Title :
A constrained iterative deconvolution technique with an optimal filtering: application to a hydrocarbon concentration sensor
Author :
Neveux, Philippe ; Sekko, E. ; Thomas, Gérard
Author_Institution :
CNRS, Univ. Claude Bernard, Villeurbanne, France
fDate :
8/1/2000 12:00:00 AM
Abstract :
A deconvolution method for estimating unburned hydrocarbon concentration in boiler smokes is presented. In order to qualify a boiler regarding to the ecological European Standards an iterative constrained estimation algorithm including a filtering step has been set up. The application of such technique to both synthetic signals and experimental data has shown its robustness in regard to measurement noise and its reliability to restore a signal
Keywords :
air pollution control; deconvolution; ecology; gas sensors; inverse problems; optimal control; organic compounds; parameter estimation; smoke; standards; boiler smokes; constrained iterative deconvolution; ecological European Standards; hydrocarbon concentration sensor; iterative constrained estimation algorithm; measurement noise; optimal filtering; reliability; robustness; signal restoration; synthetic signal; unburned hydrocarbon concentration; Deconvolution; Distortion measurement; Filtering algorithms; Hydrocarbons; Iterative algorithms; Iterative methods; Noise measurement; Pollution measurement; Signal processing algorithms; Signal restoration;
Journal_Title :
Instrumentation and Measurement, IEEE Transactions on
