A novel method for fault diagnosis of hydro generator based on NOFRFs. (October 2015)
- Record Type:
- Journal Article
- Title:
- A novel method for fault diagnosis of hydro generator based on NOFRFs. (October 2015)
- Main Title:
- A novel method for fault diagnosis of hydro generator based on NOFRFs
- Authors:
- Xia, Xin
Zhou, Jianzhong
Li, Chaoshun
Zhu, Wenlong - Abstract:
- Highlights: Modeling the hydro generator with non-linear output frequency response functions. A novel online identification method is proposed for NOFRFs of hydro generator. The nonlinear behavior of different states of hydro generator is analyzed. Some failure mechanism of hydro generator is classified. Abstract: Fault diagnosis and recognition of hydro generator are important issues which encounter in repair and security posture assessment. It influences the operational planning and security directly. Volterra series as an effective modeling method has been widely used in modeling and fault diagnosis of hydro generator, but the larger number of kernels limits its application in faults diagnosis. Non-linear output frequency response functions (NOFRFs) as a transformation style of Volterra series have a more intuitive visual and simple structure. In this paper, NOFRFs have been proposed to be employed in fault diagnosis of hydro generator, and a novel online identification method is proposed at the same time. Firstly, NOFRFs models of hydro generators are built. Secondly, a new method for online identification is proposed according to the operational characteristics of hydro generators. Finally, simulation verification has been done to demonstrate the advantage of the proposed method, and experimental studies are put forward on a hydro generator to analyze the failure mechanism in different states. The results indicate that the proposed method is useful and concise for faultHighlights: Modeling the hydro generator with non-linear output frequency response functions. A novel online identification method is proposed for NOFRFs of hydro generator. The nonlinear behavior of different states of hydro generator is analyzed. Some failure mechanism of hydro generator is classified. Abstract: Fault diagnosis and recognition of hydro generator are important issues which encounter in repair and security posture assessment. It influences the operational planning and security directly. Volterra series as an effective modeling method has been widely used in modeling and fault diagnosis of hydro generator, but the larger number of kernels limits its application in faults diagnosis. Non-linear output frequency response functions (NOFRFs) as a transformation style of Volterra series have a more intuitive visual and simple structure. In this paper, NOFRFs have been proposed to be employed in fault diagnosis of hydro generator, and a novel online identification method is proposed at the same time. Firstly, NOFRFs models of hydro generators are built. Secondly, a new method for online identification is proposed according to the operational characteristics of hydro generators. Finally, simulation verification has been done to demonstrate the advantage of the proposed method, and experimental studies are put forward on a hydro generator to analyze the failure mechanism in different states. The results indicate that the proposed method is useful and concise for fault diagnosis and nonlinear analysis of hydro generators. … (more)
- Is Part Of:
- International journal of electrical power & energy systems. Volume 71(2015:Oct.)
- Journal:
- International journal of electrical power & energy systems
- Issue:
- Volume 71(2015:Oct.)
- Issue Display:
- Volume 71 (2015)
- Year:
- 2015
- Volume:
- 71
- Issue Sort Value:
- 2015-0071-0000-0000
- Page Start:
- 60
- Page End:
- 67
- Publication Date:
- 2015-10
- Subjects:
- Hydro generator -- Fault diagnosis -- NOFRFs -- Volterra series -- Identification
Electrical engineering -- Periodicals
Electric power systems -- Periodicals
Électrotechnique -- Périodiques
Réseaux électriques (Énergie) -- Périodiques
Electric power systems
Electrical engineering
Periodicals
621.3 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01420615 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.ijepes.2015.02.022 ↗
- Languages:
- English
- ISSNs:
- 0142-0615
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.220000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 7388.xml