Journal
MEASUREMENT SCIENCE AND TECHNOLOGY
Volume 27, Issue 3, Pages -Publisher
IOP PUBLISHING LTD
DOI: 10.1088/0957-0233/27/3/035005
Keywords
vibration signal; fault diagnosis; bearing; image
Funding
- National Natural Science Foundation of China [51475455]
- Natural Science Foundation of Jiangsu [BK20141127]
- Fundamental Research Funds for Central Universities [2014Y05]
- Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)
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Bearing fault diagnosis has been a challenge in the monitoring activities of rotating machinery, and it's receiving more and more attention. The conventional fault diagnosis methods usually extract features from the waveforms or spectrums of vibration signals in order to correctly classify faults. In this paper, a novel feature in the form of images is presented, namely analysis of the spectrum images of vibration signals. The spectrum images are simply obtained by doing fast Fourier transformation. Such images are processed with two-dimensional principal component analysis (2DPCA) to reduce the dimensions, and then a minimum distance method is applied to classify the faults of bearings. The effectiveness of the proposed method is verified with experimental data.
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