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自动化设备外表面腐蚀区域激光清洗技术研究 被引量:1
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作者 李萌锋 黄少敏 林燕强 《工业加热》 CAS 2022年第6期42-46,共5页
自动化设备表面材质易发生腐蚀,导致设备存在运行安全隐患问题。提出自动化设备外表面腐蚀区域激光清洗技术。确定激光清洗过程中材质表面与介质膜间温度随时间与空间变化的规律,判定设备外表面腐蚀区域中微粒杂质的吸附力与毛细力。基... 自动化设备表面材质易发生腐蚀,导致设备存在运行安全隐患问题。提出自动化设备外表面腐蚀区域激光清洗技术。确定激光清洗过程中材质表面与介质膜间温度随时间与空间变化的规律,判定设备外表面腐蚀区域中微粒杂质的吸附力与毛细力。基于此建立最小二乘积空间插补算法,利用拟合空间中任意三点到设立终点坐标的距离关系,取得有关空间向量的直线。用这条垂直线代替原始空间中内的所有曲线段,获取最优距离,完成自动化设备外表面腐蚀区域激光清洗。仿真实验结果证明,所提方法对腐蚀区域的氧元素和其他杂质去除效果较好,整体能耗较小,且方法应用效率较高,能保证清洗后设备的表面纹路、机理、不会被破坏,且不会出现腐蚀残留,可以有效完成腐蚀区域的清洗。 展开更多
关键词 介质膜 吸附力 毛细力 空间插补算 最小二乘积法
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PARAMETERIZATION OF TRIANGULAR MESHES
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作者 SHENHui-cun ZHOULai-shui ZHANGLi-yan 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2004年第2期106-110,共5页
A new algorithm called the weighted least square discrete parameterization (WLSDP) is presented for the parameterization of triangular meshes over a convex planar region. This algorithm is the linear combination of th... A new algorithm called the weighted least square discrete parameterization (WLSDP) is presented for the parameterization of triangular meshes over a convex planar region. This algorithm is the linear combination of the discrete Conformal mapping(DCM) and the discrete Authalic mapping(DAM). It provides the good properties of both DCM and DAM, such as robustness and low distortion. By adjusting the scaling factor q embedded in the WLSDP, satisfactory parameterizations in different special applications can be achieved. 展开更多
关键词 triangular meshes weighted least square discrete parameterization discrete Conformal mapping discrete Authalic mapping
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Pose optimization based on integral of the distance between line segments 被引量:3
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作者 ZHANG YueQiang LI Xin +2 位作者 LIU HaiBo SHANG Yang YU QiFeng 《Science China(Technological Sciences)》 SCIE EI CAS CSCD 2016年第1期135-148,共14页
In this paper, new solutions for the problem of pose estimation from correspondences between 3D model lines and 2D image lines are proposed. Traditional line-based pose estimation methods rely on the assumption that t... In this paper, new solutions for the problem of pose estimation from correspondences between 3D model lines and 2D image lines are proposed. Traditional line-based pose estimation methods rely on the assumption that the noises(perpendicular to the line) for the two endpoints are statistically independent. However, these two noises are in fact negatively correlated when the image line segment is fitted using the least-squares technique. Therefore, we design a new error function expressed by the average integral of the distance between line segments. Three least-squares techniques that optimize both the rotation and translation simultaneously are proposed in which the new error function is exploited. In addition, Lie group formalism is utilized to describe the pose parameters, and then, the optimization problem can be solved by means of a simple iterative least squares method. To enhance the robustness to outliers existing in the match data, an M-estimation method is developed to convert the pose optimization problem into an iterative reweighted least squares problem. The proposed methods are validated through experiments using both synthetic and real-world data. The experimental results show that the proposed methods yield a clearly higher precision than the traditional methods. 展开更多
关键词 machine vision perspective-n-line problem line distance function pose optimization M-estimation
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