首页期刊导航|武汉大学自然科学学报(英文版)
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武汉大学自然科学学报(英文版)
武汉大学自然科学学报(英文版)

刘经南

双月刊

1007-1202

Whdy@whu.edu.cn

027-68752259

430072

湖北武昌珞珈山武汉大学梅园一舍

武汉大学自然科学学报(英文版)/Journal Wuhan University Journal of Natural SciencesCSCDCSTPCD北大核心
查看更多>>本刊创刊于1996年。本刊是自然科学综合性学术期刊,主要刊登自然科学各学科的最新研究成果。本刊已被《EI》、《CA》、《SA》、《AJ》、《JOURICK》、《MR》等作为刊源收录,《SCI》正在对本刊进行评估。
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    Optimization of Surface Plasmon Resonance Sensor Based on Multilayer Film Structure

    LIU JinSHENG XiangHUANG BoREN Wenjia...
    352-358页
    查看更多>>摘要:A prism-excited multilayer film Surface Plasmon Resonance (SPR) sensing structure of graphene-silver-graphenemeasured mediums is proposed to solve the unstablility and oxidization problem of metallic silver films for SPR sensors.By adding a graphene layer,the poor stability and the oxidization problem of silver film are solved.The electromagnetic field and reflection mechanism of the multilayer film structure are theoretically analyzed.The characteristics of the different metal materials for SPR,the distinct silver film thickness,and different graphene layers are studied through experiments to optimize the sensor design.Compared with the gold film sensor,the sensitivity of the multilayer film sensor with graphene layer is improved.The designed SPR sensor is used to detect a sucrose solution with a concentration of 0%-64%,and its refractive index is 1.33 to 1.45,linear correlation coefficient is 0.998 4.Good resonance effect and sensing characteristics are thus obtained.

    A Fault Diagnosis Method Based on Wavelet Singular Entropy and SVM for VSC-HVDC Converter

    XU BingbingWANG TianzhenLUO KaiGAO Diju...
    359-368页
    查看更多>>摘要:The converter is the core component of voltage source converter-high voltage direct current (VSC-HVDC),which is related to the stable operation of the system.The converter has a complex structure where the accuracy of feature extraction is low,and the computation speed of traditional fault diagnosis strategies is slow.To solve this problem,a fault diagnosis strategy based on wavelet singular entropy (WSE) and support vector machine (SVM) was proposed.This method includes fault and label setting,converter fault feature extraction based on wavelet singular entropy,and converter fault classification based on support vector machine.The DC-side voltage signal was used as the detection signal,and the wavelet singular entropy was used for feature extraction to avoid noise interference.The classification is based on SVM.The experimental verification in PSCAD simulation proved that the method has better fault diagnosis ability for various faults and meets the needs of converter fault diagnosis.