This paper presents a novel data-driven approach for detecting cracks in reciprocating compressor valves by analyzing vibration data. The main idea is that the time-frequency representation will show typical patterns, depending on the fault state and other variables. The problem of detecting these patterns reliably is solved by taking a detour via two dimensional autocorrelation. This emphasizes the patterns and reduces noise effects, thus identifying appropriate features becomes easier. The features are then classified using well known pattern recognition approaches. The methods performance is validated by analyzing real world measurement data.
- Aerospace Division
Detecting Cracks in Reciprocating Compressor Valves Using Pattern Recognition in Frequency Space
- Views Icon Views
- Share Icon Share
- Search Site
Pichler, K, Lughofer, E, Buchegger, T, Klement, EP, & Huschenbett, M. "Detecting Cracks in Reciprocating Compressor Valves Using Pattern Recognition in Frequency Space." Proceedings of the ASME 2012 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. Volume 1: Development and Characterization of Multifunctional Materials; Modeling, Simulation and Control of Adaptive Systems; Structural Health Monitoring. Stone Mountain, Georgia, USA. September 19–21, 2012. pp. 749-756. ASME. https://doi.org/10.1115/SMASIS2012-8052
Download citation file: