Proceedings ArticleDOI
Detection of stator winding fault in induction motors using a motor square current signature analysis (MSCSA)
V. Fernao Pires,Daniel Foito,João Martins,A. J. Pires +3 more
- pp 507-512
TLDR
The motor square current signature analysis (MSCSA) is proposed, which uses the results of spectral analysis of the instantaneous square stator current to analyse the short-circuit fault inter-turn on an induction motor.Abstract:
In this paper the short-circuit fault inter-turn on the stator of an induction motor is analysed by an online diagnostic method. For the diagnostic method it is proposed the motor square current signature analysis (MSCSA). This method uses the results of spectral analysis of the instantaneous square stator current. The effects of stator square current spectrum are described and the related frequencies determined. This method is similar to the instantaneous power signature analysis, however has the advantage of just require one current sensor. Several simulation and experimental results are presented in order to illustrate the characteristics of the proposed method.read more
Citations
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Journal ArticleDOI
Condition Monitoring and Fault Diagnosis of Induction Motors: A Review
TL;DR: This paper presents the state of the art review describing different type of IM faults and their diagnostic schemes, and several monitoring techniques available for fault diagnosis of IM have been identified and represented.
Journal ArticleDOI
Condition Monitoring and Fault Diagnosis of Induction Motor
TL;DR: It is observed that the vibration-based techniques are reported to be effective for the identification of mechanical faults while motor current signature analysis is effective for electrical fault in an induction motor.
Proceedings ArticleDOI
Stator winding short-circuit fault diagnosis in induction motors using random forest
TL;DR: In this article, an approach to detect stator winding short-circuit faults in squirrel-cage induction motors based on Random Forest and Park's Vector is proposed, which is accomplished by scoring the unbalance in the current and voltage waveforms as well as in Park's vector, both for current and Voltage.
Proceedings ArticleDOI
Detection of inter-turn stator faults in induction motors using short term averaging of forwards and backwards rotating stator current phasors for fast prognostics
TL;DR: There are several methods for detecting shorted turns in the stators of induction motors and some of them are simple, straightforward and efficient.
Detection of Induction Machine Winding Faults Using Genetic Algorithm
TL;DR: In this article, an identification technique for fault detection of induction machines using genetic algorithm is investigated, which indicates the presence of a winding fault and provides information about its nature and location.
References
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Journal ArticleDOI
A Survey on Testing and Monitoring Methods for Stator Insulation Systems of Low-Voltage Induction Machines Focusing on Turn Insulation Problems
TL;DR: An in-depth literature review of testing and monitoring methods that diagnose the condition of the turn-to-turn insulation of low-voltage machines, which is a rapidly expanding area for both research and product development efforts.
Proceedings ArticleDOI
An unsupervised, on-line system for induction motor fault detection using stator current monitoring
TL;DR: In this article, a new method for online induction motor fault detection is presented, which utilizes artificial neural networks to learn the spectral characteristics of a good motor operating online, which may contain many harmonics due to the load which correspond to normal operating conditions.
Journal ArticleDOI
Monitoring and diagnosis of induction motors electrical faults using a current Park's vector pattern learning approach
H. Nejjari,Mohamed Benbouzid +1 more
TL;DR: In this article, Park's vector-based approach is used to diagnose electrical faults in induction motors, and the proposed methodology has been experimentally tested on a 4 kW squirrel-cage induction motor.
Journal ArticleDOI
Rotor Cage Fault Diagnosis in Three-Phase Induction Motors by Extended Park's Vector Approach
TL;DR: In this article, a new approach based on the spectral analysis of the motor current Park's vector modulus was proposed for detecting rotor cage faults in operating three-phase induction machines.
Journal ArticleDOI
Fuzzy inference systems implemented on neural architectures for motor fault detection and diagnosis
TL;DR: Two neural fuzzy (NN/FZ) inference systems, namely, fuzzy adaptive learning control/decision network (FALCON) and adaptive network based fuzzy inference system (ANFIS), with applications to induction motor fault detection/diagnosis problems are presented.
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