WANG Chuan, YIN Wen-qing, YANG Zhi-jun, et al. Temperature compensation of thermal gas flowmeter based on RBF neural networks[J]. 2016, 35(12): 99-102.
WANG Chuan, YIN Wen-qing, YANG Zhi-jun, et al. Temperature compensation of thermal gas flowmeter based on RBF neural networks[J]. 2016, 35(12): 99-102. DOI: 10.13873/J.1000-9787(2016)12-0099-04.
RBF神经网络热式气体流量计温度补偿
摘要
为了解决热式气体流量计测量电路中采用硬件温度补偿成本高且精度不够等问题
利用神经网络的特点
设计了一种基于径向基函数(RBF)神经网络的软件温度补偿方法。实验表明:通过RBF神经网络温度补偿
有效地抑制了温度对流量计测量结果的影响
实现了环境温度梯度变化下气体流量测量的准确性和稳定性
测量准确度达到1.0级
且重复性好。
Abstract
In order to solve problem of high cost and low precision of hardware circuit temperature compensation in thermal gas flow-meter measurement circuit
using character of neural network
a software temperature compensation method designed based on radial basis function( RBF) neural networks. Experiments show that after temperature compensation of RBF neural networks
the accuracy reaches 1. 0 level and maintains the accuracy
stability and repeatability at the same time
which effectively restrains the influence caused by gradient change of temperature.
Optimization of hot-wire thermal flow sensor based on a neural net model [J] . Moh’d Sami Ashhab,Ahmed Al-Salaymeh. Applied Thermal Engineering . 2005 (8)