Abstract

In this paper, the application of neural networks and fuzzy logic to the diagnosis of faults in rotating machinery is investigated. The learning-vector-quantization (LVQ) neural network is applied in series and in parallel to a fuzzy inference engine, to diagnose 1x faults. The faults investigated are unbalance, misalignment, and structural looseness. The method is applied to a test rig (Hassan et al., 2003, ASME Paper No. GT 2003-38450), and the effectiveness of the integrated Neural Network and Fuzzy Logic method is illustrated.

1.
El-Shafei
,
A.
, and
Rieger
,
N.
, 2003, “
Automated Diagnostics of Rotating Machinery
,” presented at ASME Turbo Expo, Atlanta, GA, ASME Paper No. GT 2003-38453.
2.
Mobley
,
R. K.
, 1990,
An Introduction to Predictive Maintenance
,
Van Nostrand Reinhold
, New York.
3.
Mitchell
,
J. S.
, 1993,
An Introduction to Machinery Analysis and Monitoring
, 2nd ed.,
PennWell Books
, Tulsa, OK.
4.
Li
,
C. J.
, and
Fan
,
Y.
, 1999, “
Recurrent Neural Networks for Fault Diagnosis and Severity Assessment of a Screw Compressor
,”
ASME J. Dyn. Syst., Meas., Control
0022-0434,
121
, pp.
724
729
.
5.
Dellomo
,
M. R.
, 1999, “
Helicopter Gearbox Fault Detection: A Neural Network Based Approach
,”
ASME J. Vibr. Acoust.
0739-3717,
121
, pp.
265
270
.
6.
David
,
J. S.
, and
Babb
,
A. H.
, 1973,
Maintainability Engineering
,
Pitman
, New York.
7.
Wowk
,
V.
, 1991,
Machinery Vibration: Measurement and Analysis
,
McGraw-Hill
, New York.
8.
Randall
,
R. B.
, 1987,
Frequency Analysis
, 3rd ed.,
Brüel & Kjaer
, Denmark
9.
Shih-Yaug
,
L.
, and
Jen-Gwo
,
C.
, 1995, “
Development of a Machine Troubleshooting Expert System Via Fuzzy Multiattribute Decision-Making Approach
,” in
Expert Systems with Applications 81
,
Pergamon
, New York, pp.
187
201
.
10.
Bishop
,
C. M.
, 1995,
Neural Networks for Pattern Recognition
,
Oxford University Press
, New York.
11.
Bezdek
,
J. C.
, 1981,
Pattern Recognition with Fuzzy Objective Function Algorithms
,
Plenum
, New York.
12.
Zurada
,
J. M.
, 1992,
Introduction to Artificial Neural Systems
,”
West Publishing Co.
, St. Paul, MN.
13.
Zadeh
,
L. A.
, 1975, “
The Concept of a Linguistic Variable and its Application to Approximate Reasoning, Part 1
,”
Inf. Sci. (N.Y.)
0020-0255,
8
, pp.
199
249
;
Zadeh
,
L. A.
,1975, “
The Concept of a Linguistic Variable and its Application to Approximate Reasoning, Part 2
,”
Inf. Sci. (N.Y.)
0020-0255,
8
, pp.
301
357
;
Zadeh
,
L. A.
,1975, “
The Concept of a Linguistic Variable and its Application to Approximate Reasoning, Part 3
,”
Inf. Sci. (N.Y.)
0020-0255,
9
, pp.
43
80
.
14.
Hassan
,
T. A. F.
,
El-Shafei
,
A.
,
Zeyada
,
Y.
, and
Rieger
,
N.
, 2003, “
Comparison of Neural Network Architectures for Machinery Fault Diagnosis
,” presented at ASME Turbo Expo, Atlanta, GA, ASME Paper No. GT 2003-38450.
15.
Hagan
,
M. T.
,
Demuth
,
H. B.
, and
Beale
,
M.
, 1996,
Neural Network Design
,
PWS
, Warsaw.
16.
Demuth
,
H.
, and
Baele
,
M.
, 1998, “
Neural Network Toolbox for Use With MATLAB
,” V. 3, by MathWorks, Inc.
17.
Luo
,
F.-A.
, and
Unbehauen
,
R.
, 1998,
Applied Neural Networks for Signal Processing
,
Cambridge University Press
, Cambridge.
18.
Hagan
,
M. T.
, and
Menhaj
,
M.
, 1994, “
Training Feedforward Networks with Marquardt Algorithm
,”
IEEE Trans. Neural Netw.
1045-9227,
5
(
6
), pp.
989
993
.
19.
El-Shafei
,
A.
, 1993, “
Measuring Vibration for Machinery Monitoring and Diagnostics
,”
Shock Vib. Dig.
0583-1024,
25
(
1
), pp.
3
14
.
20.
Matlab Fuzzy Logic Toolbox help files, version 5.3.
21.
Sugeno
,
M.
, 1985,
Industrial Applications of Fuzzy Control
,
Elsevier Science
, Amsterdam.
22.
Zadeh
,
L. A.
, 1965, “
Fuzzy Sets
,”
Inf. Control.
0019-9958,
8
, pp.
338
353
.
23.
Zadeh
,
L. A.
, 1973, “
Outline of a New Approach to the Analysis of Complex Systems and Decision Processes
,”
IEEE Trans. Syst. Man Cybern.
0018-9472,
3
(
1
), pp.
28
44
.
24.
Zadeh
,
L. A.
, 1988, “
Fuzzy Logic
,”
Computer
0018-9162,
1
(
4
), pp.
83
93
.
25.
Zadeh
,
L. A.
, 1989, “
Knowledge Representation in Fuzzy Logic
,”
IEEE Trans. Knowl. Data Eng.
1041-4347,
1
, pp.
89
100
.
26.
Jang
,
J.-S. R.
, and
Sun
,
C.-T.
, 1997,
Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence
,
Prentice Hall
, Englewood Cliffs, NJ.
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