Optimize for isothermal forging electrohydraulic servo system based on EtherCAT and geneticBP neural network
                                                                               LI Xin1, WANG Xiaoyan2
(1. Department of Scientific Research, Nanchong Professinal Technic College, Nanchong 637131, China;2. College of Mechanical Engineering, Chongqing University, Chongqing 400030, China)

Abstract: Aiming at the problems of low accuracy for forging load, speed, and unstable for beam in finitestroke forokoked, a scheme for process optimization was proposed based on EtherCAT and geneticBP network. Master monitoring interface was designed by LabVIEW. Then communication protocol between each module was configured, and ActiveX was used to design interface between geneticBP and LabVIEW, UDP/IP was used to exchange monitoring data. Simulation precision was used to simulate the optimization accuracy of the nonlinear model, and beam state was monitored in real time. The results indicate that the overall control error of load and speed is less than 2.5% through geneticBP algorithm optimization, and beam leveling state is stable, which effectively improves the problems of isothermal forging electrohydraulic servo system.

Key words: isothermal forging electrohydraulic servo system; EtherCAT; LabVIEW; geneticBP neural network