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Online Heat Pattern Estimation in a Shaft Furnace by Particle Filter Logic

Authors:
Yoshinari Hashimoto
Kazuro Tsuda

Keywords: Particle Filter; Data Assimilation.

Abstract:
In steel-making plants, there are many processes, such as the blast furnace, in which the internal state is not directly observable. Automation of such processes based on process visualization is an urgent issue. Because the number of sensors is limited, the state estimation utilizing partial sensor information is necessary. We developed a technique which visualizes the whole temperature distribution of a shaft furnace by combining the sensor information and a nonlinear model calculation. Assuming that the difference between the model calculation and actual data derives from the fluctuation of unknown parameters which cannot be measured online, the parameters are estimated by a particle filter. This way, a robust state estimation logic was established. This technique was implemented and evaluated in a ferro-coke pilot plant at JFE Steel Corporation. As a result, estimation accuracy improved by 30 % compared with the model calculation without the state estimation.

Pages: 183 to 188

Copyright: Copyright (c) IARIA, 2014

Publication date: October 12, 2014

Published in: conference

ISSN: 2308-4537

ISBN: 978-1-61208-371-1

Location: Nice, France

Dates: from October 12, 2014 to October 16, 2014