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An interactive method for predicting industrial equipment defects

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Abstract

As a major aspect of vibratory verification and the recognition of imperfections and defects in rotating machines, gears have been the subject of much research. These elements are very requested and likely to present defects which evolve rapidly to the rupture. An approach is provided for fault identification on the premise of time-frequency signal analysis techniques. It is shown that the new technique is significant of the energy concentration on the instantaneous frequency of the individual components in the vibration signal, which allows monitoring of the signal amplitude and frequency modulation with a high degree of accuracy and in a small range of frequencies. The analysis of gear defects made on the measured signals can link the observed effects of vibration to material causes that generate them and provided a very powerful tool for maintenance purposes, especially in industry where competition is expressed by the quality and the costs. The main objective of this work is to improve the gear safety, the identification, and the development of vibration analysis techniques for the detection and diagnosis of defects in critical security on the systems gear transmission. To confirm the theoretical results, we have taken an example of furnace gear reducer.

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Acknowledgements

We thank all the members who contributed to this work, without forgetting all the people who helped us to pass this study.

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Authors and Affiliations

  1. Laboratoire de Mécanique Appliquée, Département de Génie Mécanique, Université des Sciences et de la Technologie d’Oran Mohamed Boudiaf, USTO-MB, BP 1505, El M’naouer, 31000, Oran, Algerie

    A. Slimane, S. Kebdani, S. Slimane & N. Sardi

  2. Laboratory of Materials and Reactive Systems (LMSR), Department of Mechanical Engineering, University of Sidi-Bel-Abbes, Bp 89, Cité Ben M’hidi, 22000, Sidi Bel Abbes, Algeria

    B. Bouchouicha, M. Benguediab & K. Bahram

  3. Laboratory of Structures and Solids Mechanics (LMSS), Faculty of Technology, University of Sidi-Bel-Abbes, Bp 89, Cité Ben M’hidi, 22000, Sidi Bel Abbes, Algeria

    M. Chaib

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  1. A. Slimane
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  2. S. Kebdani
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  3. B. Bouchouicha
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  4. M. Benguediab
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  5. S. Slimane
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  6. K. Bahram
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  7. M. Chaib
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  8. N. Sardi
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Correspondence to A. Slimane.

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Slimane, A., Kebdani, S., Bouchouicha, B. et al. An interactive method for predicting industrial equipment defects. Int J Adv Manuf Technol 95, 4341–4351 (2018). https://doi.org/10.1007/s00170-017-1416-5

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  • DOI: https://doi.org/10.1007/s00170-017-1416-5

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