Section Curve Reconstruction and Mean-Camber Curve Extraction of a Point-Sampled Blade Surface

Li, Wenlong; Xie, He; Li, Qidong; Zhou, Liping; Yin, Zhouping

doi:10.1371/journal.pone.0115471

Cited by 26 publications

(7 citation statements)

References 25 publications

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“…For robotic machining systems, grinding and polishing is a continuous contact complex surface processing technology; however, it is an effective means to achieve satisfactory surface roughness; thus, many studies focused on how to improve blade surface quality by surface reconstruction, trajectory planning and calibration, etc. (Li et al , 2014).…”

Section: Introductionmentioning

confidence: 99%

A point cloud registration-based calibration algorithm for robot offline programming automatic loading in aero-grinding applications

Cai

Zeng

et al. 2022

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Purpose During the process of the robotic grinding and polishing operations on aero-engine blades, the key problem of calibration error lies in fixture error and uneven margin. To solve this problem, this paper aims to propose a novel method to achieve rapid online calibration of the workpiece coordinate system through laser-based measurement techniques. Design/methodology/approach The authors propose a calibration strategy based on point cloud registration algorithm. The main principle is presented as follows: aero blade mounted on clamping end-effector is hold by industry robot, the whole device is then scanned by a 3D laser scanner to obtain its surface point cloud, and a fast segmentation method is used to acquire the point cloud of the workpiece. Combining Super4PCS algorithm with trimmed iterative closest point, we can align the key points of the scanned point cloud and the sampled points of the blade model, thus obtaining the translation and rotation matrix for calculating the workpiece coordinate and machining allowance. The proposed calibration strategy is experimentally validated, and the positioning error, as well as the margin distribution, is finally analyzed. Findings The experimental results show that the algorithm can well accomplish the task of cross-source, partial data and similar local features of blade point cloud registration with high precision. The total time spent on point cloud alignment of 100,000 order of magnitude blade is about 4.2 s, and meanwhile, the average point cloud alignment error is reduced to below 0.05 mm. Originality/value An improved point cloud registration method is proposed and introduced into the calibration process of a robotic system. The online calibration technique improves the accuracy and efficiency of the calibration process and enhances the automation of the robotic grinding and polishing system.

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Section: Introductionmentioning

confidence: 99%

A point cloud registration-based calibration algorithm for robot offline programming automatic loading in aero-grinding applications

Cai

Zeng

et al. 2022

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“…Airfoils are also found in fans, compressors, and turbines, which makes it relevant to consider studies on optical blade inspection for other sectors. These studies include extraction of the sectional foil curves [10], reconstruction of mean camber line [11], leading edge and trailing edge localization [12], shape matching [13], and position and orientation error evaluations.…”

Section: Introductionmentioning

confidence: 99%

Identification of the geometric design parameters of propeller blades from 3D scanning

2022

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This paper presents a new method for the identification of geometric design parameters of ISO 484 class propeller blades from scanned point cloud data. The method can be used for tolerance inspection and in-line measurement of manufactured blades, and for wear assessment and reverse engineering of propellers in service. The geometry of the propeller blades is specified by a set of blade sections stacked radially on concentric cylindrical surfaces. For each of these sections, the chord line and mean camber line is determined, and geometric design parameters such as the pitch, skew, chord length, camber, and thickness distributions are identified. The proposed method is a complete procedure for identifying the design parameters of marine propeller blades from point cloud data, and includes a novel method for the precise identification of the mean camber line based on Voronoi diagrams and Delaunay triangulation. The paper includes validation of the proposed method in experiments where reverse engineering is applied to a propeller blade of the KVLCC2 propeller, and in 3D scanning of a large, high-skew thruster blade where the results were compared to CMM measurements.

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“…The effective area extraction for the laser highlights on the metal surface was performed in [14], which improves the accuracy of the laser centerline. The connectivity of laser lines of blade contours was repaired in [15], which improves morphological repair algorithm. The centerline extraction algorithm was improved in [16] so that the irregular speckle laser centerline can be better extracted.…”

Section: Introductionmentioning

confidence: 99%

“…The cause of these speckles is that during the process of extracting the laser centerline of flatbed lap weld, the intensity of laser fringe is not enough for center line extraction due to the complexity of ambient conditions. These speckles can cause some information about the laser center line lost and this kind of loss cannot be solved completely by general image preprocessing method such as Mathematical Morphology operation (MMO) [15]. The data loss caused by speckle is large-scale, unlike the short crack.…”

Section: Introductionmentioning

confidence: 99%

Repair Method of Data Loss in Weld Surface Defect Detection Based on Light Intensity and 3D Geometry

Shiyi

Xing

2020

IEEE Access

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Weld surface quality inspection is an indispensable part in the welding automation engineering. When Laser Triangulation Method (LTM) is used to scan the weld surface, external factors will interfere with the laser center line, resulting in data loss and quality detection failure, and massive data loss is difficult to be repaired in the traditional way. In order to improve the quality of weld surface defect detection, it is necessary to find an effective and strong anti-interference method to fix the lost data. This paper presents a method of fixing the data loss caused by external environmental factors in the process of detecting flatbed lap weld surface defects by LTM. The paper includes the analysis of the causes of data loss, its impact for practical applications and a repair method. The repair method derives a formula which is suitable for expressing three-dimensional points on weld surface by combining Bidirectional Reflectance Distribution Function (BRDF) and weld surface section model. The accuracy of the algorithm is verified by experiments on standard block and single weld cross-section. The accuracy of the method up to 92% and the repair rate improved by 30%. The method was tested on flatbed lap weld to confirm its effectiveness in the field of catching surface defects hidden in the lost data.

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Section Curve Reconstruction and Mean-Camber Curve Extraction of a Point-Sampled Blade Surface

Cited by 26 publications

References 25 publications

A point cloud registration-based calibration algorithm for robot offline programming automatic loading in aero-grinding applications

A point cloud registration-based calibration algorithm for robot offline programming automatic loading in aero-grinding applications

Identification of the geometric design parameters of propeller blades from 3D scanning

Repair Method of Data Loss in Weld Surface Defect Detection Based on Light Intensity and 3D Geometry

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