Study On Technique Of Aircraft Intersection Holes Orifice Chamfering Based On Industrial Robot

In order to remove the burr and easy to assemble the parts,the orifice chamfering work of the aircraft intersection holes in the site assembly of large aircraft components has to be conducted.However,due to the specificity of the aircraft digital assembly,conventional machine couldn’t be used to machine the intersection holes.The orifice chamfering work of intersection holes is almost rely on manual processing and the hole quality is difficult to guarantee.In this dissertation,a robotic system is presented to accomplish orifice chamfering work.The main work is as follows:The application and research status of the robotics technology in aircraft assembly is introduced.Considering the flexibility of the industrial robot,a method based on the robot is proposed to accomplish the orifice chamfering work of intersection holes.The structure and maching process of the intersection holes chamfering system are introduced.Besides that,the control system of robot chamfering system are introduced.The robot is a series structure,resulting in difficulty in guaranteeing the machining quality.First,the vibration causes are analyzed by building system dynamics model.It is found that the obvious dynamic deformation of robot is produced by axial force and the forced vibration is formed by radial force and tangential force.Furthermore,a backward machining method is proposed to suppress the vibration of the robot by decreasing the resulting force acting on the robot.Finally,large numbers of forward and backward orifice chamfering contrast experiments have been conducted and the results verify the reliability of backward machining.Robotic backward orifice chamfering surface roughness prediction model based on RBF neural network is built using rotate speed,feed speed,grating ruler displacement,foot pressure as independent input parameters,and the chamfer surface roughness Ra ranks as output parameter.The results show that the RBF neural network prediction model of surface roughness has high forecasting accurate,and can provide reliable support for surface roughness prediction.