Zhang Shu, Ma Yixiao, Lai Xin, Xiao Qian, Jia Bo, Wu Hongyan
Opt Express. 2024 Mar 25;32(7):11134-11149. doi: 10.1364/OE.517278.
This research addressed the drawbacks of the conventional hybrid structure and processing technique by presenting a novel distributed fiber optic sensor based on a hybrid Michelson and Mach-Zehnder interferometer. The sensor can achieve blind spot free positioning and has a wide response frequency, additionally its structure is not complex. It can obtain two phase signals from each of the two interferometers by using a demodulation method that uses a 3 × 3 optical coupler. To determine the position of the disturbance, we computed cross-correlations on the two signals following basic mathematical techniques. Markov Transition Field was used to transform the phase signals-which had been filtered by a band pass filter-into two-dimensional images. Tagged photos built a dataset, which is then fed into a neural network to identify patterns. Experiments have shown that the frequency response capacity of the structure was verified, and it was able to achieve location within 0-30 km with location errors of ±85 m. In a six-category pattern recognition, the testing set accuracy was 98.74%.
本研究通过提出一种基于迈克尔逊和马赫-曾德尔混合干涉仪的新型分布式光纤传感器，解决了传统混合结构及处理技术的缺点。该传感器可实现无盲点定位，具有较宽的响应频率，且结构不复杂。通过使用一种采用3×3光耦合器的解调方法，它能从两个干涉仪中的每一个获取两个相位信号。为了确定扰动的位置，我们按照基本数学技术对这两个信号进行互相关计算。马尔可夫转移场用于将经过带通滤波器滤波的相位信号转换为二维图像。标记的照片构建了一个数据集，然后将其输入神经网络以识别模式。实验表明，该结构的频率响应能力得到了验证，并且能够在0至30千米范围内实现定位，定位误差为±85米。在六类模式识别中，测试集准确率为98.74%。
