- MECHANISM AND MACHINE THEORY Journal
- February 2016
- 96, part 1
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- Maintenance is essential to prevent catastrophic failures in rotating machinery. A crack can cause a failure with costly processes of reparation, especially in a rotating shaft. In this study, the wavelet transform theory was applied to vibration signals to detect cracks in a rotating shaft. Data were obtained from an analytical Jeffcott rotor model with a breathing function to simulate cracks. Large changes in energy when a crack appears were discovered at 1x, 2x and 3x. Thereafter, vibration signals were obtained from a rotating machine at different steady-state rotational speeds using an accelerometer mounted on the bearing housing. Nine defect conditions were induced in the shaft (with depths from 4% to 50% of the shaft diameter). By matching the theoretical results with the experimental data, it was found that only the 3x component of the rotational speed is a clear indicator of the presence of a crack in this case. The energy level at this harmonic can be used for the inverse process of crack detection. Moreover, "probability of detection" curves were calculated. They showed very good results. (C) 2015 Elsevier Ltd. All rights reserved.
- cracked shaft detection; wavelet transform; condition monitoring; probability of detection; jeffcott rotor; fault diagnosis; wavelet packets; identification; system; transform; vibration; machine; unbalance; beams