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Volume 4 Issue 2
Apr.  2017

IEEE/CAA Journal of Automatica Sinica

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Zhanjun Huang, Zhanshan Wang and Huaguang Zhang, "Multilevel Feature Moving Average Ratio Method for Fault Diagnosis of the Microgrid Inverter Switch," IEEE/CAA J. Autom. Sinica, vol. 4, no. 2, pp. 177-185, Apr. 2017. doi: 10.1109/JAS.2017.7510496
Citation: Zhanjun Huang, Zhanshan Wang and Huaguang Zhang, "Multilevel Feature Moving Average Ratio Method for Fault Diagnosis of the Microgrid Inverter Switch," IEEE/CAA J. Autom. Sinica, vol. 4, no. 2, pp. 177-185, Apr. 2017. doi: 10.1109/JAS.2017.7510496

Multilevel Feature Moving Average Ratio Method for Fault Diagnosis of the Microgrid Inverter Switch

doi: 10.1109/JAS.2017.7510496
Funds:

This work was supported by National Natural Science Foundation of China 61473070

This work was supported by National Natural Science Foundation of China 61433004

Fundamental Research Funds for the Central Universities N130504002

SAPI Fundamental Research Funds 2013ZCX01

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  • Multilevel feature moving average ratio method is proposed to realize an open-switch fault diagnosis for any switch of the microgrid inverter. The main steps of the proposed method include multilevel signal decomposition, coefficient reconstruction, absolute average ratio process and artificial neural network (ANN) classification. Specifically, multilevel signal decomposition is realized by using the means of multi resolution analysis to obtain the different frequency band coefficients of the three-phase current signal. The related coefficient reconstruction is executed to achieve signals decomposition in different levels. Furthermore, according to the obtained data, the absolute average ratio process is used to extract absolute moving average ratio of signal decomposition in different levels for the three-phase current. Finally, to intelligently classify the inverter switch fault and realize the adaptive ability, the ANN technology is applied. Compared to conventional fault diagnosis methods, the proposed method can accurately detect and locate the open-switch fault for any location of the microgrid inverter. Additionally, it need not set related threshold of algorithm and does not require normalization process, which is relatively easy to implement. The effectiveness of the proposed fault diagnosis method is demonstrated through detailed simulation results.

     

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