Author/Authors
L. Lardon، نويسنده , , A. Punal and J.-P. Steyer، نويسنده ,
DocumentNumber
1384614
Title Of Article
On-line diagnosis and uncertainty management using evidence theory––experimental illustration to anaerobic digestion processes
شماره ركورد
11515
Latin Abstract
The on-line diagnosis is a key requirement in biological processes. This is particularly true in the case of wastewater treatment
processes due to the composition of media, the requirements of operating conditions and the wide variety of possible disturbances
that necessitate careful and constant monitoring of the processes. Moreover, because only partial information is available in an online
context and because of the technical and biological complexities of the involved processes, specific characteristics are required
for diagnosis purposes. Several approaches like quantitative model based, qualitative model based and process history based
methods were applied over the years. This paper present a methodological framework based on evidence theory to manage the fault
signals generated by conventional approaches (i.e., residuals from hardware and software redundancies, fuzzy logic based modules
for process state assessment) and to account for uncertainty. The advantages of using evidence theory like modularity, detection of
conflict and doubt in the information sources are illustrated with experimental results from a 1 m3 fixed bed anaerobic digestion
process used for the treatment of industrial distillery wastewater.
From Page
747
NaturalLanguageKeyword
fault detection and isolation , diagnosis , Evidence theory , anaerobic digestion , Biological process
JournalTitle
Studia Iranica
To Page
763
To Page
763
Link To Document