Identification of the Air Supply System for Combustion, With the Help of Artificial Neural Networks
Journal Title: Advances in Robotics & Mechanical Engineering - Year 2018, Vol 1, Issue 3
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. This entrepreneurial improvement as an integral process cannot avoid the technological improvement based on a consistent application of advances in science and technology.
Authors and Affiliations
Enrique Santana Lopez, Deynier Montero Góngora, Orlando Víctor Vega Arias
Keywords
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- EP ID EP581432
- DOI 10.32474/ARME.2018.01.000113
- Views 105
- Downloads 0
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