Signal Processing Techniques to Improve an Acoustic Emissions Sensor

Eric Bechhoefer, Yongzhi Qu, Junda Zhu, and David He
Submission Type: 
Full Paper
AttachmentSizeTimestamp
phmc_13_003.pdf641.84 KBOctober 10, 2013 - 6:39pm

Acoustic Emissions (AE) are stress waves produced by the
sudden internal stress redistribution of material caused by
changes in the internal structure of the material. Possible
causes of these changes are crack initiation and growth,
crack opening/closure, or pitting in monolithic materials
(gear/ bearing material). Where as vibration can measure the
effect of damage, AE is a direct measure of damage.
Unfortunately, AE methodologies suffer from the need of
high sample rates (4 to 10 Msps) and relatively immature
algorithms for condition indictors (CI). This paper
hypothesizes that the AE signature is the result of some
forcing function (e.g. periodic motion in the case of rotating
machinery). By using signal processing to demodulating the
AE signature, one can reconstruct the information carried by
the AE signature and provide improved diagnostics. As
most on-line condition monitoring systems are embedded
system, analog signal processing techniques are proposed
which reduce the effective sample rate needed to operate on
the AE signal to those similarly found in traditional
vibration processing systems. Further, by implementing
another signal processing technique, time synchronous
averaging, the AE signal is further enhanced. This
hypothesis is tested on a split torque gearbox and results are
presented.

Publication Year: 
2013
Publication Volume: 
4
Publication Control Number: 
003
Page Count: 
8
Submission Keywords: 
Acoustic Emissions
Envelope Analysis
Time Synchronous Averaging (TSA)
gear fault detection
Submission Topic Areas: 
Component-level PHM
Submitted by: 
  
 
 
 

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