Higher order statistics estimation of the modeling error for chatter monitoring
This paper proposes a design method for chatter monitoring based on the fourth order statistics estimation applied to the modelling error. Usually, a test of hypothesis is built on an a priori knowledge of the statistical distribution. The frequency function is often assumed Gaussian. In the case of machining process without chatter, the Gaussian assumption is not valid. Consequently, the proposal of an adaptive estimation of the fourth cumulant on a sliding window is introduced for machining process monitoring with possible chatters. The modelling error of the cutting force is the difference between the output of nonlinear model of cutting force and a real force estimation taking into account the stiffness of the sensor. A milling process illustrates the effectiveness of the proposed chatter monitoring strategy.
| Attachment | Size |
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| Charbonnaud Adc Prod Mach 52 Iproms07.wmv | 12.19 MB |
I work on new supervision strategies and I have proposed an application to milling process. We have applied the method only for conventional machining process. For High speed machining or micro machining, the operating conditions are differents. Each new process must be analyzed to validate the assumptions linked to our method.
Thank you for your question.
Best regards
Philippe Charbonnaud
Thank you for your contribution to IPROMS2007 and for your video presentation.
Have you tried the proposed method with different tool diameters or machining conditions? In particular, do you think your method could work well for micro milling where tool diameters can be as small as 50 um?
Thanks,
Emmanuel