海洋一号C/D（HY-1C/D）卫星中国海洋水色水温扫描仪（Chinese Ocean Color and Temperature Scanner,COCTS）主要用于探测海洋水色、水温等要素,这些要素需要经过卫星资料处理才能获取,而几何定位是预处理的核心,直接影响这些要素的质量。COCTS具有114°视场角和四元逐点摆扫的特征,据此研究出一套完整的几何定位方法。从0级数据中提取卫星星历,利用插值法从中获取采样时间对应的卫星位置和速度,进而得到轨道（ORB）坐标系到地心旋转（ECR）坐标系的转换矩阵。基于四元逐点摆扫的特征,中心视矢量分别绕X轴、Y轴旋转相应角度,获得扫描行各采样点ORB视矢量,建立视矢量与地球交叉点关系模型,从而对根据波段数据绘制的遥感图像进行地理定位。本文使用插值法替代了传统需要6个轨道根数来计算卫星位置的复杂方法,同时直接计算ORB到ECR的转换矩阵,而不采用传统的两步转换方法。经过多组数据计算及定性定量验证,HY-1C/D COCTS几何定位结果一致;采样像元尺度效应导致从星下点到两侧边缘、从赤道到两极,误差逐渐增大,约在两个像元内。该方法满足一定的定位精度要求,可以用于COCTS的几何定位。 相似文献
During the self-weight penetration process of the suction foundation on the dense sand seabed, due to the shallow penetration depth, the excess seepage seawater from the outside to the inside of the foundation may cause the negative pressure penetration process failure. Increasing the self-weight penetration depth has become an important problem for the safe construction of the suction foundation. The new suction anchor foundation has been proposed, and the self-weight penetration characteristics of the traditional suction foundation and the new suction anchor foundation are studied and compared through laboratory experiments and analysis. For the above two foundation types, by considering five foundation diameters and two bottom shapes, 20 models are tested with the same penetration energy. The effects of different foundation diameters on the penetration depth, the soil plug characteristics, and the surrounding sand layer are studied. The results show that the penetration depth of the new suction foundation is smaller than that of the traditional suction foundation. With the same penetration energy, the penetration depth of the suction foundation becomes shallower as the diameter increases. The smaller the diameter of the suction foundation, the more likely it is to be fully plugged, and the smaller the height of the soil plug will be. In the stage of self-weight penetration, the impact cavity appears around the foundation, which may affect the stability of the suction foundation.
Offshore wind energy resources are operational in cold regions, while offshore wind turbines will face the threat of icing. Therefore, it is necessary to study icing of offshore wind turbines under different icing conditions. In this study, icing sensitivity of offshore wind turbine blades are performed using a combination of FLUENT and FENSAP-ICE software, and the effects of liquid water content (LWC), medium volume diameter (MVD), wind speed and air temperature on blade icing shape are analyzed by two types of ice, namely rime ice and glaze ice. The results show that the increase of LWC and MVD will increase the amount of ice that forms on the blade surface for either glaze ice or rime ice, and an increase of MVD will expand the adhesion surface between ice and blade. Before reaching the rated wind speed of 11.4 m/s, it does not directly affect the icing shape. However, after reaching the rated wind speed, the attack angle of the incoming flow decreases obviously, and the amount of ice increases markedly. When the ambient air temperature meets the icing conditions of glaze ice (i.e., −5°C to 0°C), the lower the temperature, the more glaze ice freezes, whereas air temperature has no impact on the icing of rime ice. Compared with onshore wind turbines, offshore wind turbines might face extreme meteorological conditions, and the wind speed has no impact on the amount of ice that forms on the blade surface for most wind speeds
Facade structures from three-dimensional (3D) point cloud data (PCD) and two-dimensional (2D) optical images can provide significant information for 3D building modeling. However, a unified data model for integrating 2D imagery pixels and 3D PCD is absent in current methods, leading to a complex implementation process, large calculations, and inefficiency. An efficient facade structure extraction method for building facades is proposed in this study. Based on the conversion matrix, 2D image and 3D PCD information are merged to build an image-based laser point cloud (ILPC) data model first. Second, both the line segment detection and random sample consensus algorithms are improved according to the structure and characteristics of the ILPC data model. Finally, building facade structures are extracted and optimized. Facade structures can be extracted accurately and efficiently by the proposed method, which contains rich information support from the ILPC data model. The proposed method extracts fine building facade structures with accuracy over 0.68 in all experiments and recall up to 0.81, which are better than the Wang method. Extracted structures constitute valuable support for numerous fields, such as 3D building modeling and building information modeling construction. 相似文献
