AR filter + Minimum Entropy Deconvolution for Bearing Fault Diagnosis
This function AR_MED_FILTER takes input SIGNAL with Sampling Frequency, Fs, and applies the Yule Walker method based AR filter. The order if the filter is found by Maximum kurtosis. After the application od AR filter, the signal is passed through Minimum Entropy Deconvolution. This combined AR+MED method brings out the Bearing faults hidden in Noise.
The function plots two figures for AR alone and another for AR+MED
Example:
load('s4.mat');
signal=s4;
Fs=12000;
ar_med_filter(signal,Fs);
The File 's4.mat' is the vibration signal recorded from a OR faulty bearing with a sampling frequency of 12000Hz. The Fault frequency is 161 Hz and is brought out.
This program isa based on the paper:
Sawalhi N, Randall RB and Endo H (2007) The enhancement of fault detection and diagnosis in rolling element bearings using minimum entropy deconvolution combined with spectral kurtosis. Mechanical Systems and Signal Processing. 21:2616-2633
This function is basically written for Bearing fault diagnosis from Vibration signal.
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http://www.mathworks.in/matlabcentral/fileexchange/authors/258518
Author:Santhana Raj.A
https://sites.google.com/site/santhanarajarunachalam/
Cite As
Santhana Raj (2024). AR filter + Minimum Entropy Deconvolution for Bearing Fault Diagnosis (https://www.mathworks.com/matlabcentral/fileexchange/41614-ar-filter-minimum-entropy-deconvolution-for-bearing-fault-diagnosis), MATLAB Central File Exchange. Retrieved .
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- Signal Processing > Signal Processing Toolbox > Transforms, Correlation, and Modeling > Signal Modeling >
- Control Systems > Predictive Maintenance Toolbox >
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Acknowledgements
Inspired by: med2d(x,filterSize,termIter,termDelta,overlapMode,plotMode)
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Version | Published | Release Notes | |
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1.0.0.0 |