一种湿度传感器温度补偿的融合算法

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1、第25卷第12期传感技术学报Vol.25摇No.122012年12月CHINESEJOURNALOFSENSORSANDACTUATORSDec.2012*AFusionAlgorithmforHumiditySensorTemperatureCompensation1,2*1,21,31,24XINGHongyan,PENGJiwei,L譈Wenhua,XUWei,WUXiangjuan(1.JiangsuKeyLaboratoryofMeteorologicalObservationandInformationP

2、rocessing,NanjingUniversityofInformationScienceandTechnology,Nanjing210044,China;2.Schoolofelectronicandinformationengineering,NanjingUniversityofInformationScienceandTechnology,Nanjing210044,China;3.AtmosphericObservationTechnologyCenter,ChinaMeteorologicalAdm

3、inistration,Beijing100081,China;4.NingxiaMeteorologicalObservationTechnologySupportCenter,Yingchuan750002,China)Abstract:Accordingtothehumiditysensorsontheautomaticweatherstationinfluencedeasilybytemperatureintheactualapplication,RBFneuralnetworkandleastsquares

4、combiningfusionalgorithmisproposedtorealizecompensationofthehumiditysensor.Thecharacteristiccurvethatthehumiditysensorisundertheinfluenceofthetemperatureisdividedintotwoparts,i.e.anon鄄linearpartandalinearpart,andintheadaptivedeterminationofthelinearsegmentsandn

5、on鄄linearsegments,theleastsquaresmethodisusedtofittingastraightlineequationinlinearsegments,thenRBFneuralnetworkisusedtocompensatetheimpactoftemperatureinnon鄄linearsegments.SimulationresultsshowthatcomparedwithBPneuralnetworkandleastsquarespoly,themethodiseasil

6、yimplement,thespeedoffittingtrainingisfaster,andmakesthetemperaturescompensationforhighaccuracy.Thetemperaturecompensationofthehumiditysensorcanbeeffectivelyusedtoimprovesensormeasurementaccuracyandreliability.Keywords:humiditysensor;fusionalgorithm;RBFneuralne

7、twork;leastsquares;temperaturecompensationEEACC:7230;7320R摇摇摇摇doi:10.3969/j.issn.1004-1699.2012.12.018*一种湿度传感器温度补偿的融合算法1,2*1,21,31,24行鸿彦,彭基伟,吕文华,徐摇伟,武向娟(1.南京信息工程大学江苏省气象探测与信息处理重点实验室,南京210044;2.南京信息工程大学电子与信息工程学院,南京210044;3.中国气象局气象探测中心,北京100081;4.宁夏大气探测技术保障中心,银川75

8、0002)摘摇要:针对自动气象站上湿度传感器在实际应用过程中易受温度影响的问题,提出采用RBF神经网络与最小二乘相结合的融合算法实现湿度传感器的温度补偿。该方法将湿度传感器在温度影响下的特性曲线分为两个非线性段和一个线性段,并且自适应的确定线性段和非线性段,在线性段利用最小二乘方法拟合出直线方程,在非线性段利用RBF神经网络补偿温度产生的影响。