DocumentCode
532168
Title
Notice of Retraction
Possibilistic C-means improved support vector data description-based fault diagnosis for fiber board gluing system
Author
Yizhuo Zhang ; Huiling Yu
Author_Institution
Northeast Forestry Univ., Harbin, China
Volume
4
fYear
2010
fDate
22-24 Oct. 2010
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.
Fault signal is always a problem that interferes with the operation of fiber board gluing control system. This paper proposes a Possibilistic C-Means (PCM) improved support vector data description (SVDD) method to construct a multi-classifier for the fault diagnosis of fiber gluing control system. In the proposed method, SVDD is employed to construct a multi-classifier for the fault diagnosis in the gluing system. Because the original SVDD is sensitive to the noises and outliers, we use PCM to improve the accuracy of classifier and then conduct a series of experiments. The results of the experiments show that the method proposed can identify the actual situation accurately and provide a high identification rate up to 97%, which is better than original SVDD.
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.
Fault signal is always a problem that interferes with the operation of fiber board gluing control system. This paper proposes a Possibilistic C-Means (PCM) improved support vector data description (SVDD) method to construct a multi-classifier for the fault diagnosis of fiber gluing control system. In the proposed method, SVDD is employed to construct a multi-classifier for the fault diagnosis in the gluing system. Because the original SVDD is sensitive to the noises and outliers, we use PCM to improve the accuracy of classifier and then conduct a series of experiments. The results of the experiments show that the method proposed can identify the actual situation accurately and provide a high identification rate up to 97%, which is better than original SVDD.
Keywords
control engineering computing; fault diagnosis; joining processes; pattern classification; possibility theory; production engineering computing; support vector machines; fault diagnosis; fiber board gluing control system; multiclassifier; possibilistic c-means; support vector data description; Accuracy; Phase change materials; Welding; fault diagnosis; fiber board; gluing system; possibilistic c-means; support vector data description;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location
Taiyuan
Print_ISBN
978-1-4244-7235-2
Type
conf
DOI
10.1109/ICCASM.2010.5620078
Filename
5620078
Link To Document