Temperature Measurement Method for Blast Furnace Molten Iron Based on Infrared Thermography and Temperature Reduction Model

Pan, Dong; Jiang, Zhaohui; Chen, Zhipeng; Gui, Weihua; Xie, Yongfang; Yang, Chunhua

doi:10.3390/s18113792

Cited by 21 publications

(9 citation statements)

References 32 publications

(30 reference statements)

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“…When only the most three significant variables in terms of t-statistic are used an intermediate MAE of 0.0694 is obtained. The three ARIMA based models gave good results for w > 1000 in Equations (7) and (9), while higher training window widths gave only marginal error reduction, as can be seen in Figure 8. Figure 8 allows us to appreciate what is the best expected method in terms of MAE, depending on data availability.…”

Section: Time Series Forecastingmentioning

confidence: 83%

“…Usually, the actual hot metal temperature is intermittently measured by an operator using disposable thermocouples. Since this method only provides partial information, continuous determination of temperature by means of combined modeling and indirect measurements is a growing area of interest in BF [7][8][9][10], but comparable efforts for BOF have not yet been reported [11,12].…”

Section: Introductionmentioning

confidence: 99%

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

2019

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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.

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Section: Time Series Forecastingmentioning

confidence: 83%

Section: Introductionmentioning

confidence: 99%

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

2019

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“…Finally, the ballistic studies could be enhanced by thermal techniques, for instance in [ 23 ]. Furthermore, the industrial processes may be controlled or inspected by thermal innovative techniques, like in [ 24 , 25 ], in which the infrared techniques were used to continuously measure the molten iron temperature and provide robust data to control a blast furnace.…”

Section: Introductionmentioning

confidence: 99%

Temperature Measurement of a Bullet in Flight

Kerampran

Gajewski

Sielicki

2020

Sensors

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This study answers a primary question concerning how the temperature changes during the flight of a bullet. To answer the question, the authors performed unique research to measure the initial temperatures of bullet surfaces and applied it to four kinds of projectiles in a series of field experiments. The technique determines the temperature changes on metallic objects in flight that reach a velocity of 300 to 900 m/s. Until now, the tests of temperature change available in the literature include virtual points that are adopted to ideal laboratory conditions using classic thermomechanical equations. The authors conducted the first study of its kind, in which is considered four projectiles in field conditions in which a metallic bullet leaves a rifle barrel after a powder deflagration. During this process, heat is partly transferred to the bullet from the initial explosion of the powder and barrel-bullet friction. In this case, the temperature determination of a bullet is complex because it concerns different points on the external surface. Thus, for the first time the authors measured the temperatures at different position on the bullet surface. Moreover, the authors showed that basic thermodynamic equations allow for the credible prediction of such behavior if the initial conditions are identified correctly. This novel identification of the initial conditions of temperature and velocity of flying bullets was not presented anywhere else up to now.

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“…Measurement has been developed through the physical sciences and plays a very important role in industry, commerce, health and safety, and environmental protection [1][2][3][4][5]. A unified model of measurement systems is critical to the design and optimization of measurement systems.…”

Section: Introductionmentioning

confidence: 99%

An Information Entropy-Based Modeling Method for the Measurement System

Kong

Pan

et al. 2019

Entropy

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Measurement is a key method to obtain information from the real world and is widely used in human life. A unified model of measurement systems is critical to the design and optimization of measurement systems. However, the existing models of measurement systems are too abstract. To a certain extent, this makes it difficult to have a clear overall understanding of measurement systems and how to implement information acquisition. Meanwhile, this also leads to limitations in the application of these models. Information entropy is a measure of information or uncertainty of a random variable and has strong representation ability. In this paper, an information entropy-based modeling method for measurement system is proposed. First, a modeling idea based on the viewpoint of information and uncertainty is described. Second, an entropy balance equation based on the chain rule for entropy is proposed for system modeling. Then, the entropy balance equation is used to establish the information entropy-based model of the measurement system. Finally, three cases of typical measurement units or processes are analyzed using the proposed method. Compared with the existing modeling approaches, the proposed method considers the modeling problem from the perspective of information and uncertainty. It focuses on the information loss of the measurand in the transmission process and the characterization of the specific role of the measurement unit. The proposed model can intuitively describe the processing and changes of information in the measurement system. It does not conflict with the existing models of the measurement system, but can complement the existing models of measurement systems, thus further enriching the existing measurement theory.

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Temperature Measurement Method for Blast Furnace Molten Iron Based on Infrared Thermography and Temperature Reduction Model

Cited by 21 publications

References 32 publications

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

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

Temperature Measurement of a Bullet in Flight

An Information Entropy-Based Modeling Method for the Measurement System

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