Performance analysis for online chemical process optimization systems

在线化工过程优化系统的性能分析

• 批准号: 194372-2008
• 负责人: Forbes, Fraser
• 金额: $ 1.96万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2009
• 资助国家: 加拿大
• 起止时间: 2009-01-01 至 2010-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=423220
• 关键词: Performance; analysis; online; chemical; process

Online optimization is widely used in the chemical process industries to ensure competitiveness though a high level of process performance. Common applications of online optimization in these industries include real-time optimization (RTO), model-predictive control (MPC), reactive scheduling, supply-chain optimization, and so forth. These online optimization technologies are, typically, complex and require regular maintenance to ensure their continued high performance (i.e., the performance of these automation systems degrade over time due to a number of factors). Thus, a key, but currently missing, element of online optimization systems is an effective performance analysis subsystem, which would include: performance monitoring, failure detection, and failure diagnosis.

在线优化广泛应用于化工过程工业，以确保高水平的过程性能的竞争力。在线优化在这些行业中的常见应用包括实时优化（RTO）、模型预测控制（MPC）、无功调度、供应链优化等。这些在线优化技术通常是复杂的，并且需要定期维护以确保其持续的高性能（即，这些自动化系统的性能由于许多因素而随着时间而降低）。因此，在线优化系统的一个关键但目前缺少的元素是有效的性能分析子系统，其将包括：性能监视、故障检测和故障诊断。