Disturbance location and pattern recognition of a distributed optical fiber sensor based on dual-Michelson interferometers

A distributed fiber optic sensor based on dual-Michelson interferometers for disturbance localization and pattern recognition is proposed. The system obtains the phase difference of each of the two interferometers using a passive demodulating algorithm based on a 3×3 coupler. Two correlation signals with disturbance position information are obtained by delaying and subtracting the phase difference signals through which the disturbance location can be obtained. This method has the same frequency response over the whole sensing path, and there is no localization blind spot. The pattern recognition method of this sensing system is to obtain the spectral signal by fast Fourier transform of the demodulated interferometer phase information and input it as a feature vector into a one-dimensional convolutional neural network to verify the correct rate of pattern recognition for four behaviors: stepping, shearing, sweeping, and shaking. The total transmission distance of the system can reach 100 km; the location errors are within ±35m, and the correct rate of four pattern recognitions is higher than 97%. The sensing system has good polarization stability, which can ensure the stability of long-term operation and has a broad application prospect in long-distance perimeter security.