DocumentCode
560706
Title
Notice of Retraction
Applied research of generalized morphological filter for MOA in processing on-line monitoring data
Author
Zhuo Yang ; Xianping Zhao ; Xiangyu Tan ; Ke Wang
Author_Institution
Yunnan Power Grid Corp., Kunming, China
Volume
2
fYear
2011
fDate
8-9 Sept. 2011
Firstpage
293
Lastpage
296
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Based on the close and open transforms and their combination modes, the generalized morphological filter (GMF) with the best variable weights by constructing the inequality, considering root-mean-square error and signal to noise ratio and avoiding steepest descent method on the adaptive generalized morphological filter when iterative weight is close to the best one because of slow constrictions, is presented by this paper and applied in the on-line monitoring data processing in order to improve the precision of obtaining the real signal of MOA in the stress of complicated electromagnetic environment and ensure the accuracy of further analysis and diagnosis. The results show that the generalized morphological filter with the best variable weights can suppress isolated points, sentus, small bridges, positive and negative pulses, etc. And it is calculated and comes true simply by hardware.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Based on the close and open transforms and their combination modes, the generalized morphological filter (GMF) with the best variable weights by constructing the inequality, considering root-mean-square error and signal to noise ratio and avoiding steepest descent method on the adaptive generalized morphological filter when iterative weight is close to the best one because of slow constrictions, is presented by this paper and applied in the on-line monitoring data processing in order to improve the precision of obtaining the real signal of MOA in the stress of complicated electromagnetic environment and ensure the accuracy of further analysis and diagnosis. The results show that the generalized morphological filter with the best variable weights can suppress isolated points, sentus, small bridges, positive and negative pulses, etc. And it is calculated and comes true simply by hardware.
Keywords
adaptive filters; arresters; gradient methods; mean square error methods; MOA; adaptive generalized morphological filter; combination modes; electromagnetic environment; metal oxide arrester; online monitoring data; root-mean-square error; signal-to-noise ratio; steepest descent method; Filtering algorithms; Filtering theory; Leakage current; Monitoring; Power harmonic filters; Signal to noise ratio; MOA; leakage current; mathematical generalized morphological Filter;
fLanguage
English
Publisher
ieee
Conference_Titel
Power Engineering and Automation Conference (PEAM), 2011 IEEE
Conference_Location
Wuhan
Print_ISBN
978-1-4244-9691-4
Type
conf
DOI
10.1109/PEAM.2011.6134950
Filename
6134950
Link To Document