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On the application and design of artificial neural networks for motor fault detection. II.

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Figure

Fig. 1 1. 3D graph of B as a function of 1 I and o.
Fig. 4. Network learning curves of bearing condition, where E is the root mean-square training error used as network training stopping criterion
Fig. 6. Accuracy of MS-IFDA“ for different noise variance values as a function of sampling window size n
Fig. 7. (a) Normalized T ,  S, and N versus n,. (b) Normalized E, T, and N versus nh.
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