scholarly journals Diagnostics 101: A Tutorial for Fault Diagnostics of Rolling Element Bearing Using Envelope Analysis in MATLAB

2020 ◽  
Vol 10 (20) ◽  
pp. 7302
Author(s):  
Seokgoo Kim ◽  
Dawn An ◽  
Joo-Ho Choi
Keyword(s):  
Process Simulation ◽  
Rolling Element Bearing ◽  
Fault Identification ◽  
New Developments ◽  
Envelope Analysis ◽  
Practical Applications ◽  
Spectral Kurtosis ◽  
Rolling Element ◽  
Element Bearing ◽  
Simulation Signal

This paper presents a MATLAB-based tutorial to conduct fault diagnosis of a rolling element bearing. While there have been so many new developments in this field, no studies have addressed the tutorial aspects in this field to help the engineers learn the concept and implement by their own effort. The three most common techniques—the autoregressive model, spectral kurtosis, and envelope analysis—are selected to demonstrate the bearing diagnosis process. Simulation signal is introduced to help understand the characteristics of fault signal and carry out the process toward the fault identification. The techniques are then applied to the two real datasets to demonstrate the practical applications, one made by the authors and the other by the Case Western Reserve University, which is known as a standard reference in testing the diagnostic algorithms.

Rolling element bearing diagnosis using spectral kurtosis based on optimized impulse response wavelet

2019 ◽  
Vol 26 (3-4) ◽  
pp. 175-185 ◽  
Author(s):  
Abbas Rohani Bastami ◽  
Amir Bashari
Keyword(s):  
Impulse Response ◽  
Great Influence ◽  
Rolling Element Bearing ◽  
Envelope Analysis ◽  
Spectral Kurtosis ◽  
Vibration Data ◽  
Resonance Band ◽  
Rolling Element ◽  
Element Bearing ◽  
Short Time

Envelope analysis is widely used in fault diagnosis of rolling element bearings (REBs). In envelope analysis, it is necessary to select a frequency band which is related to the resonance of the bearing. Spectral kurtosis (SK) is known as a powerful method to find the resonance band in vibration of a defective REB. SK, calculated by short time Fourier transform, suffers from its dependency on the window length. In this article, a special wavelet transform is used to obtain a SK diagram. It is shown that choice of mother wavelet function has great influence on the resulting SK diagram. The proposed wavelet is based on the impulse response of a damped single degree of freedom system. An optimization algorithm is used to optimize the SK diagram for fault detection. The method is tested for both simulated and experimental vibration data.

Cyclic Spectrum Analysis on Rolling-Element Bearing with Inner-Race Point Defect

2011 ◽  
Vol 291-294 ◽  
pp. 1469-1473
Author(s):  
Wei Ke ◽  
Yong Xiang Zhang ◽  
Lin Li
Keyword(s):  
Point Defect ◽  
Signal To Noise Ratio ◽  
Vibration Signal ◽  
Rolling Element Bearing ◽  
Bearing Fault ◽  
Rolling Element ◽  
Element Bearing ◽  
Simulation Signal ◽  
Inner Race ◽  
Cyclic Spectrum

Vibration signal of rolling-element bearing is random cyclostationarity when a fault develops, the proper analysis of which can be used for condition monitor. Cyclic spectrum is a common cyclostationary analysis method and has a great many algorithms which have distinct efficiency in different application circumstance, two common algorithms (SSCA and FAM) are compared in the paper. The FAM is recommended to be used in diagnosing rolling-element bearing fault via calculation of simulation signal in different signal to noise ratio. The cyclic spectrum of practice signal of rolling-element bearing with inner-race point defect is analyzed and a new characteristic extraction method is put forward. The preferable result is acquired verify the correctness of the analysis and indicate that the cyclic spectrum is a robust method in diagnosing rolling-element bearing fault.

Envelope Analysis Using the Teager-Kaiser Energy Operator for Condition Monitoring of a Wind Turbine Bearing

2014 ◽  
Vol 564 ◽  
pp. 170-175 ◽  
Author(s):  
Ifigeneia Antoniadou ◽  
Thomas P. Howard ◽  
R.S. Dwyer-Joyce ◽  
Matthew B. Marshall ◽  
Jack Naumann ◽  
...  
Keyword(s):  
Energy Operator ◽  
Rolling Element Bearing ◽  
Envelope Analysis ◽  
Novel Approach ◽  
Rolling Element ◽  
Element Bearing ◽  
The Hilbert Transform ◽  
Frequency Demodulation ◽  
Signal Processing Methods ◽  
Demodulation Method

Different signal processing methods are applied to experimental data obtained from a rolling element bearing rig in order to perform damage detection. Among these methods the Teager-Kaiser energy operator is also proposed as a more novel approach. This energy operator is an amplitude-frequency demodulation method used in this paper as an alternative to the Hilbert Transform in order to perform envelope analysis on the datasets analysed.

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