相关向量机在光纤预警系统模式识别中的应用

发布时间：2018-03-16 03:00

  本文选题：光纤预警　切入点：模式识别　出处：《天津大学学报(自然科学与工程技术版)》2014年12期 　论文类型：期刊论文

【摘要】：由于传统模式识别方法存在过学习、训练时间长等缺陷,不能满足光纤预警系统实时在线监测的要求.相关向量机能够克服传统方法的缺点,识别精度高,向量机个数需求少,因此,将相关向量机应用于光纤预警系统模式识别中,采用小波能谱和小波信息熵的特征提取方法,在测试阶段采用有向无环图的方法进行多类识别.通过对威胁管道安全的事件进行实验,识别精度达到92.67%,向量机个数只有2个,验证了相关向量机方法应用于光纤预警系统的可行性和有效性.
[Abstract]:Because of the shortcomings of traditional pattern recognition methods, such as learning and long training time, it can not meet the requirements of real-time on-line monitoring of optical fiber early warning system. Correlation vector machines can overcome the shortcomings of traditional methods, and the recognition accuracy is high, and the number of vector machines needs less. Therefore, correlation vector machine is applied to pattern recognition of optical fiber early warning system. Wavelet spectrum and wavelet information entropy are used to extract features. In the testing stage, the method of directed acyclic graph is used to identify many kinds of information. Through the experiments on the events threatening the safety of pipelines, the recognition accuracy is 92.67, and the number of vector machines is only 2. The feasibility and effectiveness of the application of correlation vector machine in optical fiber early warning system are verified.
【作者单位】： 天津大学精密测试技术与仪器国家重点实验室;
【基金】：国家自然科学基金资助项目(61240038)
【分类号】：TP212;TN911.7

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中国期刊全文数据库 前1条

1 袁浩东;陈宏;侯亚丁;;基于全矢小波包能量熵的滚动轴承智能诊断[J];机械设计与制造;2012年02期

【共引文献】

中国期刊全文数据库 前6条

1 李浩;董辛e，

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