Detection of Broken Rotor Bar Defect in Squirrel Cage Induction Machine

Lahouasnia, Nasreddine; Rachedi, Mohamed Faouzi; Deghboudj, Thamir

doi:10.1109/icaee47123.2019.9015159

Cited by 4 publications

(3 citation statements)

References 8 publications

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“…have used, in their work [ 33 ], DWT and PSD method to reveal BRBs faults in an induction motor. In [ 34 ] Nasreddine Lahouasnia et al. have demonstrated the identification of one BRB fault of an induction machine using the DWT analysis.…”

Section: Experimental Results and Validationmentioning

confidence: 99%

An experimental method for diagnostic of incipient broken rotor bar fault in induction machines

Sabir

Ouassaid

Ngote

2022

Heliyon

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Section: Experimental Results and Validationmentioning

confidence: 99%

An experimental method for diagnostic of incipient broken rotor bar fault in induction machines

Sabir

Ouassaid

Ngote

2022

Heliyon

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“…e simulation results of motor models with stable and variable speed were compared and the speed oscillation was used for fault detection in [11]. A faulty IM model was established based on multiloop theory and the currents were analyzed to detect the BRB fault in [12]. For stator fault, a model with interturn short-circuit fault was established based on reference frame transformation theory and the fault detection was realized by analyzing the changes of currents, speed, and torque in [13,14].…”

Section: Introductionmentioning

confidence: 99%

Method for Identifying Stator and Rotor Faults of Induction Motors Based on Machine Vision

Lipeng

Xiang

Wang

et al. 2021

Mathematical Problems in Engineering

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The detection results need to be analyzed and distinguished by professional technicians in the fault detection methods for induction motors based on signal processing and it is difficult to realize the automatic identification of stator and rotor faults. A method for identifying stator and rotor faults of induction motors based on machine vision is proposed to solve this problem. Firstly, Park’s vector approach (PVA) is used to analyze the three-phase currents of the motor to obtain Park’s vector ring (PVR). Then, the local binary patterns (LBP) and gray level cooccurrence matrix (GLCM) are combined to extract the image features of PVR. Finally, the vectors of image features are used as input and the types of induction motor faults are identified with the help of a random forest (RF) classifier. The proposed method has achieved high identification accuracy in both the Maxwell simulation experiment and the actual motor experiment, which are 100% and 95.83%, respectively.

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“…When the type of electrical signals extracted of current analysis in electric motors is explored, an open field of research appears to find new methods and tools that are better adapted to what is currently required, so far there are several methods that use the Wavelet Transforms in their discrete version that show the ability to work with signals that can be generated from the use of faulty alternating current induction motors as [15][16][17][18][19][20][21][22][23][24][25][26][27].…”

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confidence: 99%

Analysis Optimization and Comparison to Detect Failures in the Squirrel-Cage Rotor using High-Level Wavelets

García Irving I,

Cabrera J. Mario

2023

IJEER

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The methods and tools used for signal analysis extracted from the induction motors, such as the motor current signature analysis (MCSA) used for data collection on a non-invasive basis, the multi-resolution analysis (MRA) and discrete wavelet transform (DWT), are efficient tools for the signal analysis at different levels or resolutions, these tools have been applied together to improve detection of failures in the rotor of induction motors in condition of no-load. This work focuses on the study of rotor cage end ring, in a condition with lower-load or no-load where uncertainty predominates, this area of study is complicated to analyze correctly with conventional methods, but in these circumstances, the analysis using TDW has better performance. The article presents an alternative way of detecting failures in three phases induction motors in no-load state method with an optimized method and a comparison between results of the analysis with two different levels of the high-order Wavelet Daubechies, studying and evaluating its performance for the detection of broken ring, all this supported with a specific signal pre-processing and post-processing to improve the results of detection in incipient faults.

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Detection of Broken Rotor Bar Defect in Squirrel Cage Induction Machine

Cited by 4 publications

References 8 publications

An experimental method for diagnostic of incipient broken rotor bar fault in induction machines

An experimental method for diagnostic of incipient broken rotor bar fault in induction machines

Method for Identifying Stator and Rotor Faults of Induction Motors Based on Machine Vision

Analysis Optimization and Comparison to Detect Failures in the Squirrel-Cage Rotor using High-Level Wavelets

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