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Research on Three-Dimensional Shape Curve Reconstruction Technology for a Scraper Conveyor on an Intelligent Working

Fukang Qiao1,2, Xinqiu Fang1,2, Ningning Chen1,2

  • 1School of Mines, China University of Mining and Technology, Xuzhou 221116, China.

Sensors (Basel, Switzerland)
|November 14, 2023
PubMed
Summary

This study introduces a novel fiber Bragg grating (FBG) sensor system for accurately reconstructing the shape of scraper conveyors in intelligent coal mining. The method ensures precise shape perception and straightness control, crucial for efficient mining operations.

Keywords:
Frenet motion framecubic b-spline interpolationcurve prediction interpolationcurve reconstruction methodintelligent miningintelligent working facescraper conveyor

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Area of Science:

  • Mining Engineering
  • Sensor Technology
  • Data Science

Background:

  • Intelligent coal mining requires precise shape perception of scraper conveyors for "three straight and two flat" operations.
  • Current methods lack accurate shape perception of scraper conveyors, hindering intelligent mining advancements.

Purpose of the Study:

  • To develop and validate a method for reconstructing the shape of scraper conveyors using fiber Bragg grating (FBG) sensors.
  • To address the technical challenge of accurate shape perception for scraper conveyors in intelligent coal mining.

Main Methods:

  • Established a mathematical model linking FBG central wavelength variation to strain and curvature.
  • Employed cubic B-spline interpolation for discrete curvature data processing.
  • Derived a spatial curve reconstruction algorithm using the Frenet moving frame and a gated recurrent unit (GRU) model for prediction and error reduction.

Main Results:

  • Successfully reconstructed the shape of the scraper conveyor with an absolute error of approximately 2 mm at the end.
  • Experimental validation confirmed the reconstructed curve closely matched the actual shape for various curvature radii (6m, 7m, 8m).
  • The gated recurrent unit (GRU) model demonstrated robustness against potential damage to some grating measuring points.

Conclusions:

  • The developed FBG-based curvature sensing and reconstruction algorithm is feasible for engineering applications in intelligent mining.
  • This technology significantly contributes to achieving accurate shape curve perception and straightness control for scraper conveyors.
  • The findings pave the way for enhanced automation and efficiency in fully mechanized mining faces.