UNCLASSIFIED
UNCLASSIFIED
EXPERIMENTAL METHODS FOR
MULTI-GENRE NETWORKS
Acoustic Emission Analysis of Fuel Pumps
Roman Madoerin
Materials Science and Engineering
University of North Texas
ARL Mentor: Dr. Stephen Berkebile
Directorate / Division: VTD / VICTOR ERP
Project Duration: 06/01/2020 to 08/21/2020
• Unmanned Aerial Systems rely on high pressure fuel source to
operate
• Substandard fuels cause damage and failure
– Scuffing is a major source of damage
– Fuel pumps experience failure through scuffing
– When they fail, the engine doesn’t receive enough fuel
• We will:
– Run different fuels in drone engines
• Substandard fuels (ethanol and dodecane)
• Observe failure mechanisms using Acoustic Emission
• Goal: Demonstrate Acoustic Emission (AE) can distinguish
failure mechanisms
– First, need to understand normal operating signal
Stalker Unmanned
Aerial System (UAS)
Scuffing on a high-pressure
fuel pump piston.
• Material micromechanical events create high
frequency soundwaves
• These waves propagate through the material
• Record ultrasound waves at the surface with the
sensor
• Uses:
– Detect cracks during tensile and compression testing
– Detect changes in sliding mechanical interfaces
Acoustic emission testing of tensile test.
Example AE comparison
• AE signal always present at sliding interfaces
• Signal changes when damage is present
• Easily distinguishable differences between signals
• Three data types
– Raw acoustic emission (AE)
– Tachometer- one tic per rotation
– Tachometer- one tic per degree of rotation
• Establish baseline
– Discover patterns
– Make calculations
– Compare data sets
• Acoustic emission and tachometer data
– Plot raw data
• Observe signal patterns
– Calculations
• Speed
• Root mean square (RMS)
• Bandpass Filter to compare RMS at frequency
ranges
• Correlation of AE peaks to tachometer signal
• No AE data of failing fuel pumps yet
– More data collected in future
• Challenging transposing the tachometer signal
– MATLAB has a lot of useful functions for this
– Abundance of noise and peak splitting
– Difficult to distinguish peaks
• Top graph-2940 RPM
• Bottom graph-1100 RPM
• Slower speed has fewer
peaks
• Also lower base signal
• Tachometer signal
• AE vs. angle and speed vs time
Speed correlated to AE frequency
• Angle between the peaks is analyzed
• When angle distribution is plotted, a pattern arises
• Understanding baseline signal
• AE peak frequency correlated to speed
– Speed determined from the AE data
– More noise at high speeds
• Fourier transform shows frequencies
– Majority of activity at 100-300 kHz
• Angle increment correlation to the AE peaks
– Peaks occur at specific angles
– Two distinct correlation locations
TAKE HOME MESSAGE
Regular signal characteristics exist that
will help locate damage indicators
• We will plot the AE signal and tachometer data over
the whole test
• More angle correlation analysis
• More Fourier transform analysis
• Analyze pressure data
• Get more data to look for failure mechanisms
Background Background
Background Objectives Technical Approach
ChallengesResults and Discussion
Results and Discussion
Results and Discussion Results and Discussion
• Angle between the peaks is analyzed
• When angle distribution is plotted, a pattern arises
Results and Discussion
Results and Discussion Conclusion
Next Steps
AE sensor
Pressure censor
Fuel pump and sensors
AE vs time plot Zoomed view of AE peak
2940 RPM AE signal
1100 RPM AE signal
Speed vs time plot
Image of example tachometer Top dead center tachometer data
Moving average speed vs. timeAE intensity vs. rising angle
AE vs angle plot (2940 RPM) Zoomed view
Angle spacing data
Angle distribution (2940 RPM) Angle distribution 1100RPM)
RMS=0.4389
RMS=0.8504
Bandpass ratios at different frequencies
RMS and speed data
(Top) Stalker XE UAS. (n.d.). Retrieved July 23, 2020, from
https://www.lockheedmartin.com/en-us/products/stalker.html
(Bottom) Source: CCDC ARL.
Prognosis, M. (2018, July 21). Acoustic Emission
Testing Market Globally Grow at a CAGR of 7.5% by
2025: Top Key Players (Olympus, MISTRAS Group,
SGS SA, GE, X-R-I Testing, Applus+, Arcadia
Aerospace, Exova Group, Acuren, COMET, Ashtead
Technology). Retrieved June 29, 2020, from
https://www.openpr.com/news/1138684/acoustic-
emission-testing-market-globally-grow-at-a-cagr-of-7-5-
by-2025-top-key-players-olympus-mistras-group-sgs-sa-
ge-x-r-i-testing-applus-arcadia-aerospace-exova-group-
acuren-comet-ashtead-technology.html
Dykas, B., & Harris, J.
(2017). Acoustic emission
characteristics of a single
cylinder diesel generator at
various loads and with a
failing injector. Mechanical
Systems and Signal
Processing, 93, 397-414.
doi:10.1016/j.ymssp.2017.01.
049
Retrieved July 21, 2020, from
http://zone.ni.com/reference/
en-XX/help/372416L-
01/svtconcepts/svspeedfreq/
