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1 Polish Maritime Research

1 2022

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A convolutional neural network-based method of inverter fault diagnosis in a ship’s DC electrical system

Yan Guohua, Hu Yihuai, Shi Qingguo

Polish Maritime Research

2022

nr 4

105--114

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.