Hybrid Peak Detection Methods for Fiber Bragg Grating Temperature Sensor

Abstract

The center of temperature measured in the Fiber Bragg Grating temperature sensor produces a shift in the Bragg wavelength. There are a wide variety of algorithms used to detect this shift. However, these algorithms are highly affected by the noise generated in the sensor system. In recent years, many techniques have emerged that suppress this noise. Of these, wavelet noise reduction stands out as a popular technique. When the literature is reviewed, it is stated that this popular approach is superior to traditional methods. Contrary to what is said in the literature, this study proves that without the need for complex wavelet system or even curve fitting, it leads us to the same results and sometimes even better than traditional filtering. The hybrid approach proposed here is based on the traditional Fourier Filtering technique and the maximum method, which is a direct method in determining the central wavelength. In the error analysis, it is seen that the hybrid algorithm based on Fourier Filtering, which is the traditional filtering technique, gives the smallest relative error when compared with the real value.