Title :
Artificial Neural Network Analysis of Microwave Spectrometry on Pulp Stock: Determination of Consistency and Conductivity
Author :
Green, Eric C. ; Jean, Buford Randall ; Marks, R.J., II
Author_Institution :
Sch. of Law, Texas Univ., Austin, TX
Abstract :
A method for calibrating a microwave sensor is described. The method utilizes an artificial neural network trained to infer the consistency and conductivity of pulp stock slurry from the measured output spectrum of a microwave instrument. The method is both efficient and robust for extracting the multiple parameter information from the microwave signal output
Keywords :
microwave detectors; microwave spectrometers; neural nets; paper pulp; slurries; artificial neural network analysis; microwave instrument; microwave sensor; microwave signal output; microwave spectrometry; pulp stock slurry; Artificial neural networks; Conductivity measurement; Data mining; Instruments; Microwave measurements; Microwave sensors; Microwave theory and techniques; Robustness; Slurries; Spectroscopy; Microwave sensor; microwave spectrometry; neural network; pulp stock;
Journal_Title :
Instrumentation and Measurement, IEEE Transactions on
DOI :
10.1109/TIM.2006.884284
