Research Article
Vibration Images-Driven Fault Diagnosis Based on CNN and Transfer Learning of Rolling Bearing under Strong Noise
Table 1
CNN model parameters preset.
| Items | Parameters |
| Batch size | 24 | Convolution1 kernel | Lengthwidthnumber = 556, stride = 1 | Convolution2 kernel | Lengthwidthnumber = 5516, stride = 2 | Convolution3 kernel | Lengthwidthnumber = 55120 | Pool1 set | Type = max pooling, lengthwidth = 44, stride = 4 | Pool2 set | Type = max pooling, lengthwidth = 66, stride = 6 | Activate function | Relu | Loss function | Cross entropy | Optimizer | Stochastic gradient descent | Initial learning rate | 0.001 | Regularization | None |
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