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

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Xin Zhang ◽  
Changfeng Yan ◽  
Yaofeng Liu ◽  
Pengfei Yan ◽  
Yubo Wang ◽  
...  
Keyword(s):  
Rolling Bearing ◽  
Vibration Response ◽  
Rolling Element Bearing ◽  
Mechanical Equipment ◽  
Vibration Signals ◽  
Modeling And Analysis ◽  
Outer Race ◽  
Rolling Element ◽  
Element Bearing ◽  
Localized Faults

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.

Fault Diagnosis based on Wavelet Analysis for Bearings under Low Rotating Speed

2011 ◽  
Vol 291-294 ◽  
pp. 2006-2009
Author(s):  
Hua Qing Wang ◽  
Yong Wei Guo ◽  
Jin Ji Gao ◽  
Feng Wang
Keyword(s):  
Fault Diagnosis ◽  
Wavelet Analysis ◽  
Rolling Bearing ◽  
Rolling Element Bearing ◽  
Vibration Signals ◽  
Bearing Faults ◽  
Rotating Speed ◽  
Analysis Technique ◽  
Rolling Element ◽  
Element Bearing

Bearing faults signal is very weak under a low rotating speed, and therefore fault diagnosis for bearings under a low rotating speed, is more difficult than under a high rotating speed. The wavelet analysis technique is adopted for fault diagnosis of rolling element bearing under low rotating speed. This work also acquired vibration signals and acoustic emission signals from the rolling bearing under low speed respectively, and analyzed the both kinds of signals for diagnosing the typical bearing faults contrastively.

Contact characteristic and vibration mechanism of rolling element bearing in the process of fault evolution

2021 ◽  
Vol 235 (1) ◽  
pp. 19-36 ◽  
Author(s):  
Wenbing Tu ◽  
Jinwen Yang ◽  
Wennian Yu ◽  
Ya Luo
Keyword(s):  
Fault Diagnosis ◽  
Vibration Response ◽  
Rolling Element Bearing ◽  
Bearing Fault Diagnosis ◽  
Rolling Element ◽  
Vibration Mechanism ◽  
Contact Characteristic ◽  
Element Bearing ◽  
Bearing Vibration ◽  
Fault Evolution

The vibration response of rolling element bearing has a close relation with its fault. An accurate evaluation of the bearing vibration response is essential to the bearing fault diagnosis. At present, most bearing dynamics models are built based on rigid assumptions, which may not faithfully reveal the dynamic characteristics of bearing in the presence of fault. Moreover, previous similar works mainly focus on the fault with a specified size without considering the varying contact characteristics as the fault evolves. This paper developed an explicit dynamics finite element model for the bearing with three types of raceway faults considering the flexibility of each bearing component in order to accurately study the contact characteristic and vibration mechanism of defective bearings in the process of fault evolution. The developed model is validated by comparing its simulation results with both analytical and experimental results. The dynamic contact patterns between the rolling elements and the fault, the additional displacement due to the fault and the faulty characteristics within the bearing vibration signal during the fault evolution process are investigated. The analysis results from this work can provide practitioners an in-depth understanding towards the internal contact characteristics with the existence of raceway fault and theoretical basis for rolling bearing fault diagnosis.

A multichannel fusion approach based on coupled hidden Markov models for rolling element bearing fault diagnosis

2011 ◽  
Vol 226 (1) ◽  
pp. 202-216 ◽  
Author(s):  
W B Xiao ◽  
J Chen ◽  
G M Dong ◽  
Y Zhou ◽  
Z Y Wang
Keyword(s):  
Markov Models ◽  
Hidden Markov ◽  
Wavelet Packet ◽  
Rolling Element Bearing ◽  
Vibration Signals ◽  
Bearing Fault Diagnosis ◽  
Rolling Element ◽  
Coupled Hidden Markov Models ◽  
Element Bearing ◽  
Fusion Approach

This paper presents a novel multichannel fusion approach based on coupled hidden Markov models (CHMMs) for rolling element bearing fault diagnosis. Different from a hidden Markov model (HMM), a CHMM contains multiple state sequences and observation sequences, and hence has powerful potential for multichannel fusion. In this study, a two-chain CHMM is employed to integrate the two-channel vibration signals collected from bearings, i.e. the horizontal and vertical vibration signals. Efficient probabilistic inference and parameter estimation algorithms are developed for the model. An experiment was carried out to validate the proposed approach. Normalized wavelet packet energy and wavelet packet energy entropy are extracted as features for classification respectively. Then, the results of the proposed approach are compared with those of the currently used approach based on HMMs and one-channel signals. The results show that the proposed approach is feasible and effective to improve the classification rate.

scholarly journals Estimation of the Defect Width on the Outer Race of a Rolling Element Bearing under Time-Varying Speed Conditions

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Guang-Quan Hou ◽  
Chang-Myung Lee
Keyword(s):  
Research Work ◽  
Defect Size ◽  
Remaining Useful Life ◽  
Rolling Element Bearing ◽  
Time Varying ◽  
Entry And Exit ◽  
Outer Race ◽  
Time Frequency ◽  
Rolling Element ◽  
Element Bearing

Fault diagnosis and failure prognostics for rolling element bearing are helpful for preventing equipment failure and predicting the remaining useful life (RUL) to avoid catastrophic failure. Spall size is an important fault feature for RUL prediction, and most research work has focused on estimating the fault size under constant speed conditions. However, estimation of the defect width under time-varying speed conditions is still a challenge. In this paper, a method is proposed to solve this problem. To enhance the entry and exit events, the edited cepstrum is used to remove the determined components. The preprocessed signal is resampled from the time domain to the angular domain to eliminate the effect of speed variation and measure the defect size of a rolling element bearing on outer race. Next, the transient impulse components are extracted by local mean decomposition. The entry and exit points when the roller passes over the defect width on the outer race were identified by further processing the extracted signal with time-frequency analysis based on the continuous wavelet transform. The defect size can be calculated with the angle duration, which is measured from the identified entry and exit points. The proposed method was validated experimentally.

Rolling element bearing fault diagnosis based on multi-scale global fuzzy entropy, multiple class feature selection and support vector machine

2019 ◽  
Vol 41 (14) ◽  
pp. 4013-4022 ◽  
Author(s):  
Keheng Zhu ◽  
Liang Chen ◽  
Xiong Hu
Keyword(s):  
Fault Diagnosis ◽  
Fuzzy Entropy ◽  
Rolling Element Bearing ◽  
Support Vector ◽  
Vibration Signals ◽  
Bearing Fault Diagnosis ◽  
Multi Scale ◽  
Rolling Element ◽  
Element Bearing ◽  
Bearing Vibration

Multi-scale fuzzy entropy (MFE) is a recently developed non-linear dynamic parameter for measuring the complexity of vibration signals of rolling element bearing over different scales. However, the calculation of fuzzy entropy (FuzzyEn) in each scale ignores the sequence’s global characteristics while the bearing vibration signals’ global fluctuation may vary as the bearing runs under different states. Therefore, in this paper, the multi-scale global fuzzy entropy (MGFE) method is put forward for extracting the fault features from the bearing vibration signals. After the feature extraction, multiple class feature selection (MCFS) method is introduced to select the most informative features from the high-dimensional feature vector. Then, a new rolling element bearing fault diagnosis approach is proposed based on MGFE, MCFS and support vector machine (SVM). The experimental results indicate that the proposed approach can effectively fulfill the fault diagnosis of rolling element bearing and has good classification performance.

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.

Advanced Rolling-Element Bearing Diagnostics Based on Cyclic Spectral Analysis

2007 ◽  
Vol 347 ◽  
pp. 265-270
Author(s):  
Jerome Antoni ◽  
Roger Boustany
Keyword(s):  
Background Noise ◽  
Rolling Element Bearing ◽  
Outer Race ◽  
Spectral Signatures ◽  
Bearing Diagnostics ◽  
Rolling Element ◽  
Cyclical Behaviour ◽  
Element Bearing ◽  
Incipient Fault ◽  
Inner Race

Rolling-element bearing vibrations are random cyclostationary, that is they exhibit a cyclical behaviour of their statistical properties while the machine is operating. This property is so symptomatic when an incipient fault develops that it can be efficiently exploited for diagnostics. This paper gives a synthetic but comprehensive discussion about this issue. First, the cyclostationarity of bearing signals is proved from a simple phenomenological model. Once this property is established, the question is then addressed of which spectral quantity can adequately characterise such vibration signals. In this respect, the cyclic coherence - and its multi-dimensional extension in the case of multi-sensors measurements -- is shown to be twice optimal: first to evidence the presence of a fault in high levels of background noise, and second to return a relative measure of its severity. These advantages make it an appealing candidate to be used in adverse industrial environments. The use and interpretation of the proposed tool are then illustrated on actual industrial measurements, and a special attention is paid to describe the typical "cyclic spectral signatures" of inner race, outer race, and rolling-element faults.

scholarly journals Analytical model and spectral characteristics of acoustic emission signal produced by localized fault of rolling element bearing

2021 ◽  
Vol 39 (4) ◽  
pp. 831-838
Author(s):  
Fazhong Li ◽  
Zengshui He ◽  
Lin Zhang ◽  
Anbo Ming ◽  
Yongsheng Yang
Keyword(s):  
Acoustic Emission ◽  
Analytical Model ◽  
High Frequency ◽  
Spectral Characteristics ◽  
Rolling Element Bearing ◽  
Outer Race ◽  
Emission Signal ◽  
Rolling Element ◽  
Excitation Mechanisms ◽  
Element Bearing

The accurate description of acoustic emission signals produced by the localized fault of a rolling element bearing plays an important role in its feature extraction and analysis. This paper analyzes the excitation mechanisms and develops the analytical model of acoustic emission signals produced when the rolling element bearing passes across the localized fault on the inner or outer race. Based on the analytical model, the spectral characteristics are discussed substantially. Simulations and experiments are carried out to validate the efficacy of the model developed in the paper. The experimental results show that the response signal thus produced has two parts. The first one is produced by the entry of the rolling element bearing, while the other is produced by the departure of the rolling element bearing. The energy of both parts is concentrated around the resonance frequency of the acoustic emission transducer. Generally, the interval of adjacent acoustic emission events is not equivalent to each other and the corresponding spectrum is continuous in the high frequency band.

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