Liang Jin

Three-dimensional deformation measuring system based on vision method

In order to realize automatic vision measurement for surface deformation, a three-dimensional surface deformation measuring system is proposed based on digital image correlation and binocular stereovision, and its applied key technologies such as camera calibration, correlation matching, three-dimensional displacement and strain reconstruction are deeply investigated. First, according to distortion errors of digital camera, a self-calibration method with 10-parameters model is elaborated. And a rapid image correlation algorithm based the relation of stereovision epipolar geometry is presented to improve the efficiency of the image matching. Then based on these technologies, a method for displacement and strain reconstruction is discussed. Calibration experimental results show that the precision of the camera calibration is better than 0.07 pixels. Metal tensile test demonstrates that the precision of strain measurement is very close to strain extensometer, so the system can satisfy the requirements of non-contact, higher precision and three-dimensional deformation field measurement.

Measurement on structural deformation of load-bearing power transmission tower based on 3D optical method

The actual load-bearing capacities of Power Transmission Towers(PTTs) should be estimated by a real-scale model experiment due to their complex structures,therefore an optical full-field 3D deformation measurement method is proposed to overcome the difficulties of large-scale,large-displacement,3D deformation,rapid multi-point measurement in PTT real-scale model experiments.Based on close-range photogrammetry technology,this method utilizes specialized markers as measured targets to reconstruct the 3D coordinates of those pre-pasted artificial targets through analyzing the captured photo-set in each epoch,then it conducts the coordinate system global registration according to un-movable targets.By tracking and comparing the 3D coordinates of the deformable targets between different epoches,the 3D load-deformation diagram of the PPT stucture is obtained.Acceptance experiment results indicate that the accuracy of this method could reach about 0.1 mm/4 m and real-scale model experiments show the proposed method could meet accuracy and efficiency requirements of PPT load-deformation measurement.Comparing with traditional deformation sensors,the proposed method can satisfy measuring requirements of non-contact(non-interfere),on-spot,high precision,rapid speed,strong anti-jamming and stabilization.

PoU based sharp features extraction from point cloud

Sharp features of 3D point clouds play an important role in many geometric computations and modeling application. In this paper, a novel modified Partition of Unity (PoU) Based Sharp feature extraction algorithm is proposed, which is directly operated on discrete point clouds. For every point in target point cloud, spherical neighborhood with radius δ is acquired with the help of KD-Tree and weighted average position of points within the δ -neighborhood is computed using modified PoU method. Distance which is the projection of the displace between original point and its Weighted average position along normal direction is defined as the criteria for a point belong to sharp feature or crease line. Experiments on both synthetic data and practical scanner point clouds indicate that our algorithm are both efficient and effective to the task of sharp feature extraction from point clouds. Our method is easy to be implemented and more sensitive to sharp features as well as its low computational complexity.