Full-Text Search:
Home|About CNKI|User Service|中文
Add to Favorite Get Latest Update

A Fusion Algorithm for Humidity Sensor Temperature Compensation

XING Hongyan1,2*,PENG Jiwei1,2,Lü Wenhua1,3,XU Wei1,2,WU Xiangjuan4(1.Jiangsu Key Laboratory of Meteorological Observation and Information Processing, Nanjing University of Information Science and Technology,Nanjing 210044,China; 2.School of electronic and information engineering,Nanjing University of Information Science and Technology,Nanjing 210044,China; 3.Atmospheric Observation Technology Center,China Meteorological Administration,Beijing 100081,China; 4.Ningxia Meteorological Observation Technology Support Center,Yingchuan 750002,China)  
According to the humidity sensors on the automatic weather station influenced easily by temperature in the actual application,RBF neural network and least squares combining fusion algorithm is proposed to realize compensation of the humidity sensor.The characteristic curve that the humidity sensor is under the influence of the temperature is divided into two parts,i.e.a non-linear part and a linear part,and in the adaptive determination of the linear segments and non-linear segments,the least squares method is used to fitting a straight line equation in linear segments,then RBF neural network is used to compensate the impact of temperature in non-linear segments.Simulation results show that compared with BP neural network and least squares poly,the method is easily implement,the speed of fitting training is faster,and makes the temperatures compensation for high accuracy.The temperature compensation of the humidity sensor can be effectively used to improve sensor measurement accuracy and reliability.
Download(CAJ format) Download(PDF format)
CAJViewer7.0 supports all the CNKI file formats; AdobeReader only supports the PDF format.
©CNKI All Rights Reserved