Brushless Synchronous Machine Field Winding Interturn Fault Severity Estimation Through Deep Neural Networks

Pascual, Rubén; Mahtani, Kumar; Rivero, Eduardo; Platero, Carlos A.

doi:10.1109/tec.2023.3338198

IEEE Trans. Energy Convers.

2024

DOI: 10.1109/tec.2023.3338198

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Brushless Synchronous Machine Field Winding Interturn Fault Severity Estimation Through Deep Neural Networks

Rubén Pascual,

Kumar Mahtani,

Eduardo Rivero

et al.

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2024

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Fault Diagnosis in Electrical Machines for Traction Applications: Current Trends and Challenges

Pastura,

Zigliotto

2024

Energies

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The widespread diffusion of electric vehicles poses new challenges in the field of fault diagnostics. Past studies have been focused mainly on machines designed for industrial applications, where the operating conditions and requirements are significantly different. This work presents a review of the most recent studies about fault diagnosis techniques in electrical machines feasible for traction applications, with a focus on the most adopted approaches of the last years and on the latest trends. Considerations about their applicability for electric vehicle purposes, along with some areas that require further research, are also provided.

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Fault Diagnosis in Electrical Machines for Traction Applications: Current Trends and Challenges

Pastura,

Zigliotto

2024

Energies

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Brushless Synchronous Machine Field Winding Interturn Fault Severity Estimation Through Deep Neural Networks

Cited by 1 publication

References 45 publications

Fault Diagnosis in Electrical Machines for Traction Applications: Current Trends and Challenges

Fault Diagnosis in Electrical Machines for Traction Applications: Current Trends and Challenges

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