- Tytuł:
- A convolutional neural network-based method of inverter fault diagnosis in a ship’s DC electrical system
- Autorzy:
-
Yan, Guohua
Hu, Yihuai
Shi, Qingguo - Powiązania:
- https://bibliotekanauki.pl/articles/32898224.pdf
- Data publikacji:
- 2022
- Wydawca:
- Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
- Tematy:
-
multi-energy hybrid ships
inverters
fault diagnosis
CNN - Opis:
- Multi-energy hybrid ships are compatible with multiple forms of new energy, and have become one of the most important directions for future developments in this field. A propulsion inverter is an important component of a hybrid DC electrical system, and its reliability has great significance in terms of safe navigation of the ship. A fault diagnosis method based on one-dimensional convolutional neural network (CNN) is proposed that considers the mutual influence between an inverter fault and a limited ship power grid. A tiled voltage reduction method is used for one-to-one correspondence between the inverter output voltage and switching combinations, followed by a combination of a global average pooling layer and a fully connected layer to reduce the model overfitting problem. Finally, fault diagnosis is verified by a Softmax layer with good anti-interference performance and accuracy.
- Źródło:
-
Polish Maritime Research; 2022, 4; 105-114
1233-2585 - Pojawia się w:
- Polish Maritime Research
- Dostawca treści:
- Biblioteka Nauki
Artykuł