The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL
Transactions ID Number: 28-918
Full Name: Haslinda Zabiri
Position: Lecturer
Age: ON
Sex: Female
Address: Chemical Eng. Dept., Universiti Teknologi PETRONAS, Bandar Sri Iskandar, 31750 Tronoh Perak
Country: MALAYSIA
Tel: +605-3687625
Tel prefix: 00
Fax: +605-3656176
E-mail address: haslindazabiri@petronas.com.my
Other E-mails: zhaslinda@yahoo.com
Title of the Paper: NN-based Algorithm for Control Valve Stiction Quantification
Authors as they appear in the Paper: H. Zabiri, A. Maulud, N. Omar
Email addresses of all the authors:
Number of paper pages: 10
Abstract: Control valve stiction is the most commonly found valve problem in the process industry. Quantification of the actual amount of stiction present in a loop is an important step that may help in scheduling the optimum maintenance work for the valves. In this paper, a Neural-network based stiction quantification algorithm is developed. It is shown that the performance of the proposed quantification algorithm is comparable to other method whereby accurate estimation of the stiction amount can be achieved even in the presence of random noise. Its robustness towards external oscillating disturbances is also investigated
Keywords: Control valve, stiction, neural network, quantification
EXTENSION of the file: .doc
Special (Invited) Session: Development of Quantification Algorithm for Control Valve Stiction
Organizer of the Session: 609-099
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IP ADDRESS: 202.185.20.111
