Paper Info
Title
Monitoring method of slurry quality in wet flue gas desulfurization system based on fuzzy C-means clustering
Abstract
In this paper, a method of slurry quality monitoring and diagnosis in Wet Flue Gas Desulfurization(WFGD) system was proposed based on feature extraction of slurry quality and Fuzzy C-means(FCM) clustering. Focusing on the WFGD system of a 600 MW unit in a certain power plant, a new index for slurry quality monitoring was put forward. And clustering centers could be obtained to be the standard modes for slurry quality identification by adopting FCM to perform clustering analysis, in which the desulfurization efficiency and pH were regarded as feature information. Slurry quality diagnosis could be realized eventually by calculating the membership between the unknown samples and the standard modes of slurry quality. Furthermore, a fuzzy quantitative monitoring index was presented to quantitatively monitor the slurry quality state during its actual operation according to the theory of fuzzy membership. On the basis of diagnostic analysis of the field operating data, it demonstrates that the method raided in this dissertation can monitor the slurry quality state efficiently, providing foundation for operation adjustment.
Year
DOI
Venue
2016
10.1109/ICSAI.2016.7810949
2016 3rd International Conference on Systems and Informatics (ICSAI)
Keywords
Field
DocType
desulfurized slurry quality,characteristic index,fuzzy C-means,state monitoring
Computer science,Fuzzy logic,Feature extraction,Control engineering,Cluster analysis,Diagnostic analysis,Flue-gas desulfurization,Slurry,Power station
Conference
ISBN
Citations 
PageRank 
978-1-5090-5522-7
0
0.34
References 
Authors
3
6
Name
Order
Citations
PageRank
Zongliang Qiao100.68
Fengqi Si233.45
Jianxin Zhou300.34
lei zhang4403143.70
Xuezhong Yao500.34
Wenyun Bao600.34