Abstract
The application of the pattern recognition technique for process monitoring in end milling is discussed in this paper. Cutting forces, torque, and spindle vibrations are monitored during machining, and are used to generate several signal features which are shown to be rather sensitive to the process conditions under consideration. Five machining conditions (classes) are considered in this study, namely; tool life end, chatter, stable cutting, air and transient cutting. A linear discriminant function-based technique is used for the identification of process conditions. The performance of the classifier is evaluated by numerous cutting tests. The results indicate correct rates of recognition for each class ranging from 85% to 100%.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
