Prediction of Dry-Low Emission Gas Turbine Operating Range from Emission Concentration Using Semi-Supervised Learning.
Dry-Low Emission gas turbine
K-means
emission concentration
extreme gradient boosting
load management
Journal
Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366
Informations de publication
Date de publication:
10 Apr 2023
10 Apr 2023
Historique:
received:
07
03
2023
revised:
27
03
2023
accepted:
03
04
2023
medline:
28
4
2023
pubmed:
28
4
2023
entrez:
28
4
2023
Statut:
epublish
Résumé
Dry-Low Emission (DLE) technology significantly reduces the emissions from the gas turbine process by implementing the principle of lean pre-mixed combustion. The pre-mix ensures low nitrogen oxides (NO
Identifiants
pubmed: 37112203
pii: s23083863
doi: 10.3390/s23083863
pmc: PMC10145957
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Universiti Teknologi Petronas
ID : YUTP (015LC0-382)
Organisme : Ministry of Higher Education
ID : PRGS/1/2020/TK09/UTP/02/2
Références
Sensors (Basel). 2021 Dec 01;21(23):
pubmed: 34884053