Bearing fault diagnosis based on spectrum images of vibration signals. (2nd February 2016)

• Record Type: Journal Article
• Authors: Li, Wei; Qiu, Mingquan; Zhu, Zhencai; Wu, Bo; Zhou, Gongbo
• Is Part Of: Measurement science & technology. Volume 27:Number 3(2016:Mar.)
• Publication Date: 2016-02-02
• Subjects: vibration signal -- fault diagnosis -- bearing -- image; Physical measurements -- Periodicals; Scientific apparatus and instruments -- Periodicals; Equipment and Supplies -- Periodicals; Science -- instrumentation -- Periodicals; Technology -- instrumentation -- Periodicals; Mesures physiques -- Périodiques; Physical measurements; Scientific apparatus and instruments; Periodicals; 502.87
• DOI: 10.1088/0957-0233/27/3/035005
• Languages: English
• ISSNs: 0957-0233

Abstract

Abstract: 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.