A new infrared camera-based technology for the optimization of the Waelz process for zinc recycling

Matthes, Jörg; Waibel, Patrick; Keller, Hubert B.

doi:10.1016/j.mineng.2011.04.020

Cited by 25 publications

(14 citation statements)

References 3 publications

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“…Thus, linear regression regression is adopted to quantify the measurement errors caused by the dust on the surface of the measured object. The specific formulas for the measurement error calculation, in which R-square was 0.993, is shown in (6).…”

Section: B Compensation Modelmentioning

confidence: 99%

Influence of Dust on Temperature Measurement Using Infrared Thermal Imager

et al. 2020

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Temperature measurement by infrared thermal imager is an attractive technique in many fields, and it is of great importance to ensure the measurement accuracy of the infrared thermal imager. Aiming at the influence of dust on the temperature measurement of infrared thermal imager, this paper summarized the dust influence into three categories: dust on the surface of the measured object, dust on the infrared thermal imager's lens and dust in the optical path between the measured object and the infrared thermal imager, and conducted three dust experiments. To quantify the measurement errors caused by dust, the infrared thermal image features that are affected by dust are extracted and a compensation model is established based on polynomial regression. The results indicate that dust can introduce measurement errors of infrared thermal imager and the proposed compensation method can compensate for the measurement errors caused by dust and improve the accuracy of infrared thermal imager.

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Section: B Compensation Modelmentioning

confidence: 99%

Influence of Dust on Temperature Measurement Using Infrared Thermal Imager

et al. 2020

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“…Matthes et al [11], no entanto, relatam que a temperatura máxima dos sólidos atinge 1250°C e a redução da zincita, ZnO, já começa a 800°C, através da Reação 1. ZnO + C  Zn(g) + CO (Reação 1)…”

Section: O Forno Waelzunclassified

“…Após, o zinco volatilizado é reoxidado (ainda dentro do forno) na zona gasosa, conforme a Reação 2 [11].…”

Section: O Forno Waelzunclassified

Modelo Termodinâmico Para O Forno Waelz

Reis¹,

Heck²

2018

ABM Proceedings

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ResumoO pó de aciaria elétrica (PAE) é um importante subproduto da indústria siderúrgica devido ao seu alto teor de Zn. Assim, tecnologias vêm sendo desenvolvidas visando seu aproveitamento, sendo o forno Waelz a mais difundida delas atualmente. Sua operação, por contar com um forno rotativo de grandes dimensões, que abriga uma infinidade de fenômenos físico-químicos, apresenta difícil previsibilidade ab initio. Por essa razão, este trabalho faz uso de uma ferramenta avançada da termodinâmica computacional, destinada à modelagem de processos, chamada SimuSage, a fim de modelar o seu comportamento. Para a criação do modelo utilizou-se também uma base de dados termodinâmicos advinda do software FactSage e a plataforma Lazarus. Com base em dados e resultados operacionais da literatura, foi possível realizar simulações no modo adiabático e comparar os resultados com os da prática industrial. Constatou-se uma grande sensibilidade do modelo com relação à quantidade de ar de entrada considerada no sistema, mas, também, boa aproximação dos resultados com relação à composição química dos produtos Óxido Waelz e Escória Waelz. Palavras-chave: Pó de aciaria elétrica; Forno Waelz; SimuSage. THERMODYNAMIC MODEL FOR THE WAELZ KILN AbstractThe electric arc furnace dust (EAFD) is a by-product of the steel industry due to its high content of Zn. Thus, technologies have been developed aiming for its use, and the Waelz Kiln is the most widespread of them today. However, counting on a very large rotary kiln that houses an infinity of physico-chemical phenomena, its operation is difficult to predict ab initio. For this reason, this work uses an advanced tool of computational thermodynamics, designed to process modelling, called SimuSage in order to model its behavior. To create the model, a thermodynamic database coming from the FactSage software and the Lazarus platform were also used. Based on operational data and results from de literature, it was possible to perform simulations on adiabatic mode and compare its results with the industrial practice. A high sensibility of the model was found related to the amount of input air considered in the system, but also good approximation of results regarding the chemical composition of products, Waelz Oxide and Waelz Slag.

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“…for the calculation of th control variable mean solid bed/slag temperature ϑ 3 , the detected lump regions are omitted, which improves the reliability of the solid bed temperature measurement compared to a pyrometer (see Figure 3). Additionally, information about the rheological behavior of the slag like repose and filling angle can be extracted from the IR images (Matthes et al, 2011), (He et al, 2009).…”

Section: Image Processingmentioning

confidence: 99%

Camera based Identification and Control of the Waelz Process

Matthes

Waibel

Keller

et al. 2016

Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics

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The Waelz process is the most common technique for the pyro-metallurgical treatment of zinc-bearing residues using a rotary kiln. However, this process will only result in a good zinc recovery, if the temperature of the material (slag) within the kiln is controlled at specific optimal setpoints depending on the material mixture. Until now, slag temperature measurement is carried out by pyrometers which give only pointwise information that can be disturbed by cold slag lumps. Additionally, the temperature control is performed only manually by operators, who have to adapt the amount of process air frequently to keep the process stable at the desired setpoints. In this paper an infrared-camera based measurement of the slag temperature using image processing techniques is presented. Based on that temperature measurement a process model is conducted. Its parameters are estimated by a model-output-error based process identification. The process model is used for the tuning of parameters of an automatic closed loop control. Finally, results from an industrial application of the new camera based slag temperature control are given.Matthes, J., Waibel, P., Keller, H. and Gröll, L. Camera based Identification and Control of the Waelz Process.

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A new infrared camera-based technology for the optimization of the Waelz process for zinc recycling

Cited by 25 publications

References 3 publications

Influence of Dust on Temperature Measurement Using Infrared Thermal Imager

Influence of Dust on Temperature Measurement Using Infrared Thermal Imager

Modelo Termodinâmico Para O Forno Waelz

Camera based Identification and Control of the Waelz Process

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