Bearing fault diagnosis based on spectrum images of vibration signals

Li, Wei and Qiu, Mingquan and Zhu, Zhencai and Wu, Bo and Zhou, Gongbo (2016) Bearing fault diagnosis based on spectrum images of vibration signals. Measurement Science and Technology, 27 (3). 035005. ISSN 0957-0233

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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.

Item Type: Article
Subjects: STM Open Press > Computer Science
Depositing User: Unnamed user with email support@stmopenpress.com
Date Deposited: 07 Jul 2023 03:57
Last Modified: 12 Sep 2024 06:07
URI: http://journal.submissionpages.com/id/eprint/1749

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