基于自校准技术提出了用于影像仪的误差分离方法。建立了自校准算法模型, 并利用影像仪对算法模型进行了实验验证。该算法运用普通栅格板来替代标准器, 将栅格板置于影像仪工作台3个不同位置得到3组测量数据, 通过研制的测量数据转换模型将得到的数据代入自校准算法模型中, 最终将测量结果中包含的仪器系统误差分离出来, 实现了自校准。由于运用了测量数据转换模型, 有效解决了实验过程中栅格板所在坐标系与影像仪工作台坐标系不重合的问题, 提高了影像仪测量结果的准确度。测试实验显示: 测量点实际测得的误差为毫米级, 经过自校准算法处理后得到的测量点的系统误差最大为0.49 μm, 最小为0.00 μm, 表明将自校准算法应用于影像测量仪结果的误差分离具有较好的可行性。

A measuring error separation method was proposed on the basis of self-calibration algorithm for an imaging instrument. A self-calibration model was established and verified by the imaging instrument. A regular grid plate was used to replace the standard, and the grid plate was put on the image instrument stage in three different positions to get three sets of measurement data. The data were put into the self-calibration model through the developed transformation model in advance. Then, the system error contained in the measurement results was separated, and self-calibration was implemented. As measurement data transformation model was established, the problem of misalignment between grid plate and stage coordinate system was solves effectively during the process of experiment and the measuring accuracy of the imaging instrument was improved. Experiments show that the error of the measurement point is or millimeter scale without the self-calibration algorithm, but the maximum and minimum errors of the measurement point after self-calibration are 0.49 μm and 0.00 μm respectively. The results mean that it is feasible to apply the self-calibration algorithm to error separation of measurement results for the image measuring instrument.