Abstract

Owing to the frequency of occurrence and high risk associated with bearings, identification, and characterization of bearing faults in motors via nondestructive evaluation (NDE) methods have been studied extensively, among which vibration analysis has been found to be a promising technique for early diagnosis of anomalies. However, a majority of the existing techniques rely on vibration sensors attached onto or in close proximity to the motor in order to collect signals with a relatively high SNR. Due to weight and space restrictions, these techniques cannot be used in unmanned aerial vehicles (UAVs), especially during flight operations since accelerometers cannot be attached onto motors in small UAVs. Small UAVs are often subjected to vibrational disturbances caused by multiple factors such as weather turbulence, propeller imbalance, or bearing faults. Such anomalies may not only pose risks to UAV’s internal circuitry, components, or payload, they may also generate undesirable noise level particularly for UAVs expected to fly in low-altitudes or urban canyon. This paper presents a detailed discussion of challenges in in-flight detection of bearing failure in UAVs using existing approaches and offers potential solutions to detect overall vibration anomalies in small UAV operations based on IMU data.

References

References
1.
Kopardekar
,
P.
,
Rios
,
J.
,
Prevot
,
T.
,
Johnson
,
M.
,
Jung
,
J.
, and
Robinson
,
J. E.
,
2016
, “
Unmanned Aircraft System Traffic Management (UTM) Concept of Operations
,”
AIAA Aviation Forum
,
AIAA
, p.
3292
.
2.
FAA
,
2018
, “
Unmanned Aerial System (UAS) Traffic Management (UTM), Concept of Operations
,”
Federal Aviation Administration
,
Technical Report
.
3.
Corbetta
,
M.
,
Banerjee
,
P.
, and
Luchinsky
,
D. G.
,
2019
, “
Real-Time UAV Trajectory Prediction for Safety Monitoring in Low-Altitude Airspace
,”
AIAA Aviation 2019 Forum
, p.
3514
.
4.
Banerjee
,
P.
, and
Corbetta
,
M.
,
2020
, “
In-Time UAV Flight-Trajectory Estimation and Tracking Using Bayesian Filters
,”
2020 IEEE Aerospace Conference
.
5.
NASA
,
2017
, “
Aeronautics Research Mission Directoratestrategic Implementation Plan
,”
[Online]
https://www.nasa.gov/aeroresearch/strategy
6.
Freeman
,
P. M.
,
2014
, “
Reliability Assessment for Lowcost Unmanned Aerial Vehicles
.”
7.
NASA Goddard Space Flight Center
,
Greenbelt
,
M. U.
,
2009
, “
Flight Assurance Procedure p-302-720: Performing a Failure Modes and Effects Analysis
.”
8.
Byers
,
C. C.
, and
Salgueiro
,
G.
,
2017
, “
Pre-Flight Self Test for Unmanned Aerial Vehicles (UAVS)
,”
Jan
.
10
. U.S. Patent No. 9,540,121.
9.
Qiu
,
H.
,
Lee
,
J.
,
Lin
,
J.
, and
Yu
,
G.
,
2006
, “
Wavelet Filter-Based Weak Signature Detection Method and its Application on Rolling Element Bearing Prognostics
,”
J. Sound Vib.
,
289
(
4–5
), pp.
1066
1090
. 10.1016/j.jsv.2005.03.007
10.
Kumar
,
A.
, and
Kumar
,
R.
,
2020
, “
Signal Processing for Enhancing Impulsiveness Towards Estimating Location of Multiple Roller Defects in a Taper Roller Bearing
,”
ASME J. Nondestruct. Eval., Diag. Prognostics Eng. Syst.
,
3
(
1
), p.
011003
. 10.1115/1.4045010
11.
Yan
,
R.
, and
Gao
,
R. X.
,
2008
, “
Rotary Machine Health Diagnosis Based on Empirical Mode Decomposition
,”
ASME J. Vib. Acoust.
,
130
(
2
), p.
21007
. 10.1115/1.2827360
12.
Liu
,
J.
,
Wang
,
W.
, and
Golnaraghi
,
F.
,
2008
, “
An Extended Wavelet Spectrum for Bearing Fault Diagnostics
,”
IEEE Trans. Instrum. Measure.
,
57
(
12
), pp.
2801
2812
. 10.1109/TIM.2008.927211
13.
Yu
,
Y.
,
Dejie
,
Y.
, and
Junsheng
,
C.
,
2006
, “
A Roller Bearing Fault Diagnosis Method Based on Emd Energy Entropy and ANN
,”
J. Sound. Vib.
,
294
(
12
), pp.
269
277
. 10.1016/j.jsv.2005.11.002
14.
Caciotta
,
M.
,
Cerqua
,
V.
,
Leccese
,
F.
,
Giarnetti
,
S.
,
De Francesco
,
E.
,
De Francesco
,
E.
, and
Scaldarella
,
N.
,
2014
, “
A First Study on Prognostic System for Electric Engines Based on Envelope Analysis
,”
2014 IEEE Metrology for Aerospace (MetroAeroSpace)
,
IEEE
, pp.
362
366
.
15.
Lee
,
J.
,
Qiu
,
H.
,
Yu
,
G.
, and
Lin
,
J.
,
2009
, “
Rexnord Technical Services (2007), “Bearing Data Set”, IMS, University of Cincinnati. NASA AMES Prognostics Data Repository
.”
16.
ArduPilot-Dev-Team
,
2019
, “
Measuring Vibration
,” https://ardupilot.org/copter/docs/common-measuringvibration.html
17.
Bondyra
,
A.
,
Gasior
,
P.
,
Gardecki
,
S.
, and
Kasiński
,
A.
,
2017
, “
Fault Diagnosis and Condition Monitoring of UAV Rotor Using Signal Processing
,”
2017 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)
,
IEEE
, pp.
233
238
.
18.
Banerjee
,
P.
,
Chakraborty
,
D.
, and
Rinker
,
T.
,
2017
, “
Damage Detection Using Time-Frequency Decayrate Based Features
,”
IEEE International Conference on Prognostics and Health Management (ICPHM)
,
IEEE
, pp.
143
147
.
You do not currently have access to this content.