Process control sensor systems for copper production, ProCuPro

用于铜生产的过程控制传感器系统，ProCuPro

• 批准号: 530122-2018
• 负责人: Loock, HansPeter
• 金额: $ 5.83万
• 依托单位: Queen's University
• 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=692216
• 关键词: Process; control; sensor; systems; copper

Sensors and process control technology are lacking in copper production, and indeed in most non-ferrous production processes, because many of these processes are pyrometallurgical, i.e. they occur at high temperatures and in corrosive environments. Stand-off sensors such as optical probes and spectrometric systems can provide an elegant solution to this measurement challenge. Funded in part by NSERC-Engage and OCE, first steps have been taken by Queen's University and KPM towards an all-optical temperature probe, which had been tested by Aurubis, Hamburg in May 2018 by a queen's graduate student. With the current proposal, we intend to expand the suite of optical technologies for in-line probing of high-temperature industrial processes. We will use particle scattering to obtain dust particle size distributions. We will use fiber probe technologies to measure atomic emission, and absorption spectroscopy for chemical analysis. These techniques will be validated using off-line analysis through, e.g. by gas chromatography, X-ray Photoelectron Spectroscopy (XPS) and X-ray Diffraction (XRD). By correlating optical online measurements and product yields to the adjustable input parameters (feed composition, SO2 and O2 concentration, fuel concentration) we will create a database of operating conditions that will allow the operator to target the process towards a desired product composition and yield. The proposed work aligns very well with the objectives of the initiative "Advanced Manufacturing-Industry 4.0" as it entails the digital transformation of metal manufacturing, through the interactions between a distributed and multi-parameter sensor system, a deep database and the machinery operators. By correlating online and off-line information with desired product yields one may expect to increase reliability, product quality while reducing energy costs and reducing the environmental footprint. Graduate students and postdoctoral fellows will be trained in research lab at Queen's and Potsdam University, at a pilot plant at KPM and eventually on the production floor of an industrial smelter in Germany. Interactions with German project partners UPPC and Loptek will require visits to their facilities.

在铜生产中，实际上在大多数有色金属生产过程中，缺乏传感器和过程控制技术，因为这些过程中有许多是火法冶金，即它们发生在高温和腐蚀性环境中。 光学探头和光谱系统等独立传感器可以为这一测量挑战提供出色的解决方案。在NSERC-Engage和OCE的部分资助下，皇后大学和KPM已经朝着全光学温度探头迈出了第一步，该探头已于2018年5月在汉堡的Aurubis由皇后大学的研究生进行了测试。 通过目前的提议，我们打算扩大用于高温工业过程在线探测的光学技术套件。我们将使用粒子散射来获得灰尘的粒度分布。我们将使用光纤探针技术来测量原子发射，并使用吸收光谱进行化学分析。这些技术将使用离线分析进行验证，例如通过气相色谱法、X射线光电子能谱法（XPS）和X射线衍射法（XRD）。 通过将光学在线测量和产品产量与可调输入参数（进料组成、SO2和O2浓度、燃料浓度）相关联，我们将创建一个操作条件数据库，使操作员能够将工艺目标对准所需的产品组成和产量。 拟议的工作与“先进制造-工业4.0”倡议的目标非常一致，因为它需要通过分布式多参数传感器系统，深度数据库和机械操作员之间的交互来实现金属制造的数字化转型。通过将在线和离线信息与期望的产品产量相关联，人们可以期望提高可靠性、产品质量，同时降低能源成本并减少环境足迹。 研究生和博士后研究员将在皇后和波茨坦大学的研究实验室、KPM的一家试验工厂以及最终在德国的一家工业冶炼厂的生产车间接受培训。与德国项目合作伙伴UPPC和Loptek的互动将需要访问他们的设施。