Three-dimensional defects detection of high-voltage cable joint based on iterative residual fitting

Abstract

Aiming at the three-dimensional defects detection of high-voltage cables joint, a method based on iterative residual fitting is proposed. The three-dimensional point cloud data was obtained by reconstructing the laser line projected onto the surface of the high-voltage cable joint. In order to remove noise generated by reconstruction which is located above or below the curve, a simple and effective strategy that the noise can be filtered by the gradient change in the neighborhood is adopted. Then a continuous iterative residual fitting method is proposed to effectively reduce the interference of the defect area on the curve fitting accuracy, thereby obtaining the accurate equation expression of the cable surface curve. By comparing the residual value of the high-voltage cable surface points relative to the fitting curve, the points of the defect area are marked. Finally three-dimensional defect area is extracted through segmentation and clustering. Experiments have verified the effectiveness of this method. Compared with the cylindrical fitting method, it can be seen that both the center deviation and the deviation in the length, width and height of extracted defects are better than the cylindrical fitting method. The recognition rate of concave and convex defects of the proposed method are 96.29% and 93.20% respectively .

3D reconstruction and defect pattern recognition of bonding wire based on stereo vision

“…After projection, the interval between adjacent points in the X-axis is calculated and noted as E i . The calculation equation is (15).…”

“…Jovancevic et al [6] detected the surface flatness of an aircraft by comparing the difference of the normal vectors of adjacent points. Zheng et al [15] used curve fitting to solve the defect detection problem in high-voltage cable joints. Miao et al [16] used the FPFH (Fast Point Feature Histograms) to extract characteristics and detect defects on turbine blades.…”

“…Zheng et al. [15] used curve fitting to solve the defect detection problem in high‐voltage cable joints. Miao et al.…”

“…Point cloud-based defect detection techniques have been widely used in various industries, such as aircraft manufacturing [6], rail manufacturing [7], PCB [8], heritage restoration [9], and agriculture and forestry industries [10]. Object defect detection based on 3D point clouds usually includes methods based on standard model comparison [11][12][13][14] and methods based on point cloud geometric features [6,[15][16][17]. Standard model comparison-based methods must have standard model point clouds, but the length and curvature of bonding wires are variable, as shown in Figure 2, so this method is not flexible enough.…”