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机构地区:[1]中航工业北京航空精密机械研究所,北京100076
出 处:《航空精密制造技术》2017年第4期20-23,43,共5页Aviation Precision Manufacturing Technology
摘 要:为了提高光学三角法测头在实际应用中的测量精度,本文在分析光学三角法测量原理的基础上,提出了一种基于自适应区域平均中点匹配算法的光学测头精度优化方法。该方法以空间域滤波思想为基础,可以根据测头的测量值自动判断测量误差的大小以及优化区域的大小,并可以针对不同表面给出相应的精度优化方法。实验结果表明,该优化算法可以准确描述被测物体表面的轮廓特征,并且能够降低测量误差50%以上,从而有效解决了光学扫描测量精度不足的问题,使测头能够达到微米级的测量精度,实现了零件的高效率、高精度测量。In order to improve the measuring accuracy of optical displacement sensors used in actual production scene, an accuracy optimization method used for optical displacement sensors based on the algorithm of the selfadjustingfield and average midpoint matching is proposed. Based on the idea of spatial filtering, the method could determine the measuring errors and the optimization area according to the different measured surfaces automatically. As the experiment results show, the optimization method could be used to describe the measured object precisely and decrease the measuring error to up to 50%, which may deal with the low accuracy of the optical scanning and measuring task. With the accuracy optimization method proposed, the sensor can reach the measuring accuracy of micrometer level. The measurement of high efficiency and high precision can be achieved.
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