Analysis of airgap flux, current and vibration signals as a function of the combination of static and dynamic airgap eccentricity in 3-phase induction motors

Dorrell, David G.; Thomson, William T.; Roach, S.

doi:10.1109/ias.1995.530349

Cited by 203 publications

(147 citation statements)

References 4 publications

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“…The spectrum for static eccentricity fault shows dominant components at rotational frequency, f r (25 Hz here for a two pole-pair SM) and its odd multiples. These frequency components evolve due to flux density waves, rotating in the air gap due to the presence of the eccentricity, as mathematically demonstrated by [10]. As a result, the field current gives rise to distinct frequency components which are function of f s and f r , depending on the nature of the fault [24].…”

Section: Field Current Indicator Detecting Different Eccentricity Faimentioning

confidence: 99%

“…[1] Major faults in SMs occur from inter-turn short circuit of stator or rotor windings, and eccentricity due to nonuniformity in the airgap, broken damper bar, stator-rotor rubbing etc. [4][5][6][7][8][9][10][11][12]. Bearing faults though not quite common in large SMs are matter of importance [13] for high-speed machines.…”

Section: Introductionmentioning

confidence: 98%

“…Zero sequence voltage component was used for simultaneous diagnosis of stator faults arising from inter-turn shorts and resistive unbalance [16]. On the contrary, the sensor-based approach deals with interpretation of the obtained data either by installing new sensors or using the existing ones and often times combined with modelbased approach to offer logical conclusions [9][10][11][12]20,21]. The measurements are based on rotor parameters such as field current, airgap flux measurement [4,[9][10][11] or stator parameters such as vibration, stator voltage, current, circulating current, etc.…”

Section: Introductionmentioning

confidence: 99%

“…The measurements are based on rotor parameters such as field current, airgap flux measurement [4,[9][10][11] or stator parameters such as vibration, stator voltage, current, circulating current, etc. [4,[10][11][12][13]20,21]. Such an approach is always The present investigation is an attempt of enforcing realistic faults into a low voltage (lv) SM [12] and evaluating the efficacy of different fault indicators.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of different monitoring parameters for synchronous machine fault diagnostics

2016

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Early detection and diagnosis of faults in synchronous machine (SM) are crucial since they drive critical applications. In this paper, the authors exploited the combined information from numerical simulation and experimental validation to evaluate the merits of certain fault indicators, for detecting machine faults. A specially designed SM was chosen for both simulation and measurement with the ability to physically introduce electro-mechanical failures. Shorted turn fault was made through accessible intermediate terminals of respective stator and rotor windings. Eccentricity faults of different intensity were created by suitable changeover of customized end-shield. Finite element method was used to develop healthy and faulty simulation models. The experimental setup facilitated measurement and subsequent calculation of key parameters such as stator branch currents, phase current, circulating current, rotor field current and shaft voltage. From the investigation of both simulation and experimental data, field current and shaft voltage were found to be two effective fault indicators from safety and reliability prospects. Both indicators have the ability to identify and discriminate between electro-mechanical and electrical faults. Further, it is demonstrated that with availability of physical dimensions and measured rotor parameters, a know-how can be created to detect failures, well before a catastrophic event occurs.

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Section: Field Current Indicator Detecting Different Eccentricity Faimentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Evaluation of different monitoring parameters for synchronous machine fault diagnostics

2016

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“…Traditional models of UMP [1,2] distinguish between static and dynamic eccentricity. In the first case, the position of minimal radial air-gap is fixed in space: the rotor is symmetrical with respect to its axis and rotates about it.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear effects due to electromechanical interaction in generators with smooth poles

Pennacchi

2009

Nonlinear Dyn

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Electromechanical interaction in rotating machinery is an interesting nonlinear phenomenon. The methods used to analyze this phenomenon depend on the type of the electrical machine, synchronous or asynchronous, and on its size, but they are often related to the study of the unbalanced magnetic pull (UMP). In this paper the nonlinear behavior of generators with smooth poles of high-speed turbogenerators is presented during and after the excitation of the magnetic field in the air-gap in order to fully exploit the effect of the UMP. In the first part of the paper a method, which allows the simulation of the dynamical behavior of a flexible rotor caused by the UMP, is presented. In the second part, the simulation of a magnetic field excitation transient in a turbogenerator is presented and the nonlinear aspects in the system response and forcing are highlighted.

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Diagnosis methods for stator winding faults in three-phase squirrel-cage induction motors

Ojaghi

Sabouri

Faiz

2013

Int. Trans. Electr. Energ. Syst.

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SUMMARYInduction motors condition monitoring is a very important process for immediate detection of the incipient faults. This prevents the spread of the faults up to risky degrees and avoids catastrophic stop of the motor and relevant production line. The stator winding fault is one of the most commonly occurring faults in alternating current machines. This paper is a comprehensive survey on the stator winding faults causes, diagnosis methods, indexes, and modeling and simulation methods. An efficient method is used to model and simulate the squirrel‐cage induction motor performance under inter‐turn fault. The results are used to obtain the performance of some common indexes of the fault and recognize the most proper index. Finally, some simulation results are compared with the corresponding experimental results and good agreements are achieved. Copyright © 2013 John Wiley & Sons, Ltd.

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Analysis of airgap flux, current and vibration signals as a function of the combination of static and dynamic airgap eccentricity in 3-phase induction motors

Cited by 203 publications

References 4 publications

Evaluation of different monitoring parameters for synchronous machine fault diagnostics

Evaluation of different monitoring parameters for synchronous machine fault diagnostics

Nonlinear effects due to electromechanical interaction in generators with smooth poles

Diagnosis methods for stator winding faults in three-phase squirrel-cage induction motors

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