Fault Diagnosis Method of Polymerization Kettle Equipment Based on Rough Sets and BP Neural Network

المؤلفون المشاركون

Gao, Shu-zhi
Zhao, Na
Wang, Jie-sheng

المصدر

Mathematical Problems in Engineering

العدد

المجلد 2013، العدد 2013 (31 ديسمبر/كانون الأول 2013)، ص ص. 1-12، 12ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2013-07-30

دولة النشر

مصر

عدد الصفحات

12

التخصصات الرئيسية

هندسة مدنية

الملخص EN

Polyvinyl chloride (PVC) polymerizing production process is a typical complex controlled object, with complexity features, such as nonlinear, multivariable, strong coupling, and large time-delay.

Aiming at the real-time fault diagnosis and optimized monitoring requirements of the large-scale key polymerization equipment of PVC production process, a real-time fault diagnosis strategy is proposed based on rough sets theory with the improved discernibility matrix and BP neural networks.

The improved discernibility matrix is adopted to reduct the attributes of rough sets in order to decrease the input dimensionality of fault characteristics effectively.

Levenberg-Marquardt BP neural network is trained to diagnose the polymerize faults according to the reducted decision table, which realizes the nonlinear mapping from fault symptom set to polymerize fault set.

Simulation experiments are carried out combining with the industry history datum to show the effectiveness of the proposed rough set neural networks fault diagnosis method.

The proposed strategy greatly increased the accuracy rate and efficiency of the polymerization fault diagnosis system.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Gao, Shu-zhi& Wang, Jie-sheng& Zhao, Na. 2013. Fault Diagnosis Method of Polymerization Kettle Equipment Based on Rough Sets and BP Neural Network. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-12.
https://search.emarefa.net/detail/BIM-1032154

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Gao, Shu-zhi…[et al.]. Fault Diagnosis Method of Polymerization Kettle Equipment Based on Rough Sets and BP Neural Network. Mathematical Problems in Engineering No. 2013 (2013), pp.1-12.
https://search.emarefa.net/detail/BIM-1032154

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Gao, Shu-zhi& Wang, Jie-sheng& Zhao, Na. Fault Diagnosis Method of Polymerization Kettle Equipment Based on Rough Sets and BP Neural Network. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-12.
https://search.emarefa.net/detail/BIM-1032154

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1032154