Computer-aided detection of airgap eccentricity in operating three-phase induction motors by Park's vector approach

Cardoso, António J. Marques; Saraiva, E. S.

doi:10.1109/28.245712

Cited by 139 publications

(27 citation statements)

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“…Park's vector is a circular pattern for ideal conditions, while its shape deviates due to fault. This method has been used for detection of air gap eccentricity fault [39,40].…”

Section: A Open-loop Controlmentioning

confidence: 99%

Review of eccentricity fault detection techniques in IMs focusing on DFIG

Faiz

Moosavi

2015

2015 IEEE 5th International Conference on Power Engineering, Energy and Electrical Drives (POWERENG)

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Induction machines are widely used in different applications. Unpredicted breakdown of these machines usually leads to costly downtime and repairs. These expenses can be minimized by using proper condition monitoring techniques. Eccentricity fault is one of the widespread faults causing machine malfunction; its detection could be useful for preventing of harmful consequences. In this paper, different works on eccentricity fault diagnosis of induction machines with different types of supply have been reviewed. Due to extensive use of induction machines in wind turbines (WT) as doubly-fed induction generator (DFIG), in addition to declaration of importance of eccentricity fault diagnosis in DFIG, detection of eccentricity fault in DFIG is also reviewed.

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“…Park's vector is a circular pattern for ideal conditions, while its shape deviates due to fault. This method has been used for detection of air gap eccentricity fault [39,40].…”

Section: A Open-loop Controlmentioning

confidence: 99%

Review of eccentricity fault detection techniques in IMs focusing on DFIG

Faiz

Moosavi

2015

2015 IEEE 5th International Conference on Power Engineering, Energy and Electrical Drives (POWERENG)

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“…More recently [14], [15], [16], [17] space vector feature extraction has been applied in fault classification and diagnosis. In [16] and [17] the current space vector is examined using pattern recognition approaches and neural networks are trained to identify the faulty conditions.…”

Section: B Current Space Vector Analysismentioning

confidence: 99%

Space vector feature extraction for condition monitoring of the slip energy recovery drive

Tsoumas

Safacas

2005

2005 International Conference on Electrical Machines and Systems

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Mechanical imbalance and eccentricity are usual faults in induction motors. These two faults can be identified by their effects in the stator current spectrum using motor current signature analysis. However, if the motor is supplied by electronic converters the identification of the fault is more complex, since additional harmonic components appear, caused by the converter. The main objective of the present work is to investigate the possibility of identifying these faults in a motor which is supplied by a power converter, specifically the slip energy recovery drive. To this purpose, the rotor current space vector modulus harmonic components are examined. The system is at first investigated through simulation in Matlab-Simulink. Thereafter, experimental tests are conducted. Characteristic results are presented and discussed.

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“…This happens because the PSH Other methods, proposed in the literature, address the eccentricity fault diagnosis as well. In [14], the use of the current's Park vector was proposed. In [15] the use of the instantaneous power and in [16] the instantaneous reactive power spectrum has been used.…”

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confidence: 99%

The zero-sequence current spectrum as an on-line static eccentricity diagnostic mean in Δ-connected PSH-induction motors

Gyftakis

Kappatou

2013

2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)

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Φ Abstract --It has been reported that the only-static and only-dynamic eccentricity cannot be reliably detected in induction motors which produce Principal Slot Harmonics (PSH) with the use of the traditional MCSA method. Most work was focused in the detection of dynamic and mixed, rather than static eccentricity. In this paper, the detection of the only-static eccentricity fault in Δ-connected induction motors with the use of the zero-sequence current spectrum is thoroughly investigated. The frequency spectrum of the zerosequence current is studied with the application of the Fast Fourier Transform in a PSH-induction motor operating under different constant speed cases and for different fault levels. The work is carried out with transient FEM simulations. The results will show that the proposed method succeeds in the only static eccentricity diagnosis and its severity, while the MCSA proves to be unreliable.

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Computer-aided detection of airgap eccentricity in operating three-phase induction motors by Park's vector approach

Cited by 139 publications

References 1 publication

Review of eccentricity fault detection techniques in IMs focusing on DFIG

Review of eccentricity fault detection techniques in IMs focusing on DFIG

Space vector feature extraction for condition monitoring of the slip energy recovery drive

The zero-sequence current spectrum as an on-line static eccentricity diagnostic mean in Δ-connected PSH-induction motors

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Computer-aided detection of airgap eccentricity in operating three-phase induction motors by Park's vector approach

Cited by 139 publications

References 1 publication

Review of eccentricity fault detection techniques in IMs focusing on DFIG

Review of eccentricity fault detection techniques in IMs focusing on DFIG

Space vector feature extraction for condition monitoring of the slip energy recovery drive

The zero-sequence current spectrum as an on-line static eccentricity diagnostic mean in &#x0394;-connected PSH-induction motors

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Product

Resources

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The zero-sequence current spectrum as an on-line static eccentricity diagnostic mean in Δ-connected PSH-induction motors