Title
Detecting cracks in reciprocating compressor valves using pattern recognition in the pV diagram.
Abstract
We present a novel approach to detecting leaking reciprocating compressor valves based on the idea that a leaking valve affects the shape of the pressure-volume diagram (pV diagram). This effect can be observed when the valves are closed. To avoid disturbances due to the load control, we concentrate on the expansion phase, and linearize it using the logarithmic pV diagram. The gradient of the expansion phase serves as an indicator for the fault state of the valve. Since the gradient is also affected by the pressure conditions, both are used as features in our approach. After feature extraction, classification is performed using several established approaches and a one-class classification method based on linearizing the classification boundary and thresholding. The method was validated using real-world data, and the results show high classification accuracy for varying compressor loads and pressure conditions as well as different valve types.
Year
DOI
Venue
2015
10.1007/s10044-014-0431-5
Pattern Anal. Appl.
Keywords
Field
DocType
Fault detection, Varying load conditions, Varying pressure conditions, pV diagram, Feature extraction, Classification
Pattern recognition,Pressure volume diagram,Fault detection and isolation,Control theory,Feature extraction,Diagram,Gas compressor,Artificial intelligence,Thresholding,Logarithm,Reciprocating compressor,Mathematics
Journal
Volume
Issue
ISSN
18
2
1433-755X
Citations 
PageRank 
References 
1
0.36
11
Authors
6
Name
Order
Citations
PageRank
Kurt Pichler1674.69
Edwin Lughofer2194099.72
Markus Pichler3978.49
Thomas Buchegger4704.52
Erich Peter Klement5989128.89
Matthias Huschenbett631.36