Abstract
The detection of leaks in circulating fluidized bed boiler tubes is an important issue in thermal power plants, because leaks lead to enormous economic and social losses. To address this issue, a time-based maintenance (TBM) method has been employed in power plants, but it cannot detect leakage of a tube during operation. Instead, a condition-based maintenance (CBM) method is required to detect unexpected leakage of a boiler tube in real time. This paper proposes an acoustic emission (AE)-based diagnostic system for detecting leakage of a circulating fluidized bed boiler tube using a data acquisition (DAQ) system and support vector machines (SVMs) for data acquisition, data analysis, and leakage detection. Experimental results show that the proposed diagnosis system perfectly detects leakage of a boiler tube on the simulation testbed.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Lee, S.B., Roh, S.M.: Developing an early leakage detection system for thermal power plant boiler tubes by using acoustic emission technology. J. Korean Soc. Nondestr. Test. 36(3), 181–187 (2016)
Kang, T., Han, S.-W., Lee, J.-H., Yoon, D.-B., Park, J.-H.: Development of CBM (condition-based maintenance) based abnormal condition diagnosis of centrifugal pump. In: Conference of the Korean Society for Noise and Vibration Engineering, pp. 318–320 (2016)
Kim, D.-H., Lee, S.-B., Kim, Y.-H., Won, J.-H., Son, Y.-C., Cha, Y.-J.: Pulverizer condition monitoring system using acoustic emission technique in thermal power plant. J. Korean Soc. Nondestr. Test. 37(6), 435–442 (2017)
Kim, Y.-H., Jeong, I.-K., Kim, J.-M.: Development of embedded based real time wireless data acquisition system for diagnosis of industrial equipment faults. J. Korean Soc. Eng. Art Sci. 15(1), 115–116 (2017)
Park, S., Kim, K.-J., Lee, J.-S., Lee, S.-R.: Red tide prediction using neural network and SVM. J. Inst. Electron. Eng. Korea 48(5), 39–45 (2011)
Acknowledgment
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).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Kim, YH., Jeong, IK., Kim, JY., Ban, JK., Kim, JM. (2020). Development of an Intelligent Diagnosis System for Detecting Leakage of Circulating Fluidized Bed Boiler Tubes. In: Madureira, A., Abraham, A., Gandhi, N., Varela, M. (eds) Hybrid Intelligent Systems. HIS 2018. Advances in Intelligent Systems and Computing, vol 923. Springer, Cham. https://doi.org/10.1007/978-3-030-14347-3_30
Download citation
DOI: https://doi.org/10.1007/978-3-030-14347-3_30
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-14346-6
Online ISBN: 978-3-030-14347-3
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)