Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Milling force estimation using angular domain harmonics with Kalman filter using acceleration data
Download
Mertİlme_MSc_Thesis_Final.pdf
Date
2024-11-28
Author
İlme, Mert
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
10
views
1
downloads
Cite This
In order to make a contribution to the Industry 4.0 concept, today’s milling research is mainly focusing on the identification of the cutting process. To identify the cutting process, it is vital to know the cutting forces. Since directly measuring the force is costly and inconvenient, there is a need for a simpler way to indirectly estimate the cutting forces. In this thesis, a novel model-based estimation algorithm using the acceleration data is proposed. The model is based on a angular domain force model which consists of the harmonics at the orders of the tooth passing frequency. The force model is converted into the acceleration model by the frequency response function of the workpiece. The acceleration model is integrated into the Kalman filter. With the measured acceleration feedback, the Kalman filter estimates the cutting force. The proposed method is verified with experimental data.
Subject Keywords
Milling
,
Cutting force estimation
,
Kalman filtering
URI
https://hdl.handle.net/11511/112711
Collections
Graduate School of Natural and Applied Sciences, Thesis
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
M. İlme, “Milling force estimation using angular domain harmonics with Kalman filter using acceleration data,” M.S. - Master of Science, Middle East Technical University, 2024.