Multi-sensor Dean Stark alternative for online bitumen/solids/water estimation

用于在线沥青/固体/水估算的多传感器 Dean Stark 替代方案

• 批准号: 550316-2020
• 负责人: Prasad, Vinay
• 金额: $ 5.83万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=701822
• 关键词: Multi; sensor; Dean; Stark; alternative

In the context of oil sands sensing, very few commercial technologies exist, and the lack of sensors has held back progress in automation, monitoring, control and optimization of the extraction process.This project involves the development of a sensor that can measure the composition, i.e. the bitumen, water and clay content in the process streams in oil sands extraction online. This information is vital for the monitoring, control and optimization of the process, but is challenging for many reasons: the widely varying composition in the process streams and the complexity of the mixtures themselves in terms of the number of components. This will be addressed in this project by using a multifunctional sensor, i.e. an array of techniques, and by combining the information from these sensors using sophisticated data fusion and informatics techniques. The elements of the sensing strategy include multiple spectroscopic and microwave-based techniques, which can be deployed online. These sensors will be calibrated against offline techniques so that they can then be employed online in a 'soft sensing' framework.

在油砂传感的背景下，很少有商业技术，缺乏传感器 该项目阻碍了自动化，监视，控制和优化的提取过程。此信息对于过程的监视，控制和优化至关重要，但是由于许多原因：过程流中的构图广泛变化以及混合物本身的复杂性在组件的数量方面。该项目将通过使用多功能传感器，即一系列技术来解决这一点，并使用复杂的数据融合和信息学技术将来自这些传感器的信息组合在一起。传感策略的元素包括可以在线部署的多种光谱和基于微波炉的技术。这些传感器将针对离线技术进行校准，以便可以在“软感应”框架中在线使用它们。