DocumentCode
1924600
Title
An On-Line Monitoring Method of the Exhaust Steam Dryness in Steam Turbine
Author
Zhang, Chun-Fa ; Zhao, Ning ; Wang, Hui-Jie ; Chen, Ya-Mi ; Yan, Yi-ran
Author_Institution
North China Electr. Power Univ., Baoding
Volume
1
fYear
2007
fDate
19-22 Aug. 2007
Firstpage
437
Lastpage
442
Abstract
With the development of information and computer technology, it is possible to monitor and analyze on-line features of large steam turbine-generator units. The energy consumption rate and the exhaust steam dryness are two important indices. Base on the analyses of those existed calculation methods for turbine varying condition, we give a sequential varying condition calculation that starts with steam extraction of the final stage or the second final stage (superheated steam condition). According to the initially assumed final stage flow, and the thermodynamic parameters before the final stage, also the backpressure, we can distinguish the flow patterns of the stage by discriminant criteria. Then we can conduct a stage varying condition calculation of primary stage in sequence from the front final stage parameter, so the new exhaust steam enthalpy and the exhaust steam dryness can be got. So the precise energy consumption rate and the exhaust enthalpy (or the dryness) can be got easily. Obviously, without measuring the flow or the dryness, we can accurately monitor the on-line energy consumption rate and the dryness of the units.
Keywords
computerised monitoring; exhaust systems; mechanical engineering computing; steam turbines; exhaust steam dryness; exhaust steam enthalpy; online energy consumption rate; online monitoring method; steam turbine-generator units; Computerized monitoring; Condition monitoring; Cybernetics; Energy consumption; Energy measurement; Fluid flow measurement; Machine learning; Tail; Thermodynamics; Turbines; Discriminant criteria of the flow patterns; On-line Monitoring; Varying condition calculation; the dryness of the exhaust steam;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-0973-0
Electronic_ISBN
978-1-4244-0973-0
Type
conf
DOI
10.1109/ICMLC.2007.4370184
Filename
4370184
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