Application of Time-Frequency Distributions to the Blind Source Separation of Mechanical Fault Signals
2011 ◽
Vol 383-390
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pp. 395-399
Keyword(s):
In this study, blind source separation (BSS) method was applied to separate the multi-channel fault vibration signals generated by a rotor. As the signals were non-stationary, an algorithm based on spatial time-frequency distributions was applied to the experimental vibration signals to obtain the non-stationary vibration sources that were mutually independent. Further, AR modeling estimates of these sources were calculated with BURG method. A neural network was applied to the AR modeling parameters to perform the fault classification. The separation results of an experiment on a rotor’s multi-fault show that this method is feasible for fault diagnosis.
2012 ◽
Vol 38
(1)
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pp. 175-184
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Keyword(s):
2013 ◽
Vol 6
(3)
◽
pp. 973-992
Keyword(s):
2004 ◽
Vol 11
(3)
◽
pp. 386-389
◽
Keyword(s):