Abstract

Multi-stage gearboxes are vulnerable to failures often due to the extreme operating conditions, which may result in long downtimes. The current investigation is intended to examine the fault diagnostic capabilities of the integrated vibro-acoustic condition monitoring scheme while diagnosing the local/lumped defects exist at different speed stages of a multi-stage gearbox subjected to fluctuating/varying speeds. Experiments are performed, and the raw vibration and acoustic signatures are acquired simultaneously from the three-stage spur gearbox. Later, the raw data signatures are processed individually through discrete wavelet transform, and various descriptive statistics are extracted. Further, feature-level fusion is executed to obtain the integrated vibro-acoustic feature vector set for various speed stages of the gearbox. Finally, the obtained integrated feature vector set is classified using principal component analysis (PCA). It is observed that PCA performed using the integrated vibro-acoustic scheme clearly distinguishes among the various damage severity levels of pinion tooth exist at different speed stages of the gearbox.

References

References
1.
Inturi
,
V.
,
Shreyas
,
N.
,
Chetti
,
K.
, and
Sabareesh
,
G.
,
2020
, “
Comprehensive Fault Diagnostics of Wind Turbine Gearbox Through Adaptive Condition Monitoring Scheme
,”
Appl. Acoust.
,
174
, p.
107738
. 10.1016/j.apacoust.2020.107738
2.
Shao
,
R.
,
Hu
,
W.
,
Wang
,
Y.
, and
Qi
,
X.
,
2014
, “
The Fault Feature Extraction and Classification of Gear Using Principal Component Analysis and Kernel Principal Component Analysis Based on the Wavelet Packet Transform
,”
Measurement
,
54
, pp.
118
132
. 10.1016/j.measurement.2014.04.016
3.
Teng
,
W.
,
Ding
,
X.
,
Zhang
,
X.
,
Liu
,
Y.
, and
Ma
,
Z.
,
2016
, “
Multi-Fault Detection and Failure Analysis of Wind Turbine Gearbox Using Complex Wavelet Transform
,”
Renew. Energy
,
93
, pp.
591
598
. 10.1016/j.renene.2016.03.025
4.
Vamsi
,
I.
,
Sabareesh
,
G.
, and
Penumakala
,
P.
,
2019
, “
Comparison of Condition Monitoring Techniques in Assessing Fault Severity for a Wind Turbine Gearbox Under Non-Stationary Loading
,”
Mech. Syst. Signal Process.
,
124
, pp.
1
20
. 10.1016/j.ymssp.2019.01.038
5.
Henriquez
,
P.
,
Alonso
,
J. B.
,
Ferrer
,
M. A.
, and
Travieso
,
C. M.
,
2013
, “
Review of Automatic Fault Diagnosis Systems Using Audio and Vibration Signals
,”
IEEE Trans. Syst. Man Cybern. Syst.
,
44
(
5
), pp.
642
652
. 10.1109/TSMCC.2013.2257752
6.
Kumbhar
,
S. G.
, and
Sudhagar P
,
E.
,
2021
, “
Fault Diagnostics of Roller Bearings Using Dimension Theory
,”
ASME J. Nondestruct. Eval. Diagnost. Prognost. Eng. Syst.
,
4
(
1
), p.
011001
. 10.1115/1.4047102
7.
Pamwani
,
L.
, and
Shelke
,
A.
,
2018
, “
Damage Detection Using Dissimilarity in Phase Space Topology of Dynamic Response of Structure Subjected to Shock Wave Loading
,”
ASME J. Nondestruct. Eval. Diagnost. Prognost. Eng. Syst.
,
1
(
4
), p.
041004
. 10.1115/1.4040472
8.
Choi
,
S.
, and
Li
,
C. J.
,
2006
, “
Estimation of Gear Tooth Transverse Crack Size From Vibration by Fusing Selected Gear Condition Indices
,”
Meas. Sci. Technol.
,
17
(
9
), pp.
2395
2400
. 10.1088/0957-0233/17/9/004
9.
D’Elia
,
G.
,
Mucchi
,
E.
, and
Cocconcelli
,
M.
,
2017
, “
On the Identification of the Angular Position of Gears for the Diagnostics of Planetary Gearboxes
,”
Mech. Syst. Signal Process.
,
83
, pp.
305
320
. 10.1016/j.ymssp.2016.06.016
10.
Amarnath
,
M.
, and
Krishna
,
I. P.
,
2014
, “
Local Fault Detection in Helical Gears via Vibration and Acoustic Signals Using EMD Based Statistical Parameter Analysis
,”
Measurement
,
58
, pp.
154
164
. 10.1016/j.measurement.2014.08.015
11.
Inturi
,
V.
,
Sabareesh
,
G.
, and
Penumakala
,
P.
,
2020
, “
Bearing Fault Severity Analysis on a Multi-Stage Gearbox Subjected to Fluctuating Speeds
,”
Exp. Tech.
,
44
(
5
), pp.
1852
1865
. 10.1007/s40799-020-00370-z
12.
Jena
,
D.
, and
Panigrahi
,
S.
,
2015
, “
Automatic Gear and Bearing Fault Localization Using Vibration and Acoustic Signals
,”
Appl. Acoust.
,
98
, pp.
20
33
. 10.1016/j.apacoust.2015.04.016
13.
Peng
,
Z.
,
Kessissoglou
,
N.
, and
Cox
,
M.
,
2005
, “
A Study of the Effect of Contaminant Particles in Lubricants Using Wear Debris and Vibration Condition Monitoring Techniques
,”
Wear
,
258
(
11–12
), pp.
1651
1662
. 10.1016/j.wear.2004.11.020
14.
Loutas
,
T.
,
Roulias
,
D.
,
Pauly
,
E.
, and
Kostopoulos
,
V.
,
2011
, “
The Combined Use of Vibration, Acoustic Emission and Oil Debris On-Line Monitoring Towards a More Effective Condition Monitoring of Rotating Machinery
,”
Mech. Syst. Signal Process.
,
25
(
4
), pp.
1339
1352
. 10.1016/j.ymssp.2010.11.007
15.
Nembhard
,
A. D.
,
Sinha
,
J. K.
,
Pinkerton
,
A. J.
, and
Elbhbah
,
K.
,
2014
, “
Combined Vibration and Thermal Analysis for the Condition Monitoring of Rotating Machinery
,”
Struct. Health. Monit.
,
13
(
3
), pp.
281
295
. 10.1177/1475921714522843
16.
Inturi
,
V.
,
Sabareesh
,
G.
,
Supradeepan
,
K.
, and
Penumakala
,
P.
,
2019
, “
Integrated Condition Monitoring Scheme for Bearing Fault Diagnosis of a Wind Turbine Gearbox
,”
J. Vib. Control
,
25
(
12
), pp.
1852
1865
. 10.1177/1077546319841495
17.
Biswal
,
S.
, and
Sabareesh
,
G. R.
,
2015
, “
Design and Development of a Wind Turbine Test Rig for Condition Monitoring Studies
,”
2015 International Conference on Industrial Instrumentation and Control (ICIC)
,
Pune, India
,
May 28–30
,
IEEE
, pp.
891
896
.
18.
Heyns
,
P. S.
,
Vinson
,
R.
, and
Heyns
,
T.
,
2016
, “
Rotating Machine Diagnosis Using Smart Feature Selection Under Nonstationary Operating Conditions
,”
Insight Non Destruct. Test. Cond. Monitor.
,
58
(
8
), pp.
417
422
. 10.1784/insi.2016.58.8.417
19.
Praveen
,
G.
,
Vamsi
,
I.
,
Suresh
,
K.
, and
Radhika
,
S.
,
2020
, “
Evaluation of Surface Roughness in Incremental Forming Using Image Processing Based Methods
,”
Measurement
,
164
, p.
108055
. 10.1016/j.measurement.2020.108055
20.
Bandara
,
S.
,
Rajeev
,
P.
,
Gad
,
E.
, and
Sriskantharajah
,
B.
,
2021
, “
Damage Severity Estimation of Timber Poles Using Stress Wave Propagation and Wavelet Entropy Evolution
,”
ASME J. Nondestruct. Eval. Diagnost. Prognost. Eng. Syst.
,
4
(
1
), p.
011006
. 10.1115/1.4048148
21.
Yan
,
R.
, and
Gao
,
R. X.
,
2009
, “
Multi-Scale Enveloping Spectrogram for Vibration Analysis in Bearing Defect Diagnosis
,”
Tribol. Int.
,
42
(
2
), pp.
293
302
. 10.1016/j.triboint.2008.06.013
22.
Balavignesh
,
V.
,
Gundepudi
,
B.
,
Sabareesh
,
G.
, and
Vamsi
,
I.
,
2018
, “
Comparison of Conventional Method of Fault Determination With Data-Driven Approach for Ball Bearings in a Wind Turbine Gearbox
,”
Int. J. Performability Eng.
,
14
(
3
), pp.
397
412
. 10.23940/ijpe.18.03.p1.397412
23.
Kankar
,
P. K.
,
Sharma
,
S. C.
, and
Harsha
,
S. P.
,
2011
, “
Fault Diagnosis of Ball Bearings Using Machine Learning Methods
,”
Expert Syst. Appl.
,
38
(
3
), pp.
1876
1886
. 10.1016/j.eswa.2010.07.119
24.
Inturi
,
V.
,
Sachin
,
P. R.
, and
Sabareesh
,
G. R.
,
2020
, “
Supervised Feature Selection Methods for Fault Diagnostics at Different Speed Stages of a Wind Turbine Gearbox
,”
International Conference on Modelling, Simulation and Intelligent Computing
,
Dubai, UAE
,
Jan. 29–31
, Springer
,
Singapore
, pp.
478
486
.
25.
Sugumaran
,
V.
, and
Ramachandran
,
K.
,
2011
, “
Fault Diagnosis of Roller Bearing Using Fuzzy Classifier and Histogram Features With Focus on Automatic Rule Learning
,”
Expert Syst. Appl.
,
38
(
5
), pp.
4901
4907
. 10.1016/j.eswa.2010.09.089
26.
Mustapha
,
S.
,
Braytee
,
A.
, and
Ye
,
L.
,
2018
, “
Multisource Data Fusion for Classification of Surface Cracks in Steel Pipes
,”
ASME J. Nondestruct. Eval. Diagnost. Prognost. Eng. Syst.
,
1
(
2
), p.
021007
. https://doi.org/10.1115/1.4038862
27.
Liu
,
R.
,
Yang
,
B.
,
Zio
,
E.
, and
Chen
,
X.
,
2018
, “
Artificial Intelligence for Fault Diagnosis of Rotating Machinery: A Review
,”
Mech. Syst. Signal Process.
,
108
, pp.
33
47
. 10.1016/j.ymssp.2018.02.016
28.
Saimurugan
,
M.
,
Ramachandran
,
K.
,
Sugumaran
,
V.
, and
Sakthivel
,
N.
,
2011
, “
Multi Component Fault Diagnosis of Rotational Mechanical System Based on Decision Tree and Support Vector Machine
,”
Expert Syst. Appl.
,
38
(
4
), pp.
3819
3826
. 10.1016/j.eswa.2010.09.042
29.
Safizadeh
,
M.
, and
Latifi
,
S.
,
2014
, “
Using Multi-Sensor Data Fusion for Vibration Fault Diagnosis of Rolling Element Bearings by Accelerometer and Load Cell
,”
Inf. Fusion
,
18
, pp.
1
8
. 10.1016/j.inffus.2013.10.002
30.
Lee
,
S. B.
,
Kang
,
W.
, and
Sung
,
H. J.
,
2008
, “
Organized Self-Sustained Oscillations of Turbulent Flows Over an Open Cavity
,”
AIAA J.
,
46
(
11
), pp.
2848
2856
. 10.2514/1.36860
31.
Supradeepan
,
K.
, and
Roy
,
A.
,
2014
, “
Characterisation and Analysis of Flow Over Two Side by Side Cylinders for Different Gaps at Low Reynolds Number: A Numerical Approach
,”
Phys. Fluids
,
26
(
6
), p.
063602
. 10.1063/1.4883484
You do not currently have access to this content.