DocumentCode :
1566856
Title :
Residual Adaptive Algorithm Applied in Intelligent Real-time Calculation of Current RMS Value During Resistance Spot Welding
Author :
Gong, Liang ; Liu, Cheng-Liang ; Guo, Lei
Author_Institution :
Mechatronics Inst., Shanghai Jiao Tong Univ.
Volume :
3
fYear :
2005
Firstpage :
1800
Lastpage :
1806
Abstract :
To solve the large residual problems, which may occur during feed-forward neural network weight training, a comprehensive residual adaptive algorithm is proposed to give a better stability compared to standard Levenberg-Marquardt (L-M) algorithm and has less computational complexity than classical Newton method. The comparison with standard L-M algorithm checks the better performance of this algorithm. Then the well-trained neural network is embedded into a DSP controller to perform real-time calculation of current RMS value during resistance spot welding. Experimental result shows the validity of the residual adaptive algorithm and the feasibility of an intelligent current measuring method
Keywords :
adaptive systems; calculation; computational complexity; electric current measurement; feedforward neural nets; neurocontrollers; spot welding; stability; computational complexity; current RMS value; feedforward neural network; intelligent real-time calculation; residual adaptive algorithm; resistance spot welding; Adaptive algorithm; Computational complexity; Computational intelligence; Digital signal processing; Feedforward neural networks; Feedforward systems; Neural networks; Newton method; Spot welding; Stability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9422-4
Type :
conf
DOI :
10.1109/ICNNB.2005.1614976
Filename :
1614976
Link To Document :
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