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Health monitoring of bearing and gear faults by using a new health indicator extracted from current signals

Soualhi, Moncef and Nguyen, Thi Phuong Khanh and Soualhi, Abdenour and Medjaher, Kamal and Hemsas, Kamel Eddine Health monitoring of bearing and gear faults by using a new health indicator extracted from current signals. (2019) Measurement, 141. 37-51. ISSN 0263-2241

(Document in English)

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Official URL: https://doi.org/10.1016/j.measurement.2019.03.065


Gear reducer motors play an important role in industry due to their robustness and simplicity of construction. However, the appearance of faults in these systems can affect the quality of the product and lead to significant financial losses. Therefore, it is necessary to perform Prognostics and Health Management (PHM) for these systems. This paper aims to develop a practical and effective method allowing an early fault detection and diagnostic for critical components of the gear reducer, in particular gear and bearing defects. This method is based on a new indicator extracted from electrical signals. It allows characterizing different states of the gear reducer, such as healthy state, bearing faults, gear faults, and combined faults. The diagnostic of these states is done by the Adaptive Neuro-Fuzzy Inference System (ANFIS). The efficiency and the robustness of the proposed method are highlighted through numerous experimental tests with different levels of loads and speeds.

Item Type:Article
HAL Id:hal-02134729
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Other partners > Université Jean Monnet - St Etienne (FRANCE)
Other partners > Université Ferhat Abbas Sétif - UFAS (ALGERIA)
Laboratory name:
Deposited On:24 Apr 2019 08:47

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