전기학회논문지 (The Transactions of The Korean Institute of Electrical Engineers)

  • 제66권10호
  • /
  • Pages.1445-1453
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  • 2017
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  • 1975-8359(pISSN)
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  • 2287-4364(eISSN)
대한전기학회 (The Korean Institute of Electrical Engineers)
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데이터마이닝 기법을 이용한 신경망 기반의 화력발전소 보일러 튜브 누설 고장 진단에 관한 연구

A Study on Fault Diagnosis of Boiler Tube Leakage based on Neural Network using Data Mining Technique in the Thermal Power Plant

  • Kim, Kyu-Han (Dept. of Electrical and Computer Engineering, Pusan National University) ;
  • Lee, Heung-Seok (Dept. of Electrical and Computer Engineering, Pusan National University) ;
  • Jeong, Hee-Myung (Dept. of Electrical and Computer Engineering, Pusan National University) ;
  • Kim, Hyung-Su (Dept. of Electricity, Gyeongnam Nambae University) ;
  • Park, June-Ho (Dept. of Electrical and Computer Engineering, Pusan National University)
  • 투고 : 2017.05.11
  • 심사 : 2017.08.18
  • 발행 : 2017.10.01
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초록

In this paper, we propose a fault detection model based on multi-layer neural network using data mining technique for faults due to boiler tube leakage in a thermal power plant. Major measurement data related to faults are analyzed using statistical methods. Based on the analysis results, the number of input data of the proposed fault detection model is simplified. Then, each input data is clustering with normal data and fault data by applying K-Means algorithm, which is one of the data mining techniques. fault data were trained by the neural network and tested fault detection for boiler tube leakage fault.

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참고문헌

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