Abstract
The production of nickel in #Cuba is one of the main export items in
our economy. In recent years, its production costs have risen
significantly, with a high incidence of electricity costs, which is why
it is necessary to take energy shock measures to reverse this situation.
Currently there are deficiencies in the Reduction Furnace plant related
to the control of the air supply and the electric power used by the
#asynchronous motors that drive the centrifugal fans, reducing the
efficiency levels of the production process and the plant in general. In
order to increase the energy efficiency of the #combustion process
supply system and reach an #optimum control model of the airflow of this
plant, variants are designed and simulated based on artificial neural
networks that allow to establish the air demand from the drive of the
fans by means of variable speed drives.The Mining and Metallurgical Industry has become one of the bases on
which the economic-industrial development of the country is based and is
one of the ones that currently faces the #challenge of Business
Improvement, a way to achieve a global competitive level.
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Identification of the Air Supply System for Combustion, With the Help of Artificial Neural Networks by Deynier Montero Gongora in BJSTR
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