Automatic extraction method of force chain information and its application in the flow photoelastic experiment of granular matter |
| |
| Affiliation: | 1. School of Civil Engineering and Architecture, Key Laboratory of Disaster Prevention and Structural Safety of Ministry of Education, Guangxi University, Nanning, 530004, China;2. School of Resources, Environment and Materials, Guangxi University, Nanning, 530004, China;1. College of Chemistry and Chemical Engineering, Guizhou University, Guiyang, 550025, China;2. Collaborative Innovation Center of Guizhou Province for Efficient Utilization of Phosphorus and Fluorine Resources, Guizhou University, Guiyang, 550025, China;1. CAS Key Laboratory of Carbon Materials, Institute of Coal Chemistry, Chinese Academy of Sciences, Taiyuan, 030001, China;2. University of Chinese Academy of Sciences, Beijing, 100049, China;3. Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing, 100049, China;1. School of Chemical Engineering, China University of Mining and Technology, Xuzhou, 221116, China;2. School of Low-Carbon Energy and Power Engineering, China University of Mining and Technology, Xuzhou, 221116, China;3. National Engineering Research Center of Coal Preparation and Purification, China University of Mining and Technology, Xuzhou, 221116, China;4. School of Engineering, The University of Newcastle, Callaghan, NSW, 2308, Australia;1. School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China;2. Center for Particle-Laden Turbulence, Key Laboratory of Mechanics on Disaster and Environment in Western China attached to the Ministry of Education of China, Department of Mechanics and Engineering Science, School of Civil Engineering and Mechanics, Lanzhou University, Lanzhou, 730000, China |
| |
| Abstract: | The force chain is the core of the multi-scale analysis of granular matter. Accurately extracting the force chain information among particles is of great significance to the study of particle mechanics and geological hazards caused by particle flow. However, in the photoelastic experiment, the precise identification of the branching points of force chains has not been effectively realized. Therefore, this study proposes an automatic extraction method of force chain key information. First, based on the Hough transform and the Euclidean distance, a particle geometric information identification model is established and geometric information such as particle circle center coordinates, radius, contact point location, and contact angle is extracted. Then, a particle contact force information identification model is established following the color gradient mean square method. The model realizes the rapid calibration and extraction of a large number of particle media contact force information. Next, combined with the force chain composition criterion and its quasilinear feature, an automatic extraction method of force chain information is established, which solves the problem of the accurate identification of the force chain branch points. Finally, in the photoelastic experiment of ore drawing from a single drawpoint, the automatic extraction method of force chain information is verified. The results show that the macroscopic distribution of force chains during ore drawing from a single drawpoint is left–right symmetrical. Strong force chains are mostly located on the two sides of the model but in small numbers and they mainly develop vertically. Additionally, the ends are mostly in a combination of Y and inverted Y shapes, while the middle is mostly quasilinear. Weak force chains are abundant and mostly distributed in the middle of the model, and develop in different directions. The proposed extraction method accurately extracts the force chain network from the photoelastic experiment images and dynamically characterizes the force chains of granular matter, which has significant advantages in particle geometry information extraction, force chain branch point discrimination, force chain retrieval, and force chain distribution and its azimuthal characterization. The results provide a scientific basis for studying the macroscopic and microscopic mechanical parameters of granular matter. |
| |
| Keywords: | Granular matter Photoelastic experiment Digital image processing Force chain extraction method |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
