Affiliation:
1. 6250 Applied Science Lane Vancouver, BC V6T 1Z4 Canada
2. Mechanical Engineeirng Department 2054-6250 Applied Science Lane Vancouver, BC V6T1Z4 Canada
Abstract
Abstract
The structural dynamics of a machine tool at the tool center point characterizes its vibration response and machining stability which affects productivity. The dynamics are mostly dominated by the spindle-holder-tool assembly whose main vibration mode can change during machining due to centrifugal forces, thermal expansion, and gyroscopic moments generated at high spindle speeds. This paper proposes the identification of the spindle's in-process modal parameters: natural frequency, damping ratio and modal constant, by using a limited number of vibration transmissibility and critical chatter stability measurements. The classical inverse stability solution, which tunes the modal parameters to minimize prediction errors in chatter stability limits, is augmented with vibration transmissibility under two methods: (1) transmissibility-enhanced inverse stability solution: the modal parameters are updated to minimize prediction errors in chatter stability, and vibration transmissibility; (2) artificial neural network (ANN)-integrated inverse stability solution: the ANN uses vibration transmissibility to estimate the natural frequency and damping ratio, such that the inverse stability solution only needs to identify the modal constant. While both methods are experimentally validated, it is shown that the transmissibility-enhanced inverse stability solution is a more effective approach than the time-consuming ANN alternative for the estimation of in-process spindle dynamics.
Funder
Natural Sciences and Engineering Research Council of Canada
Subject
Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Control and Systems Engineering
Cited by
6 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献