首页|基于GAF-HorNet的Φ-OTDR周界安防监测研究

基于GAF-HorNet的Φ-OTDR周界安防监测研究

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相位敏感型光时域反射(Φ-OTDR)技术是一种具有高精度振动监测优点的分布式光纤传感技术,能够检测周界安防领域中的扰动事件.针对传统识别方法中需要人工提取振动信号特征,无法保留时间的相关性导致信息丢失的问题,提出一种基于GAF-HorNet的扰动事件识别方法,该方法无需特征提取步骤,能将一维振动信号通过格拉姆角场(GAF)转为二维图像,采用HorNet训练模型并进行识别分类.为了验证该算法的性能,选择4种经典算法训练模型进行对比实验.实验结果表明,该算法对背景噪声、石头敲击、石头划、树枝划、拉拽、攀爬等 6类信号的平均识别准确率为93.56%,比现有的方法在识别率、误报率上有更好的表现.
Research on Φ-OTDR Perimeter Security Monitoring Based on GAF-HorNet
Phase-sensitive optical time-domain reflection(Φ-OTDR)technology is a distributed fiber-optic sensing technique with the advantage of high-precision vibration monitoring.It can be used to detect disturbance events in the field of perimeter security.Traditional recognition methods require the manual extraction of vibration signal features and cannot retain a time correlation,leading to information loss.To solve this problem,a disturbance event recognition method based on GAF-HorNet,which does not require a feature extraction step,is developed.A one-dimensional vibration signal is converted into a two-dimensional image through a Gramian angular field(GAF),and HorNet is used to train the model and perform recognition and classification.To verify the performance of the algorithm,four classical algorithms are selected to train the model for comparative experiments.The experimental results demonstrate that the average accuracy of the proposed algorithm is 93.56%for six types of signal:background noise,stone knocking,stone stroking,branch stroking,pulling,and climbing.Compared with previous methods,the method proposed has better recognition rate and false alarm rate performances.

optical fiber sensingphase-sensitive optical time-domain reflectometergramian angular fieldsclassification recognition

胡胜、胡歆敏、李莎莎、吕朴初、秦海鑫、赵灿、武明虎、刘聪

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湖北工业大学电气与电子工程学院,湖北 武汉 430068

华中科技大学光学与电子信息学院,湖北 武汉 430074

光纤传感 相位敏感光时域反射计 格拉姆角场 分类识别

2024

激光与光电子学进展
中国科学院上海光学精密机械研究所

激光与光电子学进展

CSTPCD北大核心
影响因子:1.153
ISSN:1006-4125
年,卷(期):2024.61(9)
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