Real-Time Cutting Force/Torque Prediction During Turning
Author(s) -
Kazuto Enomoto,
Masaya Takei,
Yasuhiro Kakinuma
Publication year - 2012
Publication title -
international journal of automation technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.513
H-Index - 18
eISSN - 1883-8022
pISSN - 1881-7629
DOI - 10.20965/ijat.2012.p0669
Subject(s) - machining , stiffness , torque , shear force , automation , observer (physics) , process (computing) , machine tool , computer science , shear (geology) , mechanical engineering , reliability (semiconductor) , control theory (sociology) , engineering , structural engineering , materials science , artificial intelligence , physics , power (physics) , control (management) , thermodynamics , quantum mechanics , composite material , operating system
The automation of machining processes requires highly accurate process monitoring. However, the use of additional sensors leads to a significant increase in the cost and reduces the stiffness and reliability of mechanical systems. Hence, we propose a system called the cutting force observer, which uses a sensor-less and real-time cutting force estimation methodology based on the disturbance observer theory. Monitoring methods using the cutting force observer may enhance the productivity during turning. One of the parameters that significantly affect the cutting process is the shear angle. The determination of the shear angle is very important as it can be used for identifying the machining conditions. In this study, an external sensor-less monitoring system of the shear angle during turning is developed, and its performance is evaluated.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom