Abstract
Abstract
Intelligent perception of a scraper conveyor straightness and attitude monitoring of mechanical supporting equipment in the stope have practical and theoretical values for mining. This study proposed an optical fiber curvature sensor and a scraper conveyor’s curve reconstruction method. The optical fiber curvature sensor comprises the fiber grating strain sensing optical cables, the flexible substrate, and the packaging material. The coordinate positions of each monitoring point are obtained through the strain–curvature conversion relationship and the slope recurrence algorithm, and then the reconstruction curve is obtained by fitting. The finite element simulation verifies the feasibility of the curve reconstruction method used for the deformation monitoring via optical fiber curvature sensors. The reconstruction error analysis results show that the root mean square error of reconstructions for two kinds of 2D plane bending and 3D space bending are 2.98%, 1.89%, and 3.13%, respectively. Their mean absolute errors are 8.9, 3.56, and 9.82 mm, respectively, verifying the feasibility and high accuracy of the proposed curve reconstruction equation. The research results provide a theoretical basis for the shape perception and straightening control of scraper conveyors in the intelligent working surface.
Funder
the Special funds for guiding the construction of world-class universities (disciplines) and distinctive development in central universities
the Open Competition Mechanism to Select the Best Candidates Foundation of Shanxi Province
Fundamental Research Funds for the Central Universities
National Natural Science Foundation of China
Natural Science Foundation of Jiangsu Province
Postdoctoral Science Foundation of Jiangsu Province
the Postgraduate Research & Practice Innovation Program of JiangsuProvinc
the Graduate Innovation Program of China University of Mining and Technology
Subject
Applied Mathematics,Instrumentation,Engineering (miscellaneous)