Proceedings ArticleDOI
Bearing fault diagnosis of a three phase induction motor using stockwell transform
Megha Singh,Abdul Gafoor Shaik +1 more
- pp 1-6
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TLDR
In this paper, the S-transform based feature extraction can be effectively utilized for bearing fault detection and diagnosis in a three phase induction motor using Stockwell transform of stator currents.Abstract:
This paper presents bearing fault detection and its diagnosis in a three phase induction motor using Stockwell transform of stator currents. The maximum magnitude and maximum phase angle plots are obtained from S-transform for various bearing conditions both on shaft-side and fan-side. The standard deviation of these plots are utilized to detect and analyze the bearing faults. The various bearing faults analyzed under case studies include defects in innerrace, outerrace, cage and balls. The experimental study shows that the S-transform based feature extraction can be effectively utilized for bearing fault detection and diagnosis in three phase induction motor.read more
Citations
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Journal ArticleDOI
Faulty bearing detection, classification and location in a three-phase induction motor based on Stockwell transform and support vector machine
Megha Singh,Abdul Gafoor Shaik +1 more
TL;DR: F faulty bearing detection, classification and its location in a three-phase induction motor using Stockwell transform and Support vector machine is presented.
Journal ArticleDOI
A Review to Diagnose Faults Related to Three-Phase Industrial Induction Motors
Muhammad Aman Sheikh,Sheikh Tahir Bakhsh,Muhammad Irfan,Nursyarizal Mohd Nor,Grzegorz Nowakowski +4 more
Proceedings ArticleDOI
Location of Defective Bearing in Three-Phase Induction Motor Using Stockwell Transform and Support Vector Machine
Megha Singh,Abdul Gafoor Shaik +1 more
TL;DR: This paper presents a technique to locate defective bearing based on Stockwell Transform of stator current signals and has been tested successfully for the bearing faults such as ball and outerrace fault.
Book ChapterDOI
Induction Motor Internal and External Fault Detection
TL;DR: S-Transformation, which is superior as compared to CWT and STFT as it does not contain any cross terms, is used for bearing fault detection, and random forest, an algorithm which is easy to implement and requires minimum memory, are used for detection of external faults.
Journal ArticleDOI
Progressive Bearing Fault Detection in a Three-Phase Induction Motor Using S-Transform via Pre-Fault Frequency Cancellation
TL;DR: In this paper , the authors proposed spectral analysis of stator current to estimate motor faults, FFT analysis is commonly preferred, but the problems associated with normal FFT analyses will mislead the fault diagnosis, and each technique requires special attention to get good results.
References
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Proceedings ArticleDOI
Models for bearing damage detection in induction motors using stator current monitoring
TL;DR: In this article, the influence of rolling-element bearing faults on induction motor stator current has been investigated and a new detailed approach is proposed based on two effects of a bearing fault: the introduction of a particular radial rotor movement and load torque variations caused by the bearing fault.
Journal ArticleDOI
Incipient Bearing Fault Detection via Motor Stator Current Noise Cancellation Using Wiener Filter
TL;DR: In this article, the bearing fault signature is detected alternatively by estimating and removing nonbearing fault components via a noise cancellation method, and a fault indicator is established based on the remaining components which are mainly caused by bearing faults.
Journal ArticleDOI
Induction Motor Bearing Failure Detection and Diagnosis: Park and Concordia Transform Approaches Comparative Study
TL;DR: Two fault detection and diagnosis techniques, namely the Park transform approach and the Concordia transform, are briefly presented and compared and outline the main features of the aforementioned approaches for small- and medium-size induction motors bearing failure detection and/or diagnosis.
Proceedings ArticleDOI
Stator current analysis for bearing damage detection in induction motors
TL;DR: In this paper, the authors presented experimental results for diagnosing faults in bearings with different raceway defects via motor current spectral analysis, which indicated that inner race faults are very difficult to detect by searching for their signatures in the current.
Journal ArticleDOI
Motor Current Signature Analysis for Bearing Fault Detection in Mechanical Systems
TL;DR: In this paper, a 2D wavelet scalogram has been used for the detection and occurrence of outer race faults of various sizes in ball bearings of mechanical systems using motor current signatures of induction motor.
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