Acoustic Vibration Approach for Detecting Faults in Hydroelectric Units: A Review
Fang Dao,
Yun Zeng,
Yidong Zou,
Xiang Li and
Jing Qian
Additional contact information
Fang Dao: Faculty of Metallurgy and Energy Engineering, Kunming University of Science and Technology, Kunming 650031, China
Yun Zeng: Faculty of Metallurgy and Energy Engineering, Kunming University of Science and Technology, Kunming 650031, China
Yidong Zou: Faculty of Metallurgy and Energy Engineering, Kunming University of Science and Technology, Kunming 650031, China
Xiang Li: Faculty of Metallurgy and Energy Engineering, Kunming University of Science and Technology, Kunming 650031, China
Jing Qian: Faculty of Metallurgy and Energy Engineering, Kunming University of Science and Technology, Kunming 650031, China
Energies, 2021, vol. 14, issue 23, 1-16
Abstract:
The health of the hydroelectric generator determines the safe, stable, and reliable operation of the hydropower station. In order to keep the hydroelectric generator in a better state of health and avoid accidents, it is crucial to detect its faults. In recent years, fault detection methods based on sound and vibration signals have gradually become research hotspots due to their high sensitivity, achievable continuous dynamic monitoring, and easy adaptation to complex environments. Therefore, this paper is a supplement to the existing state monitoring and fault diagnosis system of the hydroelectric generator; it divides the hydroelectric generator into two significant parts: hydro-generator and hydro-turbine, and summarizes the research and application of fault detect technology based on sound signal vibration in hydroelectric generator and introduces some new technology developments in recent years, and puts forward the existing problems in the current research and future development directions, and it is expected to provides some reference for the research on fault diagnosis of the hydroelectric generator.
Keywords: hydroelectric generator; acoustic vibration signal; fault detection; crack; de-noising (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
https://www.mdpi.com/1996-1073/14/23/7840/pdf (application/pdf)
https://www.mdpi.com/1996-1073/14/23/7840/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:14:y:2021:i:23:p:7840-:d:685536
Access Statistics for this article
Energies is currently edited by Ms. Agatha Cao
More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().