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Shock and Vibration
Volume 2016 (2016), Article ID 5971081, 14 pages
http://dx.doi.org/10.1155/2016/5971081
Research Article

Stator Vibration Characteristic Identification of Turbogenerator among Single and Composite Faults Composed of Static Air-Gap Eccentricity and Rotor Interturn Short Circuit

1Department of Mechanical Engineering, North China Electric Power University, Baoding 071003, China
2State Grid Hebei Electric Power Research Institute, Shijiazhuang 050021, China

Received 8 May 2016; Accepted 14 August 2016

Academic Editor: Lu Chen

Copyright © 2016 Yu-Ling He et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper investigates the radial stator vibration characteristics of turbogenerator under the static air-gap eccentricity (SAGE) fault, the rotor interturn short circuit (RISC) fault, and the composite faults (CFs) composed of SAGE and RISC, respectively. Firstly, the impact of the faulty types on the magnetic flux density (MFD) is analyzed, based on which the detailed expressions of the magnetic pull per unit area (MPPUA) on the stator under different performing conditions are deduced. Then, numerical FEM simulations based on Ansoft and an experimental study are carried out, taking the SDF-9 type fault simulating generator as the study object. It is shown that SAGE will increase the stator vibration at 2f (f is the electrical frequency) which already exists even in normal condition, while RISC and CF will bring in stator vibrations at f, 2f, 3f, and 4f at the same time. The vibration amplitudes under CF are larger than those under RISC. As SAGE increases, the vibration amplitudes of each harmonic component under CF will all be increased, while the development of RISC will decrease the 2nd harmonic vibration but meanwhile increase the 4th harmonic vibration. The achievements of this paper are beneficial for fault identification and condition monitoring of the turbogenerator.