Application of Independent Component Analysis in Rolling Element Bearing Vibration Signal Analysis

2010 ◽  
pp. 117-122
Author(s):  
Xianguang Tang ◽  
Yu Guo ◽  
Yanchun Ding ◽  
Huawen Zheng ◽  
Yan Gao
Keyword(s):  
Independent Component Analysis ◽  
Signal Analysis ◽  
Vibration Signal ◽  
Component Analysis ◽  
Independent Component ◽  
Rolling Element Bearing ◽  
Rolling Element ◽  
Element Bearing ◽  
Bearing Vibration ◽  
Vibration Signal Analysis

A Novel Threshold for the Diagnostics of Rolling Element Bearing

2014 ◽  
Author(s):  
P. Borghesani ◽  
S. Chatterton ◽  
P. Pennacchi ◽  
A. Vania
Keyword(s):  
Signal Analysis ◽  
Damage Index ◽  
Vibration Signal ◽  
Rolling Element Bearing ◽  
Rolling Element ◽  
Element Bearing ◽  
Vibration Signal Analysis ◽  
Definition Of ◽  
Envelope Spectrum ◽  
Damage Type

The identification of the damage type in rolling element bearings is usually performed by means of suitable vibration signal analysis tools such as the most used and simplest method, Envelope Analysis through the corresponding Square Envelope Spectrum. The diagnostics and the monitoring of the bearing health are often performed by means of other approaches based on the evaluation of a damage index as the root mean square, the Kurtosis of the filtered signal, or more efficient indexes as the so-called Ratio of Cyclic Content. At any rate, in the case of real-time diagnostics, the definition of a threshold for the assessment of the bearing health is mandatory due to the presence in the vibration signal of additional sources and noises. In the paper, a threshold for the band-Kurtosis index that depends only on the sampling frequency and the bandwidth of the filter used for the demodulation of the vibration signal has been introduced. The effectiveness of the threshold has been proven by the experimental data of a damaged bearing.

A fault diagnosis method for rolling element bearing (REB) based on reducing REB foundation vibration and noise-assisted vibration signal analysis

2018 ◽  
Vol 233 (7) ◽  
pp. 2574-2587 ◽  
Author(s):  
Heng-di Wang ◽  
Si-er Deng ◽  
Jian-xi Yang ◽  
Hui Liao
Keyword(s):  
Fault Diagnosis ◽  
Empirical Mode Decomposition ◽  
Vibration Signal ◽  
Rolling Element Bearing ◽  
Mode Decomposition ◽  
Rolling Element ◽  
Foundation Vibration ◽  
Diagnosis Method ◽  
Element Bearing ◽  
Vibration Signal Analysis

Owing to the problem of the incipient fault characteristics being difficult to be extracted from the raw vibration signal of rolling element bearing, based on the empirical mode decomposition and kurtosis criteria, a fault diagnosis method for rolling element bearing is proposed by reducing rolling element bearing foundation vibration and noise-assisted vibration signal analysis. Firstly, rolling element bearing vibration signal is decomposed into a set of intrinsic mode functions using empirical mode decomposition and the intrinsic mode function component with the maximal kurtosis value is selected. Afterwards, zero mean normalization is applied to the selected intrinsic mode function component, and then the intrinsic mode function’s foundation vibration components within [Formula: see text] are removed to minimize the interference. In order to eliminate interruption and intermittency after removal of the foundation vibration components, white noise is added to the newly generated signal. The noise-added signal is decomposed via empirical mode decomposition, and later on, IMF1 with the highest frequency band is selected and demodulated using envelope analysis. The resulting envelope spectrum can show more significant fault pulse characteristics, which are highly helpful to diagnose the rolling element bearing incipient faults. The proposed method in this paper was applied to the fault diagnosis for low noise REB 6203 and the testing results showed that the method could identify the rolling element bearing incipient faults accurately and quickly.

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.

scholarly journals Vibration analysis based on the spectrum kurtosis for adjustment and monitoring of ball bearing radial clearance

2018 ◽  
Vol 211 ◽  
pp. 06006 ◽  
Author(s):  
Anthimos Georgiadis ◽  
Xiaoyun Gong ◽  
Nicolas Meier
Keyword(s):  
Signal Analysis ◽  
Vibration Signal ◽  
Radial Clearance ◽  
Spectral Kurtosis ◽  
Vibration Data ◽  
Bearing Clearance ◽  
Bearing Condition Monitoring ◽  
Bearing Vibration ◽  
Vibration Signal Analysis

Vibration signal analysis is a common tool to detect bearing condition. Effective methods of vibration signal analysis should extract useful information for bearing condition monitoring and fault diagnosis. Spectral kurtosis (SK) represents one valuable tool for these purposes. The aim of this paper is to study the relationship between bearing clearance and bearing vibration frequencies based on SK method. It also reveals the effect of the bearing clearance on the bearing vibration characteristic frequencies This enables adjustment of bearing clearance in situ, which could significantly affect the performance of the bearings. Furthermore, the application of the proposed method using SK on the measured data offers useful information for predicting bearing clearance change. Bearing vibration data recorded at various clearance settings on a floating and a fixed bearing mounted on a shaft are the basis of this study

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