Integrated Prognostics, Maintenance and Life Extending Control of Mechanical and Production Systems

9424587该提案支持对连续时间生产过程的综合预测、维护和延长寿命控制的研究。研究包括三个任务。第一项任务是建立随机疲劳损伤动力学模型，该模型的数据由实验确定，并从已发表的文献中获得。本文将以一个具体的化石燃料电厂模型为例。第二个任务侧重于基于连续变化和离散事件模型的决策和控制策略的综合。该公式将包括在有限时间范围内使用非线性规划的前馈策略，在反馈回路中用于非线性决策和控制的约束参数优化，以及使用有限状态自动机的概念用于协调和监督级别的维护决策和寿命延长控制的交互式离散事件策略。第三项任务是在仿真试验台上对决策与控制系统进行仿真。如果成功，这项研究将提高工厂的安全性、操作可靠性和连续生产过程的可用性，如化工厂和加工厂、纸浆厂和造纸厂以及大型轧钢厂。结果还应扩展到离散的生产过程，如制造玻璃容器和灯泡，半导体，陶瓷搪瓷涂料的电器和食品产品。这项研究向基于感官和操作信息的控制和诊断系统可用于改善工厂操作特性的概念迈进了一步。

9424587 This proposal supports research in integrated prognostics, maintenance, and life-extending control of continuous time production processes. The research includes three tasks. The first task involves the development of stochastic fatigue damage dynamics models with data determined by experiment and obtained from published literature. A specific fossil fuel power plant model will be used as an example case. The second task focuses on the synthesis of decision and control policies based on both continuously varying and discrete-event models. This formulation will include a feed-forward policy over a finite time horizon using nonlinear programming, a constrained parameter optimization for nonlinear decision and control in a feedback loop, and interactive discrete event strategies for maintenance decisions and life-extending control at the coordination and supervisory levels using the concept of finite-state automata. The third task is the simulation of the decision and control system on a simulation testbed. If successful, this research will lead to enhanced plant safety, operational reliability, and availability of continuous-time production processes such as chemical and processing plants, pulp and paper mills, and large rolling mills. The results should also be extendable to discrete production processes such as the manufacture of glass containers and light bulbs, semi-conductors, ceramic-enamel coatings on appliances, and food products. This research comprises a step toward the notion that control and diagnostic systems based on sensory and operational information can be used to improve plant operational characteristics.