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

Volume

49

Issue

4

fYear

2000

fDate

8/1/2000 12:00:00 AM

Firstpage

852

Lastpage

856

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;

fLanguage

English

Journal_Title

Instrumentation and Measurement, IEEE Transactions on

Publisher

ieee

ISSN

0018-9456

Type

jour

DOI

10.1109/19.863937

Filename

863937