This paper investigates a variety of signal-monitoring and data-driven processing techniques to classify seed faults imposed on floating ring main crankshaft compressor bearings. Simulated main bearing shaft motion using an adaptation of the mobility method is first applied to demonstrate the plausibility of the method. Condition monitoring for three different fault types is experimentally investigated through seeded fault testing. A novel method for feature extraction utilizes a fast Fourier frequency-domain transformation coupled with a binning method that uses information across the entire frequency range. A principal component transformation process is then applied to reduce the dimension of the frequency-based feature vector to a small set of generalized features. A Bayesian classifier on the generalized features designed through seeded fault training data is shown to have excellent classifier performance across all fault types. A single-axis position measurement of the crankshaft shows the most promising results compared to a traditional accelerometer on the bearing housing and a novel accelerometer on the crankshaft. The single-axis measurement provides a cost-efficient alternative method to the two-axis orbit measurement typically used for traditional journal bearings.

References

References
1.
Yang
,
B.
,
Han
,
T.
,
An
,
J.-L.
,
Kim
,
H.-C.
, and
Ahn
,
B.-H.
,
2004
, “
Technical Note: A Condition Classification System for Reciprocating Compressors
,”
Struct. Health Monit.
,
3
(
3
), pp. 
277
284
.10.1177/1475921704045628
2.
Ahmed
,
M.
,
Gu
,
F.
, and
Ball
,
A.
,
2011
, “
Feature Selection and Fault Classification of Reciprocating Compressors Using a Genetic Algorithm and Probabilistic Neural Network
,”
J. Phys.: Conf. Ser.
,
305
(
1
), pp. 
1
12
.
3.
Jiang
,
X. F.
,
Qiu
,
Z. H.
, and
Zong
,
Y.
,
2011
, “
Air Compressor Wear Condition Monitoring Based on Oil Analysis Technology
,”
Appl. Mech. Mater.
,
66–68
, pp. 
498
503
.
4.
Kaewkongka
,
T.
,
Joe Au
,
Y. H.
,
Rakowski
,
R. T.
, and
Jones
,
B. E.
,
2003
, “
A Comparative Study of Short Time Fourier Transform and Continuous Wavelet Transform for Bearing Condition Monitoring
,”
Int. J. COMADEM
,
6
(
1
), pp. 
41
48
.
5.
Parnell
,
V. L.
,
Boedo
,
S.
,
Kempski
,
M. H.
,
Kochersberger
,
K. B.
, and
Haselkorn
,
M. H.
,
2007
, “
Health Monitoring of LAV Planet Gear Bushings Using Vibration Signature Analysis Techniques
,”
SAE 2007 Commercial Vehicle Engineering Congress and Exhibition
,
Rosemont, IL
,
SAE International
.
6.
Yang
,
D.-M.
,
Stronach
,
A. F.
,
Macconnell
,
P.
, and
Penman
,
J.
,
2002
, “
Third-Order Spectral Techniques for the Diagnosis of Motor Bearing Condition Using Artificial Neural Networks
,”
Mech. Syst. Sig. Process.
,
16
(
2–3
), pp. 
391
411
.10.1006/mssp.2001.1469
7.
Luo
,
G. Y.
,
Osypiw
,
D.
, and
Irle
,
M.
,
2003
, “
On-Line Vibration Analysis with Fast Continuous Wavelet Algorithm for Condition Monitoring of Bearing
,”
J. Vib. Control
,
9
(
8
), pp. 
931
947
. 1077-546310.1177/10775463030098002
8.
Tandon
,
N.
, and
Parey
,
A.
,
2006
, “Condition Monitoring of Rotary Machines,”
Condition Monitoring and Control for Intelligent Manufacturing
,
L. Whang
, and
R. Gao
, eds.,
Springer Series in Advanced Manufacturing
,
London
, pp. 
109
136
.
9.
Chen
,
Y.
,
Du
,
R.
, and
Qu
,
L.
,
1995
, “
Fault Features of Large Rotating Machinery and Diagnosis Using Sensor Fusion
,”
J. Sound Vib.
,
188
(
2
), pp. 
227
242
. 0022-460X10.1006/jsvi.1995.0588
10.
Rohde
,
S. M.
, and
Ezzat
,
H. A.
,
1980
, “
Analysis of Dynamically Loaded Floating-Ring Bearings for Automotive Applications
,”
ASME J. Lubr. Technol.
,
102
(
3
), pp. 
271
276
. 0022-230510.1115/1.3251501
11.
Kumar
,
A.
, and
Booker
,
J. F.
,
1991
, “
A Finite Element Cavitation Algorithm
,”
ASME J. Tribol.
,
113
(
2
), pp. 
276
286
.10.1115/1.2920617
12.
Booker
,
J. F.
,
1971
, “
Dynamically-Loaded Journal Bearings: Numerical Application of the Mobility Method
,”
ASME J. Lubr. Technol.
,
93
(
1
), pp. 
168
176
.10.1115/1.3451507
13.
Goenka
,
P. K.
,
1984
, “
Analytical Curve Fits for Solution Parameters of Dynamically Loaded Journal Bearings
,”
ASME J. Tribol.
,
106
(
4
), pp. 
421
427
.10.1115/1.3260950
14.
Holzenkamp
,
M.
,
2013
, “
Modeling and Condition Monitoring of Fully Floating Reciprocating Compressor Main Bearings Using Data Driven Classification
,”
Rochester Institute of Technology
, Rochester, NY.
15.
Chirico
,
A. J.
, and
Kolodziej
,
J. R.
,
2012
, “
Fault Detection and Isolation for Electro-Mechanical Actuators Using a Data-Driven Bayesian Classification
,”
SAE Int. J. Aerosp.
,
5
(
2
), pp. 
494
502
.10.4271/2012-01-2215
16.
De Boe
,
P.
, and
Golinval
,
J.-C.
,
2003
, “
Principal Component Analysis of a Piezosensor Array for Damage Localization
,”
Struct. Health Monit.
,
2
(
2
), pp. 
137
144
.10.1177/1475921703002002005
17.
van der Heijden
,
F.
,
Duin
,
R.
,
de Ridder
,
D.
, and
Tax
,
D.
,
2004
,
Classification, Parameter Estimation and State Estimation an Engineering Approach Using Matlab
,
Wiley
,
Chichester, England
.
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