Leakage Classification Based on Improved Kullback-Leibler Separation in Water Pipelines

  • Thi Ngoc Tu Luong
  • Jong-Myon KimEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11814)


One of the least difficult, quickest, and most useful strategies for the characteristic selection of real applications such as leak detection systems is the selection method based on Kullback-Leibler divergence. Nevertheless, this technique has issues when the preparation dataset is not sufficiently expansive. This paper proposes an improvement on this method to overcome its limitations. The assessment results show that the proposed strategy is steadier, more dependable, and has higher precision than the original technique.


Acoustic emissions Leakage classification Kullback-Leibler divergence 



This work was supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry & Energy (MOTIE) of the Republic of Korea (No. 20172510102130, No. 20192510102510).


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computer EngineeringUniversity of UlsanUlsanKorea

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