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