面向DVS振动信号识别率提升的特征选择算法研究  

Research on feature selection algorithm for DVS vibration signalrecognition rate improvement

作　　者：马喆 李玮哲 张建忠 李健 王婷玉 和祥 杨滨远 张明江 MA Zhe;LI Weizhe;ZHANG Jianzhong;LI Jian;WANG Tingyu;HE Xiang;YANG Binyuan;ZHANG Mingjiang(College of Physics and Optoelectronic Engineering,Taiyuan University of Technology,Taiyuan 030024,China;Key Laboratory of Advanced Transducers and Intelligent Control System,Ministry of Education,Taiyuan University of Technology,Taiyuan 030024,China)

机构地区：[1]太原理工大学物理与光电工程学院,山西太原030024 [2]太原理工大学新型传感器与智能控制教育部重点实验室,山西太原030024

出　　处：《红外与激光工程》2024年第8期228-238,共11页Infrared and Laser Engineering

基　　金：国家重点研发计划项目(2023YFF0715700);国家自然科学基金项目(62205237,62075153,62075151,62205234);山西省基础研究计划(交控)联合资助项目(202303011222005);山西省青年科学基金项目(20210302124396,202103021223042);山西省重点研发计划项目(202102150101004)。

摘　　要：分布式光纤振动传感(Distributed Optic-fiber Vibration Sensing, DVS)系统可对振动信号实现分布式测量,在实际应用中通常采用模式识别算法对各种振动事件进行识别,然而目前模式识别特征大都固定冗余,不能充分展现振动信号的特性,导致误报率高的问题。针对上述问题,搭建了一套直接探测结构的DVS系统样机,并提出了基于模拟退火算法和Fisher Score算法相结合的混合式特征选择方法。首先使用Fisher Score算法选取合适的特征初始集合,再将Fisher Score嵌入模拟退火算法的新解产生环节中,实现对入侵振动信号的特征组合整体效果较好的选择。通过实验对算法性能进行验证,结果表明:该算法可以剔除冗余入侵振动信号特征,拥有较快的收敛速度,使系统的识别率由80.23%提升至94.46%。Distributed optic-fiber vibration sensing(DVS)system enables distributed measurement of vibration signals.Despite the prevalent utilization of pattern recognition algorithms in practical applications to discern various vibration events,extant pattern recognition features often exhibit fixity and redundancy,thereby inadequately capturing the nuanced characteristics of vibration signals,resulting in a pronounced false alarm rate challenge.This study presents a prototype of a direct detection structure DVS system devised to confront the issues above.Also,a hybrid feature selection methodology is proposed here,integrating the simulated annealing algorithm with the Fisher Score algorithm.Initially,the Fisher Score algorithm is employed to identify an apt initial feature set,subsequently integrating the Fisher Score into the new solution generation phase of the simulated annealing algorithm to optimize the overall efficacy of the feature amalgamation for intrusion vibration signals.Experimental validation of the algorithm underscores its capability to obviate redundant intrusion signal features,evince rapid convergence,and elevate the system's recognition rate from 80.23%to 94.46%.Objective The distributed fiber-optic vibration event recognition system comprises two key components of the distributed fiber-optic vibration sensing(DVS)system and the vibration event recognition module.This system is highly effective for locating vibration events and has garnered significant attention in applications such as perimeter security,pipeline leakage detection,and earthquake monitoring.In the studies on pattern recognition of intrusion vibration signals collected by DVS,it is essential to handle large volumes of high-dimensional feature vector data,where each component represents a specific characteristic of the data.However,existing pattern recognition features are often fixed and redundant,with some algorithms failing to address the core problem effectively,leading to a high false alarm rate.To enhance pattern recognition accur

关 键 词：分布式光纤振动传感 特征提取 模拟退火算法 Fisher Score算法 

分 类 号：TN29[电子电信—物理电子学]