Leakage Detection of a Boiler Tube Using a Genetic Algorithm-like Method and Support Vector Machines

  • Young-Hun Kim
  • Jaeyoung Kim
  • Jong-Myon KimEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 942)


In this paper, we propose a method to detect boiler tube leakage using a genetic algorithm (GA)-like method and support vector machines (SVM). The GA-like method allows for selection of significant features, and the SVM detects a leak in boiler tubes using the selected features. Experimental results indicate that the proposed method outperforms a state-of-the-art principle component analysis (PCA) method in leakage detection.


Boiler tube Genetic algorithm Support vector machine Tube leakage detection 



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. 20161120100350, No. 20181510102160, No. 20162220100050).


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Electrical and Computer EngineeringUniversity of UlsanUlsanSouth Korea
  2. 2.School of IT ConvergenceUniversity of UlsanUlsanSouth Korea

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