The Research On Movement Pose Accuracy And Image Processing Of The Welding Seam Of Arc Welding Robot

The movement pose accuracy of arc welding robot is an important indicator to reflectthe performance of the robot, as well as the guarantee for the robot's normal operation andmeeting the requirements on high-accuracy welding. With meeting the practical needs ofproduction of Nanyang RG Petro-machinery (Group) Co., Ltd. as the purpose, this paperdevelops an arc welding robot for welding of large structural parts like oil derrick, tankand etc., and performs systematic research on the arc welding robot developed fromaspects such as error modeling analysis, accuracy evaluation on coordinated movementtrack, calibration of geometric parameter error and welding seam tracking, etc. The majorefforts are as follow:(1) According to the features of large structural parts like oil derrick, tank andetc. that the welding seams are of large number and relatively unitary forms, this paperanalyzes in detail functional combinations need to be realized for welding by robot; andselected from many combinations the body design of Arc Welding Robot and makes aprototype of the robot,and builds a robot kinematic model and performs kinematicsimulation; and builds a Arc Welding Robot pose error model by using "smalldisplacement perturbation method", and deduces the error calculus formula for hand poseof the robot.(2) According to the fact that Arc Welding Robot mainly performs welding of spatialline welding seams, this paper analyzes the arithmetic principle of coordinated linemovement of arc welding robot, fits spatial line welding seams with "least squares fittingmethod" on its basis, and uses the deviation between the least squares fitting of the actualtrack and the instructive track to evaluate the accuracy of coordinated movement track ofthe robot; relative evaluation indicators are also determined to provide criterion for theaccuracy evaluation of coordinated movement track of the arc welding robot system,thebinocular stereo visual measurement method is used to measure the geometric parametererror of all articulations of the robot, and corresponding error are compensated. The resultshows that after error compensation, the accuracy of the movement track of the robotgreatly improves. (3) According to the practical situation of welding production, two welding seamtracking systems are designed. One is proximity sensor welding seam trackingsystem. This system is of simple construction and convenient operation and will not beinfluenced by arc flue dust and splash; however, it is not able to track for tanks withadditional components like protruding platform. So, another welding seam trackingsystem based on binocular stereo vision is designed, and in order to solve the problem ofimage processing of the welding seam tracking system, an image processing technologybased on mutual information is presented.(4) To accelerate the calculation of mutual information, this paper presents to use theprinciple pf maximization of entropy to subdivide images, making the subdivided imagescontain more details of the original image, consequently the mutual information betweenthe subdivided binary image and the binary template and the mutual information betweenthe original gray level image and the gray level template have similar distribution. Boththeory and welding test prove that the algorithm presented in this paper can effectivelyguarantee that the welding seam tracking is real-time and accurate.