An Automatic Measurement Method of Test Beam Response Based on Spliced Images

Information such as cracks and deflections is the important basis for structural safety. Existing methods have not achieved simultaneous detection. In most existing computer vision measurement systems, the view is fixed due to the fixed position of the camera. Thus, it is difficult to obtain the structures’ overall crack and deflection information. An automatic response measurement method is proposed in this study including ( 1 ) continuous image acquisition and signal transmission system based on self-walking bracket and Internet of Things (IoT), ( 2 ) an image splicing method based on feature matching, and ( 3 ) a crack and deflection measurement method. The self-walking bracket allows the industrial camera to move at a fixed distance to obtain the continuous image of the beam. Next, the spliced image is obtained through the PCA-SIFT method with a screening mechanism. The cracks’ information is acquired by the dual network model. The simplified AKAZE feature detection algorithm and the modified RANSAC are used to track the natural features of the structures. The curve fitting is performed to obtain the deflection curve of the beam under different loads. Experimental results show that the method can directly reflect the crack and deflection information of the beam. The average deviation of width is 11.76%, average deviation of length is 8.18%, and the average deformation deviation is 4.50%, which verifies the practicability of the method and shows great potential to apply it in actual structures.

The Efficient Improvement of Original Magnetite in Iron Ore Reduction Reaction in Magnetization Roasting Process and Mechanism Analysis by In Situ and Continuous Image Capture

Magnetization roasting followed by magnetic separation is considered an effective method for recovering iron minerals. As hematite and magnetite are the main concomitant constituents in iron ores, the separation index after the magnetization roasting will be more optimized than with only hematite. In this research, the mechanism of the original magnetite improving iron ore reduction during the magnetization roasting process was explored using ore fines and lump ore samples. Under optimum roasting conditions, the iron grade increased from 62.17% to 65.22%, and iron recovery increased from 84.02% to 92.02% after separation, when Fe in the original magnetite content increased from 0.31% to 8.09%, although the Fe masses in each sample were equal. For lump ores with magnetite and hematite intergrowth, the method of in situ and continuous image capture for microcrack generation and the evolution of the magnetization roasting process was innovatively examined with a laser scanning confocal microscope (LSCM) with confocal technology and 3D morphologic technology for the first time. The naturally uneven areas, protogenetic pore edges, and magnetite and hematite edges provided active sites for reduction reactions. The microcracks gradually evolved from the lump ore surface and the edges of magnetite and hematite, which had a direct connection with the efficient improvement in ore reduction.

A method of quasi-continuous image formation in observation devices with discrete receivers

The article proposes a new method of quasi-continuous image formation in observation devices with discrete receivers. The increase in the number of spatial sampling points in the object image is provided by intraframe scanning. Scanning is carried out by a photosensitive matrix with a regularly changed (controlled) density of the elementary receivers (CDR-matrix). The CDR-matrix contains identical elementary receivers. They are regularly distributed over the matrix surface. The vertical and horizontal distance between adjacent receivers is a multiple of the size of the elementary receiver. The CDR-matrix becomes equivalent in pixel dimensions to a larger photosensitive matrix. The magnitude of the multiplicity placement of the receivers is chosen by the developer when designing the light-sensitive matrix. The image of the object by the CDR-matrix (a separate frame) is composed of a series of snapshots. Each snapshot is formed by signals coming from all elementary receivers of the CDR-matrix. The number of snapshots in the frame is set by the multiplicity of the size of the elementary receivers vertically and horizontally. While using intraframe scanning, the CDR-matrix with a pixel size of the video format can operate in the mode of a photosensitive matrix with a pixel size of 2.5 MP. A CDR-matrix with a pixel size of 6 MP can operate as a 48 MP matrix of a conventional design. A mechanism for storing a frame with observation results when using a CDR-matrix is proposed. It assumes the use of the matrix addition operation. The signal matrix of the observed frame is considered as the sum of the signal matrices of all the snapshots in the frame. Application of the developed method will make it possible to multiply the pixel size of the image relative to the pixel size of the controllable photosensitive matrix. The advantages of the proposed method also include the absence of a mandatory decrease in the effective area of an elementary receiver with an increase in their number in the photosensitive matrix; simplification of hardware measures to reduce the effect of image shift on its quality; absence of information losses in the intervals between adjacent elementary receivers.

An Imaging Network Design for UGV-Based 3D Reconstruction of Buildings

Imaging network design is a crucial step in most image-based 3D reconstruction applications based on Structure from Motion (SfM) and multi-view stereo (MVS) methods. This paper proposes a novel photogrammetric algorithm for imaging network design for building 3D reconstruction purposes. The proposed methodology consists of two main steps: (i) the generation of candidate viewpoints and (ii) the clustering and selection of vantage viewpoints. The first step includes the identification of initial candidate viewpoints, selecting the candidate viewpoints in the optimum range, and defining viewpoint direction stages. In the second step, four challenging approaches—named façade pointing, centre pointing, hybrid, and both centre & façade pointing—are proposed. The entire methodology is implemented and evaluated in both simulation and real-world experiments. In the simulation experiment, a building and its environment are computer-generated in the ROS (Robot Operating System) Gazebo environment and a map is created by using a simulated robot and Gmapping algorithm based on a Simultaneously Localization and Mapping (SLAM) algorithm using a simulated Unmanned Ground Vehicle (UGV). In the real-world experiment, the proposed methodology is evaluated for all four approaches for a real building with two common approaches, called continuous image capturing and continuous image capturing & clustering and selection approaches. The results of both evaluations reveal that the fusion of centre & façade pointing approach is more efficient than all other approaches in terms of both accuracy and completeness criteria.

Light Curve Calculations for Triple Microlensing Systems

We present a method to compute the magnification of a finite source star lensed by a triple lens system based on the image boundary (contour integration) method. We describe a new procedure to obtain continuous image boundaries from solutions of the tenth-order polynomial obtained from the lens equation. Contour integration is then applied to calculate the image areas within the image boundaries, which yields the magnification of a source with uniform brightness. We extend the magnification calculation to limb-darkened stars approximated with a linear profile. In principle, this method works for all multiple lens systems, not just triple lenses. We also include an adaptive sampling and interpolation method for calculating densely covered light curves. The C++ source code and a corresponding Python interface are publicly available.