High-precision dual-parameter demodulation method for spiral chirped fiber gratings based on deep learning

Key Points

• Achieving high-precision parameter recovery enhances signal processing in fiber gratings, improving sensor accuracy and reliability.
• The method reduced parameter estimation error significantly, achieving a 90% accuracy rate compared to traditional techniques.
• Utilizing deep learning, this approach allows for real-time processing of data from fiber gratings in various applications.
• The findings may enable advancements in optical sensing, though further validation in real-world settings is necessary.