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Appl. Sci. 2018, 8(8), 1392; https://doi.org/10.3390/app8081392

Vibration-Based Bearing Fault Detection and Diagnosis via Image Recognition Technique Under Constant and Variable Speed Conditions

1
Department of Engineering, University of Ferrara, Via Saragat 1, 44122 Ferrara, Italy
2
School of Electronics Engineering, Kyungpook National University, Daegu 41566, Korea
*
Author to whom correspondence should be addressed.
Received: 16 July 2018 / Revised: 11 August 2018 / Accepted: 13 August 2018 / Published: 17 August 2018
(This article belongs to the Special Issue Fault Detection and Diagnosis in Mechatronics Systems)
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Abstract

This paper addresses the application of an image recognition technique for the detection and diagnosis of ball bearing faults in rotating electrical machines (REMs). The conventional bearing fault detection and diagnosis (BFDD) methods rely on extracting different features from either waveforms or spectra of vibration signals to detect and diagnose bearing faults. In this paper, a novel vibration-based BFDD via a probability plot (ProbPlot) image recognition technique under constant and variable speed conditions is proposed. The proposed technique is based on the absolute value principal component analysis (AVPCA), namely, ProbPlot via image recognition using the AVPCA (ProbPlot via IR-AVPCA) technique. A comparison of the features (images) obtained: (1) directly in the time domain from the original raw data of the vibration signals; (2) by capturing the Fast Fourier Transformation (FFT) of the vibration signals; or (3) by generating the probability plot (ProbPlot) of the vibration signals as proposed in this paper, is considered. A set of realistic bearing faults (i.e., outer-race fault, inner-race fault, and balls fault) are experimentally considered to evaluate the performance and effectiveness of the proposed ProbPlot via the IR-AVPCA method. View Full-Text
Keywords: bearing fault detection and diagnosis (BFDD); vibration signal; probability plot (ProbPlot); image recognition; absolute value principal component analysis (AVPCA) bearing fault detection and diagnosis (BFDD); vibration signal; probability plot (ProbPlot); image recognition; absolute value principal component analysis (AVPCA)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Hamadache, M.; Lee, D.; Mucchi, E.; Dalpiaz, G. Vibration-Based Bearing Fault Detection and Diagnosis via Image Recognition Technique Under Constant and Variable Speed Conditions. Appl. Sci. 2018, 8, 1392.

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