Research On Automatic Bending Control System And Optimization Of Bending Process Parameters Of Hydraulic Coreless Bending Machine

The hydraulic coreless bending machine studied in this paper is a machine that bends the pipe into a certain angle.It is mainly used for the processing of hydraulic pipes.The quality of the bending pipe is of great significance to the hydraulic system.The bending of the pipe is a nonlinear complex process with multi-factor coupling interactive effects.if the various parameters are improperly selected during the bending process of the pipe,it is prone to cause quality defects,such as cracking,cross-section distortion,wrinkling,rebound,etc.Therefore,it is of great significance to improve the degree of automation of the pipe bending machine and to reasonably select the forming parameters for ensuring the development of the pipe bending machine and the quality of the bending pipe.In this paper,the methods and defects of pipe bending are firstly summarized.Based on the plane strain assumption,exponential hardening model,Mises yield criterion and other conditional theories,the mechanical model of pipe bending forming is analyzed,and the process parameters of the coreless bending process of the pipe are studied experimentally.The influence of process parameters such as bending angle,relative bending radius,relative pipe diameter and bending speed,on wall thickness reduction,cross-section distortion and spring-back defects in the process of coreless bending of pipes is studied experimentally.Then,the hydraulic coreless bending machine is taken as the research object,and the database of bending processing parameters is established according to the characteristics of stainless-steel tube coreless bending.The camera is used as the sensor,and the automatic coreless bending control system based on image processing technology is designed and implemented.Finally,based on the process parameter database,the nonlinear mapping relationship between process parameters and forming quality is established by BP neural network,and particle swarm optimization algorithm are used to optimize the design of the bending process parameters for ensuring the maximum working efficiency when the quality of bending pipe meets the requirements.