Coil,Transformer and IPM motor

Citation Author(s):
Zining
Wang
Xinsheng
Yang
Submitted by:
Zining Wang
Last updated:
Mon, 12/11/2023 - 22:43
DOI:
10.21227/k66a-xz05
Data Format:
License:
0
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Abstract 

For coil dataset,the shape of one data is [160,160,5]

For transformer dataset,the shape of one data is [400,400,5]

For IPM motor dataset,the shape of one data is [180,180,5]

The first five layers consist of input device property information, while the sixth layer represents the FEA magnetic field distribution results.

When using, please note to split the dataset into two parts, with x being transformed as follows:

X = data[:, :, :5]
X = np.transpose(X, (2, 0, 1))
X = torch.from_numpy(X)

, and y being transformed as follows:

y = data[:, :, 5]
y = torch.from_numpy(y)
y = y.unsqueeze(0)

 

 

Instructions: 

For coil dataset,the shape of one data is [160,160,5]

For transformer dataset,the shape of one data is [400,400,5]

For IPM motor dataset,the shape of one data is [180,180,5]

The first five layers consist of input device property information, while the sixth layer represents the FEA magnetic field distribution results.