Title :
Application of Hopfield network integrating with SA operator in fitting of micro-drill´s main lips
Author :
Ge, Dong-Yuan ; Yao, Xi-Fan ; Xiang, Wen-Jiang
Author_Institution :
Sch. of Mech. & Automotive Eng., South China Univ. of Technol., Guangzhou, China
Abstract :
For measurement chips of micro-drill´s main lips, a novel data processing was presented. While the line of micro-drill´s main lips is fitted, the special structure´s Hopfield neural network is designed according to normal equation. The neural network has 2 neurons, the weights of which are elements of normal equation´s symmetry matrix, the input numerical value of which are the vector consisted of equation´s right terms, and asynchronous work means is adopted. And via integrating simulated annealing algorithm, the iteration is carried at every control temperature in the light of Metropolis acceptive criterion, the probability of convergence global optical solution is 1 with iteration operator. While the temperature approximate to desired value and the network attain to stability states, the states vector can be taken as coefficients of fitted main lips line, According to which the straightness errors or chips of micro-drill´s main lips line can be solved.
Keywords :
Hopfield neural nets; drilling; fitting (assembly); iterative methods; mechanical engineering computing; simulated annealing; stability; temperature control; Hopfield neural network; SA operator; control temperature; iteration operator; metropolis acceptive criterion; micro drill main lips; simulated annealing algorithm; stability states; symmetry matrix; Artificial neural networks; Equations; Hopfield neural networks; Lips; Mathematical model; Pixel; Simulated annealing; Global convergence; Hopfield network; Metrology; Micro-drill; Objective function; Simulated annealing; States vector;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-6712-9
DOI :
10.1109/WCICA.2010.5555042