Fault detection in reciprocating compressor valves under varying load conditions

Author:

Pichler Kurt,Lughofer Edwin,Pichler Markus,Buchegger Thomas,Klement Erich Peter,Huschenbett Matthias

Funder

Austrian COMET-K2 programme of the Linz Center of Mechatronics (LCM)

Austrian federal government

federal state of Upper Austria

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference30 articles.

1. M. Huschenbett, G. Will, Thermodynamic simulation of reciprocating compressors to enable diagnostics based on measured temperatures and pressures, In: Proceedings of the 4th Conference of the European Forum of Reciprocating Compressors, Antwerp, Belgium, 2005.

2. Early detection of leakages in the exhaust and discharge systems of reciprocating machines by vibration analysis;Bardou;Mech. Syst. Signal Process.,1994

3. Y.H. Lin, H.C. Wu, C.Y. Wu, Automated condition classification of a reciprocating compressor using time–frequency analysis and an artificial neural network, Smart Mater. Struct. 15 (2006) 1576–1584.

4. Y.H. Lin, H.S. Liu, C.Y. Wu, Automated valve condition classification of a reciprocating compressor with seeded faults: experimentation and validation of classification strategy, Smart Mater. Struct. 18 (2009).

5. Cyclostationary modelling of reciprocating compressors and application to valve fault detection;Zouari;Int. J. Acoust. Vib.,2007

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