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Detail aplikovaného výsledku
KOZOVSKÝ, M.; BLAHA, P.; VÁCLAVEK, P.
Originální název
On the edge implementation of quantized ANN for interturn short-circuit diagnostics
Anglický název
Druh
Software
Abstrakt
The prepared software package contains a set of scripts for the conversion of neural networks for inter-turn short-circuit detection from floating point arithmetic to integer arithmetic suitable for implementation in tensor processing units - TPUs. A trained neural network and a representative dataset are needed to use the quantization process. The resulting neural network contains only integer types and can be easily implemented in low-cost microcontrollers without float processing units FPU or into TPU platforms. The size of the neural network is reduced to approximately one-quarter of the original size with just a minimum reduction in classification accuracy. The resulting quantized networks were tested on a test system for the analysis of inter-turn short-circuits in a multiphase PMS motor with a Nerve Blue platform equipped with an additional Coral TPU accelerator.
Abstrakt aglicky
Klíčová slova
neural network, quantisation, inter-turn short circuit
Klíčová slova anglicky
Umístění
CEITEC Admas, 651/139, Purkyňova, 612 00 Brno
Licenční poplatek
K využití výsledku jiným subjektem je vždy nutné nabytí licence
www
http://ai4di.ceitec.cz/vysledky