Bearing faults diagnosis using cepstral analysis and 1D Convolutional neural network
DOI:
https://doi.org/10.5281/zenodo.8070908Keywords:
Rolling bearing, cepstral analysis, faults diagnosis, 1D convolutional neural networkAbstract
The diagnosis of faults in the rotating machines has become necessary recently, in the order to ensure their safety and efficiency. the rolling bearing is one of the most components prone to failure in the rotating machines. In this work, we propose a novel approach to detecting and classifying the rolling bearing faults by using the cepstral analysis and 1D-CNN. First, the real, complex and power cepstrum are calculated, which are later used as input to the classifier. Second, a 1D-CNN is used as a classifier to diagnose the bearing faults. The proposed method is tested on the CWRU dataset from bearings under variable working conditions. Results of the proposed method gave a testing accuracy of 97.5 % for the complex cepstrum method and it
also gave a testing accuracy of 99.88% for the real and the power cepstrum.
References
I. Attoui, B. Oudjani, N. Boutasseta, N. Fergani, M. Bouakkaz, A. Bouraiou, Novel predictive features using a wrapper model for rolling bearing fault diagnosis based on vibration signal analysis, Int. J. Adv. Manuf. Technol. 106 (2020) 3409–3435. https://doi.org/10.1007/s00170-019-04729-4.
Z. Duan, T. Wu, S. Guo, T. Shao, R. Malekian, Z. Li, Development and trend of condition monitoring and fault diagnosis of multi-sensors information fusion for rolling bearings: a review, Int. J. Adv. Manuf. Technol. 96 (2018) 803–819. https://doi.org/10.1007/s00170-017-1474-8.
Y. Toumi, B. Bengherbia, S. Lachenani, M. Ould Zmirli, FPGA Implementation of a Bearing Fault Classification System Based on an Envelope Analysis and Artificial Neural Network, Arab. J. Sci. Eng. (2022). https://doi.org/10.1007/s13369-022-06599-7.
C. Liu, A. Cichon, G. Królczyk, Z. Li, Technology development and commercial applications of industrial fault diagnosis system: a review, Int. J. Adv. Manuf. Technol. (2021). https://doi.org/10.1007/s00170-021-08047-6.
R. Liu, B. Yang, E. Zio, X. Chen, Artificial intelligence for fault diagnosis of rotating machinery: A review, Mech. Syst. Signal Process. 108 (2018) 33–47. https://doi.org/10.1016/j.ymssp.2018.02.016.
J. van den Hoogen, S. Bloemheuvel, M. Atzmueller, Classifying multivariate signals in rolling bearing fault detection using adaptive wide-kernel cnns, Appl. Sci. 11 (2021). https://doi.org/10.3390/app112311429.
K. Bhakta, N. Sikder, A. Al Nahid, M.M.M. Islam, Fault Diagnosis of Induction Motor Bearing Using Cepstrum-based Preprocessing and Ensemble Learning Algorithm, in: 2nd Int. Conf. Electr. Comput. Commun. Eng. ECCE 2019, IEEE, 2019: pp. 1–6. https://doi.org/10.1109/ECACE.2019.8679223.
Bearing Data Center | Case School of Engineering | Case Western Reserve University, (n.d.). https://engineering.case.edu/bearingdatacenter (accessed April 4, 2022).
Published
Issue
Section
License
Copyright (c) 2022 AINTELIA Science Notes Journal
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
COPYRIGHT NOTICE
Authors submitting a manuscript do so on the understanding that if accepted for publication, copyright of the article shall be assigned to Aintelia® Science Notes Journal (ASNJ).
By submitting their work, authors agree to the following terms:
-
Copyright Transfer: Copyright of the published article is transferred to Aintelia® Science Notes Journal. The journal reserves the right to publish, reproduce, distribute, and archive the work.
-
Licensing: While the journal retains the copyright, the article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). This allows third parties to share and adapt the work for non-commercial purposes, provided the original work and the journal are properly cited.
-
Author Rights: Authors retain the right to use their article for their own scholarly needs, such as including it in a thesis or dissertation, presenting it at conferences, or distributing it to students for educational purposes, provided that the journal is cited as the original publisher.
