Application of data fusion based on RBF neural networks in waste gas data processing

PANG Min; ZHU Wei-xing

doi:10.13873/j.1000-97872007.04.022

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Application of data fusion based on RBF neural networks in waste gas data processing

更新时间：2025-09-11

- Application of data fusion based on RBF neural networks in waste gas data processing
- Issue 4, Pages: 87-89(2007)
- 作者机构：
  
  1. 江苏大学电气信息工程学院
  2. 江苏大学电气信息工程学院,江苏,镇江,212013
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-97872007.04.022
  CLC： TP274.2;X701
- Published：2007
- 稿件说明：
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[1]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(04):87-89.

PANG Min, ZHU Wei-xing. Application of data fusion based on RBF neural networks in waste gas data processing[J]. 2007, (4): 87-89.
[1]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(04):87-89. DOI： 10.13873/j.1000-97872007.04.022.

PANG Min, ZHU Wei-xing. Application of data fusion based on RBF neural networks in waste gas data processing[J]. 2007, (4): 87-89. DOI： 10.13873/j.1000-97872007.04.022.

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。

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.

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references

基于RBF神经网络和遗传算法的建模与优化研究 [J]. 于文莉,陈亚军,李海. 玉溪师范学院学报 . 2005(03)

基于RBF网络的信息融合在机器人足球中的应用 [J]. 杨涛,黄心汉,彭刚,伍翼,高健. 计算机工程与设计 . 2005(03)

多传感器数据融合方法的研究与进展 [J]. 郭戈,罗志刚. 机电一体化 . 2003(05)

基于径向基函数神经网络法识别变压器油中微量特征气体 [J]. 常炳国,吴浩扬,刘君华,周晓华. 西安交通大学学报 . 1999(12)

改进的多目标多传感器数据融合相关算法 [J]. 尹晓东,刘后铭. 地质科技管理 . 1994(03)

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