Improved spectral demodulation algorithm with EEMDAD for sapphire fiber Fabry-Perot high-temperature sensing

Area of Science:

• Optics and Photonics
• Materials Science
• Sensor Technology

Background:

• Sapphire fiber Fabry-Perot sensors are crucial for high-temperature measurements.
• Order jumps in spectral demodulation limit sensor accuracy and reliability.
• Existing algorithms struggle to effectively suppress these demodulation jumps.

Purpose of the Study:

• To propose an improved spectral demodulation algorithm for sapphire fiber Fabry-Perot high-temperature sensing systems.
• To suppress order jumps and enhance demodulation accuracy.
• To ensure the reliable operation of high-temperature sensors.

Main Methods:

• Developed an improved spectral demodulation algorithm incorporating ensemble empirical mode decomposition (EEMD) average denoising.
• Applied the algorithm to a sapphire fiber Fabry-Perot high-temperature sensing system.
• Validated the algorithm through simulations and experimental testing in stable and variable temperature environments.

Main Results:

• The proposed algorithm effectively suppresses order jumps in spectral demodulation.
• Noise reduction in the spectrum leads to decreased fluctuations in key sensor parameters.
• Demonstrated significant improvement in demodulation accuracy and sensor reliability.
• Achieved excellent demodulation performance in both stable and dynamic temperature conditions.

Conclusions:

• The developed algorithm successfully overcomes the long-standing order jumping problem in sapphire fiber Fabry-Perot high-temperature sensing.
• The method enhances signal-to-noise ratio and improves overall demodulation accuracy.
• Ensures dependable performance of high-temperature sensors in practical applications.