Engineering Faculty Internship: Intelligent Machine Tool Monitoring: A Neural Network Approach

这项研究将扩展和增强以前的工作， 基于知识的机器故障诊断，使用人工神经网络 网络. 这一努力的起点将是 以前机器监控研究的框架。 分析 将进行行为现象建模， 建立空间定量和定性关系 考虑因素和故障诊断模型。 这个模型将是 连接到真实的世界进行智能监控。 用于诊断的机床智能监控 目的在自动化制造中非常重要 环境. 这项工作是在密切合作下进行的 与一个主要的制造组织，并可能产生 重要成果。

This research will extend and augment previous work on knowledge-based machine fault diagnosis, using artificial neural networks. The starting point of this effort will be the framework of previous machine monitoring research. Analytical modeling of behavioral phenomenon will be carried out to establish quantitative and qualititative relationships of spatial considerations and fault diagnosis models. This modeling will be interfaced to the real world to carry out intelligent monitoring. Intelligent monitoring of machine tools for diagnostic purposes is of great importance in automated manufacturing environments. This work is being conducted in close cooperation with a major manufacturing organization and is likely to yield important results.