Real-time Deep Neural Networks for internet-enabled arc-fault detection
We examine methods for detecting and disrupting electronic arc faults, proposing an approach leveraging Internet of Things connectivity, artificial intelligence, and adaptive learning. We develop Deep Neural Networks (DNNs) taking Fourier coefficients, Mel-Frequency Cepstrum data, and Wavelet featur...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Elsevier
2019
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| Online Access: | https://hdl.handle.net/1721.1/121372 |