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.
基于RBF网络的数据融合在废气数据处理中的应用
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.