Bearing faults monitoring in electrical rotating machines through three-phase electrical signals analysis

Georgia Cablea 1 Pierre Granjon 1 Christophe Bérenguer 1
1 GIPSA-SAIGA - SAIGA
GIPSA-DA - Département Automatique, GIPSA-DIS - Département Images et Signal
Abstract : Condition monitoring methods based on electrical signals analysis have been used for mechanical and electrical fault detection for a while now. Moreover, the research focus has shifted from single-phase signals analysis to three-phase signals approaches. The main advantages of using three-phase approaches can be stated as separation of balanced and unbalanced electrical quantities as well as better performances in terms of mechanical faults detection. However, such approaches still have a low industrial penetration in part due to their relatively higher complexity compared to single-phase approaches. The current paper proposes an easy to implement method for condition monitoring of bearings, which takes into account the whole three-phase electrical signals. After presenting the theoretical development of the method, the algorithm for computing mechanical faults indicators is given. Moreover, the paper presents experimental results of the proposed approach, using electrical signals acquired on a dedicated test bench.
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Georgia Cablea, Pierre Granjon, Christophe Bérenguer. Bearing faults monitoring in electrical rotating machines through three-phase electrical signals analysis. 13th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies (CM2016/MFPT2016), Oct 2016, Paris, France. ⟨hal-01402872⟩

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