| 一种应用于光缆外破在线监控的模式识别方案 |
| |
| 引用本文： | 彭和阔,宋耀华,王翦,徐锲,沈仁根,林亦雷,贾耕涛,吴海生,于松,艾鑫,肖倩.一种应用于光缆外破在线监控的模式识别方案[J].光学仪器,2018,40(2):56-61. |
| |
| 作者姓名： | 彭和阔 宋耀华 王翦 徐锲 沈仁根 林亦雷 贾耕涛 吴海生 于松 艾鑫 肖倩 |
| |
| 作者单位： | 复旦大学材料科学系;国家电网上海市电力公司信息通信公司;上海欧忆能源科技有限公司;上海复旦智能监控成套设备有限公司 |
| |
| 基金项目： | 国家重大科学仪器设备开发专项项目（2012YQ150213）；上海市科委项目（14DZ2281200、17DZ2280600） |
| |
| 摘 要： | 电力通信网络线路常因沿途的工程机械施工,人为外力破坏等行为造成毫无预警的危害和损坏。为了实现对线路外破隐患高效预警,需要在现有预警定位的基础上,加上对碰撞敲击、管孔侵入、机械施工和开盖报警等行为的识别。将分布式光纤传感技术、梅尔频率倒谱系数和径向基神经网络相结合,提出一种可应用于光缆外破在线监控的模式识别方案。测试的总体识别率达97.78%,现场模拟的事件报警准确率高。该方案可广泛应用于长距离管线检测领域。
|
| 关 键 词： | 分布式光纤振动传感技术 梅尔频率倒谱系数 径向基函数 模式识别 |
| 收稿时间： | 2017/7/8 0:00:00 |
A pattern recognition scheme for online monitoring optical cable |
| |
| PENG Hekuo,SONG Yaohu,WANG Jian,XU Qie,SHEN Rengen,LIN Yilei,JIA Gengtao,WU Haisheng,YU Song,AI Xin and XIAO Qian.A pattern recognition scheme for online monitoring optical cable[J].Optical Instruments,2018,40(2):56-61. |
| |
| Authors: | PENG Hekuo SONG Yaohu WANG Jian XU Qie SHEN Rengen LIN Yilei JIA Gengtao WU Haisheng YU Song AI Xin and XIAO Qian |
| |
| Affiliation: | Department of Materials Science, Fudan University, Shanghai 200433, China,Department of Materials Science, Fudan University, Shanghai 200433, China,Department of Materials Science, Fudan University, Shanghai 200433, China,Department of Materials Science, Fudan University, Shanghai 200433, China,Information and Communication Company, SMEPC, SGCC, Shanghai 200122, China,Information and Communication Company, SMEPC, SGCC, Shanghai 200122, China,Information and Communication Company, SMEPC, SGCC, Shanghai 200122, China,Shanghai OE Energy Technology Co., Ltd., Shanghai 200041, China,Shanghai OE Energy Technology Co., Ltd., Shanghai 200041, China,Shanghai Fudan Intelligent Surveillance Equipment Co., Ltd., Shanghai 200433, China and Department of Materials Science, Fudan University, Shanghai 200433, China |
| |
| Abstract: | Power line communication network always suffer from the engineering construction and artificial damage without warning.In order to realize the effective early warning to the hidden danger of line,we need to add some pattern recognition scheme on the basis of the existing early-alert,which can distinguish different vibration signal such as knock,pipeline intrusion,mechanical construction and manhole covers opening.In this paper,the distributed optical fiber sensing technology,Mel frequency cepstral coefficient and radial basis function neural network are used in this optical cable online monitoring pattern recognition scheme.The overall recognition rate of the test sample is 97.78%.The accuracy of the incident alarm is remarkable in the scene simulation.The scheme can be widely used in the area of long-distance pipe detection. |
| |
| Keywords: | distributed fiber-optic vibration sensing technology Mel frequency cepstral coefficient radial basis function pattern recognition |
| 本文献已被 CNKI 等数据库收录！ |
| 点击此处可从《光学仪器》浏览原始摘要信息 |
|
点击此处可从《光学仪器》下载全文 |
|
