Cutting Force Estimation in a Micromilling Process

Author(s):  
B W Huang ◽  
J Z Cai ◽  
W L Hsiao
Author(s):  
Taiki Sato ◽  
Shuntaro Yamato ◽  
Yasuhiro Imabeppu ◽  
Naruhiro Irino ◽  
Yasuhiro Kakinuma

Abstract External sensor-less cutting force estimation using a load-side disturbance observer (LDOB) has potential to estimate the cutting force with high accuracy in both feed and cross-feed directions. However, the accuracy of its low frequency components in feed direction decrease due to effect of the friction and heat of a ball-screw-driven stage. In this study, DC and AC components of the cutting force is estimated by different methods; friction-compensated motor thrust force and LDOB, and the cutting force was estimated in real time by hybridizing them. In particular, regarding the friction model, the dynamic and static characteristics of the friction force in each axis (X, Y, Z) were identified from the idling test results. In addition to the model that depends on the velocity, the characteristics of the friction that depend on the position was also identified and considered when compensating for the motor thrust force. Then, a simple moving average filter with an appropriate window length is applied to the cutting force by LDOB and motor thrust force, and the DC component error of LDOB is corrected by that of motor thrust force. The validity of the proposed method was evaluated through end-milling tests. The experimental results showed that estimation accuracy of cutting force using the proposed method can be greatly improved in feed directions. On the other hand, in cross-feed direction, the cutting estimation was performed using the conventional LDOB.


2019 ◽  
Vol 41 ◽  
pp. 272-279
Author(s):  
Shuntaro Yamato ◽  
Yasuhiro Imabeppu ◽  
Naruhiro Irino ◽  
Norikazu Suzuki ◽  
Yasuhiro Kakinuma

2009 ◽  
Vol 3 (4) ◽  
pp. 415-421 ◽  
Author(s):  
Daisuke Kurihara ◽  
◽  
Yasuhiro Kakinuma ◽  
Seiichiro Katsura ◽  

Measuring cutting force is effective in monitoring machining processes, but requires that a force sensor be installed on the tool table. The parallel disturbance observer we propose in table control using velocity response and current reference realizes both robust control and cutting force estimation without additional sensors. Performance of this method was evaluated through simulation and experiments.


2020 ◽  
Vol 37 (11) ◽  
pp. 803-812
Author(s):  
Ki Hyeong Song ◽  
Dong Yoon Lee ◽  
Kyung Hee Park ◽  
Jae Hyeok Kim ◽  
Young Jae Choi

2017 ◽  
Vol 83 (851) ◽  
pp. 17-00098-17-00098 ◽  
Author(s):  
Yuki YAMADA ◽  
Yasuhiro KAKINUMA

2013 ◽  
Vol 69 (5-8) ◽  
pp. 1731-1741 ◽  
Author(s):  
H. Perez ◽  
E. Diez ◽  
J. J. Marquez ◽  
A. Vizan

Author(s):  
Yuki Yamada ◽  
Yasuhiro Kakinuma ◽  
Takamichi Ito ◽  
Jun Fujita ◽  
Hirohiko Matsuzaki

Cutting force is widely regarded as being the one of the most valuable information for tool condition monitoring. Considering sustainability, sensorless cutting force monitoring technique using inner information of machine tool attracts attention. Cutting force estimation based on motor current is one of the example, and it is applicable to detection of tool breakage with some signal processing technique. However, current signal could not capture fast variation of cutting force. By improving monitoring performance of cutting force, the hidden tool condition information is more accessible. In this study, monitoring performance of cutting force variation due to tool fracture was enhanced by using multi-encoder-based disturbance observer (MEDOB) and simple moving average. Friction force and torque which deteriorate monitoring performance was eliminated by moving average. First, monitoring accuracy of cutting force was verified through end milling test. Next, local peak value of estimated cutting force was extracted and the ratio of neighboring peak value was calculated to capture the tool fracture. Estimated value using MEDOB could capture the variation resulting from tool fracture.


2004 ◽  
Vol 44 (14) ◽  
pp. 1511-1526 ◽  
Author(s):  
A. Lamikiz ◽  
L.N. López de Lacalle ◽  
J.A. Sánchez ◽  
M.A. Salgado

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