To reduce the output power ununiformity mainly caused by the exponential attenuation of pump power in a distributed feedback fiber laser (DFB FL) sensor array, a power equalization method based on array structure optimization is proposed. By analyzing the influencing factors of the output power flatness of the array, an output power prediction model of a DFB FL wavelength division multiplexing (WDM) array is established, and the standard deviation coefficient of the output power is proposed as the main evaluating indicator for assessing the output power flatness. An array structure optimization scheme based on the simulated annealing algorithm is designed, and the optimized array structure of the 64-element DFB FL sensor array is achieved. The results show that the power fluctuation of the optimized array is significantly reduced from universal 5–10 dB to smaller than 2.6 dB, while the performance of the DFB FL sensor array is improved with better noise floor and increased multiplexing capacity, as well as improved array design efficiency.
In order to ensure that a perimeter security system can work effectively, a convenient and effective event detection algorithm has an important engineering significance. Given the above background, in this paper, we propose a high reliability intrusion event recognition method and vibration sensing system, based on ultra-weak fiber Bragg grating array, by using high dimensional random matrix. We obtain a high sensitivity optical interference signal by constructing a patch-matched optical interference system, then compose the demodulated interference signal into a high-dimensional random matrix. The statistical characteristics of the matrix for the Marcenko-Pastur (M-P) law and ring law are used to confirm the presence of intrusion events efficiently, which can reflect the limit spectrum distribution of the high-dimensional random matrix; meanwhile, the abnormal state quantity and moment are obtained. Further, the average spectral radius value is used to judge the fault cause. Field experimental results show that the proposed method can effectively obtain the correct monitoring data for the sensor array. By comparing the monitoring results of normal operation and crusher operation, we can detect the intrusion event in 4.5 s, and the accuracy rate can reach more than 90%, which verifies that the proposed high-dimensional random matrix analysis method can work properly, proving a practical engineering application prospect.
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