Abstract
This paper describes the use of subharmonic sampling to distinguish between different instability types in milling. It is demonstrated that sampling time-domain milling signals at integer multiples of the tooth period enables secondary Hopf and period-n bifurcations to be automatically differentiated. A numerical metric is applied, where the normalized sum of the absolute values of the differences between successively sampled points is used to distinguish between the potential bifurcation types. A new stability map that individually identifies stable and individual bifurcation zones is presented. The map is constructed using time-domain simulation and the new subharmonic sampling metric.
Original language | English |
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Article number | 041009 |
Journal | Journal of Manufacturing Science and Engineering |
Volume | 139 |
Issue number | 4 |
DOIs | |
State | Published - Apr 1 2017 |
Externally published | Yes |
Funding
This material was based on the work supported by the National Science Foundation under Grant No. CMMI-1561221.
Funders | Funder number |
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National Science Foundation | CMMI-1561221 |
Keywords
- Bifurcation
- Machining
- Periodic
- Sampling
- Stability