Detection of Induction Motors Rotor/Stator Faults Using Electrical Signatures Analysis

Shehata, S. A.; El-Goharey, Hamdy S. K.; Marei, Mostafa I.; Ibrahim, Ahmad

doi:10.24084/repqj11.318

Cited by 11 publications

(7 citation statements)

References 5 publications

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“…Its main advantages are the availability of the stator current measurements and the simple implementation. However, it suffer from load influence and supplying voltage low quality (Trzynadlowski, 1999;Zagirnyak et al, 2013;Prakasam and Ramesh, 2016;Shehata et al, 2013).…”

Section: Total and Partial Power As A Mean Of Diagnosticmentioning

confidence: 99%

“…Even that this method exhibits numerous advantages such as the elimination of electrical distortions and influence of supplying voltage low quality; it is not yet explored for incipient fault detection under varying supply/frequency and load conditions (Mehla and Dahiya, 2007;Mehrjou et al, 2011;Singhal and Khandekar, 2013). To overcome these disadvantages some techniques concentrated on the use of machine's current signature analysis (MCSA) (Shehata et al, 2013;Prakasam and Ramesh, 2016). The mean advantage of the MCSA technique is the availability of the stator current measurements in the major industrial applications.…”

Section: Introductionmentioning

confidence: 99%

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Simulation of different power methods for induction generator faults detection and diagnosis

Leksir

Bensaker

2019

IJPEC

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This paper deals with a simulation of different power methods to detect and diagnose induction generator faults. Instantaneous partial and total power, active and reactive power, complex apparent power and transformed power from mechanic to electric nature are revisited, simulated and discussed in this paper for induction generator rotor broken bars and stator short cuts faults detection and diagnosis. Fast Fourier transform (FFT) and PQ transform algorithms are used as comparison tools. Simulation results show that, on one hand, active, reactive and complex apparent power can only be used to detect evolution of rotor faults. On the other hand, partial, total and power transferred from mechanical to electrical nature are able to detect induction generator faults evolution with the advantage of eliminating electrical distortions and influence of low quality of supplying voltage. Furthermore, the implementation of the PQ transformation offers the possibility to isolate load influence from rotor faults and stator ones.

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Section: Total and Partial Power As A Mean Of Diagnosticmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Simulation of different power methods for induction generator faults detection and diagnosis

Leksir

Bensaker

2019

IJPEC

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“…It has already been mentioned that condition monitoring based on electrical measurements seems to be the trend towards efficient O&M for induction generators; it is cheaper than other common techniques and can monitor both electrical and mechanical faults [5]. Such techniques include: current, voltage, instantaneous power and flux analysis [32,33]. Stator current analysis is the most common of these techniques [5,6].…”

Section: Electrically-based Condition Monitoring Techniquesmentioning

confidence: 99%

Current signature analysis to monitor DFIG wind turbine generators: A case study

2018

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As wind energy continues to develop with increasing wind turbine power capacities often deployed offshore, reducing operation and maintenance costs have become a critical aspect. Condition monitoring has been found to be the key to achieve this goal. Under this framework, the induction generator of a wind turbine is a major contributor to failure rates and downtime where doublyfed induction generators are the dominant technology employed. This paper presents a spectral analysis of a real doubly-fed induction generator of an inservice wind turbine. A one-year measurement campaign on an operating wind turbine has been used to perform the study. Three test cases representing different wind turbine operating conditions are presented to illustrate the results. All the peaks found in the spectra have been identified, and the frequency components related to electrical rotor unbalance have been found. The results show which components are more suitable for effective condition monitoring.

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“…Different signal processing and signal analysis using mathematical techniques can identify faults in the DFIG (Shahata et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Fuzzy monitoring of stator and rotor winding faults for DFIG used in wind energy conversion system

Merabet

Bahi

2017

IJMIC

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According to its high robustness, the use of doubly-fed induction generators in the wind energy conversion takes an important place in the world of production of electrical energy. This type of conversion became very attractive because of its manufacturing environments, low cost and operation with an easily available power supply. The increase interest in wind energy conversion has been accompanied by efforts to improve reliability, effective condition monitoring and better efficiency. In this work, a new technique is proposed for monitoring and detection of inter-turn short-circuit ITSC and open phase circuits in the stator or rotor windings of wind turbines based on doubly-fed induction generator The principle of the suggested technique is based on the acquisition of the stator and the rotor currents of a doubly-fed induction generator with the aim to calculate the values of root mean square amplitude, in addition to the knowledge expressed in rules and membership function. This technique is verified using simulations performed via the model of doubly-fed induction generators built in MATLAB ® Simulink. Bahi Tahar received his Engineering, Magister and Doctorate degrees in Electrical Engineering from the Badji Mokhtar University, Annaba, Algeria in 1983, 1986 and 2006, respectively. Since 1983, he has been with the Department of Electrical of the University of Annaba, Algeria where he is currently a Professor of Electrical Engineering. His main research fields include the control of electrical machines, power electronic applications and renewable energy. This paper is a revised and expanded version of a paper entitled 'Monitoring and detection of the electromagnetic fault in a wind turbine based in DFIG using fuzzy logic approach' presented at Keywords

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Detection of Induction Motors Rotor/Stator Faults Using Electrical Signatures Analysis

Cited by 11 publications

References 5 publications

Simulation of different power methods for induction generator faults detection and diagnosis

Simulation of different power methods for induction generator faults detection and diagnosis

Current signature analysis to monitor DFIG wind turbine generators: A case study

Fuzzy monitoring of stator and rotor winding faults for DFIG used in wind energy conversion system

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