NN-based algorithm for control valve stiction quantification
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...
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| Main Authors: | , , |
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| Format: | Citation Index Journal |
| Published: |
2009
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| Subjects: | |
| Online Access: | http://eprints.utp.edu.my/606/1/paper.pdf http://www.scopus.com/inward/record.url?eid=2-s2.0-67650909290&partnerID=40&md5=37a1b54d2c4a1bdb0abbe7c0ca68d7f1 http://eprints.utp.edu.my/606/ |
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| Summary: | 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.
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