Study on Self-Configuration Method of Neural Network Model for Grinding Troubles On-Line Monitoring

2007 ◽  
pp. 199-203
Author(s):  
Gui Jie Liu ◽  
Qiang Wang ◽  
Xiao Long Shi ◽  
Ren Ke Kang
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
On Line

The Random Neural Network Model for the On-Line Multicast Problem

2005 ◽  
pp. 157-164 ◽  
Author(s):  
Giovanni Aiello ◽  
Salvatore Gaglio ◽  
Giuseppe Lo Re ◽  
Pietro Storniolo ◽  
Alfonso Urso
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Random Neural Network ◽  
On Line

Fault Diagnosis of Coal Electrical Shearer Based on Quantum Neural

2014 ◽  
Vol 574 ◽  
pp. 452-456 ◽  
Author(s):  
Xian Min Ma ◽  
Mei Hui Xu
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Network Model ◽  
Neural Network Model ◽  
Learning Algorithm ◽  
Nonlinear Function ◽  
Theory Analysis ◽  
Quantum Neural Network ◽  
On Line ◽  
Nonlinear Feature

An improved quantum neural network model and its learning algorithm are proposed for fault diagnosis of the coal electrical haulage shearer in order to on line monitor working states of the large mining rotating machines. Based on traditional BP neural network, the three-layer quantum neural network is constructed to combine quantum calculation and neural network for the error correction learning algorithm. According to the information processing mode of the biology neuron and the quantum computing theory, the improved quantum neural network model has the ability of identifying uncertainty in fault data classifications and approximating the nonlinear function for different fault types to monitor the electrical motor voltage, current, temperature, shearer location, boom inclination, haulage speed and direction in the coal electrical cutting machines. The theory analysis and simulation experiment results show that the control performances and the safety reliability of the coal shearer are obviously improved, while the quantum neural network model is applied to the nonlinear feature fault diagnosis of the coal electrical haulage shearer.

Sign in / Sign up

Export Citation Format

Share Document