Title :
Classification Technology for Automatic Surface Defects Detection of Steel Strip Based on Improved BP Algorithm
Author :
Peng Kaixiang ; Zhang Xuli
Author_Institution :
Sch. of Inf. Eng., Univ. of Sci. & Technol. Beijing, Beijing, China
Abstract :
The quality detection of the cold-strip steel using artificial neural networks is studied. A simple Back-propagation (BP) algorithm based on error function was presented. It deals with the saturation areas that play a significant role in the slow convergence of standard BP algorithm. A modified error function was constructed to make the weight adjustment to avoid falling into the saturation areas. The simulation and experiment results show the effect of improved BP algorithm on the classification of the surface defects of steel strip.
Keywords :
backpropagation; convergence; neural nets; pattern classification; quality assurance; steel; steel industry; BP algorithm; artificial neural networks; automatic surface defects detection; backpropagation algorithm; classification technology; cold-strip steel; error function; quality detection; steel strip; Artificial neural networks; Backpropagation algorithms; Computer errors; Computer networks; Convergence; Inspection; Metals industry; Neural networks; Steel; Strips; Back-propagation; Cold-strip steel; Error function; Fast convergence; Surface defect;
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
DOI :
10.1109/ICNC.2009.487
