Study on the determination method of the normal value of relative internal efficiency of the last stage group of steam turbine
Li-hua Cao,
Jing-wen Yu and
Yong Li
Energy, 2016, vol. 98, issue C, 101-107
Abstract:
The characteristics of the last stage group of condensing steam turbine are analyzed, and a method based on the synthetic BP (back-propagation) neural network is proposed for determining the normal value of relative internal efficiency of the last stage group. In order to consider the influence of the regenerative system, the influential factors of the relative internal efficiency of the last stage group firstly are determined, and the corresponding mathematical model is set up, and finally using the BP neural network to fit the equation. In this paper, the relative internal efficiency could be calculated by the method of BP instead of finding the exhaust enthalpy in the wet region first. The results show that the average relative errors between the network output values and the calculated values of off-design condition are less than 1%, which verify the accuracy, feasibility and validity of this method.
Keywords: Steam turbine; Fault diagnosis; Synthetic neural network; Relative internal efficiency; Last stage group (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544216000256
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:98:y:2016:i:c:p:101-107
DOI: 10.1016/j.energy.2016.01.015
Access Statistics for this article
Energy is currently edited by Henrik Lund and Mark J. Kaiser
More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().