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Open AccessFeature PaperArticle

Hot Metal Temperature Prediction at Basic-Lined Oxygen Furnace (BOF) Converter Using IR Thermometry and Forecasting Techniques

Polytechnic School of Engineering, University of Oviedo, 33204 Gijón, Spain
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Energies 2019, 12(17), 3235; https://doi.org/10.3390/en12173235
Received: 18 June 2019 / Revised: 20 July 2019 / Accepted: 14 August 2019 / Published: 22 August 2019
In oxygen steelmaking, the charge calculation strongly depends on hot metal temperature prediction. Although a hot metal temperature drop from the blast furnace in a steel plant may be too complex to be accurately modeled in detail, the combined use of sensors and statistical models can improve temperature estimation and result in better cost, quality and productivity, as well as lower emissions. In order to develop a simple but robust method for hot metal temperature forecasting, the suitability of infrared thermometry and time series forecasting has been studied. Simultaneous infrared thermometer measurement and video recording was used for designing the processing of the thermometer signal. The resulting temperature estimations are in good agreement with disposable thermocouple measurements giving an error of 11 °C with 60% reliability (chances of obtaining a successful output). Conversely, the time series approach was based mainly on the AutoRegressive Integrated Moving Average (ARIMA) model in which five additional process variables were introduced as exogenous predictors, as well as using a moving window of past observations for continuous model training. The resulting error was 15 °C with more than 90% reliability. Combining measuring and modeling approaches reduced the error to 13 °C with 100% reliability, thereby providing a hybrid procedure that has long-term stability and is self-adaptive to varying production scenarios. View Full-Text
Keywords: steelmaking; BOF charge model; infrared thermometry; data-driven modeling; time series forecasting; ARIMA steelmaking; BOF charge model; infrared thermometry; data-driven modeling; time series forecasting; ARIMA
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Díaz, J.; Fernández, F.J.; Suárez, I. Hot Metal Temperature Prediction at Basic-Lined Oxygen Furnace (BOF) Converter Using IR Thermometry and Forecasting Techniques. Energies 2019, 12, 3235.

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