Abstract

This paper proposes a new approach to leak localization in industrial-fluid pipelines. Although the leak localization problem has been the subject of numerous scientific and engineering research projects and publications, further improvements would be useful in specific applications, for example, leak localization in metal pipelines which are elements of a huge pipeline network operating in manufacturing industry. The proposed methodology, which is designed to improve accuracy of leak location in steel pipelines, exploits a burst phenomenon in acoustic emission (AE) signals and combines signal processing with a physical wave-propagation model. The algorithm seeks AE bursts based on a detection theorem and then combines neighboring bursts into unique burst groups. Filtered AE events which are pairs of bursts from two signal channels allows information extraction of fault location. The combination of grouping and filtering elucidates event concentration and reduces error. The resulting localization method has a mean error of approximately 2.5% of the distance between the two sensors, while conventional approaches suffer from serious errors greater than 10% on average.

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