Fracture and Structural Integrity e-ISSN 1971-8993 Open access
SI: Fracture Mechanics versus Environment Vol. 13, No. 49 (2019)

Detection and diagnosis of fault bearing using wavelet packet transform and neural network

Author and affiliation details
  • Said DJABALLAH Corresponding author University of Biskra, LGEM Laboratory said3988@gmail.com
  • Kamel Meftah University of Biskra, LGEM Laboratory, Algeria
  • Khaled Khelil University of Souk Ahras, Algeria
  • Mohsein Tedjini University of Biskra, LGM Laboratory, Algeria
  • Lakhdar Sedira University of Biskra, LGM Laboratory, Algeria
DOI
10.3221/IGF-ESIS.49.29
Pages
291-301
Published
Published inVol. 13, No. 49 (2019)Go to the issue

Abstract

Bearings, considered crucial components in rotating machinery, are widely used in the industry. Bearing status monitoring has become an essential step in the deployment of preventive maintenance policy. This work is part of the diagnosis and classification of bearing defects by vibration analysis of signals from defective bearings using time domain and frequency analysis and wavelet packet transformations (Wavelet Packet Transform WPT) with Artificial Neural Networks (ANN). WPT is used for extracting defect indicators to train the neural classifier. The main goal is the determination of the wavelet generating the most representative indicators of the state of the bearings for better detection and classification of defects. Using the WPT-based neural classifier, the obtained simulation results showed that the db6 wavelet with level 3 decomposition is best suited for diagnosing and classifying bearing defects

Keywords

Article history

  1. ReceivedUntil the next stage: 22 days
  2. Revision requestedUntil the next stage: 8 days
  3. RevisedUntil the next stage: 20 days
  4. AcceptedUntil the next stage: 63 days
  5. Published

How to cite

APA

DJABALLAH, S., Meftah, K., Khelil, K., Tedjini, M., & Sedira, L. (2019). Detection and diagnosis of fault bearing using wavelet packet transform and neural network. Fracture and Structural Integrity, 13(49), 291–301. https://doi.org/10.3221/IGF-ESIS.49.29

IEEE

S. DJABALLAH, K. Meftah, K. Khelil, M. Tedjini, and L. Sedira, “Detection and diagnosis of fault bearing using wavelet packet transform and neural network,” Fracture and Structural Integrity, vol. 13, no. 49, pp. 291–301, 2019, doi: 10.3221/IGF-ESIS.49.29.

MLA

DJABALLAH, Said, et al. “Detection and diagnosis of fault bearing using wavelet packet transform and neural network.” Fracture and Structural Integrity, vol. 13, no. 49, 2019, pp. 291–301. https://doi.org/10.3221/IGF-ESIS.49.29.

Chicago

DJABALLAH, Said, Kamel Meftah, Khaled Khelil, Mohsein Tedjini, and Lakhdar Sedira. 2019. “Detection and diagnosis of fault bearing using wavelet packet transform and neural network.” Fracture and Structural Integrity 13 (49): 291–301. https://doi.org/10.3221/IGF-ESIS.49.29.

Harvard

DJABALLAH, S., Meftah, K., Khelil, K., Tedjini, M. and Sedira, L. (2019) ‘Detection and diagnosis of fault bearing using wavelet packet transform and neural network’, Fracture and Structural Integrity, 13(49), pp. 291–301. doi: 10.3221/IGF-ESIS.49.29.

Vancouver

DJABALLAH S, Meftah K, Khelil K, Tedjini M, Sedira L. Detection and diagnosis of fault bearing using wavelet packet transform and neural network. Fracture and Structural Integrity. 2019;13(49):291-301. doi:10.3221/IGF-ESIS.49.29

BibTeX

@article{djaballah2019, author = {DJABALLAH, Said and Meftah, Kamel and Khelil, Khaled and Tedjini, Mohsein and Sedira, Lakhdar}, title = {Detection and diagnosis of fault bearing using wavelet packet transform and neural network}, journal = {Fracture and Structural Integrity}, year = {2019}, volume = {13}, number = {49}, pages = {291--301}, doi = {10.3221/IGF-ESIS.49.29}, url = {https://doi.org/10.3221/IGF-ESIS.49.29}, issn = {1971-8993} }

RIS

TY - JOUR AU - DJABALLAH, Said AU - Meftah, Kamel AU - Khelil, Khaled AU - Tedjini, Mohsein AU - Sedira, Lakhdar TI - Detection and diagnosis of fault bearing using wavelet packet transform and neural network JO - Fracture and Structural Integrity T2 - Fracture and Structural Integrity PY - 2019 DA - 2019/06/09 VL - 13 IS - 49 SP - 291 EP - 301 DO - 10.3221/IGF-ESIS.49.29 UR - https://doi.org/10.3221/IGF-ESIS.49.29 SN - 1971-8993 ER -

Licence

Copyright © 2019 Said DJABALLAH, Kamel Meftah, Khaled Khelil, Mohsein Tedjini, Lakhdar Sedira.

Copyright 
Authors are allowed to retain both the copyright and the publishing rights of their articles without restrictions.  

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