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A Silicon-tipped Fiber-optic Sensing Platform with High Resolution and Fast Response
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Elastomer-Embedded Multiplexed Optical Fiber Sensor System for Multiplane Shape Reconstruction.

Arnaldo Leal-Junior1, Leandro Macedo1, Leticia Avellar1

  • 1Graduate Program in Electrical Engineering, Federal University of Espírito Santo, Vitória 29075-910, Brazil.

Sensors (Basel, Switzerland)
|January 21, 2023
PubMed
Summary
This summary is machine-generated.

A novel multiplexed polymer optical fiber sensor system enables precise multiplane shape reconstruction and real-time monitoring of dynamic loads. This system offers a feasible solution for movement analysis and structural health monitoring applications.

Keywords:
optical fiber sensorspolymer optical fibersshape reconstruction

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Area of Science:

  • Sensors and Sensing Technology
  • Optical Fiber Sensors
  • Polymer Optics

Background:

  • Multiplexed sensors are crucial for complex shape reconstruction.
  • Polymer optical fibers (POFs) offer flexibility and ease of integration.
  • Intensity variation-based sensing provides a cost-effective approach.

Purpose of the Study:

  • To develop and evaluate a multiplexed intensity variation-based sensor system for multiplane shape reconstruction.
  • To compare two configurations of the sensor system embedded in polydimethylsiloxane (PDMS) resin.
  • To assess the real-time monitoring and shape reconstruction capabilities under various loading conditions.

Main Methods:

  • Development of a sensor system using a polymer optical fiber (POF) and a flexible light-emitting diode (LED) belt.
  • Utilizing optical source modulation to create 30 independent sensors with one photodetector.
  • Employing the finite element method (FEM) for strain distribution analysis.
  • Experimental testing under pressure and momentums (roll, pitch, yaw).
  • Applying k-means clustering for real-time loading condition estimation.

Main Results:

  • Configuration 1 (continuous PDMS) showed higher sensitivity (83.58 a.u./kPa) than Configuration 2 (40.06 a.u./kPa).
  • Configuration 2 exhibited significantly lower cross-sensitivity (0.94 a.u./kPa) compared to Configuration 1 (45.5 a.u./kPa).
  • Real-time shape reconstruction and loading condition monitoring were achieved with a 90.55% success rate using k-means clustering.

Conclusions:

  • The proposed sensor system is effective for multiplane shape reconstruction and real-time monitoring.
  • Configuration 1 offers superior sensitivity, while Configuration 2 provides better sensor isolation.
  • The sensor system is a viable option for integrated sensing in movement analysis, structural health monitoring, and robotics.