六极铁作为高能同步辐射光源(High Energy Photon Source,HEPS)储存环八铁单元的重要部件之一,其技术工艺较为复杂,对加工精度和中心引出精度要求都很高。本文对HEPS六极铁的机械中心引出标定方案进行了研究,利用极缝偏差角对常规标定...六极铁作为高能同步辐射光源(High Energy Photon Source,HEPS)储存环八铁单元的重要部件之一,其技术工艺较为复杂,对加工精度和中心引出精度要求都很高。本文对HEPS六极铁的机械中心引出标定方案进行了研究,利用极缝偏差角对常规标定坐标系进行旋转,使三个极缝面更接近理论位置,从而减小磁铁主场斜分量;对每块磁铁进行两次机械中心标定,极缝间距的实测值与设计值的标准偏差在0.015 mm,坐标系旋转前后的基准点偏差标准值为0.09 mm,旋转角最大可达0.6 mrad。这种考虑极缝偏差角的建系方法可以提高标定的精度,能为实际工作中同类型、准直精度有相同要求的设备标定提供参考,有利于加速器装置的顺利安装,对加速器准直测量具有十分重要的意义。展开更多
In this paper, a new approach of muhi-modality image registration is represented with not only image intensity, but also features describing image structure. There are two novelties in the proposed method. Firstly, in...In this paper, a new approach of muhi-modality image registration is represented with not only image intensity, but also features describing image structure. There are two novelties in the proposed method. Firstly, instead of standard mutual information （ MI ） based on joint intensity histogram, regional mutual information （ RMI ） is employed, which allows neighborhood information to be taken into account. Secondly, a new feature images obtained by means of phase congruency are invariants to brightness or contrast changes. By incorporating these features and intensity into RMI, we can combine the aspects of both structural and neighborhood information together, which offers a more robust and a high level of registration accuracy.展开更多
文摘In this paper, a new approach of muhi-modality image registration is represented with not only image intensity, but also features describing image structure. There are two novelties in the proposed method. Firstly, instead of standard mutual information （ MI ） based on joint intensity histogram, regional mutual information （ RMI ） is employed, which allows neighborhood information to be taken into account. Secondly, a new feature images obtained by means of phase congruency are invariants to brightness or contrast changes. By incorporating these features and intensity into RMI, we can combine the aspects of both structural and neighborhood information together, which offers a more robust and a high level of registration accuracy.
