Spectrum interrogation of fiber acoustic sensor based on self-fitting and differential method

Area of Science:

• Fiber optic sensing
• Acoustic signal processing
• Optical spectroscopy

Background:

• Fiber optic sensors are susceptible to environmental changes like temperature and refractive index (RI) variations.
• Acoustic signals induce dynamic spectral variations in fiber sensors, appearing as ripple waveforms during wavelength scanning.
• Existing methods struggle to accurately recover time-domain signals while mitigating environmental noise.

Purpose of the Study:

• To propose and validate a novel interrogation method for fiber acoustic sensors.
• To recover the time-domain signal from the sensor's optical spectrum.
• To demonstrate the method's ability to compensate for environmental perturbations.

Main Methods:

• Utilizing the ripple waveform in the sensor's optical spectrum, generated by wavelength scanning.
• Extracting frequency components from the ripple spectrum using wavelength scanning speed.
• Recovering the time-domain signal by applying a differential process between the ripple spectrum and a self-fitted curve.
• Employing a long period grating (LPG) as the fiber acoustic sensor head.

Main Results:

• Successfully recovered time-domain acoustic signals from the sensor spectrum.
• The differential process effectively eliminated interference from environmental factors like temperature and RI.
• Demonstrated the feasibility and robustness of the proposed interrogation method using an LPG sensor.
• Validated the compensation for environmental fluctuations.

Conclusions:

• The proposed interrogation method enables accurate time-domain signal recovery from fiber acoustic sensors.
• The differential technique provides effective compensation for environmental perturbations, enhancing sensor reliability.
• This method is applicable to various fiber acoustic sensors, including those based on gratings and interferometers.