that excellent bearing fault classification was achievable using wavelet scattering feature vectors derived from vibration signals with lengths of at least 6000 samples.

Effect of Surface Roughness on the Friction Moment in a Lubricated Deep Groove Ball Bearing

Deep groove ball bearings (DGBBs) are extensively utilized in industrial machinery, mechanical systems, and household appliances due to their simple design, low maintenance, and ability to operate at high speeds. A critical issue in the performance of these bearings is the power loss by internal friction torque, which adversely affects system efficiency, longevity, and reliability, particularly in demanding applications such as aviation and marine systems. The friction torque in DGBBs is influenced by factors such as load, speed, surface roughness, and lubricant viscosity, making the precise understanding of these elements essential for optimizing system efficiency. Despite its significance, the effect of surface roughness on friction torque in DGBBs remains underexplored. This paper presents an analytical model to evaluate the frictional moments resulting from interactions between the ball–race and ball–cage in lubricated, low-speed DGBBs. This model employs a mixed elastohydrodynamic lubrication approach to determine the friction coefficient at the contact interfaces. This study explores how surface roughness and speed affect both ball–race and ball–cage friction torque, offering a comprehensive analysis of their influence on overall frictional torque. Additionally, the effect of surface roughness on ball–cage contact forces is investigated, enhancing the understanding of its contribution to friction torque. These insights aim to improve DGBB design and operation, maximizing performance and energy efficiency.

Automated Variational Nonlinear Chirp Mode Decomposition for Bearing Fault Diagnosis

The variational non-linear chirp mode decomposition (VNCMD) requires initialization of number of modes (NMs) and instantaneous frequency (IF). This paper proposes an automated method for NM selection and IF initialization which works on the scale-space representation based automated boundary detection in magnitude spectrum (MS). The proposed automated VNCMD (AVNCMD) method is applied for bearing fault detection in which the kurtosis based dominant mode selection method is recommended. The instantaneous amplitude (IA) and IF with spectral entropy are computed from the dominant mode. Features are given to feed forward neural network classifier. Methodology is investigated on two datasets for inner race, outer race, and ball race faults detection. The proposed method classifies inner race, outer race, and ball race bearing faults with 97.52% accuracy and classifies inner race and outer race bearing fault with 100% accuracy. Efficacy of the proposed method is compared with the existing methods to justify the superiority.

Bearing Models for Advanced Ball Bearing Simulation

A comprehensive quasi-static and dynamic ball bearing model is described using many enhanced features, including novel calculations of the contact angle variations and ball–race sliding speeds in two directions, accounting for race curvature, pivoting effects and gyroscopic effects, appropriate lubricant rheology, and sliding forces (driving the balls against miscellaneous braking forces and moments such as, for example, the hydrodynamic rolling force). Ball–cage impact forces and cage-guiding ring forces are also considered, leading to a set of six dynamic differential equations to consider for each ball and three dynamic differential equations for the cage, where movement is assumed to be restricted to one plane. Quasi-static calculations can be undertaken by neglecting the cage and setting the accelerations of each degree of freedom of the ball to zero. New analytical or curve-fitted models are also provided using the mean values of sliding speed and viscosity to calculate sliding forces and moments, avoiding the use of contact slices with some useful relationships derived for calculating the rolling line locations, bearing torque, and dissipated bearing power. Several examples of calculated results are given and compared to available numerical or experimental results published in the literature. Finally, a new tool developed in-house is proposed for predicting many properties, particularly of interest at high speed, including the ball bearing torque, power loss, risk of smearing, and risk of cage failure.

Impact of Whirl and Axial Motion on Ball Bearing Turbocharger Dynamics

Ball bearing turbochargers (TCs) incorporate an angular contact ball bearing cartridge to reduce friction and oil consumption, improving the efficiency of internal combustion engines. In this investigation, axial and radial TC rotor motion was experimentally measured and used to develop a model of the TC rotor-bearing system, allowing for a detailed analysis of the TC bearing under varying operating conditions. In order to achieve the experimental objectives of this investigation, eddy-current proximity probes were used to measure the radial motion at the turbine and compressor sides of the TC. The measured radial motion shows whirl with subharmonics at low speed. The measured axial motion of the rotor was found to increase with TC speed. In order to analytically investigate the bearing dynamics, a complete TC model was developed that includes the mass distribution and flexibility of the TC compressor, shaft and turbine, and squeeze-film dampers (SFDs) that support the bearing cartridge. The model was used to replicate the whirl and axial motion of the test rig and then to determine which model parameters could be adjusted to minimize whirl without negatively affecting the bearing dynamics. Simulation results revealed that centrifugal effects cause a change in the bearing internal geometry, with a small clearance becoming a preload at higher speeds. When this effect is coupled with less compliant SFDs, the subharmonics are reduced and the overall sliding and number of large load cycles at the ball–race contacts are minimized, contributing to lower bearing friction and improved overall life.

Ball-Bearing Fault Classification Using Comparative Analysis of Wavelet Coefficient based on Entropy Measurement

Ball bearing is used to provide free rotation around a fixed axis. Various kinds of faults exist in the bearing such as inner race fault, outer race fault and ball race fault. One very effective method to diagnose the bearing fault is vibration signal analysis. Empirical mode decomposition (EMD) has been used for ball-bearing fault diagnosis in mechanical systems using vibration signal analysis. Classification of the ball-bearing fault has always been a challenging task. Various classification schemes such as Extreme learning machine (ELM), K-means Clustering, and Support vector machine (SVM), have been reported in the literature for ball-bearing fault classification. SVM is restricted by multiclass classification efficiency, and ELM is restricted by the longer training. In this paper, the entropy analysis of the wavelet coefficient obtained from the third level decomposition of the residue signal (obtained after subtracting the highest frequency component from the raw signal) has been done for ball-bearing fault classification. A comparative analysis of the wavelet coefficient based on entropy measurement has been presented here. High fault classification accuracy has been achieved using the proposed method for the detection of ball-bearing fault. Shannon entropy, Average Shannon entropy, and Renyi’s entropy are parameters for the justification of the proposed approach. The result shows the best wavelet to be chosen among the available discrete wavelet based on various entropy measurements.

Study of the Contact Characteristics of Machine Tool Spindle Bearings under Strong Asymmetric Loads and High-Temperature Lubrication Oil

The contact characteristics of angular contact ball bearings are closely related to the thermal failure of high-speed spindle systems. This paper establishes a closed-loop iterative model for analyzing the ball–race contact characteristics of machine tool spindle bearings at different combined loads and oil supply temperatures, based on a five-degree-of-freedom quasi-static analysis model and the finite difference method. Additionally, the accuracy of the proposed model is verified by comparing the measured values of temperature rise with the predicted values. Based on the verification of the accuracy of the model, the contact characteristics of machine tool spindle bearings under strong asymmetric loads and high-temperature lubrication oil are discussed in detail. The results show that at elevated temperatures, the internal loads of angular contact ball bearings operating under combined loads become concentrated, which will lead to reduced fatigue life of the bearings and even thermal seizure.

Fault Size Estimation of Bearings Using Multiple Decomposition Techniques with Artificial Neural Network

A running machine generates multi-frequency vibration signals which can be captured by accelerometers. Empirical mode decomposition, wavelet decomposition, and wavelet packet decomposition are the commonly used methods to decompose the multi-frequency signal. Quick fault classification, accurate signal decomposition, and fault size detection are still a problem in machines with rotary components. In the proposed work, fault diameter in rotary part of machine is detected and classified using the machine learning methods. In the first stage, we have employed empirical mode decomposition (EMD) for high-frequency noise removal. Residue signal is obtained by removing first IMF from base signal considering first IMF as a high-frequency noisy signal, followed by wavelet decomposition. Entropy of the wavelet coefficient obtained from 3rd level decomposition of residue signal is calculated which acts as an input parameter to the machine learning techniques to determine the diameter for fault. Three different sets have been taken for inner race, outer race, and ball race correspondingly. The proposed method classifies and detects the fault diameter up to 99.5%. The proposed method can be used for different types of continuous as well as discrete wavelets.

Grease lubrication of miniature ball bearings

Estimation of the power loss in miniature ball bearing grease lubricated is a complex problem. Usually the applied loads (radial and axial) have small values and the methodologies recommended by the bearing companies are cannot applied for these conditions. For a ball bearing, some friction processes have differential contribution to the total friction torque and power loss. For very low loads, the lubricant is the most important source for friction torque. In the present paper the authors determined experimentally the friction torque both in a standard 7000C angular contact ball bearing (ACBB) and a modified 7000C ACBB containing only 3 balls without cage, operating with very low axial load and lubricated with lithium soap grease. The experimental values of the friction torque have been correlated with the theoretical Houpert’s IVR model developed for hydrodynamic rolling resistances in ball race contacts considering the viscosity of the base oil of grease.

TEKERLEKLİ SANDALYE BASKETBOL OYUNCULARINDA KLASİFİKASYON PUANLARINA GÖRE BİYOMOTOR VE TEKNİK ÖZELLİKLER: PİLOT ÇALIŞMA

Purpose: This study was conducted to examine the biomotor and technical skills of wheelchair basketball players through their classification scores.
 Methods: A total of 22 male athletes, 11 with low trunk control (1 to 2.5 points) and 11 with high trunk control (3 to 4.5 points) from Turkish Wheelchair Basketball First League, voluntarily participated in the research. Athletes were grouped according to the International Wheelchair Basketball Federation functional classification system. Biomotor features of the athletes and wheelchair basketball skill test scores were measured. SPSS 24.0 program was used for data analysis. Group differences were determined by Mann-Whitney U analysis.
 Results: The study revealed statistically significant differences were in classification points, trunk balance, modified sit-up, modified abdominal endurance, 20 m speed, slalom without the ball, slalom with the ball and 6-min endurance race test parameters (p

Analysis of faults in rotor-bearing system using three-level full factorial design and response surface methodology

This article presents the experimental and statistical methodology for localized fault analysis in the rotor-bearing system. These defects on outer race, on inner race, and on a combination of ball and outer race are considered. In this study speed, load and defects were considered as the essential process variables to understand their significance and effects on vibration response for the rotor-bearing system. Three factors at three levels were considered for experimentation, and the experiment was designed for L27 based on design of experiments (DOE) methodology. From the experiments, the vibration response results are recorded in terms of root mean square value for the analysis. Response surface methodology (RSM) is used for identifying the interaction effect of varying process parameters upon the response of vibrations by response surface plot. The rotor-bearing test setup is used for experimentation and is analyzed by using DOE. This study establishes the prediction of fault in the rotor-bearing system in combined parametric effect analysis and its influence with DOE and RSM.

Numerical investigation of the oil–air distribution inside ball bearings with under-race lubrication

Oil distribution inside the under-race lubricated bearing is crucial for lubrication and cooling of high-speed ball bearings. An under-race lubricated ball bearing is modeled to numerically investigate the effects of operating parameters and feed hole configuration on the distribution behavior of lubricant oil. The results of the numerical simulation indicate that the average oil volume fraction changes with a convex trend as the outer race rotating speed increases, while it changes monotonically with the inner race rotating speed, oil volume flow rate, and oil temperature. The extent of oil spreading on the outer race, cage, ball, and inner race decreases successively. Optimizing the feed hole configuration according to the average oil volume fraction is helpful to achieve precise lubrication of the under-race lubricated ball bearing.

Анализ повреждений подшипников тяговых машин на электроподвижном составе при питании от преобразователей частоты и напряжения

The technical and economic efficiency of electric rolling stock (ERS) is determined by the characteristics of its traction electric drives, the key ones of them being the manufacturing cost, repair and maintenance costs, service life, specific energy consumption, and operational reliability. The modern ERS uses induction electric drives with pulse-width control of the voltage and frequency control of the rotation frequency. The field experience gained from operation of electric drives equipped with semiconductor converters has shown a growing number of cases involving accelerated wear of the traction machine bearings. Currents through the bearings or shaft currents, which usually flow from the electrical machine shaft through the bearings, have been known since the time the electrical machines were invented. Owing to recent achievements made in power electronics, the application field of inductor motors has become much wider. In particular, the use of inverters with pulse-width modulation (PWM) and high switching frequency make it possible to operate an electric drive with a lower acoustic noise and with more efficient energy conversion; however, the use of inverters also entails the generation of bearing currents in induction motors. The article analyzes possible factors causing the occurrence of bearing currents. Typical changes occurring in the bearings as a result of electric current flowing through them are shown: the rolling surface becomes dull, grooves on the ball race occur, and lubrication becomes degraded. The influence of operating parameters on the frequency of the occurring breakdowns and the distribution of forces in the bearing system depending on the load are considered. A conclusion is drawn that the potential problem of bearing currents should be solved using design, structural, and algorithmic methods at different stages of design and operation of electrical systems involving adjustable electric drives.

Анализ повреждений подшипников тяговых машин на электроподвижном составе при питании от преобразователей частоты и напряжения

The technical and economic efficiency of electric rolling stock (ERS) is determined by the characteristics of its traction electric drives, the key ones of them being the manufacturing cost, repair and maintenance costs, service life, specific energy consumption, and operational reliability. The modern ERS uses induction electric drives with pulse-width control of the voltage and frequency control of the rotation frequency. The field experience gained from operation of electric drives equipped with semiconductor converters has shown a growing number of cases involving accelerated wear of the traction machine bearings. Currents through the bearings or shaft currents, which usually flow from the electrical machine shaft through the bearings, have been known since the time the electrical machines were invented. Owing to recent achievements made in power electronics, the application field of inductor motors has become much wider. In particular, the use of inverters with pulse-width modulation (PWM) and high switching frequency make it possible to operate an electric drive with a lower acoustic noise and with more efficient energy conversion; however, the use of inverters also entails the generation of bearing currents in induction motors. The article analyzes possible factors causing the occurrence of bearing currents. Typical changes occurring in the bearings as a result of electric current flowing through them are shown: the rolling surface becomes dull, grooves on the ball race occur, and lubrication becomes degraded. The influence of operating parameters on the frequency of the occurring breakdowns and the distribution of forces in the bearing system depending on the load are considered. A conclusion is drawn that the potential problem of bearing currents should be solved using design, structural, and algorithmic methods at different stages of design and operation of electrical systems involving adjustable electric drives.

Cross‐domain bearing fault diagnosis with refined composite multiscale fuzzy entropy and the self organizing fuzzy classifier

AbstractIn this article, the use of refined composite multiscale fuzzy entropy (RCMFE) for cross‐domain diagnosis of bearings is introduced and verified with two publicly available datasets of varying operating conditions, a factor that challenges the diagnostic ability of trained models. For classification, the self organizing fuzzy (SOF) classifier is used. The diagnostic framework which primarily only involves extracting RCMFE feature and training the SOF classifier, is able to detect and isolate faults with over 97% accuracy when the classes are comprised of a single fault type and size. Compared to related works, the proposed approach does not require deep learning for feature extraction nor any domain adaptation technique as the RCMFE feature is robust against changing operating conditions. Furthermore, the method does not need target domain data during training. With regard to fault isolation, when the classes in the training data contain all the available fault sizes instead of a single size, the classifier can distinguish inner race faults from outer race and ball fault with an average accuracy of 96%. However, the accuracy for differentiating ball and outer race faults falls slightly to an average of 86%. Thus even for the latter arrangement which poses a tougher transfer learning problem, the proposed approach still performs very well.

Minimum Energy Hypothesis in Quasi-Static Equilibrium Solutions for Angular Contact Ball Bearings

The commonly used quasi-static model for angular contact bearings is enhanced by coupling contact mechanics and bearing kinematic analyses with traction or friction behavior in ball–race contacts. The points of pure rolling in the contacts, which constitute the primary inputs in the kinematic equations, are determined by minimizing the frictional dissipation based on a prescribed elastohydrodynamic traction model. Such an intricate coupling between contact mechanics, bearing kinematics, and lubricant behavior provides significant enhancement of simple quasi-static model for greatly improved prediction of traction behavior and heat generation in ball bearing contacts. The predictions are in close agreement with those obtained by much more sophisticated dynamic analysis based on integration of classical differential equations of motion of bearing elements. The enhanced quasi-static model can therefore be effectively used as a design tool for optimizing thermal dissipation in ball–race contacts in ball bearings. To facilitate immediate evaluation and implementation of the model to practical problems, a standalone software, containing the enhanced quasi-static model, is made freely available at www.PradeepKGuptaInc.com/AdoreQS.html.

Multi-scale deep intra-class transfer learning for bearing fault diagnosis

The tremendous success of deep learning in machine fault diagnosis is dependent on the hypothesis that training and test datasets are subordinated to the same distribution. This subordination is difficult to meet in practical scenarios of industrial applications. On the one hand, the working conditions of rotating machinery can change easily. On the other hand, vibration data and labels are difficult to obtain to train a specific model for each working condition. In this study, we solve these problems by constructing a novel deep transfer learning model called multi-scale deep intra-class adaptation network, which first uses the modified ResNet-50 to extract low-level features and then constructs a multiple scale feature learner to analyze these low-level features at multiple scales and obtain high-level features as input for the classifier. Pseudo labels are then computed to shorten the conditional distribution distance of vibration data collected under different working loads for intra-class adaptation. The proposed method is validated using two datasets to recognize the bearing normal state, the inner race, the ball and outer race faults, and their fault degrees under four different working loads. The high-precision diagnosis results of 24 transfer learning experiments reveal the reliability and generalizability of the constructed model.

Nonlinear vibration response analysis of a double-row self-aligning ball bearing due to surface imperfections

This work attempts to study the vibration response of a double-row self-aligning ball bearing due to surface and localized imperfections. For the contact deformation at the ball–race interactions, the Hertzian load–deflection relation is used for the evaluation of time-varying contact stiffness. The elastohydrodynamic theory is applied to find out the central film thickness. For both the inner and outer race waviness cases, the system response is observed as periodic (with vibrations of high amplitude) at [Formula: see text], i.e. multiples of Nb and its vicinity, but gradually turns to quasi-periodic as the value of waviness order reach some intermediate value. In the case of a localized defect, the double impulse phenomenon marks the entry and exit events of the rolling element in and out of the rectangular spall. Hence, this analysis can be used as a diagnostic tool with system dynamic characteristics for distributed and localized defect identification.

Mixed thermal elastohydrodynamic lubrication analysis with dynamic performance of aero ball bearing during start-up and shut-down

In this study, a coupling model is developed to include the aero ball bearing dynamic performance in the mixed thermal elastohydrodynamic lubrication analysis, and the low-speed and heavy-load conditions during start-up and shut-down are involved. Based on the bearing quasi-dynamics, the inside motion state of the main loading surface is obtained, and the mixed thermal elastohydrodynamic lubrication is conducted to get bearing lubrication state and properties. The numerical lubrication model under low-speed and heavy-load conditions is validated against published tested data, which reveal well consistency in central film thickness. The lubrication properties between a single ball and inner race during start-up have been studied, which indicate the lubrication film transforms from boundary lubrication to unsafe mixed thermal elastohydrodynamic lubrication, and then goes into safe lubrication. The lubrication properties of the balls at different azimuths have been investigated during shut-down and compared with those in start-up, which have a similar opposite changing trend, but not a simple invertible process. The time in boundary lubrication region during shut-down is shorter, and the ball number in boundary lubrication region gets less, which means the lubrication properties are relatively better. At last, the parametric study on mixed thermal elastohydrodynamic lubrication properties during shut-down has been carried out. It is found that the small bearing curve coefficient and increasing ball number can reduce the boundary lubrication time and improve the bearing lubrication.

Four approaches for calculating power losses in an angular contact ball bearing

Using the ball forces and moments equilibrium, the locations of the pure rolling lines on the inner and outer ball-race contact of a modified 7205B angular contact ball bearing were determined. The latter locations were used for defining the angular and orbital speeds of the balls. Also, tangential forces values have been determined considering a constant friction coefficient. Finally, the total friction torque and the corresponding dissipated power equations in an angular contact ball bearing (ACBB) operating in dry conditions have been proposed. Original models using four possible approaches were used and the calculated results compared successfully to the experimental ones. The proposed experimental test rig can be considered as a rheometer used for determining the ball–race friction coefficient.