Distributed ultra large strain measurement range sensing based on spectral shift adjacent point difference method in OFDR

Abstract

Compared with the time-domain distributed optical fiber sensing technology, optical frequency domain reflectometry (OFDR) has the advantages of high spatial resolution and low detection optical power requirements. However, in the large strain measurement, OFDR encountered such a problem: the correlation of the Rayleigh scattering spectra between strain signals and reference signals is relatively low if the loading strain is too large, resulting in incorrect demodulation. To address this issue, we propose a new method called the spectral shift adjacent point difference method. In our approach, the cross-correlation operations using two sets of non-strain signals are performed, and the average value of the cross-correlation’s spectral shift is selected as a reference standard. Then the spectral shift of the entire sensing fiber is obtained by re-sweeping frequency when the strain is loaded along the sensing fiber. The data points with a spectral shift adjacent point difference less than the reference standard will be retained, while other data points with spectral shift adjacent point difference greater than the reference standard will be considered as noisy fake spikes and removed. Finally, interpolation fitting is performed on the retained data points along the entire sensing fiber to obtain the demodulated spectral shifts realize large strain measurement. The experimental results show that the maximum measurable strain by the proposed method can reach 10,800 µε with a spatial resolution of 7.84 mm, which is an order of magnitude higher than the conventional method. The experiment demonstrates the high stability and excellent repeatability of the proposed processing method. The proposed method has the advantage of simple algorithm and easy implementation, and making it more competent in the field of large strain measurement.