지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2017.7
- 수록면
- 1,014 - 1,026 (13page)
이용수
초록· 키워드
오류제보하기
The traditional fault diagnosis method for photovoltaic (PV) inverters has a difficult time meeting the requirements of the current complex systems. Its main weakness lies in the study of nonlinear systems. In addition, its diagnosis time is long and its accuracy is low. To solve these problems, a hidden Markov model (HMM) is used that has unique advantages in terms of its training model and its recognition for diagnosing faults. However, the initial value of the HMM has a great influence on the model, and it is possible to achieve a local minimum in the training process. Therefore, a genetic algorithm is used to optimize the initial value and to achieve global optimization. In this paper, the HMM is combined with a genetic algorithm (GHMM) for PV inverter fault diagnosis. First Matlab is used to implement the genetic algorithm and to determine the optimal HMM initial value. Then a Baum-Welch algorithm is used for iterative training. Finally, a Viterbi algorithm is used for fault identification. Experimental results show that the correct PV inverter fault recognition rate by the HMM is about 10% higher than that of traditional methods. Using the GHMM, the correct recognition rate is further increased by approximately 13%, and the diagnosis time is greatly reduced. Therefore, the GHMM is faster and more accurate in diagnosing PV inverter faults.
목차
Abstract
Ⅰ. INTRODUCTION
Ⅱ. ANALYSIS OF FAULT TYPES
Ⅲ. OPTIMIZATION OF THE HMM BY A GENETIC ALGORITHM
Ⅳ. FAULT DIAGNOSIS TECHNIQUE BASED ON THE GHMM
Ⅴ. EXPERIMENTAL VERIFICATION
Ⅵ. CONCLUSIONS
REFERENCES
참고문헌 (18)
참고문헌 신청
[학술지(정기간행물)] - S. Peuget / 1997 / Fault detection and isolation on a PWM inverter by knowledge-based model / IEEE Trans. Ind. Appl. 34 (6) : 1318 ~ 1326
[학술지(정기간행물)] - R. L. de Araujo Ribeiro / 2003 / Fault detection of open-switch damage in voltage-fed PWM motor drive systems / IEEE Trans. Power Electron. 18 (2) : 587 ~ 593
[학술대회논문] - H. Keskes / 2014 / DAG SVM and pitch synchronous wavelet transform for induction motor diagnosis / Proc. Iet International Conference on Power Electronics, Machines and Drives : 0166 ~ 0166
[학술지(정기간행물)] - D. J. Chen / 2013 / Open circuit fault diagnosis method for three level inverter based on multi neural network / Transactions of China Electrotechnical Society 28 (6) : 120 ~ 126
[학술대회논문] - G. S. Hu / 2005 / Classification of power quality disturbances using wavelet and fuzzy support vector machines / Proc. International Conference on Machine Learning and Cybernetics IEEE 7 : 3981 ~ 3984
[학술지(정기간행물)] - R. L. de Araujo Ribeiro / 2003 / Fault detection of open-switch damage in voltage-fed PWM motor drive systems / IEEE Trans. Power Electron. 18 (2) : 587 ~ 593
[학술대회논문] - H. Keskes / 2014 / DAG SVM and pitch synchronous wavelet transform for induction motor diagnosis / Proc. Iet International Conference on Power Electronics, Machines and Drives : 0166 ~ 0166
[학술지(정기간행물)] - D. J. Chen / 2013 / Open circuit fault diagnosis method for three level inverter based on multi neural network / Transactions of China Electrotechnical Society 28 (6) : 120 ~ 126
[학술대회논문] - G. S. Hu / 2005 / Classification of power quality disturbances using wavelet and fuzzy support vector machines / Proc. International Conference on Machine Learning and Cybernetics IEEE 7 : 3981 ~ 3984
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UCI(KEPA) : I410-ECN-0101-2018-560-001033803