This paper focuses on condition-monitoring of three different valve failure modes common in reciprocating compressors. They are missing valve poppets, valve spring fatigue, and valve seat wear. First, a targeted instrumentation study is performed on a Dresser–Rand ESH-1 industrial reciprocating compressor to investigate detection methods for these failures. This is followed by the development of a novel health classification methodology based on frequency analysis and Bayes theorem. The method is shown to successfully classify the condition of the valves to a high degree of accuracy when applied to actual seeded valve faults in the compressor.

References

1.
Fagundes Schirmer
,
A. G.
,
Gernades
,
N. F.
, and
De Caux
,
J. E.
,
2004
, “
On-Line Monitoring of Reciprocating Compressors
,”
NPRA Maintenance Conference
, San Antonio, TX, May 25–28.
2.
Motriuk
,
R. W.
,
1996
, “
Reciprocating Compressor Valve Failure—Digital Modelling and Analysis
,”
1st International Pipeline Conference (IPC'96), Calgary, AB, Canada
, June 9–13, pp.
993
1002
.
3.
Metcalf
,
J. R.
, and
Woollatt
,
D.
,
1995
, “
Reciprocating Compressor Valve Reliability Improvements
,” 24th Turbomachinery Symposium, College Station, TX, September 25–28, pp.
167
173
.
4.
Matsumura
,
M.
,
Kato
,
M.
, and
Hirata
,
T.
,
1992
, “
Behavior and Analysis of Reciprocating Compressor Valve
,” KOBELCO Technology Review,
14
, pp.
20
24
.
5.
Bloch
,
H. P.
,
2006
,
A Practical Guide to Compressor Technology
,
Wiley
,
New York
.
6.
Sela
,
U.
,
2000
, “
Reciprocating Compressor Condition Monitoring
,”
Hydrocarbon Process
.,
79
(2), pp. 59–62.
7.
Schultheis
,
S. M.
,
Lickteig
,
C. A.
, and
Parchewsky
,
R.
,
2007
, “
Reciprocating Compressor Condition Monitoring
,”
36th Turbomachinery Symposium
, College Station, TX, September 10–13, pp.
107
113
.
8.
Woollatt
,
D.
,
1993
, “
Factors Affecting Reciprocating Compressor Performance
,”
Hydrocarbon Process.
,
72
(6), pp.
57
64
.
9.
Ahmed
,
M.
,
Gu
,
F.
, and
Ball
,
A.
,
2011
, “
Feature Selection and Fault Classification of Reciprocating Compressors Using a Genetic Algorithm and a Probabilistic Neural Network
,”
9th International Conference on Damage Assessment of Structures (DAMAS 2011)
, Oxford, UK, July 11–13.
10.
Ahmed
,
M.
,
Gu
,
F.
, and
Ball
,
A.
,
2011
, “
Fault Classification of Reciprocating Compressor Based on Neural Networks and Support Vector Machines
,”
17th International Conference on Automation & Computing
, Huddersfield, UK, September 10, pp.
213
218
.
11.
Manepatil
,
S.
,
Yadava
,
G. S.
, and
Nakra
,
B. C.
,
2000
, “
Modelling and Computer Simulation of Reciprocating Compressor With Faults
,”
J. Inst. Eng. (India): Mech. Eng. Division
,
81
, pp.
108
116
.
12.
Manepatil
,
S. S.
, and
Tiwari
,
A.
,
2006
, “
Fault Diagnosis of Reciprocating Compressor Using Pressure Pulsations
,”
International Compressor Engineering Conference at Purdue
, West Lafayette, IN, July 17–20.
13.
Elhaj
,
M.
,
Gu
,
F.
,
Ball
,
A. D.
,
Albarbar
,
A.
,
Al-Qattan
,
M.
, and
Naid
,
A.
,
2008
, “
Numerical Simulation and Experimental Study of a Two-Stage Reciprocating Compressor for Condition Monitoring
,”
Mech. Syst. Signal Process.
22
(
2
), pp.
374
389
.10.1016/j.ymssp.2007.08.003
14.
Guerra
,
C. J.
, and
Kolodziej
,
J. R.
,
2013
, “
A Validated System-Level Thermodynamic Model of a Reciprocating Compressor With Application to Valve Condition Monitoring
,”
ASME Dynamic Systems and Control Conference
, Palo Alto, CA, October 21–23.
15.
Holzenkamp
,
M.
,
Kolodziej
,
J. R.
,
Boedo
,
S.
, and
Delmotte
,
S.
,
2013
, “
An Experimentally Validated Model for Reciprocating Compressor Main Bearings for Applications in Health Monitoring
,”
ASME Dynamic Systems and Control Conference
, Palo Alto, CA, October 21–23.
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