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
- 학술대회자료
- 저자정보
- 발행연도
- 2011.5
- 수록면
- 1,005 - 1,012 (8page)
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초록· 키워드
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The multilevel inverters (MLIs) utilization has been increased in recent years due to their lots of advantages. The MLI has many switches that increase the probability of fault events. In this paper a fault diagnosis method for a cascade H-bridge 7-level inverter is proposed. The output phase voltage is used to detect fault type and their locations. The histogram analysis is used for feature extraction and these features have been used as input to the Neural Networks (NNs). The multilayer perceptron NNs have been used for fault diagnosis. Simulation results are given for a cascade 7-level inverter at different modulation indices and show that this method is accurate for detection of faults and their locations. This method works correctly under noisy condition and the classification performance for the noise with variance up to 1500 is 100%. The proposed method is faster and less complicated because of using histogram analysis instead of using sophisticated methods such as FFT or wavelet
목차
Abstract
Ⅰ. INTRODUCTION
Ⅱ. FAULTS AND THEIR EFFECTS
Ⅲ. FAULT DIAGNOSIS METHOD USING HISTOGRAM ANALYSIS AND NEURAL NETWORKS
Ⅳ. SIMULATION RESULTS
Ⅴ. CONCLUSION
REFERENCES
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UCI(KEPA) : I410-ECN-0101-2013-560-000300069