摘要
研究发现,随着酸碱浓度及温度变化范围的增大,其电导率与PH值和温度之间呈严重非线性函数关系。本文应用 PBP 神经网络和 GA-BP 学习算法。对不同浓度区的非线性测量方程进行神经统计建模,实现了大范围的非接触式 PH 值在线检测仪的研制。
Based on experimental studies the electricity transfer rate nonlinearly depends on both the PH value and the temperature of the measured liquid, and the nonlinearity characteristics increases as the scopes of the variable increase. In the work we model effectively the Nonlinear Measure Equations (NMEs) by using PBP neural network and a so called GA-BP training algorithm with off-line learning the measured teacher signals (samples) in three various operating scales. This implements the development of touch-free PH value measurement instrument for a large scope of measuring and without temperature compensation.
出处
《测试技术学报》
1998年第3期350-355,共6页
Journal of Test and Measurement Technology
关键词
PBP神经网络
GA-BP学习算法
PH值检测仪
PBP neural network
GA-BP learning algorithm: touch-free PH value measurement instrument
intelligent instrumentation.
