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.

Faults diagnosis of rolling element bearings based on modified morphological method

2011 ◽  
Vol 25 (4) ◽  
pp. 1276-1286 ◽  
Author(s):  
Yabin Dong ◽  
Mingfu Liao ◽  
Xiaolong Zhang ◽  
Fazhan Wang
Keyword(s):  
Rolling Element Bearings ◽  
Morphological Method ◽  
Rolling Element ◽  
Faults Diagnosis

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

A Kalman Filter Based Technique for Stator Turn-Fault Detection of the Induction Motors

2017 ◽  
Vol 18 (6) ◽  
Author(s):  
Teymoor Ghanbari ◽  
Haidar Samet
Keyword(s):  
Kalman Filter ◽  
Fault Detection ◽  
High Performance ◽  
Induction Motors ◽  
Simple Technique ◽  
Harmonic Distortion ◽  
Stator Current ◽  
Three Phase ◽  
Power Frequency ◽  
Faults Diagnosis

AbstractMonitoring of the Induction Motors (IMs) through stator current for different faults diagnosis has considerable economic and technical advantages in comparison with the other techniques in this content. Among different faults of an IM, stator and bearing faults are more probable types, which can be detected by analyzing signatures of the stator currents. One of the most reliable indicators for fault detection of IMs is lower sidebands of power frequency in the stator currents. This paper deals with a novel simple technique for detecting stator turn-fault of the IMs. Frequencies of the lower sidebands are determined using the motor specifications and their amplitudes are estimated by a Kalman Filter (KF). Instantaneous Total Harmonic Distortion (ITHD) of these harmonics is calculated. Since variation of the ITHD for the three-phase currents is considerable in case of stator turn-fault, the fault can be detected using this criterion, confidently. Different simulation results verify high performance of the proposed method. The performance of the method is also confirmed using some experiments.

scholarly journals Automatic Condition Monitoring of Industrial Rolling-Element Bearings Using Motor’s Vibration and Current Analysis

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Zhenyu Yang
Keyword(s):  
Point Defect ◽  
Condition Monitoring ◽  
Single Point ◽  
Operating Conditions ◽  
Multiple Point ◽  
Rolling Element Bearings ◽  
Current Analysis ◽  
Rolling Element ◽  
High Frequency Resonance ◽  
Short Time

An automatic condition monitoring for a class of industrial rolling-element bearings is developed based on the vibration as well as stator current analysis. The considered fault scenarios include a single-point defect, multiple-point defects, and a type of distributed defect. Motivated by the potential commercialization, the developed system is promoted mainly using off-the-shelf techniques, that is, the high-frequency resonance technique with envelope detection and the average of short-time Fourier transform. In order to test the flexibility and robustness, the monitoring performance is extensively studied under diverse operating conditions: different sensor locations, motor speeds, loading conditions, and data samples from different time segments. The experimental results showed the powerful capability of vibration analysis in the bearing point defect fault diagnosis. The current analysis also showed a moderate capability in diagnosis of point defect faults depending on the type of fault, severity of the fault, and the operational condition. The temporal feature indicated a feasibility to detect generalized roughness fault. The practical issues, such as deviations of predicted characteristic frequencies, sideband effects, time-average of spectra, and selection of fault index and thresholds, are also discussed. The experimental work shows a huge potential to use some simple methods for successful diagnosis of industrial bearing systems.

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