A new quality evaluation parameter for Rayleigh backscattering spectrum and its adaptive subset window algorithm in distributed fiber strain measurement

摘要

Rayleigh backscattering spectrum (RBS) correlation based distributed fiber strain measurement can be achieved by calculating the RBS offset using cross-correlation function from an unstrained and strained optical fiber under test. Thus the subset window length and the quality of the RBS in the subset have an important impact on the accuracy of the cross-correlation analysis and the strain measurement. How to evaluate the quality of different RBS signals plays an important role in optimizing the subset window length and improving the use of the technique. In this paper, a parameter called mean of the square of intensity gradient (MSIG) is proposed for quality assessment of the RBS signals. Further, an adaptive subset window algorithm base on the MSIG of each subset is developed for the subset window selection. The experiments verify the effectiveness and accuracy of the proposed parameter. The results show that the RBS with larger MSIG has smaller standard deviation error and higher signal quality. The adaptive subset window algorithm based on MSIG proposed in this paper can effectively improve the strain calculation accuracy of the distributed fiber strain measurement.