DocumentCode
2684603
Title
Notice of Retraction
Online fault detection of erythromycin fermentation based on dynamic MPCA
Author
Wang Zhifeng
Author_Institution
Sch. of Electron. & Electr. Eng., Shanghai Second Polytech. Univ., Shanghai, China
Volume
3
fYear
2010
fDate
24-26 Aug. 2010
Firstpage
440
Lastpage
443
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.
An online fault detection approach is developed based on the multivariate statistical process control in this paper. It integrates the time-lagged windows of process dynamic behavior with the multi-way principal component analysis(MPCA). Using the previous process variables during the process without expensive computations to anticipate the future measurements, the method emphasizes particularly for on-line process monitoring and exactly faults detecting which results in extraordinary behavior of processes. Like traditional MPCA approaches, the only information needed to set up the control chart is the historical data collected from the past successful fermentation processes. This leads to simple monitoring charts, easy tracking of the progress in each process and monitoring the occurrence of the observable upsets. Erythromycin fermentation process is used to investigate the potential application of the proposed method.
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.
An online fault detection approach is developed based on the multivariate statistical process control in this paper. It integrates the time-lagged windows of process dynamic behavior with the multi-way principal component analysis(MPCA). Using the previous process variables during the process without expensive computations to anticipate the future measurements, the method emphasizes particularly for on-line process monitoring and exactly faults detecting which results in extraordinary behavior of processes. Like traditional MPCA approaches, the only information needed to set up the control chart is the historical data collected from the past successful fermentation processes. This leads to simple monitoring charts, easy tracking of the progress in each process and monitoring the occurrence of the observable upsets. Erythromycin fermentation process is used to investigate the potential application of the proposed method.
Keywords
Internet; chemical engineering; control charts; fault diagnosis; fermentation; microorganisms; principal component analysis; process monitoring; production engineering computing; control chart; dynamic MPCA; erythromycin fermentation; multivariate statistical process control; multiway principal component analysis; online fault detection; time lagged window; Monitoring; Radio access networks; dynamic MPCA; erythromycin fermentation; fault detection; online; statistical process control;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer, Mechatronics, Control and Electronic Engineering (CMCE), 2010 International Conference on
Conference_Location
Changchun
Print_ISBN
978-1-4244-7957-3
Type
conf
DOI
10.1109/CMCE.2010.5610278
Filename
5610278
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