Rolling Bearing Analysis Research Articles

Vibration response-based time-variant reliability and sensitivity analysis of rolling bearings using the first-passage method

The vibration response of rolling bearings exhibits random and uncertain characteristics due to factors such as random process loads, material property degradation, and uncertain dimensional parameters. The time-variant reliability of rolling bearings obtained based on such vibration response is more realistic and accurate. In this paper, a novel vibration response-based time-variant reliability and sensitivity analysis model of rolling bearings is proposed. First, the forces on the rolling bearing are analyzed and the stress distribution is derived. Then, the equivalent stiffness and damping in the bearing vibration equation are obtained based on the ball-raceway contact model. To approximate the real degradation process, the vibration equation considering the impact load is proposed, and the statistical characteristics of the impact load with time are obtained from degradation data of the conducted bearing tests. Subsequently, the first-passage method is adopted to efficiently evaluate the time-variant reliability of rolling bearings based on the vibration response. In addition, reliability sensitivity index is derived to analyze the influence of input parameters on the reliability of rolling bearings, which improves design efficiency and provides references for further structural optimization. The accuracy and validity of the proposed model and method are verified by two cases of different bearing types.

Reliability analysis of rolling bearings considering failure mode correlations

AbstractAs an essential mechanical component, a rolling bearing can exhibit multiple failure modes that may occur independently or in correlation with one another. A reliability analysis method that meticulously accounts for the interdependencies among various bearing failure modes is presented in this paper. The examination of wear and fatigue failure mechanisms in rolling bearings is carried out using the Physics of Failure (PoF) approach. By considering the influence of uncertain variables, the limit state functions for individual failure modes are formulated through the application of stress‐strength interference theory. In the context of wear failure, the limit state function is derived using working clearance as the characteristic quantity. On the other hand, the limit state function for fatigue failure is constructed with a focus on fatigue damage accumulation. The Copula function is used to characterize the relationship between wear failure and fatigue failure, and a reliability calculation model for rolling bearings is developed, considering the correlation between these failure modes. Ultimately, the proposed method is utilized to assess the reliability of bearings under two different sets of test conditions. The feasibility of this method is confirmed through test data, demonstrating its effectiveness in predicting bearing reliability. Through the application of this method, engineers can optimize bearing size parameters, select appropriate initial clearances, and enhance the reliability design of bearing.

Influence of various balls and groove curvature radii on dynamic stiffness of ball bearings based on nonlinear dynamic model

In the context of this study, a novel dynamic model is integrated with the stiffness matrix model so that the dynamic forces effect the stiffness calculation real-timely to form the dynamic stiffness, which is a novel solution for the dynamic performance analysis of rolling bearings under different loads, assemblies and bearing structures. Based on this model, the influence of ball quantity and groove curvature radii on the dynamic stiffness of ball bearings is explored. The optimal ball's quantity and groove curvature radii combination were determined to attain the desired magnitude and fluctuation of bearing stiffness. The results show that favorable stiffness can be achieved when the number of balls is decreased by one or two, the radius of outer groove curvature approximates the ball radius, and the radius of inner groove curvature is appropriately larger than the ball radius. This configuration offers theoretical backing for optimizing the structural dimensions of ball bearings.

Tribological and dynamic performance analysis of rolling bearings with varied surface textures operating under lubricant contamination

This study aimed to evaluate the ability of textured rolling bearings to capture and store contaminants in a lubricant-contaminated state. Cylindrical thrust roller bearings (CTRBs) were selected for investigation, and circular textures were prepared on the bearing raceway surface using laser etching. The effects of pit location, diameter, depth, and area density on the tribological and dynamic performance of rolling bearings operating in a contaminated environment were examined. Results showed that adding texture only to the shaft washer raceway improved friction reduction and dynamic performance. Additionally, carefully designed textures could suppress vibration energy in the medium and high frequency bands of the bearing. Notably, the ability of the texture to capture contaminants was directly influenced by the diameter and area density of the pits. Furthermore, the relationship between the pits' depth and wear reduction capacity was closely linked to their diameter.

Dynamic modeling and analysis of rolling bearings with rolling element defect considering time-varying impact force

Accurately establishing a dynamic model of rolling bearings is significant for understanding the fault mechanism and analyzing the motion characteristics under different performance states. Since the contact process of rolling element defect is more complicated than that of race defect, the research on its characteristics is usually simplified to a certain extent. However, the excitation of the rolling element defect area is closely related to the rotational speed and the size of the defect, the commonly used displacement form of fault excitation can hardly reflect the mechanical characteristics of the actual rolling element fault. A time-varying displacement excitation function of the rolling elements is used to characterize the change of the contact gap between the rolling elements and the inner and outer races. According to the time-varying displacement excitation function, a time-varying impact force excitation function of the defective rolling element is proposed which comprehensively considers defect sizes and the rotational speeds. A four-degree-of-freedom bearing dynamics model based on Hertz basis theory is correlated with time-varying excitation, and the accuracy of the model is confirmed by comparison with the processed experimental signal. Based on the mechanical model and experimental data, the influence of the rotational speeds and defect sizes on the vibration characteristics of the bearing rolling element fault is analyzed and summarized, which provides theoretical support for investigating the mechanism of the bearing rolling element fault.

Simulation analysis of rolling bearings based on explicit dynamics

Based on LS-PrePost software, the three-dimensional display of healthy cylindrical roller bearings was established finite element model for dynamic simulation. Based on the explicit algorithm, the model analyzes the law of bearing stress level with radial outward load under the conditions of friction contact, speed and load, and based on the healthy roller bearing model, simulates the local spalling fault of the outer raceway by setting the unit defect, and analyzes the equivalent force change process when the roller through the fault area. The simulation results are compared with the theoretical calculation results to verify the correctness of the finite element model of the faulty bearings, and provide a certain reference for the fault diagnosis of rolling bearings.

Study on Rolling Bearing Life Based on Weibull Distribution and Correlation Coefficient Optimization and Maximum Likelihood Estimation

For the reliability evaluation of rolling bearing life, this paper proposes a parameter estimation method based on the correlation coefficient optimization method and the maximum likelihood estimation method (Cor-MLE), which can obtain more accurate Weibull distribution parameter estimation. Subsequently, the feasibility of Cor-MLE method for Weibull parameter estimation was verified by Monte Carlo simulation data and rolling bearing life test data. Compared with the parameter estimation results of least square method, grey model method and correlation coefficient optimization method, it is proved that the estimation results of this method have high accuracy and can meet the life analysis of rolling bearings.

Reliability and Reliability Sensitivity Analysis of Rolling Bearings Based on Contact Fatigue under Finite Probability Information

The probability information of random variables is frequently finite in the rolling bearing contact fatigue reliability design process, making it impossible to calculate the reliability index or rolling bearing reliability accurately. In this study, the dynamic model of rolling bearings is established, the Box–Behnken design and the response surface method are combined to obtain the mapping relationship between random variables, and the rolling bearing reliability design model is established with the strength obeying gamma process. The transient reliability, cumulative reliability, and reliability sensitivity analysis methods based on contact fatigue under finite probability information are used to calculate the change law and size order of the rolling bearing reliability affected by the change of each basic random variable. Finally, we apply this research method to analyse the reliability of a certain type of angular contact ball bearing compared with the Monte Carlo simulation method. This demonstrates that the method presented in this study is correct and effective.

A Review on Rolling Bearing Fault Signal Detection Methods Based on Different Sensors.

As a precision mechanical component to reduce friction between components, the rolling bearing is widely used in many fields because of its slight friction loss, strong bearing capacity, high precision, low power consumption, and high mechanical efficiency. This paper reviews several excellent kinds of study and their relevance to the fault detection of rolling bearings. We summarize the fault location, sensor types, bearing fault types, and fault signal analysis of rolling bearings. The fault signal types are divided into one-dimensional and two-dimensional images, which account for 40.14% and 31.69%, respectively, and their classification is clarified and discussed. We counted the proportions of various methods in the references cited in this paper. Among them, the method of one-dimensional signal detection with external sensors accounted for 3.52%, the method of one-dimensional signal detection with internal sensors accounted for 36.62%, and the method of two-dimensional signal detection with external sensors accounted for 19.72%. The method of two-dimensional signal detection with internal sensors accounted for 11.97%. Among these methods, the highest detection rate is 100%, and the lowest detection rate is more than 70%. The similarities between the different methods are compared. The research results summarized in this paper show that with the progress of the times, a variety of new and better research methods have emerged, which have sped up the detection and diagnosis of rolling bearing faults. For example, the technology using artificial intelligence is still developing rapidly, such as artificial neural networks, convolutional neural networks, and machine learning. Although there are still defects, such methods can quickly discover a fault and its cause, enrich the database, and accumulate experience. More and more advanced techniques are applied in this field, and the detection method has better robustness and superiority.

Non-linear Vibration Response Analysis of Rolling Bearing for Data Augmentation and Characterization

Non-linear Vibration Response Analysis of Rolling Bearing for Data Augmentation and Characterization

Thermal Analysis Based on Dynamic Performance of Rocker Arm Full-Type Needle Bearings

Based on a dynamic analysis of rolling bearings, the equations for rocker arm full-type needle bearings were established by considering the traction coefficients of FVA-M reference lubricating oil, and then they were solved by the GSTIFF (Gear Stiff) integer algorithm with variable steps. The influence of working conditions on friction power consumption and the lubricant’s convective coefficients were investigated. Then, on the basis of the heat generation and heat transfer mechanisms, the frictional power consumption was used as the boundary condition of the bearings’ simulation model. Finally, temperature fields were calculated by the finite element method. The results showed that the overall value of frictional power consumption increased gradually with the increase in either the radial load or the rotation speed. The presence or absence of lubricating oil film in the contact area affected the heat conduction of the bearing, resulting in a temperature difference. Compared with the temperature of the radial load exerted on the bearing, the maximum temperature was more sensitive to the variations in the rotation speed. When running under the conditions of a fatigue life test, the steady-state temperature value of the bearing gradually decreased from the outer raceway to the needle roller and the outer ring surface, and then to the central shaft. The maximum temperature rise was 25.9 °C relative to the ambient temperature.

Prognostics Analysis of Rolling Bearing Based on Bi-Directional LSTM and Attention Mechanism

Prognostics Analysis of Rolling Bearing Based on Bi-Directional LSTM and Attention Mechanism

Dynamic Analysis of Rolling Bearings with Roller Spalling Defects Based on Explicit Finite Element Method and Experiment

Analysis of dynamic characteristics of the defective bearing is significant for the fault diagnosis of the machinery. At present, there are few researches on numerical modeling of bearing with defective roller. To solve this problem, explicit finite element method is adopted in this paper to establish a nonlinear dynamic model of the cylindrical roller bearing with roller spalling defects. In the proposed model, the flexibility of all the components, the internal friction, the relative sliding, the finite size of the roller and the rollers-to-cage contact force are all considered. Then the proposed dynamic model is verified theoretically and experimentally. The vibration responses of bearing and the sliding behavior of defective roller and cage are analyzed based on the proposed numerical model. The results show that the roller-to-cage contact force will be increased and the slippage of the defective roller will be aggravated when the roller defect occurs. In addition, the increment of defect width and number of defective rollers will aggravate the vibration of bearing and the sliding of cage.

Dynamic asymptotic model of rolling bearings with a single fault in the inner raceway

In the previous models of rolling bearings with a single fault, the displacement deviation caused by the collision of the fault to the rolling element changes instantly. However, the displacement deviation should change gradually. Here, the asymptotic idea is introduced to describe the change of the displacement deviation. The calculation method of the deviation is given. An asymptotic model of rolling bearings with an inner raceway fault is constructed. Then, the simulation of the SKF6205 bearing with a single fault is carried out. The differences between the previous model and the asymptotic model for the responses and the displacement deviation are compared. The effects of the speed and fault size on the dynamic characteristics are analyzed. Finally, the experiments are carried out to corroborate the rationality of the constructed model. The research results can provide theoretical support for the dynamic analysis, fault diagnosis, and reliability analysis of rolling bearings.

Dynamics Analysis of Rolling Bearings for Motor of a Mobile Power Station

The electric motor is an important part of a mobile power station. Under the complex operating conditions, the stiffness of the rolling bearing exhibits strong time-varying characteristics and non-linear characteristics, which is the one of the main sources for the system non-linearity. Taking the angular contact bearing as the research object, the coupled dynamic model of the bearing-rotor system is established to calculate the time-varying stiffness. The bifurcation law exhibited by the system can be attributed to the excitation of the non-linear bearing force. The numerical calculation method is used to study the motion state bifurcation law and dynamic frequency response characteristics under the rated working condition of the motor. Considering bearing damping, clearance and radial load, the bifurcation and time domain diagrams of different parameters, displacements and rotation speeds in different directions are studied respectively. The results show that when the parameters change, the system will experience chaos, quasi-period and period-doubling motion state; Damping suppresses vibration very clearly, while changes in bearing clearance and radial load significantly cause the system’s vibration amplitude to increase, and radial load changes accelerate system vibration. A reasonable bearing is of great significance for motor the design of a mobile power station.

Fault diagnosis and severity analysis of rolling bearings using vibration image texture enhancement and multiclass support vector machines

Fault detection and diagnosis of its severity for machine health monitoring can be stated as a nested classification problem. For a faulty bearing, each fault location whether belonging to inner race, outer race or the ball can be seen as multiclass classification with three classes while the varying degree of severity in each class can be viewed as a sub classification task. The peculiar vibration patterns generated from the flaws in different bearing parts and with varying degree of distortion can be classified into various classes and subclasses for analysis of vibration signatures. This paper proposes a multiclass support vector machines (MSVMs) based fault classification approach for fault diagnosis of ball bearings. The one dimensional vibration signals are converted to two dimensional gray scale images resulting in textural patterns which are then enhanced using the wave atom transform. Features such as semivariance, skewness and entropy are extracted from the texture images and the MSVM is then trained using feature matrices generated from feature vectors. The MSVM is trained in two phases; in the first phase, the classifier categorizes the location of the fault and in the second phase the classifier does the diagnosis regarding the size of the fault at that particular location. Simulation results show that the proposed technique is highly robust in locating the fault and its severity.

Dynamic Modeling and Analysis of Rolling Bearing with Compound Fault on Raceway and Rolling Element

Rolling element bearing is a very important part of mechanical equipment and widely used in rotating machinery. Rolling element bearings could appear localized defects during the working condition, which would cause the complex vibration response of bearings. Considering the shaft and bearing pedestal, a 4 degree-of-freedom (DOF) dynamic model of rolling bearing with compound localized fault is established based on time-varying displacement, and the vibration characteristics of rolling bearing with localized faults under different conditions are investigated. The established model is verified by the experimental vibration signals in time domain and frequency domain. The results show that the vibration response of compound fault is the result of the coupling action of a single fault of rolling element and outer race. The influences of compound fault on the vibration signals of the bearing were analyzed under three conditions. With the increasing of radial load, defect size, and rotation speed, the vibration amplitude of bearing would increase correspondently, which would accelerate the failure rate of bearing and reduce the service life of bearing. This model is helpful to analyze the vibration response of the rolling element bearing with single or compound fault.

Reliability analysis of rolling bearings considering internal clearance

The internal clearance is a decisive parameter for life prediction and reliability analysis of rolling bearings. In this paper, a comprehensive reliability analysis model of rolling bearings is proposed by considering the internal clearance of rolling bearings. The model of bearings’ working clearance was established after investigating the effect mechanisms of effective interference, temperature, and centrifugal force on the clearance. The validation of the results is carried out by the reliability analysis of a real rolling bearing through the modeling of working clearance probability distribution and the research of life factor. The results indicate that the proposed methodology provides an additional reference way for the reliability analysis of rolling bearings.

Dynamic Modeling and Vibration Analysis of Rolling Bearings with Local Fault

Dynamic Modeling and Vibration Analysis of Rolling Bearings with Local Fault

Fault detection of rolling bearing based on principal component analysis and empirical mode decomposition

For the problem of inconsistent quantitative standards for running status analysis of rolling bearings, this paper uses principal component analysis (PCA) to extract a new index F, which is the joint parameters of time domain and frequency domain, and by establishing the value of F to analyze the running states of the rolling bearings. Firstly, the acceleration sensors are used to collect the vibration signal of the whole life cycle of the rolling bearings. Secondly, empirical mode decomposition (EMD) method is used to denoise the acquired vibration signal. Then, the main components of the denoised vibration signal are used to propose the characteristic parameters and synthesized into new parameter indicators. Finally, envelope analysis spectrum is used to analyze the fault classification under the new parameter index. The exepriment results show that the whole life cycle of the rolling bearings can be classified into five different operating periods by using the new parameter index, and each period represents a different bearing operating state.