RBF Neural Network Model Training by Unscented Kalman Filter and its Application in Mechanical Fault Diagnosis
2014 ◽
Vol 602-605
◽
pp. 2383-2386
◽
Keyword(s):
To improve the ability of fault diagnosis for mechanical equipment, a Radial Basis Function Neural Network (RBFNN) diagnosis method based on Unscented Kalman Filter (UKF) algorithm is proposed. In the algorithm, at first, UKF algorithm is used to estimate the parameters of RBFNN, and then the proposed method is introduced into the fault diagnosis of mechanical equipment. The simulation indicates that the established model has a good diagnosis performance for mechanical fault diagnosis.
2013 ◽
Vol 385-386
◽
pp. 589-592
2018 ◽
Vol 435
◽
pp. 012023
Keyword(s):
2019 ◽
Vol 234
(4)
◽
pp. 1167-1182
◽
1998 ◽
Vol 13
(1)
◽
pp. 177-183
◽
Keyword(s):
2014 ◽
Vol 8
(1)
◽
pp. 410-417
◽
Keyword(s):
2010 ◽
Vol 2
(3)
◽
pp. 164
Keyword(s):
Keyword(s):
Keyword(s):