针对船舱复杂构件点云提取存在人工成本高、效率低的问题, 提出了一种适用于平面舱壁类型船舱点云的分割方法。通过种子点集构建、点云法线估计及直线拟合的方式建立以船舱纵向为X轴、横向为Y轴、竖向为Z轴的独立坐标系, 以简化分割算法的复杂度; 根据船舱内部复杂构件的分布特性, 制定最佳分割次序, 基于随机采样一致性算法拟合平面的思想有序地分割船舱构件点云。选用两组不同结构的船舱点云数据进行算法验证, 实验结果表明：该方法能够从不同结构的船舱散乱点云中快速、准确地自动分割出主要构件点云, 可靠性强, 具有较高的实用价值。

To solve the high labor cost and low efficiency problems of complex tank members extraction, we propose a point cloud segmentation algorithm which is applicable to tank of plane bulkhead type. The steps of this approach are as follows: the original point cloud is firstly transformed to the independent coordinate, whose X, Y and Z axes are defined as the longitudinal, transverse and vertical directions of tank, based on seed sets building, normal estimation and linear fitting; then clouds of each tank member are segmented in the best order by plane fitting of random sample consensus (RANSAC) method according to the distribution of complex tank members. Experimental results on two sets of point clouds show that the proposed algorithm can quickly, accurately and automatically segment the clouds of main members from unorganized clouds, which demonstrate the high reliability and practical value of the proposed method.