Abstract
Accuracy of parallel kinematic machine (PKM) is affected by geometric parameters (GPs) and non-geometric parameters (NGPs). For GPs, the use kinematic error model (KEM) to calibrate these errors has been studied, but few of them have considered the influence of the linkage posture. In this paper, link-orientation-based joint error model (LOBJEM) and sensitivity analysis are presented. In LOBJEM, the original KEM, which is constant joint error model (CJEM), is derived first. The angle between each link and the Z axis is considered as the parameter to adjust the KEM to derive LOBJEM and it can cause the value of joint error to vary with the position of end effector. The calibration process includes measuring the positioning error by a laser interferometer, identifying the error terms using least square method and compensating by the numerical control code (NC-code). The error model and calibration process have been realized on the delta robot 3D printer. Compared with the CJEM, the residual error of LOBJEM was reduced from 75% to 60% of the original error. To estimate the positioning errors caused by NGPs, we constructed a backpropagation neural network model, which can reduce the final residual error to 25% of the original error.
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