Paper Info
Title
The Enhancement of Leak Detection Performance for Water Pipelines through the Renovation of Training Data.
Abstract
Leakage detection is a fundamental problem in water management. Its importance is expressed not only in avoiding resource wastage, but also in protecting the environment and the safety of water resources. Therefore, early leak detection is increasingly urged. This paper used an intelligent leak detection method based on a model using statistical parameters extracted from acoustic emission (AE) signals. Since leak signals depend on many operation conditions, the training data in real-life situations usually has a small size. To solve the problem of a small sample size, a data improving method based on enhancing the generalization ability of the data was proposed. To evaluate the effectiveness of the proposed method, this study used the datasets obtained from two artificial leak cases which were generated by pinholes with diameters of 0.3 mm and 0.2 mm. Experimental results show that the employment of the additional data improving block in the leak detection scheme enhances the quality of leak detection in both terms of accuracy and stability.
Year
DOI
Venue
2020
10.3390/s20092542
SENSORS
Keywords
DocType
Volume
intelligent leak detection,acoustic emission signals,statistical parameters,support vector machine,wavelet denoising,Shannon entropy
Journal
20
Issue
ISSN
Citations 
9.0
1424-8220
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Tu T N Luong100.34
Jong Myon Kim214432.36