| Title |
A Study on Fault Diagnosis of Boiler Tube Leakage based on Neural Network using Data Mining Technique in the Thermal Power Plant |
| Authors |
김규한(Kim, Kyu-Han) ; 이흥석(Lee, Heung-Seok) ; 정희명(Jeong, Hee-Myung) ; 김형수(Kim, Hyung-Su) ; 박준호(Park, June-Ho) |
| DOI |
https://doi.org/10.5370/KIEE.2017.66.10.1445 |
| Keywords |
Fault detection ; Multi-layer neural network ; K-Means algorithm |
| Abstract |
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. |