Abstract
In China, cemented paste backfill (CPB) is a common treatment method after the exploitation of basic energy. The homogeneity of slurry influences the performance of CPB. However, the online monitoring and characterization of homogeneity lack relevant technologies and unified standards. This article discusses an online image analysis technique applied to the online monitoring of cemented paste backfill mixing, which is based on the evolution of the texture of images taken at the surface of the mixing bed. First, the grayscale distribution of the image obtained by the high-speed camera in the CPB preparation process was analyzed by Matlab and its variance (s2) was solved, and the texture features of the image were analyzed by the variance of grayscale distribution. Then, a homogeneity discriminant model (cst) was established. The results show that the variance value of the grayscale distribution of the slurry image increases rapidly at first, then gradually decreases, and becomes stable in the final stage since it turns a constant value. When the s2 value tends to be stable, the slurry gradually reaches homogenization, and the discriminant coefficient of paste homogenization based on the homogenization discriminant model reaches 0.05. The homogenization prediction of CPB proves to be consistent with the backfill performance comparison results. The evolution of the texture allows obtaining important information on the evolution of different formulations during mixing, which can be used for intelligent monitoring of CPB preparation process.
Funder
The National Natural Science Foundation of China
The Shandong Provincial Major Science and Technology Innovation Project
the key Laboratory of Mine Ecological Effects and Systematic Restoration, Ministry of Natural Resources
China Postdoctoral science foundation
the Doctoral Fund of Henan Polytechnic University
Subject
Geology,Geotechnical Engineering and Engineering Geology
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