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Novel predictive features using a wrapper model for rolling bearing fault diagnosis based on vibration signal analysis

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Abstract

In modern diagnostic approaches, the key step consists in generating the features related to fault type and severity. In fact, the generated features should be able to help the classifier to determine the health condition of the monitored system based on the measured signal. In this paper, in order to make an effective diagnosis about the rolling-element bearing failure, novel generated features that can maintain the physical meaning of the extracted vibration signal, while identifying its relationship to rolling bearing damage, are proposed using a wrapper model. For this purpose, based only on the Most Impulsive Frequency Bands (MIFBs) of the measured vibration signals for many bearing conditions, 33 feature parameters are proposed. Using a wrapper scheme, these parameters can be reduced until a set of them are found improving the efficiency of the diagnostic approach. The effectiveness of the proposed predictive features is analyzed by comparing it with some related works using many testing data for several bearing conditions. The experimental results reveal that the proposed procedure has obtained a high level of accuracy of 99.83%.

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Authors and Affiliations

  1. Research Center in Industrial Technologies, CRTI, P.O. Box 64, Cheraga, Algeria

    Issam Attoui, Brahim Oudjani, Nadir Boutasseta & Nadir Fergani

  2. Department of Electrical Engineering, Laboratoire d’électrotechnique de Skikda «LES», Université du 20 Août 1955, 21000, Skikda, Algeria

    Mohammed-Salah Bouakkaz

  3. Unité de Recherche en Energies Renouvelables en Milieu Saharien URERMS, Centre de Développement des Energies Renouvelables, CDER, 01000, Adrar, Algeria

    Ahmed Bouraiou

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  1. Issam Attoui
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Attoui, I., Oudjani, B., Boutasseta, N. et al. Novel predictive features using a wrapper model for rolling bearing fault diagnosis based on vibration signal analysis. Int J Adv Manuf Technol 106, 3409–3435 (2020). https://doi.org/10.1007/s00170-019-04729-4

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