Process Monitoring, Diagnosis and Control

过程监测、诊断和控制

• 批准号: 9820846
• 负责人: Suraj Alexander
• 金额: $ 11.6万
• 依托单位: University of Louisville Research Foundation Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-06-01 至 2003-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9820846&HistoricalAwards=false
• 关键词: Process; Monitoring; Diagnosis; Control

This grant provides funding to develop, test, and evaluate a framework for process monitoring, diagnosis, and control. The unique feature of this framework is the integration of diagnosis, with monitoring and control. In existing process monitoring and control systems process compensatory adjustments are made without regard to the cause of process disturbances, or diagnosis is attempted without any guidance. This is not efficient. The multiresolution analysis capability of wavelet theory will be used as a "mathematical microscope" to glean process fingerprints, which are then mapped to a diagnosis. The mapping is done by extracting statistical features from wavelet transforms and utilizing neural networks. Diagnostic information obtained from the fingerprints will be used by a control decision module to make the "optimal" control decision. This framework will be tested and evaluated in the laboratory and in actual industrial settings. With manufacturing becoming more automated, many online sensors for process monitoring and control have been developed, however, the methods used for monitoring and control have not adapted to this, nor has the information available been used effectively. The results of this research, which uses both coarse and detailed views of processes, can be used for effective and efficient monitoring, diagnosis and control. This would reduce process variability, and improve process capability, resulting in higher quality and efficient production. This framework is applicable to other areas such as, equipment maintenance, medicine and finance, where the integration of monitoring and diagnosis offers considerable advantages.

这项拨款为开发、测试和评估过程监测、诊断和控制的框架提供资金。该框架的独特之处在于将诊断与监测和控制相结合。在现有的过程监视和控制系统中，过程补偿调整不考虑过程干扰的原因，或者在没有任何指导的情况下进行诊断。这是没有效率的。小波理论的多分辨率分析能力将被用作“数学显微镜”来收集过程指纹，然后将其映射到诊断中。通过提取小波变换的统计特征并利用神经网络进行映射。从指纹中获得的诊断信息将被控制决策模块用来做出“最优”的控制决策。该框架将在实验室和实际工业环境中进行测试和评价。随着制造业的自动化程度越来越高，许多用于过程监测和控制的在线传感器已经被开发出来，然而，用于监测和控制的方法并没有适应这种情况，也没有有效地利用可用的信息。这项研究的结果使用了粗略和详细的过程视图，可用于有效和高效的监测，诊断和控制。这将减少过程的可变性，提高过程能力，从而提高生产质量和效率。该框架适用于设备维护、医疗和金融等其他领域，在这些领域，监测和诊断的整合提供了相当大的优势。