High dimension feature extraction based visualized SOM fault diagnosis method and its application in p-xylene oxidation process

doi:10.1016/j.cjche.2015.03.007

›› 2015, Vol. 23 ›› Issue (9): 1509-1517.DOI: 10.1016/j.cjche.2015.03.007

• Process Systems Engineering and Process Safety • Previous Articles Next Articles

High dimension feature extraction based visualized SOM fault diagnosis method and its application in p-xylene oxidation process

Ying Tian, Wenli Du, Feng Qian

Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China

Received:2014-09-07 Revised:2015-01-26 Online:2015-10-24 Published:2015-09-28
Supported by:
Supported by the Major State Basic Research Development Program of China (2012CB720500), the National Natural Science Foundation of China (61333010 21276078), the National Science Fund for Outstanding Young Scholars (61222303), the Fundamental Research Funds for the Central Universities, Shanghai Rising-Star Program (13QH1401200), the Program for New Century Excellent Talents in University (NCET- 10-0885) and Shanghai R&D Platform Construction Program (13DZ2295300).

High dimension feature extraction based visualized SOM fault diagnosis method and its application in p-xylene oxidation process

Ying Tian, Wenli Du, Feng Qian

Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China

通讯作者: Wenli Du
基金资助:
Supported by the Major State Basic Research Development Program of China (2012CB720500), the National Natural Science Foundation of China (61333010 21276078), the National Science Fund for Outstanding Young Scholars (61222303), the Fundamental Research Funds for the Central Universities, Shanghai Rising-Star Program (13QH1401200), the Program for New Century Excellent Talents in University (NCET- 10-0885) and Shanghai R&D Platform Construction Program (13DZ2295300).

Abstract

Abstract: Purified terephthalic acid (PTA) is an important chemical raw material. P-xylene (PX) is transformed to terephthalic acid (TA) through oxidation process and TA is refined to produce PTA. The PX oxidation reaction is a complex process involving three-phase reaction of gas, liquid and solid. To monitor the process and to improve the product quality, as well as to visualize the fault type clearly, a fault diagnosis method based on selforganizing map (SOM) and high dimensional feature extraction method, local tangent space alignment (LTSA), is proposed. In this method, LTSA can reduce the dimension and keep the topology information simultaneously, and SOMdistinguishes various states on the outputmap.Monitoring results of PX oxidation reaction process indicate that the LTSA-SOM can well detect and visualize the fault type.

Key words: Self-organizing map, Local tangent space alignment, Fault diagnosis, Visualization, P-xylene oxidation

摘要： Purified terephthalic acid (PTA) is an important chemical raw material. P-xylene (PX) is transformed to terephthalic acid (TA) through oxidation process and TA is refined to produce PTA. The PX oxidation reaction is a complex process involving three-phase reaction of gas, liquid and solid. To monitor the process and to improve the product quality, as well as to visualize the fault type clearly, a fault diagnosis method based on selforganizing map (SOM) and high dimensional feature extraction method, local tangent space alignment (LTSA), is proposed. In this method, LTSA can reduce the dimension and keep the topology information simultaneously, and SOMdistinguishes various states on the outputmap.Monitoring results of PX oxidation reaction process indicate that the LTSA-SOM can well detect and visualize the fault type.

关键词: Self-organizing map, Local tangent space alignment, Fault diagnosis, Visualization, P-xylene oxidation

Ying Tian, Wenli Du, Feng Qian. High dimension feature extraction based visualized SOM fault diagnosis method and its application in p-xylene oxidation process[J]. , 2015, 23(9): 1509-1517.

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High dimension feature extraction based visualized SOM fault diagnosis method and its application in p-xylene oxidation process

High dimension feature extraction based visualized SOM fault diagnosis method and its application in p-xylene oxidation process

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