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

基于知识的实时机床故障诊断仿真系统

• 批准号: 9114621
• 负责人: Jerry Banks
• 金额: $ 10万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1991
• 资助国家: 美国
• 起止时间: 1991-09-01 至 1994-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9114621&HistoricalAwards=false
• 关键词: Real; Time; Knowledge; Based; Simulation

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.

一个概括性的框架来描述质量 退化和预测关键部件之间的故障 在几台计算机数控机床中， 将进行调查。 “失败”在本文中是指 机床内关键部件的退化和/或 成品的质量。 该框架将整合 具有实时知识库和模拟的传感器设备 模型 实施的框架将提供一个综合的 维修主管了解质量的环境 降解过程中的各种关键成分， 并获得有关其故障时间的早期警告 的间隔虽然框架是通用的，但实现 将仅限于诊断磨削质量下降 机械. 研究将侧重于建立一个经过测试的知识库 用于表征研磨过程中的质量退化过程 机器，并减少提供决策的响应时间 使用知识库和模拟。 促进转移已 将通过与工业界的互动取得成果 提案国