Intensity modulated torsion sensor based on optical fiber reflective Lyot filter

Area of Science:

• Photonics and Optical Sensing
• Fiber Optic Sensors
• Material Science

Background:

• Torsion sensing is crucial for structural health monitoring.
• Existing fiber optic torsion sensors face challenges with sensitivity and cross-sensitivity.
• Lyot filters offer unique polarization properties for sensing applications.

Purpose of the Study:

• To propose and demonstrate a highly sensitive optical fiber torsion sensor.
• To investigate the performance of a reflective Lyot filter for torsion detection.
• To address the cross-sensitivity issues in existing torsion sensors.

Main Methods:

• Constructing a reflective Lyot filter using polarization-maintaining fiber (PMF), a linear polarizer, and a fiber loop reflector.
• Utilizing intensity modulation for torsion measurement.
• Conducting theoretical simulations and experimental validation.

Main Results:

• Achieved a high torsion sensitivity of 20.336 dB/rad, an order of magnitude greater than state-of-the-art.
• Demonstrated low temperature cross-sensitivity (-2.0 × 10^-4 rad/°C) and strain cross-sensitivity (-6.39 × 10^-6 rad/με).
• Experimental results showed excellent agreement with theoretical simulations.

Conclusions:

• The proposed reflective Lyot filter-based torsion sensor is highly sensitive and robust against temperature and strain variations.
• This technology offers a viable solution for advanced torsion sensing.
• Potential applications include smart structure monitoring and other precision measurement fields.