Peak positioning method of overlapping fiber bragg grating (FBG) sensing signals

Abstract

The invention relates to a peak positioning method of overlapping FBG sensing signals, and belongs to the field of optical fiber sensing signal processing research of photoelectric detection. The method comprises the following steps: using continuous wavelet transform to process FBG reflected signals to eliminate the influence of signal noises on peak positioning accuracy; using a wavelet ridge peak finding algorithm to obtain peak initial positioning points of peak overlapping FBG signals with the continuity of extreme values at different scales; improving the wavelet ridge peak finding algorithm through matrix singular value decomposition, extracting wavelet ridges which can represent local characteristic information of the FBG reflected signals, and removing a pseudo maximum value affecting peak positioning; and combining peak energy with a signal-to-noise ratio to obtain accurate peak points of final overlapping peaks. By adopting the method, the peak overlapping problem of the FBGreflected signals can be effectively solved.

Description

technical field [0001] The invention relates to a method for processing optical fiber sensing signals, in particular to a method for locating the peak value of overlapping FBG sensing signals. Background technique [0002] Fiber Bragg Grating (FBG) sensors are widely used in electric power, construction, chemical and other fields due to their superior reliability in harsh environments, high precision and sensitivity, and immunity to electromagnetic interference. The demodulation principle is to realize the measurement of the environmental parameters to be measured by detecting the Bragg center wavelength shift caused by the change of the external environment. In practical engineering applications, the detection accuracy of the FBG sensor is mainly determined by the demodulation capability of the sensing system in addition to the characteristics of the sensor itself. For the FBG sensor demodulation system, its resolving power is the criterion for judging the quality of the s...

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Problems solved by technology

[0003] Commonly used peak location algorithms include direct comparison method, polynomial fitting method, and Gaussian curve fitting method. The direct comparison method is sensitive to background information, has low computational complexity, and poor anti-noise performance. It is only suitable for finding isolated peaks and is not suitable for complex signals. Peak-seeking; polynomial fitting method requires polynomial transformation of the collected data, and has strict requirements on the signal waveform. As the signal waveform gradually deviates from the standard quadratic shape, the greater the peak positioning error, the poorer the adaptive ability of peak-seeking; Gaussian curve Although the fitting method has a high-precision peak-finding effect, it is not suitable for automatic peak-finding of the entire signal

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