Quality control of baked carbon anodes and assessment of their performance in aluminium reduction cells

铝电解槽中烘烤碳阳极的质量控制及其性能评估

• 批准号: 509004-2017
• 负责人: Duchesne, Carl
• 金额: $ 0.93万
• 依托单位: Université Laval
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=675346
• 关键词: Quality; control; baked; carbon; anodes

The aim of this research program is to improve the decision making of primary aluminum smelters and anode manufacturers to mitigate the impact of the declining quality and increasing variability of the anode raw materials (coke and pitch) on aluminum reduction cell performance. To achieve this, new process analytical sensors will be developed and tested for rapid and non-destructive assessment of green and baked anode quality. These will be used to design an automatic control strategy to minimize the anode electrical resistivity, and to develop a baked anode inspection scheme to detect the presence of defects within their internal structure (large pores and cracks) and diagnose them. This part of the research program is expected to contribute to producing higher quality anodes and more consistently, and to enable timely feedback corrective actions to be implemented on the anode manufacturing process when abnormal situations occur. In the second part of the program, modelling tools combining the information provided by the analytical sensors and the routinely collected data from the anode manufacturing and aluminum reduction processes will also be proposed in order to better understand how the anodes populating a cell affects its performance and how individual anodes are consumed. These new learnings will subsequently be utilized to establish multivariate specifications regions for baked anode electrical resistivity and inspection results in order to sort defect green anodes before baking, and defect baked anodes before being set in the cells. The models could also support decision making on which cells would be the best candidates to receive the next set of fresh anodes and in which position in the cell to minimize the risk of deteriorating its performance. Expected benefits from improved decision making using the proposed sensors and modelling tools includes costs savings, waste reduction, lower carbon consumption, and higher energy efficiency, in addition to help maintaining the competitiveness and leadership position of the Canadian aluminum industry Worldwide.

本研究计划的目的是改善原铝冶炼厂和阳极制造商的决策，以减轻阳极原材料（焦炭和沥青）质量下降和变化增加对铝电解槽性能的影响。为了实现这一目标，将开发和测试新的工艺分析传感器，用于快速和非破坏性评估绿色和焙烧阳极质量。这些将用于设计自动控制策略，以最大限度地减少阳极电阻率，并开发一个焙烧阳极检查方案，以检测其内部结构（大孔隙和裂纹）中是否存在缺陷，并对其进行诊断。研究计划的这一部分预计将有助于生产更高质量的阳极和更一致的，并使及时反馈纠正措施，以实施阳极制造过程中发生异常情况时。在该计划的第二部分，还将提出将分析传感器提供的信息与阳极制造和铝还原过程中常规收集的数据相结合的建模工具，以便更好地了解阳极填充电池如何影响其性能以及如何消耗单个阳极。随后将利用这些新知识来建立烘焙阳极电阻率和检查结果的多元规范区域，以便在烘焙之前对有缺陷的绿色阳极进行分类，并在将有缺陷的烘焙阳极放入电解槽之前对它们进行分类。这些模型还可以支持关于哪些电池将是接收下一组新阳极的最佳候选者以及在电池中的哪个位置以最小化其性能恶化的风险的决策。使用拟议的传感器和建模工具改进决策的预期好处包括节省成本，减少浪费，降低碳消耗和提高能源效率，以及帮助保持加拿大铝业在全球的竞争力和领导地位。