Time Series Modeling and Analysis of Cutter Wear in Milling Operation

Author

Mingjin, Yang ; Xiwen, Li ; Tielin, Shi ; Shuzi, Yang

Author_Institution

Southwest Univ., Chongqing, China

Volume

3

fYear

2011

fDate

6-7 Jan. 2011

Firstpage

1023

Lastpage

1026

Abstract

The online time series Auto Regressive Models were built to analyze and monitor the cutter wear of a milling operation. The experimental setup and data acquisition scheme were presented to test the validity of these models. Signals of spindle motor power, displacement and acceleration of the milling were used for time series modeling and analysis. Experiment and analysis results showed that the models of signals of displacement in Y-axis and acceleration in X-axis are sensitive to cutter wear of the milling, and they can be employed as cutter wear conditions monitoring in the milling operation.

Keywords

autoregressive processes; condition monitoring; cutting tools; data acquisition; milling machines; time series; wear testing; cutter wear analysis; data acquisition scheme; milling acceleration; milling displacement; online time series auto regressive model; spindle motor power signal; Acceleration; Analytical models; Data acquisition; Mathematical model; Milling; Monitoring; Time series analysis; Analysis; Cutter Wear Condition; Milling Operation; Modeling; Time Series Method;

fLanguage

English

Publisher

ieee

Conference_Titel

Measuring Technology and Mechatronics Automation (ICMTMA), 2011 Third International Conference on

Conference_Location

Shangshai

Print_ISBN

978-1-4244-9010-3

Type

conf

DOI

10.1109/ICMTMA.2011.826

Filename

5721663