A secure and sensitive wavelet transform based technique for stator fault detection in the cases of line‐connected and inverter‐fed induction machines

Abstract

Here a new sensitive fault detection criterion is proposed, based on the stationary wavelet transform (SWT) decomposition components of the stator currents, for the online detection of stator winding turn-to-turn faults at an early stage of development. The energies of the desired detail components are calculated and the normalized Euclidean distance of the energy differences between the three phases is used as a new fault detection criterion. The robustness of the proposed technique against the presence of rotor turn-to-turn faults and loading variations is demonstrated. In addition, an adaptive threshold level as a function of the voltage unbalance factor is proposed to guarantee the robustness of the diagnostic technique against unbalanced voltage sources. Experimental results demonstrate the effectiveness and sensitivity of the proposed diagnostic approach for the detection of stator faults in line-connected and inverter-fed motors.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Stator ITSC Fault Diagnosis for EMU Induction Traction Motor Based on Goertzel Algorithm and Random Forest

“…Energies 2023, 16, 4949 9 of 17 where f s is the sampling frequency. The amplitude and phase of a specific frequency find are calculated using the Goertzel algorithm as shown in Formulas ( 18) and (19):…”

“…If the amplitude at a certain phase exceeded a predetermined threshold, it was determined that the ITSC fault had occurred. Discrete wavelet or wavelet packet transform was used to analyze the current value, power spectral density, and other parameters [19][20][21][22][23][24]. Parameters such as the energy ratio of a particular frequency band were used for fault diagnosis in the induction motors.…”

Sensorless Control of Induction Motor Based on Differential Flatness Theory and Reduced MRAS Observer

“…(Salima, Loubna, & Riad, 2018) present a global stability and robust nonlinear controller applied to induction motor. (Mustafa, Nikolakopoulos, & Gustafsson, 2014) present a fault classification algorithm based on a robust linear discrimination scheme, this technique is applied to detect of two kinds of Induction motor faults (broken rotor bar and short circuit in stator winding) in (Nazemi, Gallehdar, Haghjoo, & Cruz, 2021) the authors present a new sensitive fault detection criterion is proposed, based on the stationary wavelet transform (SWT) decomposition components of the stator currents in objective is, the detection of stator faults in line-connected and inverter-fed motors . Despite all these studies, we didn't manage to replace the speed sensor exactly mainly during in the load's application.…”