Tail Gas Quality Warning System in a Sulfur Recovery Unit based on H2S and SO2 Concentration Soft Sensor utilizing Multi-State-Dependent Modeling Method

Tail Gas Quality Warning System in a Sulfur Recovery Unit based on H2S and SO2 Concentration Soft Sensor utilizing Multi-State-Dependent Modeling Method

The design and development of data-driven soft sensors is important to predict the concentration of perilous pollutants in industry effluents to protect environmental health. The aim of this research is to design a tail gas quality warning system in the sulfur recovery unit (SRU) based on H2S and SO...

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Bibliographic Details
Main Authors:	Fereshte Tavakoli Dastjerd, Farhad Shahraki, Jafar Sadeghi, Mir Mohammad Khalilipour, Bahareh Bidar
Format:	Article
Language:	English
Published:	University of Sistan and Baluchestan 2023-12-01
Series:	International Journal of Industrial Electronics, Control and Optimization
Subjects:	pollutants data-driven soft sensor sulfur recovery unit multi-state-dependent parameter generalized random walk
Online Access:	https://ieco.usb.ac.ir/article_8028_4dd19a474c304b42e724082bd0ce6bc9.pdf

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