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Journal Articles ISA Transactions Year : 2017

An imbalance fault detection method based on data normalization and EMD for marine current turbines

Abstract

This paper proposes an imbalance fault detection method based on data normalization and Empirical Mode Decomposition (EMD) for variable speed direct-drive Marine Current Turbine (MCT) system. The method is based on the MCT stator current under the condition of wave and turbulence. The goal of this method is to extract blade imbalance fault feature, which is concealed by the supply frequency and the environment noise. First, a Generalized Likelihood Ratio Test (GLRT) detector is developed and the monitoring variable is selected by analyzing the relationship between the variables. Then, the selected monitoring variable is converted into a time series through data normalization, which makes the imbalance fault characteristic frequency into a constant. At the end, the monitoring variable is filtered out by EMD method to eliminate the effect of turbulence. The experiments show that the proposed method is robust against turbulence through comparing the different fault severities and the different turbulence intensities. Comparison with other methods, the experimental results indicate the feasibility and efficacy of the proposed method.
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Dates and versions

hal-02402579 , version 1 (10-12-2019)

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Milu Zhang, Tianzhen Wang, Tianhao Tang, Mohamed Benbouzid, Demba Diallo. An imbalance fault detection method based on data normalization and EMD for marine current turbines. ISA Transactions, 2017, 68, pp.302-312. ⟨10.1016/j.isatra.2017.02.011⟩. ⟨hal-02402579⟩
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