Novel auto-correction method in a fiber-optic distributed-temperature sensor using reflected anti-Stokes Raman...

Area of Science:

• Optoelectronics
• Fiber optic sensing
• Signal processing

Background:

• Fiber optic distributed temperature sensors (DTS) are crucial for environmental monitoring.
• Local losses and differential attenuation can compromise the accuracy of DTS measurements.
• Existing methods struggle to fully compensate for signal variations caused by fiber imperfections.

Purpose of the Study:

• To introduce a novel auto-correction method for fiber optic distributed temperature sensors.
• To eliminate the impact of local losses and differential attenuation on temperature readings.
• To enhance the reliability and accuracy of DTS systems.

Main Methods:

• The method utilizes both the anti-Stokes Raman back-scattered signal and its reflected signal.
• Two parts of the measured signal are processed to compensate for signal loss.
• The technique employs beams of the same wavelength to cancel local variance in the transmission medium.

Main Results:

• The novel method effectively eliminates the effects of local losses caused by micro-bending or fiber damage.
• Differential attenuation is also compensated for, leading to more accurate temperature measurements.
• Experimental verification using bending tests confirmed the auto-correction concept's validity.

Conclusions:

• The presented auto-correction method significantly improves the accuracy of fiber optic distributed temperature sensors.
• This technique offers a robust solution for mitigating signal degradation in DTS systems.
• The method holds promise for applications requiring precise and reliable temperature monitoring in challenging environments.