메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색
질문

논문 기본 정보

자료유형
학술저널
저자정보
Gui-Ji Tang (North China Electric Power University) Meng-Qiang Ke (North China Electric Power University) Yu-Ling He (North China Electric Power University) Fa-Lin Wang (North China Electric Power University)
저널정보
대한전기학회 Journal of Electrical Engineering & Technology Journal of Electrical Engineering & Technology Vol.11 No.6
발행연도
2016.11
수록면
1,614 - 1,627 (14page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색
질문

초록· 키워드

오류제보하기
The purpose of this paper is to investigate the united Electromagnetic characteristics for the effective monitoring on the static air-gap eccentricity (SAGE) of turbo-generator. Different from other studies, this paper not only studies on the unbalanced magnetic pull (UMP) and the vibration characteristics of the stator and the rotor, but also investigates the harmonic features of the magnetic flux density and the circulating current inside the parallel branches (CCPB). The theoretical calculation, together with the finite-element-method (FEM) simulation and the experiment verification, is taken for a SDF-9 type non-salient generator. It is shown that, when SAGE occurs, apparent doublefrequency UMP and vibrations will be produced both on the stator and the rotor, while the CCPB will have an obvious increment at the 1<SUP>st</SUP> harmonic component. In addition, the amplitude of the magnetic flux density will be of cosine distribution in the circumferential position of the air-gap, while in normal condition it is a constant. Moreover, the pass-band amplitude, together with the 1<SUP>st</SUP> harmonic of the magnetic flux density, will be enlarged as well. These united electromagnetic characteristics can be used as the diagnosis and monitoring criterion for SAGE.

목차

Abstract
1. Introduction
2. Theoretical Analysis
3. Calculation and Experiment Study
4. Monitoring Method for SAGE
5. Conclusion
References

참고문헌 (24)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0

UCI(KEPA) : I410-ECN-0101-2017-560-001327459