关键词: 电化学加工, 表面粗糙度, 神经网络, 预测

Abstract:

It can be an important vehicle to investigate surface roughness of the parts caused by the electrochemical processing and working current, handling backlash, electrolyte temperature, machining time, electrolyte ratio etc. These relevant processing parameters presented a non-linear relationship according to the parts roughness characteristics. Due to this relevance mechanism was still unexplored in the current electrochemical machining method, this paper investigated the relationship of previous processing parameters and the roughness characteristics in a mathematics way. Accordingly, a mathematical model was set up for expected BPNN training study. Through the experimental  data acquisition and training operations, it shows that in this way a minor prediction error is produced. In this case, utilizing the orthogonal analysis method, the surface characteristics with large changement amplitude can be realized with the optimized processing parameters.

Key words: electrochemical machining, surface roughness, neural network(NN), prediction