Bias reduction for reliable fault detection of electric motors under measurement noise of non-zero means

Progovac, Dusan; Wang, Le Yi; Yin, Gang

doi:10.1504/ijmic.2014.063871

“…Consequently, the systems of production of electrical energy must be equipped with reliable monitoring systems because possible breakdown can lead to considerable property damage (El Bouchikhi et al, 2012;Seshadrinath et al, 2014;Yanfeng et al, 2014;Entezami et al, 2012;Progovac et al, 2014). Indeed, the early detection of the failure makes it possible to minimise the turn-around time and consequently the downtime, to reduce the financial losses and the property damages to meet this requirement (Shashidhara and Raju, 2013;Schlechtingen and Ilmar, 2011).…”

Section: Introductionmentioning

confidence: 99%

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

Merabet

¹

,

Bahi

²

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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“…The monitoring and detection of wind turbine faults was studied in many research works using various approaches because of its considerable interest in the field of production of electrical energy because the condition to obtain a safer system of production to ensure the continuity service in the conversion systems of wind power. Consequently, the systems of production of electrical energy must be equipped with reliable monitoring systems because possible breakdown can lead to considerable property damage (El Bouchikhi et al, 2012;Seshadrinath et al, 2014;Yanfeng et al, 2014;Entezami et al, 2012;Progovac et al, 2014). Indeed, the early detection of the failure makes it possible to minimise the turn-around time and consequently the downtime, to reduce the financial losses and the property damages to meet this requirement (Shashidhara and Raju, 2013;Schlechtingen and Ilmar, 2011).…”

Section: Introductionmentioning

confidence: 99%

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

Merabet

¹

,

Bahi

²

2017

IJMIC

View full text Add to dashboard Cite

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.

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Active fault tolerant control for nonlinear non-Gaussian singular stochastic distribution systems

Yao¹,

Li²,

Lei³

2016

2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA)

0

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Bias reduction for reliable fault detection of electric motors under measurement noise of non-zero means

Cited by 3 publications

References 0 publications

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

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

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

Active fault tolerant control for nonlinear non-Gaussian singular stochastic distribution systems

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