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基于3D点云的矿井提升钢丝绳振动位移在线测量方法

Online measurement of vibration displacement of mine hoisting wire rope based on 3D point cloud

  • 摘要: 针对矿井提升钢丝绳空间振动位移在线精确测量难题,提出一种基于3D点云的矿井提升钢丝绳振动位移在线测量方法。针对钢丝绳点云分割中存在背景干扰和离群点问题,采用随机采样一致性算法(RANSAC)和基于密度的聚类算法(DBSCAN)相结合的钢丝绳点云分割方法,实现钢丝绳点云与背景的有效分离。针对传统体素栅格法在点云下采样过程中出现的几何特征丢失问题,提出一种自适应体素栅格算法,首先利用粒子群优化(PSO)确定最优初始体素大小,然后根据钢丝绳点云的局部密度动态调整体素尺寸,实现高效的钢丝绳点云精简。针对钢丝绳振动位移计算问题,提出一种基于分段最小二乘拟合的动态测量方法,该方法通过最小二乘法对各段点云进行直线拟合并引入误差权重计算中心点坐标,利用相对坐标法计算动态中心点与静态参考点之间的位移,实现钢丝绳空间振动位移的精确测量。为验证所提方法的有效性,分别在实验室和矿井提升环境下进行实验。实验结果表明:结合RANSAC和DBSCAN的点云分割方法能有效地从复杂背景中提取出钢丝绳点云,精确率和召回率分别在93.9%和94.3%以上;与传统体素栅格算法相比,自适应体素栅格算法精简后的钢丝绳点云更加平滑连续,在精简率为94.5%时,最大误差和平均误差分别降低68.7%和74.7%。在实验室环境下,所提出的振动位移测量方法在XZ方向上测量的平均绝对误差均小于0.62 mm,最大误差在1.2 mm以内;在实际的矿井提升环境中,XZ方向上的平均绝对误差均小于0.87 mm,最大误差在2.5 mm以内,完成一次位移测量耗时20 ms,能够满足矿井提升钢丝绳振动位移测量的准确性和实时性要求。

     

    Abstract: Aiming at the problem of accurate online measurement of spatial vibration displacement of mine hoisting wire rope, an online measurement method based on a 3D point cloud is proposed. For the problems of background interference and outliers in the wire rope point cloud segmentation, the wire rope point cloud segmentation method combining the random sampling consistency algorithm (RANSAC) and density-based clustering algorithm (DBSCAN) is adopted to achieve the effective separation of the wire rope point cloud and background. To address the loss of geometric features in the point cloud downsampling process of the traditional voxel grid method, an adaptive voxel grid algorithm is proposed, which firstly determines the optimal initial voxel size by using Particle Swarm Optimisation (PSO), and then dynamically adjusts the voxel size according to the local density of the wire rope point cloud to achieve efficient streamlining of the point cloud of the wire rope. For the problem of wire rope vibration displacement calculation, a dynamic measurement method based on segmental least squares fitting is proposed, which uses the least squares method to linearly fit the point clouds of each segment and introduces error weights to calculate the coordinates of the centroid. Then it uses the relative coordinate method to calculate the displacement between the dynamic centroid and the static reference point, to achieve an accurate measurement of the spatial vibration displacement of the wire rope. To verify the effectiveness of the proposed method, experiments are conducted in the laboratory and mine hoisting environment. The experimental results show that the point cloud segmentation method combining RANSAC and DBSCAN can effectively extract the wire rope point cloud from the complex background, and the precision and recall are above 93.9% and 94.3%, respectively; compared with the traditional voxel grid algorithm, the streamlined wire rope point cloud of the adaptive voxel grid algorithm is smoother and more continuous, and the maximal and average errors are reduced by 68.7% and 74.7%, respectively, at the streamlining rate of 94.5%. In the laboratory environment, the average absolute error of the vibration displacement measurement method proposed in this paper is less than 0.62 mm in both X and Z directions, and the maximum error is within 1.2 mm; in the actual mine hoisting environment, the average absolute error is less than 0.87 mm in both X and Z directions, and the maximum error is within 2.5 mm. It takes 20 ms to complete a displacement measurement, which can meet the accuracy and real-time requirements of mine hoisting wire rope vibration displacement measurement.

     

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