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Semirigid optimal step iterative algorithm for point cloud registration and segmentation in grid structure deformation detection
Automation in Construction ( IF 9.6 ) Pub Date : 2025-01-18 , DOI: 10.1016/j.autcon.2025.105981
Bao-Luo Li, Jian-Sheng Fan, Jian-Hua Li, Yu-Fei Liu
Automation in Construction ( IF 9.6 ) Pub Date : 2025-01-18 , DOI: 10.1016/j.autcon.2025.105981
Bao-Luo Li, Jian-Sheng Fan, Jian-Hua Li, Yu-Fei Liu
Deformation detection of grid structures is vital. In complex environments, efficiently identifying locally crooked members among tens of thousands remains a significant challenge. Point cloud-based methods provide dependable solutions for instance segmentation and deformation recognition. However, existing approaches struggle with irrelevant and deficient data, diverse component forms, and low efficiency. This paper introduces non-rigid registration to grid structure scenarios and proposes a semirigid optimal step iterative point cloud registration and segmentation algorithm (SOSIT), specifically designed for grid structures. By leveraging geometric and physical priors, including the as-designed model topology, plane section and finite rotation assumptions, along with differential stiffness and stepwise softening constraints, SOSIT addresses critical challenges in spatial topology organization, transformation matrix representation, and spatially dependent stiffness variation. The algorithm achieves state-of-the-art (SOTA) performance, with a 129-fold increase in efficiency, a 10.1 % improvement in accuracy, and an 81.5 % enhancement in robustness, enabling automated and intelligent deformation inspection and monitoring.
中文翻译:
网格结构变形检测中点云配准和分割的半刚性最优步长迭代算法
网格结构的变形检测至关重要。在复杂的环境中,在数以万计的会员中有效地识别本地的不正成员仍然是一项重大挑战。基于点云的方法为实例分割和变形识别提供了可靠的解决方案。然而,现有方法难以处理不相关和不足的数据、多样化的组件形式和低效率。该文将非刚性配准引入网格结构场景,并提出了一种专为网格结构设计的半刚性最优步长迭代点云配准和分割算法 (SOSIT)。通过利用几何和物理先验,包括设计模型拓扑、平面截面和有限旋转假设,以及差分刚度和逐步软化约束,SOSIT 解决了空间拓扑组织、变换矩阵表示和空间相关刚度变化方面的关键挑战。该算法实现了最先进的 (SOTA) 性能,效率提高了 129 倍,精度提高了 10.1%,鲁棒性提高了 81.5%,实现了自动化和智能的变形检测和监控。
更新日期:2025-01-18
中文翻译:
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网格结构变形检测中点云配准和分割的半刚性最优步长迭代算法
网格结构的变形检测至关重要。在复杂的环境中,在数以万计的会员中有效地识别本地的不正成员仍然是一项重大挑战。基于点云的方法为实例分割和变形识别提供了可靠的解决方案。然而,现有方法难以处理不相关和不足的数据、多样化的组件形式和低效率。该文将非刚性配准引入网格结构场景,并提出了一种专为网格结构设计的半刚性最优步长迭代点云配准和分割算法 (SOSIT)。通过利用几何和物理先验,包括设计模型拓扑、平面截面和有限旋转假设,以及差分刚度和逐步软化约束,SOSIT 解决了空间拓扑组织、变换矩阵表示和空间相关刚度变化方面的关键挑战。该算法实现了最先进的 (SOTA) 性能,效率提高了 129 倍,精度提高了 10.1%,鲁棒性提高了 81.5%,实现了自动化和智能的变形检测和监控。