An intelligent measurement and control system based on big data

Abstract

The application discloses an intelligent measurement and control method based on big data, which comprises the following steps: step one: adopting a differential set smoke cover combined with a furnace front flow guide cover to capture the flue gas dust in the whole production stage of a steel plant refining workshop, and conveying the flue gas dust to a dust removal measurement and control equipment terminal through a dust removal pipeline; step two: analyzing the key influence factors of the dust capture stage by analyzing the flue gas diffusion and expansion along with the completion of each process; step three: managing the dust removal parameters of different dust removal measurement and control equipment terminals based on the flue gas dust concentration value; and step four: determining the best working condition of the whole dust removal measurement and control equipment terminal by analyzing the influence of the working condition on the dust concentration of the dust removal measurement and control equipment terminal by changing the atomization conditions including water pressure and air pressure. The application solves the problem of measurement and control data errors caused by the gradual reduction of the measurement and control accuracy of the dust removal measurement and control equipment, and has the characteristics of improving the reliability and accuracy of the measurement and control equipment under the dust removal environment.

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