In-Process Monitoring and Control of Computer Numerical Control Machine Tool Operations

计算机数控机床操作的过程监控

• 批准号: 2599318
• 金额: --
• 依托单位: CARDIFF UNIVERSITY
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2599318
• 关键词: Process; Monitoring; Control; Computer; Numerical

This project will develop technology to create high-efficiency and reliability in Computer Numerical Control (CNC) machine operations using Acoustic Emission (AE), leading to an advanced tool control strategy.Machine tools are subject to wear and possible failure during their operational life that can lead to poorly manufactured parts or scrapping of a component. The aim of this four year studentship is therefore to use Acoustic Emissions to monitor the tool during the CNC process to move from the current approach of periodic wear measurements to an 'as required' approach leading to high-efficiency and importantly prevent tool failure. This project will develop a detailed understanding of AE signatures associated with the CNC process, released by the tool and the component, in normal operations and during defect development. Using Machine Learning a data interrogation approach that can identify wear will be developed leading to a control system capable of detecting tool damage that will automatically adjust the CNC process during manufacture. This will aid efficiency by removing the need to periodically measure tool wear and importantly prevent tool failure.

该项目将开发技术，以创建使用声发射（AE）的计算机数值控制（CNC）机器的高效率和可靠性，导致先进的工具控制策略。机动工具在其操作生活中可能会导致制造不良的零件或零件的零件。因此，这四年的学生的目的是使用声学排放在CNC过程中监视该工具，以从当前的定期磨损测量方法转变为“根据需要”的方法，从而导致高效效率，并且重要的是防止工具故障。该项目将对与CNC过程相关的AE签名进行详细的了解，该工具和组件在正常操作和缺陷开发过程中发布。使用机器学习可以识别磨损的数据询问方法将开发导致控制系统，该控制系统能够检测工具损坏，该刀具会在制造过程中自动调整CNC过程。这将通过消除定期测量工具磨损并重要防止工具故障的需求来帮助效率。