A fast strain sensing for intelligent overhead line based on slope-assisted technique

In order to improve the real-time performance of state sensing, the slope-assisted techniqueand the least-squares spectrum fit method based on the pseudo-Voigt model were introduced into the strain measurement of optical fiber composite overhead lines. The programs about the least squares spectrum fitting method and the slope-assisted technique based on the pseudo-Voigt model were written and applied to the strain measurement along an optical fiber composite overhead line. Based on the measured Brillouin spectra, the influence of the signal-to-noise ratio (SNR) of the working point gain and the Brillouin frequency shift (BFS) on the accuracy of the slope-assisted technique was systematically investigated. The results reveal that the BFS error decreases exponentially with SNR. The BFS error decreases rapidly and then increases slightly with the difference between BFS and working point frequency. The strain error of the slope-assisted technique is less than 60 με when the SNR of Brillouin gain at the working point is not less than 25 dB and at the same time, the frequency at the working point is always less or larger than the BFS. In addition, the corresponding critical SNR of 60 με is presented for different BFSs, and the critical SNR corresponding to different cases can be obtained by interpolation. The measurement time and computation time of the slope-assisted technique are about 1/161 and 1/600 of that of the spectrum fitting method, respectively. The work provides a reference for improving the real-time performance of sate sensing of intelligent optical fiber composite overhead lines.