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.

该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）质量下降和变异性增加对铝电解槽性能的影响。为了实现这一目标，将开发和测试新的过程分析传感器，以快速、无损地评估生阳极和烘烤阳极的质量。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，并开发烘烤阳极检查方案，以检测其内部结构（大孔和裂纹）内是否存在缺陷并进行诊断。这部分研究计划预计将有助于生产更高质量、更一致的阳极，并能够在发生异常情况时及时反馈对阳极制造过程实施纠正措施。在该计划的第二部分中，还将提出结合分析传感器提供的信息以及从阳极制造和铝还原过程中常规收集的数据的建模工具，以便更好地了解电池中的阳极如何影响其性能和各个阳极是如何消耗的。这些新知识随后将用于建立烘焙阳极电阻率和检查结果的多变量规格区域，以便在烘焙前对有缺陷的生阳极进行分类，并在放入电池之前对有缺陷的烘焙阳极进行分类。该模型还可以支持决策，确定哪些电池是接收下一组新鲜阳极的最佳候选者，以及在电池中的哪个位置以最大限度地降低其性能恶化的风险。使用所提出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，此外还有助于保持加拿大铝工业在全球范围内的竞争力和领导地位。