A Real-Time Knowledge-Based Simulation System for DiagnosingMachine Tool Failure

一个广义的框架表征质量退化和预测失效之间的关键部件在几个计算机数控机床将进行研究。此处的“故障”是指机床内关键部件的退化和/或成品的质量。该框架将集成传感设备与实时知识库和仿真模型。实施的框架将为维护主管提供一个集成环境，以了解机床内各种关键部件的质量退化过程，并获得有关其故障时间间隔的早期预警。虽然该框架是通用的，但其实现将局限于诊断磨床的质量退化。研究的重点是建立一个可测试的知识库来表征磨床内的质量退化过程，并利用知识库和仿真来减少提供决策的响应时间。成果的技术转让将通过与工业赞助者的相互作用来实现。

A generalized framework for characterizing the quality degradation and predicting failures among critical components within several computer numerically controled machine tools will be investigated. "Failure" in this context refers to degradation of the critical components within a machine tool and/or the quality of the finished product. This framework will integrate sensory devices with real-time knowledge bases and simulation models. The implemented framework will provide an integrated environment for a maintenance supervisor to understand the quality degradation process for various critical components within a machine tool and obtain early warnings about their failure time intervals. Although the framework is general, the implementation will be restricted to diagnosing quality degradation in grinding machines. The research will focus on building a tested knowledge base for characterizing the quality degradation process within grinding machines, and reducing the response time in providing decisions using knowledge bases and simulation. Technology transfer of the results will be achieved through interaction with industrial sponsors.