Detection of Boiler Tube Leakage Fault in a Thermal Power Plant Using Machine Learning Based Data Mining Technique

被引:4
作者
Kim, Kyu Han [1 ]
Lee, Heung Seok [1 ]
Kim, Jung Hwan [1 ]
Park, June Ho [1 ]
机构
[1] Pusan Natl Univ, Dept Elect & Comp Engn, Busan, South Korea
来源
2019 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY (ICIT) | 2019年
关键词
Fault detection; K-Means algorithm; clustering; neural network; thermal power plant;
D O I
10.1109/ICIT.2019.8755058
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Tube leakage of steam boiler can decrease the whole efficiency of thermal power plant, and eventually cause an outage. In this paper, we propose a fault detection method based on machine learning for boiler tube leakage fault in thermal power plant. First, we introduce the clustering-based fault detection method and explain results. Second, we propose neural network based fault detection method. Finally, to verify the performance, the proposed fault detection method is applied to faults cases due to boiler tube leakage and validate effectiveness of detection.
引用
收藏
页码:1006 / 1010
页数:5
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