Control, estimation and prognostic for partially observable deteriorating systems with multivariate observations

通过多变量观测对部分可观测的恶化系统进行控制、估计和预测

• 批准号: 121384-2011
• 负责人: Makis, Viliam
• 金额: $ 1.97万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2014
• 资助国家: 加拿大
• 起止时间: 2014-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=545304
• 关键词: Control; estimation; prognostic; partially; observable

The objective of the proposed research is to develop the optimal control, estimation, and prognostic procedures for models of partially observable deteriorating systems subject to random failure, considering both single failure mode as well as a combination of degradation and sudden failure (competing risks). The models will be formulated and developed with practical applications in mind, to represent real systems as well as possible. Condition monitoring is currently widely used both in industries and medicine to prevent the occurrence of high degradation or failure, both of which have serious consequences. In technical applications, these are mainly the cost or safety consequences, in medical applications, the high cost is combined with health issues. In most cases, diagnosis of a disease in an early stage results in a better prognosis of successful cure at lower cost. Condition monitoring and screening procedures currently in use have not been designed optimally or even sub-optimally. They are widely used and more such procedures will soon be implemented especially in the healthcare sector worldwide, but also in many larger companies mainly in industries where stopping, full inspection, and testing is very expensive. Proper system modeling and the optimal design of such procedures, which is the focus of the proposed research is expected to bring huge economic as well as health benefits. The proposed research is highly novel and unique in the world. The results obtained so far using simpler system modeling are very promising and considerably better results are expected with the proposed more advanced modeling and better utilization of multivariate data for estimation, prognostic, as well as optimal decision-making. The Principal Investigator has extensive experience with modeling, estimation and control of deteriorating systems as well as practical experience acquired through collaboration with the University of Toronto CBM Consortium companies and many other companies for many years. He will continue publishing the unique results of his research in the top international journals and it is expected that results obtained in the proposed research will contribute very significantly to the further development of the discipline.

建议的研究的目的是开发的最优控制，估计和预测程序的模型部分可观察恶化系统随机故障，考虑单一的故障模式以及组合的退化和突然故障（竞争风险）。这些模型将在考虑实际应用的情况下制定和开发，以尽可能代表真实的系统。状态监测目前广泛应用于工业和医学，以防止发生高度退化或故障，这两者都有严重的后果。在技术应用中，这些主要是成本或安全后果，在医疗应用中，高成本与健康问题相结合。在大多数情况下，在早期阶段对疾病进行诊断，可以以较低的成本获得成功治愈的更好预后。 目前使用的状况监测和筛选程序尚未被最佳地或甚至次最佳地设计。它们被广泛使用，并且很快将实施更多这样的程序，特别是在全球医疗保健行业，而且在许多大型公司中，主要是在停止，全面检查和测试非常昂贵的行业中。 适当的系统建模和优化设计等程序，这是拟议的研究重点，预计将带来巨大的经济效益以及健康效益。这项研究在国际上是非常新颖和独特的。迄今为止，使用更简单的系统建模获得的结果非常有希望，并且通过提出更先进的建模和更好地利用多变量数据进行估计、预测以及最佳决策，预计会获得更好的结果。首席研究员在建模、估计和控制退化系统方面拥有丰富的经验，并通过与多伦多大学CBM联盟公司和许多其他公司多年的合作获得了实践经验。他将继续在国际顶级期刊上发表他的研究的独特成果，预计在拟议的研究中获得的结果将对该学科的进一步发展做出非常重要的贡献。