The effect of bearings faults to coefficients obtaned by using wavelet transform
2014
In this study, artificial defects in various diameters are formed on inner race, outer race and ball bearing which are essential components of a bearing and vibration signals are collected by a data acquisition card from bearing-shaft setup. The signals acquired are decomposed from noise with wavelet transform; thus vibration signal resulting from normal operation of the system is obtained. The energy of noisy and noise-free signal is calculated and the wavelet coefficients that will be used in classifying are obtained. As a conclusion of experimental studies, the technique based on wavelet transform coefficients accomplishes the classifications of different bearings fault types successfully.
Keywords:
- Wavelet transform
- Computer vision
- Constant Q transform
- Discrete wavelet transform
- Artificial intelligence
- Stationary wavelet transform
- Computer science
- Speech recognition
- Second-generation wavelet transform
- Harmonic wavelet transform
- Control theory
- Wavelet
- Wavelet packet decomposition
- Pattern recognition
- Fast wavelet transform
- Correction
- Source
- Cite
- Save
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