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<p>This paper discusses the critical impact of informatization automation on plant automation, and takes a water plant’s coagulation dosing automation control system as an example to explore the value of integrated wireless modules in the automation of electrical equipment. Algorithms for directly identifying the parameters of the second-order continuous model by regression model and based on the step response data are investigated, as well as the selection of the DMC algorithm for mathematical modeling of the coagulation dosing automation control. Finally, the effectiveness of the automated dosing system was verified by comparing its effectiveness in improving the qualified rate of precipitation water quality, reducing drug consumption and effluent turbidity, and improving stability. The study’s results showed that after using the coagulation dosing automation system, the water plant’s sedimentation water quality pass rate was increased from the original 85%~95% to 95%~100%. The drug consumption and effluent turbidity were reduced by 20.3% and 33.09% respectively, while the stability was also improved to different degrees. The coagulation dosing automated control system can dosage chemicals more accurately, safely and stably, which has specific reference value for developing the water purification industry.</p>
</abstract>

This paper discusses the critical impact of informatization automation on plant automation, and takes a water plant’s coagulation dosing automation control system as an example to explore the value of integrated wireless modules in the automation of electrical equipment. Algorithms for directly identifying the parameters of the second-order continuous model by regression model and based on the step response data are investigated, as well as the selection of the DMC algorithm for mathematical modeling of the coagulation dosing automation control. Finally, the effectiveness of the automated dosing system was verified by comparing its effectiveness in improving the qualified rate of precipitation water quality, reducing drug consumption and effluent turbidity, and improving stability. The study’s results showed that after using the coagulation dosing automation system, the water plant’s sedimentation water quality pass rate was increased from the original 85%~95% to 95%~100%. The drug consumption and effluent turbidity were reduced by 20.3% and 33.09% respectively, while the stability was also improved to different degrees. The coagulation dosing automated control system can dosage chemicals more accurately, safely and stably, which has specific reference value for developing the water purification industry.

Research on automation control technology of electrical and electronic equipment combined with integrated wireless module

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper discusses the critical impact of informatization automation on plant automation, and takes a water plant’s coagulation dosing automation control...

Research on automation control technology of electrical and electronic equipment combined with integrated wireless module

Data publikacji: 26 lut 2024

Zakres stron: -

Otrzymano: 10 sty 2024

Przyjęty: 19 sty 2024

DOI: https://doi.org/10.2478/amns-2024-0452

Słowa kluczowe
Regression analysis, Step response, DMC algorithm, Mathematical modeling, Automated control

© 2024 Xiaodong Han, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on automation control technology of electrical and electronic equipment combined with integrated wireless module

Data publikacji: 26 lut 2024

Zakres stron: -

Otrzymano: 10 sty 2024

Przyjęty: 19 sty 2024

DOI: https://doi.org/10.2478/amns-2024-0452

Słowa kluczoweRegression analysis, Step response, DMC algorithm, Mathematical modeling, Automated control

© 2024 Xiaodong Han, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Słowa kluczowe
Regression analysis, Step response, DMC algorithm, Mathematical modeling, Automated control