首页 | 本学科首页   官方微博 | 高级检索  
     

基于RBF网络的数据融合在废气数据处理中的应用
引用本文:庞敏,朱伟兴. 基于RBF网络的数据融合在废气数据处理中的应用[J]. 传感器与微系统, 2007, 26(4): 87-89
作者姓名:庞敏  朱伟兴
作者单位:江苏大学电气信息工程学院,江苏镇江,212013
摘    要:针对禽畜养殖场环境废气体积分数数据的处理,使用多个传感器测量环境温度、湿度、某种废气的体积分数。对于传感器故障而失真的数据,使用基于RBF神经网络的数据融合方法融合对某一废气测量值的多种影响因素,估算出该废气的体积分数,从而实现失真数据的恢复。以NH3体积分数数据的处理为例,Matlab仿真结果估算误差小于6.7%,证明了基于RBF网络的数据融合方法的有效性。

关 键 词:神经网络  数据融合  废气数据处理  径向基函数
文章编号:1000-9787(2007)04-0087-03
收稿时间:2006-09-14
修稿时间:2006-09-14

Application of data fusion based on RBF neural networks in waste gas data processing
PANG Min,ZHU Wei-xing. Application of data fusion based on RBF neural networks in waste gas data processing[J]. Transducer and Microsystem Technology, 2007, 26(4): 87-89
Authors:PANG Min  ZHU Wei-xing
Affiliation:School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China
Abstract:Aiming at the data processing of waste gas volume fraction, multi-sensor is used to measure the environmental temperature,humidity, one waste gas volume fraction. For the data distortion duing to the sensor faults ,the data fusion menthod is used based on RBF neural networks which colligates manifold factors to the measurement of one waste gas,to estimate the volume fractortion of this waste gas, consequently achieving the resumption of the data distortion. Take the data processing of the volume fraction of NH3 for example, the Matiab emulation result shows that the estimate error is less than 6.7 %, the efficiency of data fusion menthod based on RBF is proved.
Keywords:neural network  data fusion  waste gas data processing  radial basis function(RBF)
本文献已被 CNKI 维普 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号