Abstract
Leaking valves are the most common reason for unexpected shutdowns of reciprocating compressors. Therefore, a leaking valve has to be detected early and reliable, even for arbitrary operating conditions. In this chapter, a data-driven approach for compressor valve monitoring is proposed. As compressors are equipped with different sensing systems and usually retrofitting new sensors is not desired or even impossible, two independent methods are developed. In the first approach, accelerometers are mounted at the valve covers to perform vibration analysis. In the case of a broken valve, certain time–frequency patterns occur, different from the patterns in the case of varying operating condition. It is thus possible to extract specific features from the time–frequency representation to distinguish between healthy and broken valves. In the second approach, pV diagrams of compression cycles are analysed. Gas flowing through a leak affects the pressure in the compression cylinder and thus the pV diagram. The pV diagram is also affected by varying operating conditions such as load, suction, and discharge pressure. Appropriate features to distinguish these cases are extracted both from the logarithmic pV diagram and the environmental pressure conditions.
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Acknowledgements
This work has been supported by the COMET-K2 “Center for Symbiotic Mechatronics” of the Linz Center of Mechatronics (LCM) funded by the Austrian federal government and the federal state of Upper Austria.
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Pichler, K. (2019). Early Fault Detection in Reciprocating Compressor Valves by Means of Vibration and pV Diagram Analysis. In: Lughofer, E., Sayed-Mouchaweh, M. (eds) Predictive Maintenance in Dynamic Systems. Springer, Cham. https://doi.org/10.1007/978-3-030-05645-2_6
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