scholarly journals A Study on Chatter Prediction in High-Speed End Milling Process by Fuzzy Neural Network.

2000 ◽  
Vol 66 (641) ◽  
pp. 332-338
Author(s):  
Chuanxin SU ◽  
Junichi HINO ◽  
Toshio YOSHIMURA
Keyword(s):  
Neural Network ◽  
High Speed ◽  
Fuzzy Neural Network ◽  
End Milling ◽  
Milling Process ◽  
Chatter Prediction ◽  
Fuzzy Neural ◽  
End Milling Process

scholarly journals Faults diagnosis in stator windings of high speed solid rotor induction motors using fuzzy neural network

2021 ◽  
Vol 12 (1) ◽  
pp. 597
Author(s):  
Ahmed Thamer Radhi ◽  
Wael Hussein Zayer
Keyword(s):  
Neural Network ◽  
Equivalent Circuit ◽  
High Speed ◽  
Fuzzy Neural Network ◽  
Induction Motors ◽  
Stator Winding ◽  
Three Phase ◽  
Fuzzy Neural ◽  
Diagnosis Method ◽  
Faults Diagnosis

The paper deals with faults diagnosis method proposed to detect the inter-turn and turn to earth short circuit in stator winding of three-phase high-speed solid rotor induction motors. This method based on negative sequence current of motor and fuzzy neural network algorithm. On the basis of analysis of 2-D electromagnet field in the solid rotor the rotor impedance has been derived to develop the solid rotor induction motor equivalent circuit. The motor equivalent circuit is simulated by MATLAB software to study and record the data for training and testing the proposed diagnosis method. The numerical results of proposed approach are evaluated using simulation of a three-phase high-speed solid-rotor induction motor of two-pole, 140 Hz. The results of simulation shows that the proposed diagnosis method is fast and efficient for detecting inter-turn and turn to earth faults in stator winding of high-speed solid-rotor induction motors with different faults conditions

Predictive Model of Surface Roughness in High-Speed End Milling Process by Factorial Design of Experiments

2007 ◽  
Vol 339 ◽  
pp. 189-194
Author(s):  
Su Yu Wang ◽  
Xing Ai ◽  
Jun Zhao
Keyword(s):  
Surface Roughness ◽  
Design Of Experiments ◽  
Factorial Design ◽  
High Speed ◽  
End Milling ◽  
Milling Process ◽  
Regression Coefficients ◽  
Milling Parameters ◽  
Factorial Design Of Experiments ◽  
End Milling Process

Predictive models are presented for the surface roughness in high-speed end milling of 0.45%C steel and P20 die-mould steel based on statistical test and multiple-regression analysis. The data for establishing model is derived from experiments conducted on a high-speed machining centre by factorial design of experiments. The significances of the regression equation and regression coefficients are tested in this paper. The effects of milling parameters on surface roughness are investigated by analyzing the experimental curves.

906 A Study on Chatter Prediction Using By Fuzzy Neural Network

2000 ◽  
Vol 005.1 (0) ◽  
pp. 309-310
Author(s):  
Satoru HANAOKA ◽  
Junichi HINO ◽  
Toshio YOSHIMURA
Keyword(s):  
Neural Network ◽  
Fuzzy Neural Network ◽  
Chatter Prediction ◽  
Fuzzy Neural
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