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Reconfiguration Error Correction Model for an FBG Shape Sensor Based on the Sparrow Search Algorithm.

Qiufeng Shang1,2,3, Feng Liu1

  • 1Department of Electronic and Communication Engineering, North China Electric Power University, Baoding 071003, China.

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|August 26, 2023
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Summary
This summary is machine-generated.

A novel model corrects errors in Fiber Bragg Grating Shape Sensors (FSS) using an improved sparrow search algorithm (SSA). This method enhances shape reconfiguration accuracy without complex calibration, offering a simpler and more efficient solution.

Keywords:
FBGcurvatureerror correctionoptimization algorithmshape sensor

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Area of Science:

  • Optoelectronics
  • Sensor Technology
  • Metrology

Background:

  • Fiber Bragg Grating Shape Sensors (FSS) are crucial for structural monitoring.
  • Reconfiguration errors limit the accuracy of FSS in real-world applications.
  • Existing calibration methods for FSS can be complex and time-consuming.

Purpose of the Study:

  • To develop a new reconfiguration error correction model for FBG Shape Sensors (FSS).
  • To improve the accuracy of shape sensing by addressing curvature and bending direction errors.
  • To introduce a self-correction mechanism for FBG placement angle and calibration errors.

Main Methods:

  • An improved sparrow search algorithm (SSA) was employed for error correction.
  • The SSA was utilized to automatically correct FBG placement angle and calibration direction.
  • Corrected parameters were then applied to refine FSS curvature and bending direction measurements.

Main Results:

  • The proposed model significantly reduced tail point reconfiguration errors from 2.56% and 4.96% to 1.12% and 2.45%.
  • The SSA-based approach demonstrated effective self-correction of FBG placement and calibration.
  • Shape reconfiguration accuracy of the FSS was substantially improved.

Conclusions:

  • A novel, simpler, and more operable reconfiguration error correction method for FSS was presented.
  • The method eliminates the need for complicated experimental calibration processes.
  • The developed model shows great potential for enhancing FSS applications requiring high accuracy.