TY - JOUR
T1 - Modeling and prediction of workpiece nonlinear physical quantities based on extended Kalman filter
AU - Zhang, Mengdi
AU - Lu, Jiping
AU - Zhang, Faping
N1 - Publisher Copyright:
© 2024 Institute of Physics Publishing. All rights reserved.
PY - 2024
Y1 - 2024
N2 - For the workpiece from the tool withdrawal time until the lifting of the fixture constraint is called the in-situ state. In this process, the workpiece's state quantity changes with time, and the state quantity can be regarded as a time series physical quantity. Therefore, the physical state and geometric physical quantities in the in-situ stage can be characterized by time sequence through the deformation theory. Kalman filter is a kind of optimal estimation method that includes two processes: prediction and correction. In the process of prediction estimation, only the optimal estimation of the last time needs to be stored, which can reduce the operation cost and improve the prediction efficiency. Since the state quantity of the workpiece in situ becomes nonlinear, this paper uses the extended Kalman filter for characterization modeling and nonlinear prediction, combines the typical heat-force coupling model with the extended Kalman filter for representation, and finally obtains the modeling characterization and result prediction of the filter state quantity.
AB - For the workpiece from the tool withdrawal time until the lifting of the fixture constraint is called the in-situ state. In this process, the workpiece's state quantity changes with time, and the state quantity can be regarded as a time series physical quantity. Therefore, the physical state and geometric physical quantities in the in-situ stage can be characterized by time sequence through the deformation theory. Kalman filter is a kind of optimal estimation method that includes two processes: prediction and correction. In the process of prediction estimation, only the optimal estimation of the last time needs to be stored, which can reduce the operation cost and improve the prediction efficiency. Since the state quantity of the workpiece in situ becomes nonlinear, this paper uses the extended Kalman filter for characterization modeling and nonlinear prediction, combines the typical heat-force coupling model with the extended Kalman filter for representation, and finally obtains the modeling characterization and result prediction of the filter state quantity.
UR - http://www.scopus.com/inward/record.url?scp=85205444702&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/2842/1/012099
DO - 10.1088/1742-6596/2842/1/012099
M3 - Conference article
AN - SCOPUS:85205444702
SN - 1742-6588
VL - 2842
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 012099
T2 - 2024 11th International Conference on Advanced Manufacturing Technology and Materials Engineering, AMTME 2024
Y2 - 22 May 2024 through 23 May 2024
ER -