Fault detection and fault identification in marine current turbines

Wang, Tianzhen; Li, Zhichao; Zheng, Yilai

doi:10.1016/b978-0-12-822473-1.00005-7

Cited by 3 publications

(2 citation statements)

References 42 publications

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“…The currents flowing through the high and low voltage windings of the transformer are in opposite directions, so the two windings are subject to a radial electromagnetic force that repels each other, with the inner low voltage winding subject to an inward radial pressure and the outer high voltage winding subject to an outward radial tension. x B is zero in the middle of the winding and maximum at both ends, generating an axial electromagnetic force x F is maximum at both ends and in opposite directions, generating a tendency to compress the winding [7]. Spoke electromagnetic force to transformer insulation performance is damaged and leads to strong deformation of the winding.…”

Section: Transformer Winding Force Analysis Based On Closing Transien...mentioning

confidence: 99%

Transformer winding mechanical fault diagnosis method based on closing transient acoustic vibration signal

Song,

Chen

2023

J. Phys.: Conf. Ser.

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The current conventional transformer winding fault diagnosis method mainly extracts the vibration signal through the time-frequency analysis method, which leads to poor diagnosis due to the lack of analysis of the transformer winding state. In this regard, a transformer winding mechanical fault diagnosis method based on the closing transient acoustic vibration signal is proposed. The closing vibration signals of the transformer in the normal and loose winding states are collected separately, the transformer winding force situation is analysed, and the transformer fault signal characteristics are extracted and combined with a fault classifier to construct a fault diagnosis model. In the experiments, the proposed method is verified for fault identification. The experimental results show that the proposed method has a high correct rate when used to identify different types of transformer faults, and has a more desirable fault diagnosis performance.

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Section: Transformer Winding Force Analysis Based On Closing Transien...mentioning

confidence: 99%

Transformer winding mechanical fault diagnosis method based on closing transient acoustic vibration signal

Song,

Chen

2023

J. Phys.: Conf. Ser.

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“…The fracture zone of the fault can be filled by air and water, so the shear wave velocity of the fracture zone can obviously be reduced. Groundwater in Jinan is abundant, the deeper part of the Wenhuaqiao Fault being water conductive (Wang et al, 2018b). The low velocity belt may come from groundwater activity in the Wenhuaqiao Fault.…”

Section: Intrusive Rocks and Fault Activitymentioning

confidence: 99%

Ambient Noise Tomography of Jinan: The Migration of Groundwater and the Formation of Geothermal Water

Lei

Feng

Chen

et al. 2022

Acta Geologica Sinica (Eng)

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Jinan is located in midwestern Shandong province, eastern China. As one of the most important cities of the Bohai Rim region and the lower reaches of the Yellow River, it is the provincial capital of Shandong, with a permanent population of more than 7 million. Jinan sits on the southeast edge of the North China Plain, on the northern edge of the central Shandong mountains, south of the Yellow River and north of the Taishan Mountain. The terrain is high in the south and low in the north: the altitude of the southern mountainous area is about 100-500 m, the altitude of the central tilted plain is about 20-100 m and the altitude on the northern alluvial plain in the middle and lower reaches of the Yellow River is below 20 m.Jinan is famous as the Spring City, with many famous springs being located in the urban region. On the one hand, these springs are important scenic spots and attract many tourists, but on the other, these springs are also disruptive factors in city construction (Zhang et al., 2017). Springs are associated with abundant groundwater and in Jinan, the groundwater has caused some troubles in the construction of underground transportation (Yang et al., 2012;Wang et al., 2018a). In recent years, the spring flow has declined a lot. Geological modelling has provided some suggestions for spring protection (Wu and Xu, 2005;Qian et al., 2006;Kang et al., 2011).In addition to spring water, the groundwater also exists in another form, that of geothermal water. There are plenty

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The multi-fault identification system of mechanical bearing based on machine vision

Zheng

et al. 2022

2022 14th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA)

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Fault detection and fault identification in marine current turbines

Cited by 3 publications

References 42 publications

Transformer winding mechanical fault diagnosis method based on closing transient acoustic vibration signal

Transformer winding mechanical fault diagnosis method based on closing transient acoustic vibration signal

Ambient Noise Tomography of Jinan: The Migration of Groundwater and the Formation of Geothermal Water

The multi-fault identification system of mechanical bearing based on machine vision

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