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时间:2020-04-22
《基于无线传感器网络的河流中稳态扩散污染源定位研究-论文.pdf》由会员上传分享,免费在线阅读,更多相关内容在应用文档-天天文库。
1、第27卷第10期传感技术学报Vol?27No?102014年10月CHINESEJOURNALOFSENSORSANDACTUATORSOct.2014TheLocalizationofPollutionSourceinSteadyDiffusionState∗inRiverBasedonWirelessSensorNetworks121∗YANGJunꎬLUOXuꎬCHAILi(1.EngineeringResearchCenterofMetallurgicalAutomationandMeasurementTechnologyꎬMin
2、istryofEducationꎬWuhanUniversityofScienceandTechnologyꎬWuhan430081ꎬChinaꎻ2.DepartmentofMedicalInformationEngineeringꎬZunyiMedicalUniversityꎬZunyiGuizhou563003ꎬChina)Abstract:Tosolvethelocalizationproblemofthepollutionsourceinriverꎬthediffusionprocessisanalyzedfirst.Instea
3、dydiffusionstateꎬageneraldiffusionmodelisproposedꎬwhichcanapplytothediffusionprocesswithcompleteabsorptionboundaryꎬperfectreflectionboundaryandimperfectreflectionboundaryꎬrespectively.Anonlinearleastsquarebasedlocalizationmethodisimprovedwiththeboundaryconstrainandthetarg
4、etofminimizingthesumofthesquareofthedifferencesbetweentheestimationandthemeasurementoftheconcentrationcomputing.Thenꎬtoimprovethenumericalstabilityandrobustnessꎬanewobjectivefunctionoflocalizationisproposed.Simulationsareconductedtothelocalizationperformancesunderdifferen
5、tlevelsofmeasurementnoiseꎬnodepositiondriftandre ̄flectioncoefficientuncertainties.Thesimulationresultsshowthatthemoretherelatedinformationerrorisꎬthelargertherootmeansquareerrorofthepositionestimationisꎬandthatthemoresensornodesareꎬthehighertheaccurateofpositionestimation
6、is.Howeverꎬwhenthenumberofnodesisuptoacertainvalueꎬthelocalizationaccuracyisimprovedhardly.Theresultsvalidatethesuperiorityoftheimprovednonlinearleastsquaremethodanditsefficiencyintheapplicationofthelocalizationofpollutionsourceinriver.Keywords:wirelesssensornetworkꎻnonli
7、nearleastsquaresꎻthelocalizationofpollutionsourceꎻpollutionsourceinwaterEEACC:6150Pꎻ7230doi:10.3969/j.issn.1004-1699.2014.10.022基于无线传感器网络的河流中稳态∗扩散污染源定位研究121∗杨君ꎬ罗旭ꎬ柴利(1.武汉科技大学冶金自动化与检测技术教育部工程研究中心ꎬ武汉430081ꎻ2.遵义医学院信息工程系ꎬ贵州遵义563003)摘要:针对河流中污染源定位问题ꎬ首先分析了河流污染源扩散模型ꎬ给出了一种处理完全吸收边界ꎬ
8、不完全反射边界以及完全反射边界的通用河流污染源稳态扩散模型ꎮ改进了在边界约束下以测量值与理论值之差的平方和为目标的非线性最小二乘算法ꎬ并提出了一种新的最小二乘污染源定位算法ꎮ该算法弥补了直接非
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