Abstract
Laser trackers (LTs) are indispensable instruments in large-scale dimensional metrology. Nevertheless, geometric errors are prone to increase in site environments due to the occurrence of mechanical and optical misalignments, which deteriorates the measurement accuracy of the LT. The geometric error parameters are difficult to determine by traditional measuring or calibrating approaches. In this paper, a classification calibration method is proposed without any other etalons or instruments that accurately estimate the geometric error parameters in a site environment. First, to determine the environmental sensitivity error parameters, a refractive index correction model in a variable temperature environment is constructed, which performs well in reducing the interference of environmental temperature fluctuations. Subsequently, a spatial measurement network is established to determine two-face sensitivity error parameters using the difference between the frontsight and backsight measurements of the targets. Finally, the two-face non-sensitivity error parameters are solved by minimizing the residuals of the coordinate transformation from each LT station to the reference frame. Indeed, the effects of temperature fluctuation and geometrical misalignments on the measurement accuracy are deeply analyzed, which provide meaningful guidance for calibration and compensation of the geometric errors of the LT. The effectiveness of the proposed method is validated by a series of site experiments. The results show that the length error is reduced to 0.030mm on average, which is 44% lower than that of the network method.
Published Version
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