应用光学, 2015, 36 (3): 424, 网络出版: 2015-09-08   

基于支持向量机的分布式光纤泄漏检测定位系统及实验分析

Support vector machine based distributed optical fiber leakage detection system and experimental analysis
作者单位
1 中国计量学院 质量与安全工程学院, 浙江 杭州 310018
2 中国计量学院 机电工程学院, 浙江 杭州 310018
摘要
针对基于Sagnac和Mach-Zehnder混合干涉仪的分布式光纤管道泄漏检测定位系统进行了泄漏实验,采用在1 km~9 km之间的20组泄漏点样本,依据支持向量机建立样本数据的回归模型,对支持向量机的相关调整参数进行了优化,对系统的灵敏度进行了分析.实验结果表明,经SVM回归分析可得,处理后样本比实验所得泄漏点位置更接近实际泄漏点位置,传统定位方法得到的泄漏点位置平均绝对误差为118.85 m,经过回归分析后样本的平均绝对误差为92.01 m,定位精确度达99.85%,定位精度提高;当泄漏点距法拉第旋转镜的距离越远,检测系统的灵敏度越小,当泄漏点位置超过10 km时,系统的灵敏度低于0.5 Hz/m.
Abstract
Leakage experiments were performed on the distributed optical fiber pipeline leakage detection system.The system was based on a mixed interference principle of Mach-Zehnder and Sagnac.20 groups of leakage point samples were gained between 1km to 9km from the leakage experiments.Support vector machines(SVMs)were used to build the sample of data model,the related parameters of SVM were optimized ,and the sensitivity of the system was analyzed.The results show that the processed samples are significantly closer to the actual leakage points than the experimental leakage points through regression analysis.The mean absolute error of experimental leakage points is 118.85m while that of the regression samples is 92.01m.The accuracy rate of positioning improves to 99.85%.The sensitivity of the detection system is lower when the leakage points are farther away from the Faraday rotation mirror.The sensitivity of the system is less than 0.5 Hz / m when the leakage points are over 10 km.
参考文献

[1] 蒋奇.分布式光纤温度传感技术在隧道监测中的应用[J].应用光学,2005,26(3):20-22.

    Jiang Qi.Application of fiber-optic distributed temperature sensor to tunnel monitoring system[J].Journal of Applied Optics,2005,26(3):20-22.

[2] Spammer S J,Swart P L,Chtcherbakov A A.Merged Sagnac-Michelson interferometer for distributed disturbance detection[J].Journal of Light Wave Technology,1997,15(6):972-976.

[3] Huang Shihchu,Lin Wuuwen,Tsai Mengtsan.Fiber optic in-line distributed sensor for detection and localization of the pipeline leaks[J].Sensors and Actuators A:Physical,2007,135(2):570-579.

[4] 胡正松,杨其华,乔波.干涉型分布式光纤水下长输气管道泄漏检测系统设计[J].激光与光电子学进展,2012,49(7):69-73.

    Hu Zhengsong,Yang Qihua,Qiao Bo.The design of interference distributed fiber-optic underwater long gas pipeline leakage detection system[J].Laser﹠Optoelectronics Progress,2012,49(7):69-73.

[5] Su C T,Yang C H.Feature selection for the SVM:anapplication to hypertension diagnosis[J].Expert Systems with Application,2008,34(1):754-763.

[6] 潘锐,李立京,张文慧.抑制分布式光纤光学传感器错误警报的混合支持向量机算法[J].红外与激光工程,2013,42(增刊2):431-439.

    Pan Rui,Li Lijing,Zhang Wenhui.Compound SVM algorithm for restraining false alarm of distributed fiber optic sensor [J].Infrared and Laser Engineering,2013,42(S2):431-439.

[7] 李彦,梁正桃,李立京,等.基于小波和支持向量机的光纤微振动传感器模式识别[J].传感器与微系统,2013,32(2):43-49.

    Li Yan,Liang Zhengtao,Li Lijing,et al.Pattern recognition of fiber-optic micro vibration sensor based on wavelet and SVM [J].Transducer and Microsystem Technologies,2013,32(2):43-49.

[8] 芦吉云,王帮峰,梁大开.基于小波包特征提取及支持向量回归机的光纤布拉格光栅冲击定位系统[J].光学精密工程,2012,20(4):712-718.

    Lu Jiyun,Wang Bangfeng,Liang Dakai.Identification of impact location by using FBG based on wavelet packet feature extraction and SVR[J].Optics and Precision Engineering,2012,20(4):712-718.

[9] 黄悦,王强,杨其华,等.水下天然气管道分布式光纤泄漏检测系统实验分析[J].激光与光电子学进展,2014,51(11):110602-1-6.

    Huang Yue,Wang Qiang,Yang Qihua,et al.The experimental analysis of distributed fiber optic underwater natural gas pipeline leakage detection system [J].Laser﹠Optoelectronics Progress,2014,51(11):110602-1-6.

[10] 章仁杰.基于PGC解调的光纤传感器天然气管道泄漏检测装置设计[D].浙江:中国计量学院,2014.

    Zhang Renjie.The design of fiber-optic sensor natural gas pipeline leakage detection device based on PGC demodulation[D].Zhejiang:China Jiliang University,2014.

[11] Keerthi S S,Lin C J.Asymptotic behaviors of support vector machines with Gaussian kernel [J].Neural Computation,2003,15(7):1667-1689.

[12] Liu Xianglou,Jia Dongxu,Li Hui.Research on Kernel parameter optimization of support vector machine in speaker recognition [J].Science Technology and Engineering,2010,10(7):1669-1673.

[13] 王健峰,张磊,陈国兴,等.基于改进的网格搜索法的SVM参数优化[J].应用科技,2012,39(3):28-31.

    Wang Jianfeng,Zhang Lei,Chen Guoxing,et al.A parameter optimization method for an SVM based on improved grid search algorithm [J].Applied Science and Technology,2012,39(3):28-31.

黄悦, 王强, 韩玲娟, 朱俊. 基于支持向量机的分布式光纤泄漏检测定位系统及实验分析[J]. 应用光学, 2015, 36(3): 424. Huang Yue, Wang Qiang, Han Lingjuan, Zhu Jun. Support vector machine based distributed optical fiber leakage detection system and experimental analysis[J]. Journal of Applied Optics, 2015, 36(3): 424.

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