Adaptive aberration spectral peak finding algorithm for fiber MEMS fiber -Perot sensor

Fiber optic MEMS Fiber -Perot sensors have gradually become a popular research topic. However, when the sensor's spectrum is distorted, there is limited research on high-precision peak detection algorithms used in demodulation. In response to this research gap, this paper proposes an adaptive peak detection algorithm to address the issue of spectral distortion. Firstly, we segment the interference spectrum demodulated by the interrogator using the Hilbert transform method to obtain multiple independent interference spectra with only one peak. For each dataset obtained through Hilbert transformation, the number of data points on both sides is detected with its peak as the center. If the number of data points on both sides is equivalent, it proves that the interference spectrum has not been distorted. Otherwise, the interference spectrum has been distorted. We propose a spectral correction algorithm based on Gaussian fitting for distorted spectra which detailed information is reported below, and achieve the accurate peak of distorted spectra by this method. We have carried out experiments in the laboratory, and the results showed that the algorithm error was less than 0.0051MPa within the pressure range of 0-3MPa.