Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Magnus Fast"'
Publikováno v:
Applied Energy. 88:3898-3904
Modern power plants are all strongly dependent on reliable and accurate sensor readings for monitoring and control, thus making sensors an important part of any plant. Failing sensors can force a plant or component into non-optimal operation, cause c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::679a96fe46219fde701bbb8a5904259a
https://doi.org/10.1016/j.apenergy.2011.03.047
https://doi.org/10.1016/j.apenergy.2011.03.047
Autor:
Thomas Palme, Magnus Fast
Publikováno v:
Energy. 35:1114-1120
The objective of this study has been to create an online system for condition monitoring and diagnosis of a combined heat and power plant in Sweden. The system in question consisted of artificial neural network models, representing each main componen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f1d7f3f8239fb80fa1579f7440a190cf
https://doi.org/10.1016/j.energy.2009.06.005
https://doi.org/10.1016/j.energy.2009.06.005
Publikováno v:
Neural Computing and Applications. 19:725-740
Accurate modeling of thermal power plant is very useful as well as difficult. Conventional simulation programs based on heat and mass balances represent plant processes with mathematical equations. These are good for understanding the processes but u
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e94244f69321696f47fa910628fbe7bb
https://doi.org/10.1007/s00521-009-0331-6
https://doi.org/10.1007/s00521-009-0331-6
Publikováno v:
Energy. 34:144-152
Development of artificial neural network (ANN) models using real plant data for the prediction of fresh steam properties from a brown coal-fired boiler of a Slovenian power plant is reported. Input parameters for this prediction were selected from a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eb18d2af8eebe5fdeb0d257b1a4ece65
https://doi.org/10.1016/j.energy.2008.10.010
https://doi.org/10.1016/j.energy.2008.10.010
Publikováno v:
Applied Energy. 86:9-17
Demonstration of different utilities for industrial use of an artificial neural network (ANN) model for a gas turbine has been reported in this paper. The ANN model was constructed with the multi-layer feed-forward network type and trained with opera
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f045441908d2bb937557a63e6aa52072
https://doi.org/10.1016/j.apenergy.2008.03.018
https://doi.org/10.1016/j.apenergy.2008.03.018
Publikováno v:
Energy. 32:2099-2109
The development of a model for any energy system is required for proper design, operation or its monitoring. Models based on accurate mathematical expressions for physical processes are mostly useful to understand the actual operation of the plant. H
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f0e78a30f6142ad2b7231fbd9f4cd300
https://doi.org/10.1016/j.energy.2007.04.008
https://doi.org/10.1016/j.energy.2007.04.008
Publikováno v:
Volume 1: Aircraft Engine; Ceramics; Coal, Biomass and Alternative Fuels; Controls, Diagnostics and Instrumentation; Education; Electric Power; Awards and Honors.
Investigation of a novel condition monitoring approach, combining artificial neural network (ANN) with a sequential analysis technique, has been reported in this paper. For this purpose operational data from a Siemens SGT600 gas turbine has been empl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8119876cc135768d0dd4f65ab69699d7
https://doi.org/10.1115/gt2009-59402
https://doi.org/10.1115/gt2009-59402
Publikováno v:
Volume 1: Aircraft Engine; Ceramics; Coal, Biomass and Alternative Fuels; Controls, Diagnostics and Instrumentation; Education; Electric Power; Awards and Honors.
This paper presents three different gas turbine condition monitoring models developed by artificial neural networks. Operational data from an ALSTOM GT11-N1 has been employed for training and evaluation of the artificial neural network models. The de
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6c3d7cd47a0cfaeddb4d09230d4a68f4
https://doi.org/10.1115/gt2009-59364
https://doi.org/10.1115/gt2009-59364
Publikováno v:
Volume 2: Controls, Diagnostics and Instrumentation; Cycle Innovations; Electric Power.
Gas turbine maintenance is crucial due to high cost for the replacement of its components and associated loss of power during shutdown period. Conventional scheduled maintenance, based on equivalent operating hours, is not the best alternative as it
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3c9acc3a7a8e5c99ed318351cf22dc32
https://doi.org/10.1115/gt2008-50768
https://doi.org/10.1115/gt2008-50768