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In this paper, the wavelet transform theory is used to fault diagnosis for wind turbine benchmark model, considering its characteristics of multi-resolution and thresholds. The paper emphasizes de-noising based on wavelet transform in signal of generated residue in order to detect faults. Executing wavelet transformation, faults in the wind turbine can be detected. We have attempted to show how wavelet...
In this paper we present a qualitative evaluation of generated residual signal using wavelet transform in purpose of fault diagnosis for wind turbine benchmark model. The fault detection is based on generating residual signal by comparing the real and an estimated behavior. The ‘Takagi-Sugeno’ (TS) fuzzy identification and modeling is considered to approximate the non linearity presented in this system...
This paper compares model-based and signal-based approaches to induction motor fault detection. A Park model was used to describe the electrical variables. System faults such as stator winding failures or broken rotor bars are investigated. Parameter variations due to heating are considered. The identification of a single parameter, modelling the temperature effect, has allowed good detection within...
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