Multi-Objective Design Optimization of Rolling Element Bearings Using ABC, AIA and PSO Technique

2013 ◽  
Vol 2 (3) ◽  
pp. 102-125
Author(s):  
Vimal Savsani
Keyword(s):  
High Reliability ◽  
Optimization Technique ◽  
Operating Conditions ◽  
Rolling Element Bearing ◽  
Design Parameters ◽  
Rolling Element Bearings ◽  
Automotive Manufacturing ◽  
Outer Race ◽  
Multi Objective ◽  
Rolling Element

Rolling element bearings are widely used as important components in most of the mechanical engineering applications. These bearings find wide applications in automotive, manufacturing and aeronautical industries. The problem associated with rolling element bearings are that the design and selection are based on different operating conditions to reach their excellent performance, long life and high reliability. This leads to the requirement of optimal design of rolling element bearings. Optimization aspects of a rolling element bearing are presented in this paper considering three different objectives namely, dynamic capacity, static capacity and elastohydrodynamic minimum film thickness. The design parameters include mean diameter of rolling, ball diameter, number of balls, and inner and outer race groove curvature radii. Different constants associated with the constraints are given some ranges and are included as design variables. The optimization procedure is carried out using artificial bee colony (ABC) optimization technique, artificial immune algorithm (AIA), and particle swarm optimization (PSO) technique. Both single and multi-objective optimization aspects are considered. The results of the considered techniques are compared with the previously published results. The considered techniques have given much better results in comparison to the previously tried approaches.

scholarly journals Chaotic prediction of vibration performance degradation trend of rolling element bearing based on Weibull distribution

2019 ◽  
Vol 103 (1) ◽  
pp. 003685041989219
Author(s):  
Li Cheng ◽  
Xintao Xia ◽  
Liang Ye
Keyword(s):  
Weibull Distribution ◽  
Relative Error ◽  
High Reliability ◽  
Prediction Method ◽  
Performance Degradation ◽  
Rolling Element Bearing ◽  
Maximum Relative Error ◽  
Rolling Element Bearings ◽  
Rolling Element ◽  
Vibration Performance

Rolling element bearings are used in all rotating machinery, and the degradation performance of rolling element bearings directly affects the performance of the machine. Therefore, high reliability prediction of the performance degradation trend of rolling element bearings has become an urgent research problem. However, the degradation characteristics of the rolling element bearings vibration time series are difficult to extract, and the mechanism of performance degradation is very complicated. The accurate physical model is difficult to establish. In view of the above reasons, based on the vibration performance data of rolling element bearings, a model of bearing performance degradation trend parameter based on wavelet denoising and Weibull distribution is established. Then, the phase space reconstruction of the series of bearing performance degradation trend parameter is carried out, and the prognosis is obtained by the improved adding weighted first-order local prediction method. The experimental results show that the bearing vibration performance degradation parameter can accurately depict the degradation trend of the bearing, and the reliability level is 91.55%; and the prediction of bearing performance degradation trend parameter is satisfactory: the mean relative error is only 0.0053% and the maximum relative error is less than 0.03%.

scholarly journals Rolling Element Bearing Fault Diagnosis Based on Multiscale General Fractal Features

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Weigang Wen ◽  
Zhaoyan Fan ◽  
Donald Karg ◽  
Weidong Cheng
Keyword(s):  
Fault Diagnosis ◽  
Fractal Dimensions ◽  
Feature Space ◽  
Operating Conditions ◽  
Rolling Element Bearing ◽  
Rolling Element Bearings ◽  
Vibration Signals ◽  
Bearing Fault Diagnosis ◽  
Rolling Element ◽  
Element Bearing

Nonlinear characteristics are ubiquitous in the vibration signals produced by rolling element bearings. Fractal dimensions are effective tools to illustrate nonlinearity. This paper proposes a new approach based on Multiscale General Fractal Dimensions (MGFDs) to realize fault diagnosis of rolling element bearings, which are robust to the effects of variation in operating conditions. The vibration signals of bearing are analyzed to extract the general fractal dimensions in multiscales, which are in turn utilized to construct a feature space to identify fault pattern. Finally, bearing faults are revealed by pattern recognition. Case studies are carried out to evaluate the validity and accuracy of the approach. It is verified that this approach is effective for fault diagnosis of rolling element bearings under various operating conditions via experiment and data analysis.

New Feature Extraction Method for the Detection of Defects in Rolling Element Bearings

2012 ◽  
Vol 134 (8) ◽  
Author(s):  
Ling Xiang ◽  
Aijun Hu
Keyword(s):  
Ensemble Empirical Mode Decomposition ◽  
Rolling Element Bearing ◽  
Rolling Element Bearings ◽  
Intrinsic Mode Functions ◽  
Feature Extraction Method ◽  
Outer Race ◽  
Mode Decomposition ◽  
Rolling Element ◽  
Envelope Spectrum ◽  
Detection Of Defects

This paper proposes a new method based on ensemble empirical mode decomposition (EEMD) and kurtosis criterion for the detection of defects in rolling element bearings. Some intrinsic mode functions (IMFs) are presented to obtain symptom wave by EEMD. The different kurtosis of the intrinsic mode function is determined to select the envelope spectrum. The fault feature based on the IMF envelope spectrum whose kurtosis is the maximum is extracted, and fault patterns of roller bearings can be effectively differentiated. Practical examples of diagnosis for a rolling element bearing are provided to verify the effectiveness of the proposed method. The verification results show that the bearing faults that typically occur in rolling element bearings, such as outer-race and inner-race, can be effectively identified by the proposed method.

Spalling Size Evaluation of Rolling Element Bearing Using Acoustic Emission

2013 ◽  
Vol 569-570 ◽  
pp. 497-504 ◽  
Author(s):  
An Bo Ming ◽  
Zhao Ye Qin ◽  
Wei Zhang ◽  
Fu Lei Chu
Keyword(s):  
Acoustic Emission ◽  
Rolling Element Bearing ◽  
Rolling Element Bearings ◽  
Outer Race ◽  
Cepstrum Analysis ◽  
Rolling Element ◽  
Rolling Elements ◽  
Element Bearing ◽  
Envelope Spectrum ◽  
Size Evaluation

Spalling of the races or rolling elements is one of the most common faults in rolling element bearings. Exact estimation of the spall size is helpful to the life prediction for rolling element bearings. In this paper, the dual-impulsive phenomenon in the response of a spalled rolling element bearing is investigated experimentally, where the acoustic emission signals are utilized. A new method is proposed to estimate the spall size by extracting the envelope of harmonics of the ball passing frequency on the outer race from the squared envelope spectrum. Compared with the cepstrum analysis, the proposed procedure shows more powerful anti-noise ability in the fault size evaluation.

An overview of dynamic modeling of rolling-element bearings

2020 ◽  
pp. 095745652094827
Author(s):  
Surajkumar G Kumbhar ◽  
Edwin Sudhagar P ◽  
RG Desavale
Keyword(s):  
Dynamic Behavior ◽  
Dynamic Modeling ◽  
Operating Conditions ◽  
Rolling Element Bearing ◽  
Rolling Element Bearings ◽  
Roller Bearings ◽  
Rolling Element ◽  
Vibration Responses ◽  
Vibration Signature ◽  
Element Bearing

The marvelous uniqueness of vibration responses of faulty roller bearings can be simply observed through its vibration signature. Therefore, vibration analysis has been claimed as an effective tool not only for primitive detection but also for subsequent analysis. The dynamic behavior of roller bearings has been investigated by systematic modeling of system and its validation under diverse operating conditions. This article presents an overview of imperative marks in the development of dynamic modeling of rolling-element bearing, which especially predicted vibration responses of damaged bearings. This study aims to address dimensional analysis; a new and imperative way to model the dynamic behavior of rolling-element bearings and their real-time performance in a rotor-bearing system. The findings are described with influential advantages over earlier research to pinpoint the intention behind its development. A literature summary is trailed by remarkable findings and future directions for research.

A Nonlinear Model for Structural Vibrations in Rolling Element Bearings: Part II—Simulation and Results

1997 ◽  
Vol 119 (2) ◽  
pp. 323-331 ◽  
Author(s):  
J. Datta ◽  
K. Farhang
Keyword(s):  
Nonlinear Model ◽  
Relative Size ◽  
Operating Conditions ◽  
Rolling Element Bearings ◽  
Governing Equations ◽  
Structural Vibrations ◽  
Outer Race ◽  
Vibrational Response ◽  
Rolling Element

This is the second of two companions papers. In the first paper, “A Nonlinear Model for Structural Vibrations in Rolling Element Bearings: Part I—Derivation of Governing Equations,” equations governing the vibrational response of rolling element bearings were developed. The mathematical formulations are utilized in this paper to study a number of effects on bearing structural vibrations. These include the effects of relative size of roller and inner and outer races, and inertias of inner and outer race assemblies, i.e., inertia of the races plus the components of an external system to which the inner and outer races are attached; the load acting on the bearing, its magnitude and nature (i.e., whether linear, rotational etc.). The studies are made under constant operating conditions (speed, lubrication) and the results obtained are discussed.

Compound faults detection of the rolling element bearing based on the optimal complex Morlet wavelet filter

2017 ◽  
Vol 232 (10) ◽  
pp. 1786-1801 ◽  
Author(s):  
Xiaohui Gu ◽  
Shaopu Yang ◽  
Yongqiang Liu ◽  
Feiyue Deng ◽  
Bin Ren
Keyword(s):  
Particle Filtering ◽  
Morlet Wavelet ◽  
Previous Method ◽  
Rolling Element Bearing ◽  
Rolling Element Bearings ◽  
Wavelet Filter ◽  
Outer Race ◽  
Rolling Element ◽  
Complex Morlet Wavelet ◽  
Envelope Spectrum

Wavelet filter is widely used in extracting fault features embedded in the noisy vibration signal, especially the complex Morlet wavelet. In most occasions, the filter parameters are optimized adaptively with a suitable objective function. And then, with the Hilbert transform demodulation analysis, the single localized fault in rolling element bearings can be detected. To extend it for compound faults detection, a novel index deduced from the different intervals of the prominent bearing fault frequencies and subsequent harmonics in the envelope spectrum is proposed. By maximizing the ratio of correlated kurtosis to kurtosis of the envelope spectrum amplitudes of the filtered signal, the optimal complex Morlet wavelet filters corresponding to the different faults are designed by the particle filtering method, respectively. Two cases of real signals are analyzed to evaluate the performance of the proposed method, which include one case of experiment signal with artificial outer race fault coupled with roller fault, as well as one case of engineering data with outer race fault coupled with inner race fault. Furthermore, some comparisons with a previous method are also conducted. The results demonstrate the effectiveness and robustness of the method in compound faults diagnosis of the rolling element bearings.

Nonlinear Mechanics of Rolling Contacts With Surface Defects

2010 ◽  
Author(s):  
Mohsen Nakhaeinejad ◽  
Jaewon Choi ◽  
Michael D. Bryant
Keyword(s):  
Surface Defects ◽  
Nonlinear Behavior ◽  
Rolling Contact ◽  
Rolling Element Bearing ◽  
Rolling Element Bearings ◽  
Detailed Model ◽  
Outer Race ◽  
Model Based ◽  
Rolling Contacts ◽  
Rolling Element

Nonlinear behavior of force and displacements in rolling contacts with the presence of surface defects are studied. Model-based fault assessments in rolling element bearings and gears require detailed modeling and dynamics of faults. A detailed model of rolling element bearings with direct correspondence between parameters of the model and physical components is developed. The model incorporates dynamics of faults, nonlinear contacts, slips and surface separations. Mechanics of contacts with inner race faults (IRF), ball faults (BF), and outer race faults (ORF) are studied using the developed model. Contacts force, displacement and impulse signals are studied for different size and types of surface defects. It is shown that impulse signals contain useful information about the severity of surface defects in rolling element bearing. Results provide model-based diagnostics a deep knowledge of rolling contact mechanics with surface defects to be used for fault assessments.

Diagnosis of Defected Rolling Bearings via Vibration Analysis Method

2010 ◽  
Author(s):  
Majid Hamedynia ◽  
Hossein Rokni D. T.
Keyword(s):  
Vibration Analysis ◽  
Operating Conditions ◽  
Rolling Element Bearing ◽  
Main Function ◽  
Rolling Element Bearings ◽  
Rotating Shaft ◽  
Abnormal Detection ◽  
Feature Extraction Method ◽  
Rolling Element ◽  
Element Bearing

The main function of rolling element bearings is to provide low friction conditions for supporting and guiding a rotating shaft. The rolling element bearing includes both ball bearings and roller bearings. Rolling element bearings operate with a rolling action whereas plain bearings operate with a sliding action. In various applications, these bearings are considered as critical mechanical components since defect in these components may lead to malfunction and catastrophic failure in some cases. Vibration analysis is one of the most established methods used to evaluate the condition of bearings in operating machines. In this paper, an abnormal detection structure, in which different types of abnormal detection routines can be applied, is proposed. Bearing fault modes and their effects on the bearing vibration are discussed. In order to achieve this purpose, a feature extraction method is developed to overcome the limitation of time domain features. Experimental data from bearings under different operating conditions are used to verify the proposed method.

Dynamic Modeling of Rolling Element Bearings With Surface Contact Defects Using Bond Graphs

2010 ◽  
Vol 133 (1) ◽  
Author(s):  
Mohsen Nakhaeinejad ◽  
Michael D. Bryant
Keyword(s):  
Three Dimensional ◽  
Surface Profile ◽  
Rolling Element Bearing ◽  
Rolling Element Bearings ◽  
Bond Graphs ◽  
Outer Race ◽  
Proposed Model ◽  
Rolling Element ◽  
Type Size ◽  
Localized Faults

Multibody dynamics of healthy and faulty rolling element bearings were modeled using vector bond graphs. A 33 degree of freedom (DOF) model was constructed for a bearing with nine balls and two rings (11 elements). The developed model can be extended to a rolling element bearing with n elements and (3×n) DOF in planar and (6×n) DOF in three dimensional motions. The model incorporates the gyroscopic and centrifugal effects, contact elastic deflections and forces, contact slip, contact separations, and localized faults. Dents and pits on inner race and outer race and balls were modeled through surface profile changes. Bearing load zones under various radial loads and clearances were simulated. The effects of type, size, and shape of faults on the vibration response in rolling element bearings and dynamics of contacts in the presence of localized faults were studied. Experiments with healthy and faulty bearings were conducted to validate the model. The proposed model clearly mimics healthy and faulty rolling element bearings.

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