A turbine blade is one of the key components of the aero-engine. Its geometric shape should be inspected carefully in the production stage to ensure that it meets the tolerance specification. In the present paper, an ...A turbine blade is one of the key components of the aero-engine. Its geometric shape should be inspected carefully in the production stage to ensure that it meets the tolerance specification. In the present paper, an approach for investment turbine blade geometric shape analysis based on multi-source digital measurement is presented. Its key technologies, such as measurement data collection, blade model reliable alignment, geometric shape deviation fast calculation and visualization, were investigated. Actual measurement data from a structure light measurement device and a Coordinate Measuring Machine(CMM) for turbine blades were used to validate the presented method. The experimental results show that the proposed method is accurate, quick and effective to implement.展开更多
Surface registration brings multiple scans into a common coordinate system by aligning their overlapping components. This can be achieved by finding a few pairs of matched points on different scans using local shape d...Surface registration brings multiple scans into a common coordinate system by aligning their overlapping components. This can be achieved by finding a few pairs of matched points on different scans using local shape descriptors and employing the matches to compute transformations to produce the alignment. By defining a unique local reference frame(LRF) and attaching an LRF to shape descriptors,the transformation can be computed using only one match based on aligning the LRFs. This paper proposes a local voxelizer descriptor,and the key ideas are to define a unique LRF using the support around a basis point,to perform voxelization for the local shape within a cubical volume aligned with the LRF,and to concatenate local features extracted from each voxel to construct the descriptor. An automatic rigid registration approach is given based on the local voxelizer and an expanding strategy that merges descriptor representations of aligned scans. Experiments show that our registration approach allows the acquisition of 3D models of various objects,and that the local voxelizer is robust to mesh noise and varying mesh resolution,in comparison to two state-of-the-art shape descriptors.展开更多
A Lattice triangular expansion matrix is presented based on the classical Hadamard matrices, which is defined over the fields of finite characteristic. Also, the modular Lattice and Pentagon expansion matrices are str...A Lattice triangular expansion matrix is presented based on the classical Hadamard matrices, which is defined over the fields of finite characteristic. Also, the modular Lattice and Pentagon expansion matrices are structured from triangular 7x7 matrix, each of the expansion matrices are modular the sides of the shape p. The issue for the existence (necessary conditions) of odd and even order matrices of that kind is addressed. The modular Lattice code is highly efficient since it requires only additions, multiplications by constant modulo p. The modular 6 Lattice triangular expanded constellation is even possible efficiency to gain advantage from the channel selection and maximum likelihood (ML) decoding in the interference Lattice alignment (IA) system.展开更多
Landmarks on human body models are of great significance for applications such as digital anthropometry and clothing design.The diversity of pose and shape of human body models and the semantic gap make landmarking a ...Landmarks on human body models are of great significance for applications such as digital anthropometry and clothing design.The diversity of pose and shape of human body models and the semantic gap make landmarking a challenging problem.Inthis paper,a learning-based method is proposed to locate landmarks on human body models by analyzing the relationship between geometric descriptors and semantic labels of landmarks.A shape alignmentalgorithm is proposed to align human body models to break symmetric ambiguity.A symmetry-awaredescriptor is proposed based on the structure of the human body models,which is robust to both pose and shape variations in human body models.AnAdaBoost regression algorithm is adopted to establish the correspondence between several descriptors and semantic labels of the landmarks.Quantitative and qualitative analyses and comparisons show that the proposed method can obtain more accurate landmarks and distinguish symmetrical landmarks semantically.Additionally,a dataset of landmarked human body models is also provided,containing 271 human body models collected from current human body datasets;each model has 17 landmarks labeled manually.展开更多
基金financially supported by the Major National S&T Project(No.2012ZX04007021)Doctoral fund of China(No.2013YD050008)
文摘A turbine blade is one of the key components of the aero-engine. Its geometric shape should be inspected carefully in the production stage to ensure that it meets the tolerance specification. In the present paper, an approach for investment turbine blade geometric shape analysis based on multi-source digital measurement is presented. Its key technologies, such as measurement data collection, blade model reliable alignment, geometric shape deviation fast calculation and visualization, were investigated. Actual measurement data from a structure light measurement device and a Coordinate Measuring Machine(CMM) for turbine blades were used to validate the presented method. The experimental results show that the proposed method is accurate, quick and effective to implement.
基金supported in part by the National Natural Science Foundation of China (No.61403357)Anhui Provincial Natural Science Foundation (No.1508085QF122)Fundamental Research Funds for the Central Universities (No.WK0110000044)
文摘Surface registration brings multiple scans into a common coordinate system by aligning their overlapping components. This can be achieved by finding a few pairs of matched points on different scans using local shape descriptors and employing the matches to compute transformations to produce the alignment. By defining a unique local reference frame(LRF) and attaching an LRF to shape descriptors,the transformation can be computed using only one match based on aligning the LRFs. This paper proposes a local voxelizer descriptor,and the key ideas are to define a unique LRF using the support around a basis point,to perform voxelization for the local shape within a cubical volume aligned with the LRF,and to concatenate local features extracted from each voxel to construct the descriptor. An automatic rigid registration approach is given based on the local voxelizer and an expanding strategy that merges descriptor representations of aligned scans. Experiments show that our registration approach allows the acquisition of 3D models of various objects,and that the local voxelizer is robust to mesh noise and varying mesh resolution,in comparison to two state-of-the-art shape descriptors.
文摘A Lattice triangular expansion matrix is presented based on the classical Hadamard matrices, which is defined over the fields of finite characteristic. Also, the modular Lattice and Pentagon expansion matrices are structured from triangular 7x7 matrix, each of the expansion matrices are modular the sides of the shape p. The issue for the existence (necessary conditions) of odd and even order matrices of that kind is addressed. The modular Lattice code is highly efficient since it requires only additions, multiplications by constant modulo p. The modular 6 Lattice triangular expanded constellation is even possible efficiency to gain advantage from the channel selection and maximum likelihood (ML) decoding in the interference Lattice alignment (IA) system.
基金jointly supported by the National Natural Science Foundation of China under Grant Nos.61732015,61932018,and 61472349.
文摘Landmarks on human body models are of great significance for applications such as digital anthropometry and clothing design.The diversity of pose and shape of human body models and the semantic gap make landmarking a challenging problem.Inthis paper,a learning-based method is proposed to locate landmarks on human body models by analyzing the relationship between geometric descriptors and semantic labels of landmarks.A shape alignmentalgorithm is proposed to align human body models to break symmetric ambiguity.A symmetry-awaredescriptor is proposed based on the structure of the human body models,which is robust to both pose and shape variations in human body models.AnAdaBoost regression algorithm is adopted to establish the correspondence between several descriptors and semantic labels of the landmarks.Quantitative and qualitative analyses and comparisons show that the proposed method can obtain more accurate landmarks and distinguish symmetrical landmarks semantically.Additionally,a dataset of landmarked human body models is also provided,containing 271 human body models collected from current human body datasets;each model has 17 landmarks labeled manually.
