scholarly journals Detection of outer raceway bearing defects in small induction motors using stator current analysis

Sadhana ◽  
2005 ◽  
Vol 30 (6) ◽  
pp. 713-722 ◽  
Author(s):  
İzzet Y. önel ◽  
K. Burak Dalci ◽  
İbrahim Senol
Keyword(s):  
Induction Motors ◽  
Current Analysis ◽  
Stator Current ◽  
Bearing Defects

Bearing Fault Diagnostic of Induction Motor by Stator Currents Analysis Based on Park’s Vectors Approach

2014 ◽  
Vol 698 ◽  
pp. 83-89 ◽  
Author(s):  
Nail Safin ◽  
Vladimir Prakht ◽  
Vladimir Dmitrievskii
Keyword(s):  
Fault Diagnosis ◽  
Early Detection ◽  
Induction Motor ◽  
Induction Motors ◽  
Bearing Fault ◽  
Bearing Fault Diagnosis ◽  
Stator Current ◽  
Bearing Defects ◽  
Bearing Damage ◽  
Vector Approach

This paper deals with the possibilities of bearing fault diagnosis of induction motors by stator currents analysis based on Park’s vector approach. The main theoretical aspects, the experimental results and their analysis are presented. It is shown that preventive stator current diagnostics of induction motors based on Park’s vector allows us early detection of bearing defects in the inner and outer races. The current spectra additional harmonics appearing in the case of bearing damage are found.

scholarly journals Induction Motor Bearing Faults Diagnosis Using Stator Current and Vibration Analysis

2021 ◽  
Author(s):  
Mohamed Boudiaf Koura ◽  
Ahmed Hamida Boudinar ◽  
Ameur Fethi Aimer ◽  
Mohammed-el-Amine Khodja
Keyword(s):  
Vibration Analysis ◽  
Induction Motors ◽  
Rolling Element Bearings ◽  
Current Analysis ◽  
Stator Current ◽  
Vibration Technique ◽  
Rolling Element ◽  
Mechanical Faults ◽  
Faults Diagnosis ◽  
Electrical Faults

Several researches claim that the vibration technique, widely used in industry, is more efficient compared to the stator current analysis in the diagnosis of mechanical faults. On the other hand, researches show that the current technique is more advantageous especially in the diagnosis of electrical faults, in addition to the simplicity of the sensor positioning. The aim of this paper is to show that both diagnosis techniques can be complementary. For this, a comparative analysis of both diagnosis techniques performances is achieved. To this end, fault diagnosis of rolling element bearings used in induction motors is taken as an example, given the importance of bearings in energy transfer. Experimental results obtained show the complementarity of both techniques and their performances according to the faulty element of bearings.

Insulation Deterioration Detection by Zero-Sequence Current Analysis for Induction Motors

2011 ◽  
Vol 131 (12) ◽  
pp. 1457-1464 ◽  
Author(s):  
Hideki Iwanaga ◽  
Hiroshi Inujima
Keyword(s):  
Induction Motors ◽  
Current Analysis ◽  
Zero Sequence

Online Speed Detection of Induction Motors Based on Tooth Harmonic

2011 ◽  
Vol 58-60 ◽  
pp. 2517-2521
Author(s):  
Qing Xin Zhang ◽  
Hai Bin Li ◽  
Jin Li
Keyword(s):  
Induction Motors ◽  
Rotor Speed ◽  
Motor Speed ◽  
Stator Core ◽  
Current Harmonic ◽  
Stator Current ◽  
Speed Measurement ◽  
Frequency Components ◽  
Air Gap Magnetic Field ◽  
Alveolar Surface

Many methods have been used to detect the motor speed. All of these methods are based on the parameter equation of motor and the detection results are influenced by parameters of induction motor more or less. The research of Speed Measurement method without of Motor parameters effect is very significant. Based on the harmonic generated in the air gap magnetic field by the stator core on the alveolar surface, directly by the analysis and testing of stator current harmonic, the rotor speed is detected which is proportional to the speed of frequency components. Experiment results show that this method is good, and the accuracy achieve a desired effect in real time.

scholarly journals Broken Rotor Bars Fault Detection Based on Envelope Analysis Spectrum and Neural Network in Induction Motors

2018 ◽  
Vol 3 (3) ◽  
pp. 106-116
Author(s):  
Saddam BENSAOUCHA ◽  
Sid Ahmed BESSEDIK ◽  
Aissa AMEUR ◽  
Abdellatif SEGHIOUR
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Fourier Transform ◽  
Induction Motors ◽  
Current Signal ◽  
Broken Rotor Bars ◽  
Stator Current ◽  
The Neural Networks ◽  
Modulus Spectrum ◽  
Load Conditions

In this paper, a study has presented the performance of a neural networks technique to detect the broken rotor bars (BRBs) fault in induction motors (IMs). In this context, the fast Fourier transform (FFT) applied on Hilbert modulus obtained via the stator current signal has been used as a diagnostic signal to replace the FFT classic, the characteristics frequency are selected from the Hilbert modulus spectrum, in addition, the different load conditions are used as three inputs data for the neural networks. The efficiency of the proposed method is verified by simulation in MATLAB environment.

The Performance Evaluation of Machine Learning based Techniques via Stator Current and Stray Flux for Broken Bar Fault in Induction Motors

2021 ◽  
Author(s):  
M. B. Younas ◽  
N. Ullah ◽  
Taner Goktas ◽  
Muslum Arkan ◽  
V. Gurusamy
Keyword(s):  
Machine Learning ◽  
Performance Evaluation ◽  
Induction Motors ◽  
Stator Current
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