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Cited by 254

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Stator Current and Motor Efficiency as Indicators for Different Types of Bearing Faults in Induction Motors

Frosini, L., Bassi, E.·2010·IEEE Transactions on Industrial Electronics

Abstract

This paper proposes a new approach to use stator current and efficiency of induction motors as indicators of rolling-bearing faults. After a presentation of the state of the art about condition monitoring of vibration and motor current for the diagnostics of bearings, this paper illustrates the experimental results on four different types of bearing defects: crack in the outer race, hole in the outer race, deformation of the seal, and corrosion. The first and third faults have not been previously considered in the literature, with the latter being analyzed in other research works, even if obtained in a different way. Another novelty introduced by this paper is the analysis of the decrease in efficiency of the motor with a double purpose: as alarm of incipient faults and as evaluation of the extent of energy waste resulting from the lasting of the fault condition before the breakdown of the machine.

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Metadata

Authors
Frosini, L., & Bassi, E.
Venue
IEEE Transactions on Industrial Electronics
Published
2010-01
Volume
57
Issue
1
Pages
244-251
ISSN
0278-0046 (ISSN-L)
OpenAlex
W2114606054
Cited by
254
References
1
FWCI
22.29
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Stator Current and Motor Efficiency as Indicators for Different Types of Bearing Faults in Induction Motors. https://app.cochat.ai/papers/10.1109/tie.2009.2026770
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Frosini, L., & Bassi, E. (2010). Stator Current and Motor Efficiency as Indicators for Different Types of Bearing Faults in Induction Motors. IEEE Transactions on Industrial Electronics. https://doi.org/10.1109/tie.2009.2026770

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.