Algorithm of pipeline leak detection based on discrete incremental clustering method

Authors:
Jian Feng;Huaguang Zhang
Affiliations:
School of Information Science and Engineering, Northeastern University, Shenyang, P.R. China and Key Laboratory of Process Industry Automation, Ministry of Education, Northeastern University, Shen ...;School of Information Science and Engineering, Northeastern University, Shenyang, P.R. China and Key Laboratory of Process Industry Automation, Ministry of Education, Northeastern University, Shen ...
Venue:
ICIC'06 Proceedings of the 2006 international conference on Intelligent computing: Part II
Year:
2006

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Abstract

A novel approach for pipeline leak fault detection has been studied, which applies self-organizing fuzzy clustering neural network to identify work status. The proposed method utilized fuzzy neural clustering of DIC method instead of constructing exact mathematical model. After normalizing the sample data, together with prior knowledge, a fuzzy neural network is used to evaluate work status. An adaptive algorithm is developed to diagnose the leak fault. The experiment results have shown the validity and practicability of the method.