2023
DOI: 10.1002/tee.23973
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Fault Diagnosis of Shipboard Medium‐Voltage Alternating Current Power System with Fault Recording Data‐Driven SE‐ResNet18‐1 Model

Fengjian Peng,
Longhua Mu,
Chongkai Fang

Abstract: The electrification trend of marine vessels has led to the rapid development of all‐electric ships. Yet the unique topology and harsh working environment of shipboard power system have posed significant challenges to its fault diagnosis. This paper addresses the research gap in fault diagnosis for shipboard medium‐voltage alternating current (MVAC) power systems and proposes a machine learning‐based fault diagnosis scheme. Signals from fault recorders before relay triggering are used as input for the neural ne… Show more

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Cited by 2 publications
(1 citation statement)
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“…To evaluate the superiority of the proposed method, a noise immunity comparison test was carried out, and five methods were selected to compare the performance, including SVD-GST [33], 1D-ViTMSC [25], BiGRV [34], ResNet18 [35] and ViT network. Using the same experimental parameter settings, the adaptability of the fault diagnosis method under different noise levels is evaluated by adding different degrees of Gaussian white noise to the vibration signal.…”
Section: Anti-noise Testmentioning
confidence: 99%
“…To evaluate the superiority of the proposed method, a noise immunity comparison test was carried out, and five methods were selected to compare the performance, including SVD-GST [33], 1D-ViTMSC [25], BiGRV [34], ResNet18 [35] and ViT network. Using the same experimental parameter settings, the adaptability of the fault diagnosis method under different noise levels is evaluated by adding different degrees of Gaussian white noise to the vibration signal.…”
Section: Anti-noise Testmentioning
confidence: 99%