Journals >Laser & Optoelectronics Progress
ing at the precision measurement problem of the profile of aero-engine blades, a measurement method based on projected fringe order identification is presented. Firstly, a three-dimensional measurement system with composite structured light is designed and the rotation axis of the system is calibrated by the method of center circle fitting. Then, the aero-engine blades are measured by the digital fringe projection method. In the process of phase unwrapping, the projected fringe order is recognized by projecting two-dimensional code pattern combined with binocular vision, and the front and back surfaces of the blade are reconstructed respectively. In the process of point cloud data stitching, a three-dimensional stitching method combining rotating axis with iterative closest point algorithm is proposed. The experimental results show that the method does not rely on feature extraction and effectively solves the problem of insufficient surface features on aero-engine blades. Which can realize fast and accurate three-dimensional reconstruction of aero-engine blades.
.ing at the defects of fragmentation, low matching precision, and slow speed for Terracotta blocks matching, we propose a fracture surface matching method based on intrinsic shape signature (ISS) feature points. Firstly, the outer surfaces of blocks are segmented, and the fracture surfaces are extracted. Secondly, the ISS feature points of fracture surfaces are extracted, the feature sequences of feature points are calculated, and the fracture surfaces are matched based on feature sequences. Finally, an improved iterative closest point algorithm based on simulated annealing is used to match the feature point sets again. Thus, the fine matching of fracture surfaces is completed, and the blocks are matched accurately. We match four groups of Terracotta blocks, and the results show that the proposed method is more accurate and faster than other methods and effective for Terracotta blocks matching.
.ing at the problem that the existing light detection and ranging (LiDAR) point cloud filtering method cannot effectively exclude the data hole interference in the digital surface model (DSM), a skewness balance point cloud filtering method based on multispectral data guidance is proposed. This method introduces the multispectral data into the point cloud filter as the guiding image to realize the fast denoising with the spectral similarity of the noise points. The experimental results show that this method can effectively eliminate the interference caused by the data hole to the point cloud filtering, and the obtained filtering error is reduced by 0.4%-0.8% compared with the original skewness point cloud filtering method. Compared with the popular filter algorithm based on support vector machines (SVM), the error of this method is reduced by 0.1%-0.4%.
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