전기신호를 이용한 전동기 온라인 고장진단

다국어 초록 (Multilingual Abstract)

It is widely known that ESA(Electric Signature Analysis) method is very useful one for fault diagnosis of an induction motor. Online fault diagnosis system of induction motors using LabVIEW is proposed to detect the fault of broken rotor bars and shorted turns in stator. This system is not model-based system of induction motor but LabVIEW-based fault diagnosis system using FFT spectrum of stator current in faulty motor without estimating of motor parameters. FFT of stator current in faulty induction motor is measured and compared with various reference fault data in data base to diagnose the fault. This paper is focused on to predict and diagnose of the health state of induction motors in steady state. Also, it can be given to motor operator and maintenance team in order to enhance an availability and maintainability of induction motors. Experimental results are demonstrated that the proposed system is very useful to diagnose the fault and to implement the predictive maintenance of induction motors.

목차 (Table of Contents)

• Abstract
• 1. 서론
• 2. 고정자 전류 스펙트럼 분석
• 3. 실험 및 결과 고찰
• 4. 결론
• 감사의 글
• 참고문헌
• 저자소개

참고문헌 (Reference)

1 임정환, "전류스펙트럼 모니터링을 이용한 유도전동기회전자 고장검출 시스템" 건국대학교 2010

2 I. Albizu, "Techniques for online diagnosis of stator shorted turns in induction motors" Taylor & Francis Inc. 97-114, 2006

3 D. J. T. Siyambalapitiya, "Reliability improvement and economic benefits of on-line monitoring system for large induction machines" 26 : 1018-1025, 1990

4 A. Bellini, "Quantitative evaluation of induction motor broken bars by means of electrical signature analysis" 37 (37): 1248-1254, 2001

5 F. M. Discenzo, "Motor diagnostics: Technological drivers leading to 21st century predictive diagnostics" 1-12, 1997

6 N. M. Burstein, "Monitoring electric motor condition using current signature analysis: Case histories and success Stories" 1996

7 S. Chen, "Modelling and simulation of stator and rotor fault conditions in induction machines for testing fault diagnostic techniques"

8 G. B. Kliman, "Induction motor fault detection via passive current monitoring" 13-17, 1990

9 H. W. Penrose, "Applications for motor current signature analysis" Division of BJM Corp

10 M. E. H. Benbouzid, "A review of induction motors signature analysis as a medium for faults detection" 47 (47): 984-993, 2000

11 S. Chen, "A new approach to motor condition monitoring in induction motor drives" 30 : 905-911, 1994

12 H. Douglas, "A new algorithm for transient motor current signature analysis using wavelets" 40 (40): 1361-1368, 2004