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

该研究的目的是发展部分可观测退化系统随机失效模型的最优控制、估计和预测方法，既考虑单一失效模式，又考虑退化和突然失效(竞争风险)的组合。这些模型的制定和开发将考虑到实际应用，以尽可能地代表真实的系统。目前，状态监测被广泛应用于工业和医学，以防止高度退化或故障的发生，这两种情况都会产生严重的后果。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，早期诊断疾病会以较低的成本获得更好的成功治愈的预后。目前正在使用的状况监测和筛选程序的设计并不是最优的，甚至不是最优的。它们被广泛使用，很快将实施更多这样的程序，特别是在世界各地的医疗保健部门，但也会在许多较大的公司实施，主要是在停车、全面检查和测试非常昂贵的行业。适当的系统建模和此类程序的优化设计是拟议研究的重点，预计将带来巨大的经济和健康效益。这项拟议的研究在世界上是非常新颖和独特的。到目前为止，使用SIMPLE系统建模获得的结果是非常有希望的，随着所提出的更先进的建模和更好地利用多变量数据进行估计、预测和最优决策，预期会有相当好的结果。首席调查员在不断恶化的系统的建模、评估和控制方面拥有丰富的经验，以及通过与多伦多大学煤层气联盟公司和许多其他公司合作多年获得的实践经验。他将继续在国际顶级期刊上发表其独特的研究成果，预计拟议研究取得的成果将对该学科的进一步发展作出重大贡献。

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.