Fault Diagnosis of Broken Rotor Bars in Induction Motors Using Finite Element Analysis

2020 ◽  
Author(s):  
Rojan Mazouji ◽  
Hamid Khaloozadeh ◽  
Mohammad Arasteh
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Fault Diagnosis ◽  
Induction Motors ◽  
Element Analysis ◽  
Broken Rotor Bars

Analysis of Losses and Thermal in Induction Motors

2013 ◽  
Vol 446-447 ◽  
pp. 503-508
Author(s):  
Xiao Feng Ding ◽  
Hui Chang
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Pulse Width ◽  
Induction Motors ◽  
Thermal Characteristics ◽  
Sinusoidal Voltage ◽  
Element Analysis ◽  
Voltage Supply ◽  
Pulse Width Modulated ◽  
Load Conditions

This paper presents an investigation into the losses and thermal characteristics of induction motors operated from pulse width-modulated (PWM) voltage supply in comparison to that operated from sinusoidal voltage supply. It was concluded that due to the abundant harmonics in the PWM waveforms, significant losses are induced in the motor by the inverter supply. The temperature ascends correspondingly. Experiments were conducted with no load and with load conditions. The losses and thermal characteristics were calculated using finite element analysis (FEA) and validated by the experiments.

Study on Fault Diagnosis of Wind Turbine Main Bearing Based on Finite Element Analysis and Wavelet Analysis

2011 ◽  
Vol 308-310 ◽  
pp. 1264-1268 ◽  
Author(s):  
Yi Qu ◽  
Chang Zheng Chen ◽  
Bo Zhou
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Fault Diagnosis ◽  
Wavelet Analysis ◽  
Wind Turbine ◽  
Three Dimension ◽  
Main Bearing ◽  
Element Analysis ◽  
Set Up ◽  
Contact Stress Distribution

A new method based on finite element analysis and wavelet analysis for the fault diagnosis of wind turbine main bearings is presented in the paper. Firstly, take example for low speed bearing, the three-dimension models of the good and fault bearings are set up, which was discussed with using finite element method. The stress, strain and contact stress distribution were computed by this method. Then the wavelet transform of data signals collected in experiment was carried out with db6 wavelet and 4 scales on the basis of the stress wave analysis. The frequency D3 and D4 signals were reconstructed and characteristic frequencies of stress waves with the simulative faults were extracted. It has been shown that the method applying finite element analysis and wavelet analysis is an efficient method for the fault diagnosis of wind turbine main bearings.

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