- MECHANISM AND MACHINE THEORY Journal
- September 2016
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- The aim of condition monitoring is to detect faults before a catastrophic failure occurs. Cracks in rotating shafts are especially critical. The present work studies vibration signals obtained from a rotating shaft under different crack depths and locations. Tests were performed in a rig called Rotokit at a steady state at different rotation speeds. Signals obtained are analyzed by means of energy using the Wavelet theory, specifically the Wavelet Packets Transform. Nine crack depths in the shafts were tested, from 4% to 50% of the shaft diameter. Previous related work showed good reliability for crack diagnosis using 3 x energy for cracks in the middle section. In the present work, previous results are compared to the obtained for a crack in a change of section at one side. In both crack locations, large changes in energy are observed at 3 x at high speeds. Energy levels at this harmonic were used for the inverse process of crack detection, and probability of detection curves were calculated by thresholding. Cracks with depths above 12% can be detected with reliability in the locations tested using this method. (C) 2016 Elsevier Ltd. All rights reserved.
- condition monitoring; vibration analysis; crack detection; wavelet packets transform; artificial neural-network; hilbert-huang transform; wavelet transform; fault-diagnosis; transient rotor; machine; identification; unbalance